Translating Preclinical Data to Human Clearance and Pharmacokinetics October 27-28, 2016 Sheraton Boston Hotel, Boston, MA
PROGRAM AND ABSTRACTS
An ISSX Workshop 7
UPCOMING ISSX MEETINGS 2017 14th European ISSX Meeting Gürzenich Köln Cologne, Germany June 26 - 29, 2017 21st North American Meeting Rhode Island Convention Center Providence, Rhode Island, USA September 24 - 28, 2017 2018 22nd North American ISSX Meeting Palais des congrès de Montréal Montreal, Quebec, Canada July 15 - 19, 2018 2019 12th International ISSX Meeting Portland Convention Center Portland, Oregon, USA July 29 - August 1, 2019 2020 23rd ISSX North American and 35th JSSX Meeting Hilton Waikaloa Village Waikaloa, Hawaii, USA October 4 - 8, 2020
Translating Preclinical Data to Human Clearance and Pharmacokinetics Table of Contents 2 3 4 5 6 8 10 12 13 14 16 21 39 40 Inside Back Cover
Welcome Letter from Workshop Co-Chairs Committees and Sponsors General Information Schedule Overview ISSX Leadership Program Exhibitor Directory Industry-Sponsored Symposium: Qualyst Transporter Solutions, LLC Poster Information Poster Abstract Details Speaker Abstracts Poster Abstracts Abstract Keyword Index Abstract Author Index Poster and Exhibit Hall Floor Plan
Welcome to Boston! Dear Colleagues, On behalf of the Council and the Scientific Affairs Committee of the International Society for the Study of Xenobiotics, we are pleased to welcome you to the ISSX Workshop: Translating Preclinical Data to Human Clearance and Pharmacokinetics. The workshop will offer an atmosphere for discussion, both formal and informal, conducive to the exchange of information and experiences and will present attendees opportunities to interact with senior leaders in this field. The two-day workshop features well-known speakers from industry, academia, and regulatory agencies and will address critical challenges in predicting human clearance and pharmacokinetics. Our ability to accurately predict human clearance and pharmacokinetics is an essential component of drug discovery and development. The ultimate goal of the workshop is to facilitate formulation of practical strategies utilized in the pharmaceutical industry on human PK/clearance prediction based on in vitro and animal data in combination with modeling methods. Sincerely yours, Yingying Guo, Ph.D. Principal Research Scientist Eli Lilly & Company Workshop Co-Chair
Jin Zhou, Ph.D. Principal Scientist Boehringer Ingelheim Pharmaceuticals, Inc. Workshop Co-Chair
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
Committees
Workshop Organizing Committee Committee Co-Chairs Yingying Guo, Eli Lilly and Company and Jin Zhou, Boehringer Ingelheim Committee Members
Aleksandra Galetin, University of Manchester Stephen D. Hall, Eli Lilly and Company Donald Tweedie, Merck & Company
Abstract Review Committee Committee Members
Yingying Guo, Eli Lilly and Company Stephen D. Hall, Eli Lilly and Company Swati Nagar, Temple University Jin Zhou, Boehringer Ingelheim
Sponsors ISSX and the Workshop Organizing Committee thank and recognize the following companies for their support of this meeting. This activity is supported by educational grants from the following:
AbbVie
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General Information
Translating Preclinical Data to Human Clearance and Pharmacokinetics
Venue Sheraton Boston Hotel
39 Dalton Street Boston, MA 02199
Internet Access
Wi-Fi access is available throughout the workshop meeting and exhibit space.
Registration and Badges Registration Hours Republic Foyer
Name Badges
Wednesday, October 26
5:00 pm - 7:00 pm
Thursday, October 27
7:00 am - 6:30 pm
Friday, October 28
7:00 am - 4:00 pm
Name badges are required for admission to the workshop sessions, the exhibit space, and Welcome Reception. Badges help facilitate networking and communication with your fellow attendees. If you lose your badge, please visit the registration counter for assistance.
Abstracts and Posters Abstracts
Abstracts are available for review in this book and online at www.issx.org/onlineabstracts.
Posters Republic Ballroom
Thursday, October 27
7:00 am - 8:00 am 12:45 pm - 1:30 pm
Poster Set-Up Odd-Numbered Poster Presentations
Friday, October 28
8:00 am - 9:00 am 12:15 pm - 1:00 pm 4:00 pm - 4:30 pm
Poster Networking Even-Numbered Poster Presentations Poster Removal
Wednesday, October 26
5:00 pm - 7:00 pm
Exhibits Set-Up
Thursday, October 27
7:00 am - 10:10 am 10:10 am - 10:30 am 12:00 pm - 1:30 pm 4:30 pm - 7:00 pm
Exhibits Set-Up Refreshment Break Lunch and Poster Presentations Welcome Reception
Friday, October 28
8:00 am - 9:00 am 11:45 am - 1:00 pm 1:00 pm - 4:00 pm
Morning Refreshments Lunch and Poster Presentations Exhibits Removal
Thursday, October 27
7:30 am - 8:00 am 10:10 am - 10:30 am 12:00 pm - 1:30 pm 4:30 pm - 7:00 pm
Morning Refreshments Refreshment Break Lunch Welcome Reception
Friday, October 28
7:00 am - 8:00 am 8:00 am - 9:00 am 11:45 am - 1:00 pm
Industry Symposium Refreshments Morning Refreshments Lunch
Exhibits Schedule Exhibitors Republic Ballroom
Refreshments and Meals Republic Foyer and Republic Ballroom
Welcome Reception Republic Ballroom
Fully-registered attendees and their registered guests are invited to attend the Welcome Reception on Thursday, October 27 from 4:30 pm - 7:00 pm. Exhibitors will be on-hand to meet you and share information about their latest products and services. Admission to the Welcome Reception is included in the registration fee. Attendees must have their name badges in order to be admitted.
Industry-Sponsored Symposium Industry Symposium Back Bay C and D
All attendees are invited to join Qualyst Transporter Solutions, LLC for an industry-sponsored symposium on Friday, October 28 from 7:00 am - 8:00 am. Light refreshments will be served.
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
Schedule Overview
Wednesday, October 26 5:00 pm - 7:00 pm Republic Foyer
Registration Open
Thursday, October 27 7:00 am - 6:30 pm Republic Foyer
Registration Open
7:30 am - 8:00 am Republic Foyer
Morning Refreshments
8:00 am - 8:10 am Back Bay C and D
Opening and Welcome
8:10 am - 10:10 am Back Bay C and D
Session 1: Short Course: Introduction to Fundamentals and Challenges in Human PK/clearance Prediction
10:10 am - 10:30 am Republic Ballroom
Refreshment Break
10:30 am - 12:00 pm Back Bay C and D
Session 2: Methodological Aspects of Clearance Prediction for Low Clearance and Highly Bound Compounds
12:00 pm - 1:30 pm Republic Ballroom
12:00 pm - 1:30 pm
Exhibits
12:00 pm - 1:30 pm
Lunch
12:45 pm - 1:30 pm
Odd-Numbered Poster Presentations
1:30 pm - 3:45 pm Back Bay C and D
Session 3: Predicting Non-CYP Metabolizing Enzymes Mediated Clearance
3:45 pm - 4:30 pm Back Bay C and D
Panel Discussion with Session 2 and 3 Speakers
4:30 pm - 7:00 pm Republic Ballroom
Welcome Reception with Exhibitors
Friday, October 28 7:00 am - 4:00 pm Republic Foyer
Workshop Registration Open
7:00 am - 8:00 am Back Bay C and D
Qualyst Transporter Solutions, LLC Industry-Sponsored Symposium: Transporter Regulation and Adaptive Responses in the Prevention of Cholestatic Hepatotoxicity
8:00 am - 9:00 am Republic Ballroom
Morning Refreshments Poster Networking and Viewing
9:00 am - 11:45 am Back Bay C and D
Session 4: Quantitative Assessment of Hepatobiliary Transporter-mediated Clearance
11:45 am - 1:00 pm Republic Ballroom
11:45 am - 1:00 pm
Exhibits
11:45 am - 1:00 pm
Lunch
12:15 pm - 1:00 pm
Even-Numbered Poster Presentations
1:00 pm - 3:45 pm Back Bay C and D
Session 5: Human PK/clearance Prediction in Special Populations
3:45 pm - 4:00 pm Back Bay C and D
Workshop Closing
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ISSX Leadership
Translating Preclinical Data to Human Clearance and Pharmacokinetics
Council President
Geoff Tucker, University of Sheffield, UK
President-Elect/ Secretary
Thomas Baillie, University of Washington, Washington, USA
Treasurer
James Halpert, University of Connecticut, Connecticut, USA
Treasurer-Elect
Sonia de Morais, Florida, USA
Council Members
Maria Almira Correia, University of California, California, USA Uwe Fuhr, University Hospital of Cologne, Germany Natalie Hosea, Takeda California, Global DMPK, California, USA William Griffith Humphreys, Bristol-Myers Squibb, New Jersey, USA Takashi Izumi, Daiichi-Sankyo Company, Limited, Tokyo, Japan Jasminder Sahi, Sanofi Co., Shanghai, China Michael Zientek, Takeda California, Global DMPK, California, USA R. Scott Obach, Pfizer, Inc., Connecticut, USA
Awards Committee Committee Chair
Thomas Baillie, University of Washington, Washington, USA
Committee Members
Fred Guengerich, Vanderbilt University School of Medicine, Tennessee, USA Emily Scott, University of Kansas, Kansas, USA Ikumi Tamai, Kanazawa University, Japan Per Artursson, Uppsala University, Sweden Andrew McLachlan, The University of Sydney, Australia J. Brian Houston, University of Manchester, UK
Committee on Regulatory Affairs Committee Chair
J. Greg Slatter, Acerta Pharma LLC, Washington, USA
Committee Members
Eva Gil Berglund, Medical Products Agency, Sweden Takashi Izumi, Daiichi-Sankyo Company, Limited, Tokyo, Japan Charlene McQueen, EPA, North Carolina, USA Qing-li Wang, Center for Drug Evaluation and Safety, State Food and Drug Administration, China Lei Zhang, FDA, CDER, Office of Clinical Pharmacology, Maryland, USA
Finance Committee Committee Chair
Andrew Parkinson, XPD Consulting, Kansas, USA
Committee Members
ISSX Treasurer, James Halpert, University of Connecticut, Connecticut, USA ISSX Treasurer-Elect, Sonia de Morais, Florida, USA ISSX President, Geoff Tucker, University of Sheffield, UK Chandra Prakash, Agios, Massachusetts, USA Pat Murphy, PJMurphy Consulting, Indiana, USA Paul Hollenberg, University of Michigan Medical School, Michigan, USA Michael Voice, Cypex Ltd., UK Alan Wilson, Lexicon Pharmaceuticals, Texas, USA
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
ISSX Leadership
Membership Affairs Committee Committee Chair
Natalie Hosea, Takeda California, Global DMPK, California, USA
Committee Members
Christine Beedham, University of Bradford, UK Nina Isoherranen, University of Washington, Washington, USA David Stresser, AbbVie, Inc., Illinois, USA Ping Zhao, CDER/FDA, Office of Clinical Pharmacology, Maryland, USA
Nominations Committee Committee Chair
ISSX Past President, John O. Miners, Flinders University, Australia
Committee Members
Liz Gillam, University of Queensland, Australia Edmund Maser, University Medical School Schleswig-Holstein, Germany Hiroyuki Kusuhara, The University of Tokyo, Japan R. Scott Obach, Pfizer, Inc., Connecticut, United States J. Brian Houston, University of Manchester, UK Hiroshi Yamazaki, Showa Pharmaceutical University, Japan
Scientific Affairs Committee Committee Chair
R. Scott Obach, Pfizer, Inc., Connecticut, USA
Committee Members
ISSX President-Elect/Secretary, Tom Baillie, University of Washington, Washington, USA Eric Chan, National University of Singapore, Singapore Marcel Hop, Genentech, Inc., California, USA C. Roland Wolf, University of Dundee, UK Yoichi Osawa, University of Michigan Medical School, Michigan, USA Ylva Terelius, Karolinska Institute, Sweden Barry Jones, AstraZeneca, UK Ross McKinnon, Flinders University, Australia Mario Monshouwer, Roche, California, USA Yasushi Yamazoe, Food Safety Commission, Cabinet Office, Government of Japan, Japan Ikumi Tamai, Kanazawa University, Japan Michael Zientek, Takeda California, Global DMPK, California, USA
Staff Executive Director
Steven Kemp
Program Manager
ZoĂŤ Fuller
Program Coordinator
Diana DiAntonio
Program Associate
Blake Goodman
Meeting Manager
Ashley Pencak
Exhibits Manager
Brittany Jackson
Exhibit Sales Manager Steve Rabeor Accountant
Susan Ssentongo
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Program
Translating Preclinical Data to Human Clearance and Pharmacokinetics
Thursday, October 27 7:00 am - 6:30 pm Republic Foyer
Registration Open
7:30 am - 8:00 am Republic Foyer
Morning Refreshments
8:00 am - 8:10 am Back Bay C and D
Opening and Welcome Workshop Co-Chairs: Yingying Guo, Eli Lilly and Company and Jin Zhou, Boehringer Ingelheim
8:10 am - 10:10 am Back Bay C and D
Session 1: Short Course: Introduction to Fundamentals and Challenges in Human PK/clearance Prediction Chair: Yingying Guo, Eli Lilly and Company 8:10 - 8:40
Predicting in vivo Clearance of Drugs from in vitro Data: Where are we and where are we going? Jashvant Unadkat, University of Washington
8:40 - 9:10
Pathways toward Human Clearance Prediction: Better Tools, Fewer Rules Daniel Mudra, Eli Lilly and Company
9:10 - 9:40
Physiologically-based Pharmacokinetic (PBPK) Modeling to Support Decisions in Drug Development Ping Zhao
9:40 - 10:10
Panel Discussion with Session 1 Speakers
10:10 am - 10:30 am Republic Ballroom
Refreshment Break
10:30 am - 12:00 pm Back Bay C and D
Session 2: Methodological Aspects of Clearance Prediction for Low Clearance and Highly Bound Compounds Chair: Jin Zhou, Boehringer Ingelheim 10:30 - 11:15 Prediction for Low Clearance Compounds: Challenges and State of the Art Tools Scott Obach, Pfizer, Inc. 11:15 - 12:00 Prediction of Volume and of Intracellular Concentrations for Highly Protein Bound Compounds Using Traditional and Novel PBPK Framework Swati Nagar, Temple University
12:00 pm -1:30 pm Republic Ballroom 1:30 pm - 3:45 pm Back Bay C and D
12:00 pm - 1:30 pm
Exhibits
12:00 pm - 1:30 pm
Lunch
12:45 pm - 1:30 pm
Odd-Numbered Poster Presentations
Session 3: Predicting Non-CYP Metabolizing Enzymes Mediated Clearance Chair: Scott Obach, Pfizer, Inc. 1:30 - 2:15
Prediction of Hepatic and Extrahepatic UGT-mediated Clearance and Corresponding Drug-drug Interaction Risk within PBPK Paradigm Aleksandra Galetin, University of Manchester
2:15 - 3:00
How to Use in vitro and Computational Data to Estimate Clinical Outcomes for Aldehyde Oxidase Jeff Jones, Washington State University
3:00 - 3:45
Application of in vitro and Animal Approaches to Predict Clearance Mediated via Carboxylesterases Li Di, Pfizer, Inc.
3:45 pm - 4:30 pm Back Bay C and D
Panel Discussion with Session 2 and 3 Speakers
4:30 pm - 7:00 pm Republic Ballroom
Welcome Reception with Exhibitors
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
Program
Friday, October 28 7:00 am - 4:00 pm Republic Foyer
Registration Open
7:00 am - 8:00 am Back Bay C and D
Qualyst Transporter Solutions, LLC Industry-Sponsored Symposium: Transporter Regulation and Adaptive Responses in the Prevention of Cholestatic Hepatotoxicity Kenneth R. Brouwer, Qualyst Transporter Solutions, LLC
8:00 am - 9:00 am Republic Ballroom
Morning Refreshments Poster Networking
9:00 am - 11:45 am Back Bay C and D
Session 4: Quantitative Assessment of Hepatobiliary Transporter-mediated Clearance Chair: Aleksandra Galetin, University of Manchester 9:00 - 9:45
Utility and Challenges of in vitro Systems and Modeling Approaches in Prediction of Biliary Clearance Kim Brouwer, University of North Carolina
9:45 - 10:30
Evaluation of Preclinical Animal Models to Bridge the Translational Gap for Predicting Hepatic Transporter-mediated PK and DDIs Xiaoyan Chu, Merck
10:30 - 11:15 Predicting and Verifying Transporter-based Systemic and Tissue PK of Drugs Using Proteomics and PET Imaging Jashvant Unadkat, University of Washington 11:15 - 11:45 Panel Discussion with Session 4 Speakers 11:45 am - 1:00 pm Republic Ballroom 1:00 pm - 3:45 pm Back Bay C and D
3:45 pm - 4:00 pm Back Bay C and D
11:45 am - 1:00 pm
Exhibits
11:45 am - 1:00 pm
Lunch
12:15 pm - 1:00 pm
Even-Numbered Poster Presentations
Session 5: Human PK/clearance Prediction in Special Populations Chair: Jack Cook, Pfizer, Inc. 1:00 - 1:45
Case Studies Showing Application of PBPK Modelling for Prediction of PK in Patients with Hepatic and Renal Impairment Karen Rowland Yeo, Certara
1:45 - 2:30
PBPK Model Extrapolation to Pediatric Population: Querying Uncertainty, Defining a Role for Experimentation and Current Practices Andrea Edginton, University of Waterloo
2:30 - 3:15
Role of Pharmacogenetics-based Mechanistic Modeling in Early and Late Phase Clinical Studies Ping Zhao
3:15 - 3:45
Panel Discussion with Session 5 Speakers
Workshop Closing
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Exhibitor Directory
Translating Preclinical Data to Human Clearance and Pharmacokinetics
Absorption Systems Table 19 Absorption Systems supports pharmaceutical and medical device companies in identifying and overcoming ADMET barriers in development of drugs and medical devices. The company's mission is to continually develop innovative research tools that can be used to accurately predict human outcomes or to explain unanticipated human outcomes when they occur. Visit www.absorption.com to view our comprehensive contract services and applied research programs.
Ascendance Bio Table 14 Ascendance Biotechnology Inc. (formerly Hepregen) is the exclusive provider of in vitro ADME/Tox products & services using HepatoPac, a highly predictive microliver platform that is functional for many weeks. HepatoPac is a proven platform for metabolite profiling, metabolic stability, enzyme induction & transporter studies, investigative & mechanistic drug safety applications.
Corning Table 18 Corning® Gentest™ now offers new, innovative HepatoCells™ and TransportoCells™ cell-based model systems to complement our product portfolio of integrated tools for in vitro analysis of drug metabolism and transport. Corning® Gentest™ also provides a portfolio of traditional and custom in vitro Contract Research Services supporting drug discovery and development programs.
Hera BioLabs Table 7 Hera BioLabs implements Precision Toxicology™& Efficacy: the development of precisely gene-edited pre-clinical models for more translational data. Some examples include our severely immunodeficient (SCID) rat modes for xenografts and humanization, and a double knockout BCRP and PGP MDCK cell line with human transporters added back for permeability and transporter assays
MicroConstants Table 6 MicroConstants is a GLP-compliant Contract Research Organization focused on performing bioanalysis, drug metabolism, and pharmacokinetic analysis in support of new therapeutic development programs. We specialize in method development, validation, and sample analysis for small molecules and macromolecules using LC/MS/MS, HPLC/UV, and immunoassay techniques.
Optivia %LRWHFKQRORJ\ Table 3 Optivia Biotechnology, Inc. is an award-winning and innovative company offering drug transporter research products and services to biotechnology, pharmaceutical, government and academic organizations. Optivia offers a suite of transporter assay services and products to assist your organization to discover and design better drugs with improved therapeutic responses and safety profiles.
Phoenixbio Co., Ltd. Table 5 PhoenixBio produces the PXB-Mouse®, the world’s most widely used humanized liver chimeric mouse model for drug discovery/development. With a humanized liver consisting of up to 95% human hepatocytes, the in vivo PXB-Mouse model optimizes pre-clinical drug development with accurate human translatability for the DMPK, Safety, NASH/NAFLD, Oligonucleotide and HBV/HCV fields.
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
Exhibitor Directory
QPS Table 4 QPS is a GLP/GCP-compliant CRO that supports discovery, preclinical, and clinical drug development. We provide quality services in Neuropharmacology, DMPK, Toxicology, Bioanalysis, Translational Medicine, and Early & Late Phase Clinical Research to clients worldwide. Our 30+ regional laboratories, clinical facilities and offices are located in North America, Europe, India and Asia. For more information, visit http://www.qps.com.
Qualyst Transporter Solutions, LLC Table 16 Qualyst Transporter Solutions is the world’s exclusive provider of hepatic drug transporter products and contract research services utilizing the proprietary B-CLEAR® technology. Our integrated hepatic model, which uniquely separates and quantitates uptake, basolateral and biliary efflux, can investigate induction, hepatic accumulation, compound clearance, drug interactions, and hepatic-related toxicities such as cholestasis and hyperbilirubinemia.
Sekisui XenoTech Table 17 Sekisui XenoTech is a global Contract Research Organization with unparalleled experience and proven expertise from discovery through clinical support, providing cell and tissue-based products, screening, radiolabeling, API manufacturing, in vitro ADMET and pharmacology, in vivo ADMET and QWBA, metabolite ID and production, bioanalytical services and consulting. Learn more at www.xenotech.com.
Simulations Plus Table 20 GastroPlus™ is the leading PBPK modeling platform for prediction of absorption, DDIs, IVIVCs & population outcomes in humans & animals. DDDPlus™ & MembranePlus™ offer the mechanistic simulations of in vitro dissolution and permeability experiment. PKPlus™ rapidly generates NCA/compartmental PK modeling reports. All are complemented by our PBPK and pharmacometric modeling and simulation and clinical pharmacology support.
SOLVO Biotechnology Table 15 Drug transporter services from The Expert! With over 17 years of experience, and 450 clients in more than 40 countries, SOLVO is the leading worldwide provider of transporter services and products. Contact us today for a consultation on FDA/EMA regulatory requirements, transporter assay reagents, cell lines, or custom assay development.
Triangle Research Labs Table 1 Triangle Research Labs (TRL) is a fast-growing hepatocyte provider with products supporting in vitro evaluation of metabolism, drug-drug interactions, drug transporter activity, toxicity of drug candidates and other applications. TRL offers primary hepatocytes, hepatic non-parenchymal cells, NoSpin HepaRG™, and Quasi Vivo® modular cell culture systems. In 2016, TRL was acquired by Lonza Bioscience.
WuXi-XBL Table 2 WuXi AppTec Lab Testing Division offers comprehensive DMPK services in China (Shanghai, Suzhou and Nanjing) and in the US (Plainsboro, NJ) supporting drug development from discovery through IND-enabling, to definitive clinical ADME, including in vitro and in vivo DMPK, DDI, radiolabel ADME and bioanalytics.
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Industry-Sponsored Symposium Translating Preclinical Data to Human Clearance and Pharmacokinetics This Industry-Sponsored Symposium is a commercially-supported educational session held in conjunction with the ISSX Workshop. This session has been approved for presentation at the workshop. All attendees are invited to enjoy light refreshments and the educational content this session provides.
Friday, October 28 7:00 am - 8:00 am Back Bay C and D
Qualyst Transporter Solutions Industry-Sponsored Symposium: Transporter Regulation and Adaptive Responses in the Prevention of Cholestatic Hepatotoxicity Kenneth R. Brouwer, Qualyst Transporter Solutions, LLC Educational Needs Statement Significant efforts by both industry and academia have been targeted towards understanding the role of bile acid inhibition in the development of cholestasis and drug induced liver injury (DILI). Recent studies have implicated the role of BSEP (canalicular transporter in the liver responsible for bile acid efflux) inhibition in the etiology of cholestasis. However, these and other studies have failed to demonstrate a significant correlation between the potency of a compound to inhibit BSEP and its potential to induce cholestasis or drug induced liver injury. These studies suggest that the effects are multifactorial, and in addition to acute effects (i.e. inhibition of BSEP), there may also be chronic effects (i.e. transporter or metabolic induction, inhibition of bile acid synthesis) that alter the intracellular concentrations and hepatobiliary disposition of bile acids that need to be considered. Content Outline 1. Review hepatic transport proteins including localization and function. 2. Discuss experimental methods to assess the hepatobiliary disposition and regulation of bile acids. 3. Delineate the relative contributions of acute effects (inhibition) compared to effects observed after chronic exposure (induction) on: a. Uptake clearance b. Efflux clearance (basolateral and canalicular) c. Highlight potential species differences in these pathways. 4. Discuss the time dependence for the chronic effects (induction) on the hepatobiliary disposition of endogenously generated and exogenously administered bile acids. Learning Objectives 1. Classify hepatic transport proteins based on their localization (basolateral vs. canalicular) and function (whether these proteins are involved in hepatic uptake, hepatic basolateral or canalicular efflux of bile acids and/or xenobiotics). 2. Given an experimental method, explain what parameters can be determined accurately (hepatic uptake, biliary excretion, and/or basolateral efflux) using that system. 3. Recognize why it is critical to integrate both the acute effects of a compound in addition to the chronic effects of the compound treatment in the adaptive response of the liver to increased levels of bile acids. Identify the critical characteristics of a compound that may lead to cholestatic hepatotoxicity and DILI. 4. Identify the potential impact of species differences on hepatic transport protein function and regulation.
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
Poster Information
Abstract Poster Presentations Poster Session
Poster Presentations in Exhibit Hall
Odd-Numbered Posters
Thursday, October 27 12:45 pm – 1:30 pm
Poster Networking All Posters
Friday, October 28 8:00 am – 9:00 am
Even-Numbered Posters
Friday, October 2 12:15 pm – 1:00 pm
OUT OF COURTESY TO THE AUTHORS, PLEASE REFRAIN FROM TAKING PHOTOGRAPHS OR VIDEO RECORDING.
Posters will be attended during designated presentation and networking times. This is your opportunity to ask authors about their research. To obtain a copy of specific information that is being presented, please contact the author directly.
Poster Number Reference Guide Poster Keyword
Poster Numbers
Bioavailability
P1 and P2
Clearance Prediction
P3 - P7
Conjugation Reactions And Enzymes
P8 and P9
Covalent
P10
Cytochrome P450
P11 - P14
Differences In Metabolism (Disease)
P15
Drug Interaction
P18 - P20
Drug Metabolism
P21
Hepatic Uptake
P22
Hepatocytes
P23 and P24
In vitro–in vivo Extrapolation (IVIVE)
P25 - P28
Intrinsic Clearance
P29
Metabolism
P30
MetID
P31
Pharmacokinetic Modelling
P32
Pharmacokinetics and Pharmacodynamics
P33
Physiologically-based Pharmacokinetic (PBPK)
P34 and P35
Transporters
P36 and P37
Submit an Abstract for 14th European ISSX Meeting www.issxeuro2017.org The 14th European ISSX Meeting will deliver state-of-the-art science in a focused meeting. Contributing your research to this forum opens dialogue with your peers and brings focus to your important research area of interest.
The submission deadline is Sunday, February 26, 2017. 13
Poster Abstract Details
Translating Preclinical Data to Human Clearance and Pharmacokinetics
BIOAVAILABILITY (P1 – P2)
CYTOCHROME P450 (P11 – P14)
P1 - INHIBITION OF HUMAN INTESTINAL SULFOTRANSFERASE ACTIVITY BY DIETARY COMPOUNDS Phillip Gerk, Virginia Commonwealth University, Richmond, VA, USA
P11 - CREATION AND PRELIMINARY CHARACTERIZATION OF PREGNANE X RECEPTOR AND CONSTITUTIVE ANDROSTANE RECEPTOR KNOCKOUT RATS Kevin Forbes, Sage Labs, Inc., St. Louis, MO, USA
P2 - STRATEGIES TO INCREASE THE ORAL BIOAVAILABILITY OF PHENYLEPHRINE BY INHIBITING ITS METABOLISM THROUGH THE SULFATION PATHWAY USING PHENOLIC GRAS OR DIETARY COMPOUNDS Phillip Gerk, Virginia Commonwealth University, Richmond, VA, USA
P12 - IN VITRO METABOLITE CHARACTERIZATION OF MAK 1616 USING LC-MS-OFFLINE MICROCOIL NMR: A STRATEGY FOR IMPROVING METABOLIC STABILITY IN LEAD OPTIMIZATION Chandrashekhar Honrao, Center for Drug Discovery, Northeastern University, Boston, MA, USA
CLEARANCE PREDICTION (P3 – P7)
P13 - AN EVALUATION OF THE DRUG INTERACTION POTENTIAL OF T89 (T89®), A CHINESE HERBAL MEDICINE, USING A COOPERSTOWN 5+1 COCKTAIL IN HEALTHY SUBJECTS Liu Yang, Tasly Holding Group Co., Ltd., Tianjin, China
P3 - COMPARISON OF PRIMARY VS PROLIFERATIVE HUMAN HEPATOCYTES IN LONG-TERM CULTURE: METABOLIC CAPABILITY AND USEFULNESS FOR CLEARANCE PREDICTION Michelle Schaefer, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
P14 - PRIMARY HEPATOCYTE ISOLATION RESULTS DRAMATICALLY AFFECTED BY REDUCTION IN COLDISCHEMIA TIMES FOR HUMAN LIVER TISSUES Shiloh Barfield
P4 - APPLYING THE EXTENDED CLEARANCE MODEL TO THE KIDNEY Gabriela Patilea-Vrana, University of Washington, Seattle, WA, USA
DIFFERENCES IN METABOLISM (DISEASE) (P15) P15 - RESEARCH COLLECTION OF VARIANTS OF NORMAL AND FATTY DISEASE HUMAN LIVERS Maciej Czerwinski, Sekisui XenoTech LLC, Kansas City, KS, USA
P5 - QUANTIFYING AND COMMUNICATING UNCERTAINTY IN HUMAN PK PREDICTION Douglas Ferguson, Astrazeneca, Waltham, MA, USA
DRUG INTERACTION (P18 – P20)
P6 - IN VITRO EVIDENCE OF OATP1B1 INDUCED DRUGSERUM PROTEIN BINDING SHIFT AND ITS IMPLICATIONS ON PREDICTING DRUG CLEARANCE AND DRUG-DRUG INTERACTIONS Xuexiang Zhang, Optivia Biotechnology Inc., Menlo Park, CA, USA
P18 - DETERMINATION OF THE LIMIT OF DETECTION OF THE HUMAN LIVER MICROSOMAL CYP450 INACTIVATION ASSAY Tom Chan, Boehringer Ingelheim Pharmaceuticals, Ridgefield, CT, USA P19 - OATP1A2-MEDIATED DRUG INTERACTION OF TELMISARTAN AND PRAVASTATIN WITH CELIPROLOL Dong-Hyeok Kang, Kyung Hee University, Seoul, South Korea
P7 - CHARACTERIZATION OF A NOVEL IN VITRO METABOLISM SYSTEM FOR MEASURING INTRINSIC CLEARANCE OF LONG HALF LIFE DRUGS Martin B. Phillips, ScitoVation, LLC, Research Triangle Park, NC, USA
P20 - EXAMINING THE ROLE OF LYSOSOMAL SEQUESTRATION IN DESIPRAMINE CELLULAR DISPOSITION AND METABOLIC DRUG-DRUG INTERACTIONS Norikazu Matsunaga, Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, The University of Manchester, Manchester, United Kingdom
CONJUGATION REACTIONS AND ENZYMES (P8 – P9) P8 - UPCYTE HEPATOCYTES – METABOLICALLY COMPETENT AND PROLIFERATING HUMAN HEPATOCYTES Astrid Noerenberg, upcyte technologies GmbH, Hamburg, Germany
DRUG METABOLISM (P21)
P9 - SCALED-UP PRODUCTION OF HUMAN GLUCURONIDATED, OXIDATIVE AND GUT METABOLITES OF EPACADOSTAT, AN INVESTIGATIONAL NEW DRUG TARGETTING THE ENZYME INDOLEAMINE-2,3DIOXYGENASE 1 Frank Scheffler, Hypha Discovery Ltd., Uxbridge, United Kingdom
P21 - IN VITRO METABOLITE IDENTIFICATION AND CHARACTERIZATION USING LC-MS/MS-OFFLINE MICROCOIL NMR: IMPLICATIONS FOR METABOLIC STABILITY AND LEAD OPTIMIZATION Chandrashekhar Honrao, Center for Drug Discovery, Northeastern University, Boston, MA, USA
COVALENT (P10)
HEPATIC UPTAKE (P22)
P10 - PREDICTING THE HUMAN PHARMACOKINETICS AND TARGET ENGAGEMENT FOR A COVALENT BRUTON'S TYROSINE KINASE (BTK) INHIBITOR Donavon McConn, Takeda California, San Diego, CA, USA
P22 - TRANSPORTER REGULATION AND ADAPTIVE RESPONSES IN THE PREVENTION OF CHOLESTATIC HEPATOTOXICITY Kenneth Brouwer, Qualyst Transporter Solutions, Durham, NC, USA
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Translating Preclinical Data to Human Clearance and Pharmacokinetics HEPATOCYTES (P23 – P24)
Poster Abstract Details
PHARMACOKINETICS AND PHARMACODYNAMICS (P33)
P23 - DIFFERENTIAL HEPATOBILIARY DISPOSITION OF MMAE ACROSS MULTIPLE SPECIES REVEALED BY BCLEAR® AND TRANSPORTER CERTIFIEDTM HEPATOCYTES TECHNOLOGIES Gauri Deshmukh, Genentech Inc., South San Francisco, CA, USA
P33 - APPLICATIONS OF HARMONY SEARCH ALGORITHM FOR PK-PD PARAMETER ESTIMATION Jayant Sancheti, Tata Consultancy Services, Hyderabad, India
PHYSIOLOGICALLY-BASED PHARMACOKINETIC (PBPK) (P34 – P35)
P24 - IDENTIFICATION OF MAJOR PRIMARY AND SECONDARY METABOLITES OF SELECTED DRUGS IN DOG MICROPATTERNED HEPATOCYTE CO-CULTURES (MPCCS) USING LC/MS/MS ACQUISITION: CORRELATION WITH IN VIVO HUMAN METABOLISM Onyi Ofoma, Ascendance Biotechnology, Inc, Medford, MA, USA
P34 - THE COMBINED USE OF ADMET AND PBPK MODELING TO PRIORITIZE BACE1 INHIBITOR LEAD MOLECULES John A. DiBella, Simulations Plus, Inc., Lancaster, CA, USA P35 - PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODEL FOR INTRAMUSCULAR INJECTION OF ARIPIPRAZOLE John A. DiBella, Simulations Plus, Inc., Lancaster, CA, USA
IN VITRO–IN VIVO EXTRAPOLATION (IVIVE) (P25 – P28) P25 - PREDICTING EFFECTS ON OXALIPLATIN CLEARANCE: IN VITRO, KINETIC AND CLINICAL STUDIES OF CALCIUM- AND MAGNESIUM-MEDIATED OXALIPLATIN DEGRADATION Catherine Han, University of Auckland, Auckland, New Zealand
TRANSPORTERS (P36 – P37) P36 - IN VITRO EVALUATION OF OATP1B1- AND OATP1B3MEDIATED DRUG-DRUG INTERACTIONS USING STATINS AS PROBE SUBSTRATES Joseph Zolnerciks, Solvo Biotechnology USA, Seattle, WA, USA
P26 - PREDICTING IN VIVO HEPATOBILIARY CLEARANCE OF ROSUVASTATIN USING SANDWICH-CULTURED RAT HEPATOCYTES AND QUANTITATIVE PROTEOMICS Kazuya Ishida, University of Washington, Seattle, WA, USA
P37 - CHRONOPHARMACOKINETICS OF RHODAMINE 123: CIRCADIAN RHYTHM OF BILIARY EXCRETION IN RATS Lee Jisoo, Kyunghee university, Seoul, South Korea
P27 - IVIVE OF METFORMIN RENAL SECRETORY CLEARANCE BASED ON ACTIVITY AND PLASMA MEMBRANE EXPRESSION OF OCT2 IN HEK293 AND MDCKII CELLS Vineet Kumar, University of Washington, Seattle, WA, USA P28 - IS THE VIVO-IN VITRO CORRELATION OF CLEARANCE IN PRECLINICAL SPECIES INDICATIVE FOR THE HUMAN SITUATION? Carl Petersson, EMD Serono, Darmstadt, Germany
INTRINSIC CLEARANCE (P29) P29 - A NOVEL METHOD TO MEASURE FREE FRACTION IN HEPATOCYTE (FU,HEP) INCUBATIONS Karin Otte, Merck, Boston, MA, USA
METABOLISM (P30) P30 - A NEW SYSTEM FOR REACTION PHENOTYPING AND FM DETERMINATION-SILENSOMES Christophe Chesne, Biopredic International, St. Gregoire, France
METID (P31) P31 - CONVERGENCE OF PREDICTION AND DATA DRIVEN ANALYSIS FOR XENOBIOTIC METABOLISM Richard Lee, ACD/Labs, Toronto, ON, Canada
PHARMACOKINETIC MODELLING (P32) P32 - PREDICTING DOPAMINE D2 RECEPTOR OCCUPANCY OF ROPINIROLE IN RATS USING PET AND PHARMACOKINETIC-PHARMACODYNAMIC MODELING Ziteng Wang, The First Affiliated Hospital of Soochow University, Suzhou, China
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Speaker Abstracts
Translating Preclinical Data to Human Clearance and Pharmacokinetics
S1 - PREDICTING IN VIVO CLEARANCE OF DRUGS FROM IN VITRO DATA: WHERE ARE WE AND WHERE ARE WE GOING? Jashvant Unadkat Department of Pharmaceutics, University of Washington, Seattle, WA, USA In the drug development process, predicting CYP metabolic clearance of drugs using recombinant and human liver microsomes (HLMs) has been relatively successful. However, for several reasons predicting non-CYP and transporterbased clearance of drugs remains a challenge. First, the rate-determining step in the clearance of a drug must be identified – is it metabolism or transport or both. If transport is rate-determining, using recombinant enzymes or HLMs for predicting the in vivo clearance of drugs (IVIVE) will not be successful. Vice-versa is also true, that is using transporterexpressing cell lines will not help. If both processes are rate-determining, both need to be included in IVIVE. Second, quantification of non-CYP enzymes and transporters in various ADME tissues is needed. Such data are beginning to be available. For the latter, the mechanism of transport, plasma membrane vs. intracellular expression of transporters, both in vitro and in vivo, should be considered. For example, the membrane potential difference, which drives OCT2 transport, appears to be different in cell lines vs. kidney epithelial cells. Third, significant challenges remain in predicting in vivo efflux transport activity, especially in the liver and kidneys (e.g. MRP2). These challenges/gaps will be discussed. Supported by UWRAPT through funding from Biogen, Bristol-Myers Squibb, Gilead, Merck & Co., Genentech and Takeda. S2 - PATHWAYS TOWARD HUMAN CLEARANCE PREDICTION: BETTER TOOLS, FEWER RULES Daniel Mudra Drug Disposition, Eli Lilly & Company, Indianapolis, IN, USA For several decades drug discovery scientists have been focused on methods to produce accurate projections of human clearance with the goal of anticipating dose- and concentration-response relationships in the clinic. Recent advances in understanding human drug clearance mechanisms have led to an increase in the number of investigational tools and approaches available to translate preclinical data into more meaningful predictions of human clearance. Today these tools allow us to go beyond the prediction of a simple clearance value to now forecast the contribution of discrete clearance pathways and thereby anticipate the risk of drug-drug-interactions and exposure differences between healthy volunteers and diseased patients and other physiologically- or genomically-distinct populations. Several industrial groups have suggested novel approaches to integrate such investigational tools leading to a range of opinions on what is considered optimal for different stages of discovery. The contemporary approach requires integration of methods, selected according to individual compound properties, that allows scientists to balance the structural-diversity availed by modern medicinal chemistry with the just demands for clinical prediction accuracy to minimize development risk and maintain patient safety. S3 - PHYSIOLOGICALLY-BASED PHARMACOKINETIC (PBPK) MODELING TO SUPPORT DECISIONS IN DRUG DEVELOPMENT Ping Zhao Silver Spring, MD, USA Physiologically-based pharmacokinetic (PBPK) models have been increasingly used by drug developers to support dosing recommendations in drug development and regulatory submissions. The impact of PBPK analyses depends on predictive performance for a specific application. Confidence of using PBPK is the highest when predicting exposure change of a CYP substrate by co-administered CYP modulators. As such, predictions can be of higher impact to support dosing recommendations in drug labels. Although predicting PK in specific populations (e.g., subjects with organ impairment, pediatrics subjects) is of great interest, use of PBPK is limited at the stage of supporting study design of PK studies and not replacing PK studies. Future research should focus on establishing predictive performance of PBPK for other applications. S4 - PREDICTION FOR LOW CLEARANCE COMPOUNDS: CHALLENGES AND STATE OF THE ART TOOLS R. Scott Obach Pfizer Global Research and Development, Groton, CT, USA In drug discovery, the prevalence of newly synthesized compounds that have low intrinsic clearance (CLint) has increased. This trend may largely be due to the routine use of high-throughput metabolic lability assays over the past 15+ years and use of these data to build computational models of metabolic lability that are now leveraged in in drug design. This now places drug metabolism scientists in the difficult position of no longer being able to reliably measure CL int for many compounds other than to note that they are stable (i.e. below a limit of determination for the assay). To address this
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Speaker Abstracts
unmet need, a few different approaches have been devised to meet this technical challenge. These approaches will be described and discussed. They include the use of systems that can be incubated for longer, relay methods whereby “single� incubations can be done sequentially, and completely change the approach around by measuring formation of metabolites instead of consumption of parent compound. S5 - PK PREDICTION OF HIGHLY PROTEIN BOUND COMPOUNDS, AND PREDICTION OF INTRACELLULAR CONCENTRATIONS Swati Nagar Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, PA, USA Drug clearance and volume of distribution are two independent primary pharmacokinetic (PK) parameters. Accurate PK predictions therefore require the ability to predict both clearance and volume of distribution. Plasma protein binding of drugs can impact both the clearance of low intrinsic clearance drugs and the volume of distribution of drugs. This lecture will review our recent work on predicting the clearance as well as volume of distribution of highly plasma protein bound drugs with a physiologically-based PK (PBPK) modeling approach. Aspects of permeability-limited versus perfusionlimited PBPK models will be discussed, and the importance of modeling permeability-limited distribution for accurate volume predictions will be highlighted. Further, prediction of unbound intracellular concentrations will be included, with a review of our published compartmental approach to model explicit membranes. Finally, the utility of hybrid PK models that utilize both compartmental and PBPK approaches to predict drug PK will be discussed, with an overview of a novel model to predict volume of distribution. S6 - PREDICTION OF HEPATIC AND EXTRAHEPATIC UGT-MEDIATED CLEARANCE AND CORRESPONDING DRUG-DRUG INTERACTION RISK WITHIN PBPK PARADIGM Aleksandra Galetin Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, The University of Manchester, Manchester, United Kingdom Glucuronidation is an important clearance route for many drugs and endogenous compounds. Systematic under-prediction of hepatic clearance still represents a challenge in drug development; this trend is particularly evident for drugs with complex disposition involving multiple metabolic/non-P450 pathways and both metabolism and transporter(s). The presentation will illustrate multiple factors affecting in vitro-in vivo extrapolation of glucuronidation clearance, focusing in particular on the impact of the selection of the in vitro system and experimental conditions. Availability of appropriate scaling factors is discussed, in conjunction with the emerging UGT proteomic data. Relevance of extrahepatic (intestine, kidney) glucuronidation is illustrated, together with the use of clinical data to refine the developed physiologically-based pharmacokinetic (PBPK) models. Case examples will highlight the importance of transporters in glucuronide disposition and as sites of complex drug-drug interactions. S7 - HOW TO USE IN VITRO AND COMPUTATIONAL DATA TO ESTIMATE CLINICAL OUTCOMES FOR ALDEHYDE OXIDASE Jeffrey P. Jones Washington State University, Pullman, WA, USA Aldehyde oxidase (AO) plays an important role in drug metabolism and for the most part we are relatively ignorant of the how to predict the pharmacokinetics of AO substrates. The type of compounds that are AO substrates will be present both for reduction and oxidation reactions. While most metabolites are benign, evidence for time dependent inhibition will be presented. Normal sources of preclinical data, collected using animal models, are not reliable for either AO or the other potential drug metabolizing enzyme xanthine oxidase (XO). Thus, predicting metabolism can only be done with human preparations in vitro, and to some extent computational models of human metabolism. The simplest and least expensive system to work with is human liver cytosol (HLC), and the use and potential problems with this system will be presented. Reproducible data can be obtaining from heterologous expression of human AO, and recent work in our lab will be presented that metabolites can be readily synthesized using these systems, which can be a great benefit in drug development. One promising source of human in vivo data are humanized mice, although they are expensive, and their use has been very limited. Finally, hepatocytes can be used. Hepatocytes provide certain advantages over HLC, but again are rather expensive, and the results depend on the age and preparation of the hepatocytes. Overall, whatever system is used to collect in vitro data the in vivo results appear to under-predict in vivo clearance. I will attempt to present the caveats and advantages of using each of these systems.
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S8 - APPLICATION OF IN VITRO AND ANIMAL APPROACHES TO PREDICT CLEARANCE MEDIATED VIA CARBOXYLESTERASES Li Di Pdm, Pfizer, Groton, CT, USA Prediction of clearance for carboxylesterase (CES) substrates is of critical importance in designing prodrugs with optimal properties, projecting human pharmacokinetics and dose, and estimating drug-drug interaction potentials. A set of prodrugs were evaluated using in vitro assays (PAMPA, MDCK-LE, SGF, SIF, intestine S9 and hepatocyte stability), as well as in vivo IV, PO and PVC studies. In vitro-in vivo correlation was developed with a number of modeling approaches, including a full physiologically based pharmacokinetic (PBPK) model as well as a simplified competitive-rate analytical solution. The results helped to build confidence in human translation for CES substrates from in vitro to in vivo. S9 - UTILITY AND CHALLENGES OF IN VITRO SYSTEMS AND MODELING APPROACHES IN PREDICTION OF BILIARY CLEARANCE Kim L. R. Brouwer Division of Pharmacotherapy & Experimental Therapeutics, The University of North Carolina at Chapel Hill Eshelman School of Pharmacy, Chapel Hill, NC, USA The ability to accurately predict the biliary clearance of new chemical entities in vivo using in vitro systems is of great interest in drug discovery and development. Alterations in biliary clearance may impact hepatic, systemic and/or intestinal drug and/or metabolite exposure, and lead to unanticipated pharmacological or toxicological responses. Numerous in silico approaches, in vitro cellular systems, and mechanistic as well as physiologically-based pharmacokinetic models have been developed to predict biliary clearance. The strengths and limitations of these various approaches based on hepatic physiology will be reviewed. Examples of biliary clearance values and pharmacokinetic profiles that have been predicted successfully for numerous compounds using biliary clearance data from sandwich-cultured hepatocytes will be provided. Strategies to incorporate scaling factors and transporter abundance to improve in vitro-in vivo extrapolations will be discussed. Recommendations for categorizing new chemical entities with respect to high vs. low biliary clearance during the drug discovery process, and accurately predicting in vivo biliary clearance based on sandwich-cultured hepatocyte data will be provided. Acknowledgement: Supported by NIH R01 GM041935 S10 - EVALUATION OF PRECLINICAL ANIMAL MODELS TO BRIDGE THE TRANSLATIONAL GAP FOR PREDICTING HEPATIC OATP TRANSPORTER-MEDIATED PK AND DDIS X. Chu Merck & Co., Inc., Kenilworth, NJ, USA OATP1B1 and OATP1B3 are major human hepatic uptake transporters that play important roles in the disposition and elimination of many clinically used drugs. Currently, predicting the impact of OATP1B on pharmacokinetics and DDIs based on in vitro data alone is often challenged by lack of confidence in in vitro to in vivo extrapolation and the multiplicity of transporters involved in the elimination of OATP1B substrates. Furthermore, in vitro assays have limited utility to study the compounds with poor solubility and/or high nonspecific binding. Preclinical animal models therefore could be useful to bridge such translational gaps. However, lack of direct orthologs between rodent and human OATPs/Oatps, as well as overlapping substrate specificity between OATPs/Oatps isoforms make it difficult to understand the role of Oatps in single gene knockout models. In an attempt to overcome these limitations, Oatp1a/1b knockout and OATP1B1 and -1B3 humanized animal models have been generated. In this presentation, a comprehensive characterization of Oatp1a/1b knockout and humanized OATP1B1 and -1B3 animal models will be presented, case studies and the rational study design, application and limitations of transporter animal models to study OATP1B-mediated pharmacokinetics and DDIs will be discussed. S11 - PREDICTING AND VERIFYING TRANSPORTER-BASED SYSTEMIC AND TISSUE PK OF DRUGS USING PROTEOMICS AND PET IMAGING Jashvant Unadkat Department of Pharmaceutics, University of Washington, Seattle, WA, USA The next frontier in drug disposition is predicting transporter-based drug disposition, DDI and tissue drug concentrations. This is now possible as data on transporter protein expression in various human tissues are becoming available through proteomics by quantifying surrogate peptides using LC-MS/MS. My presentation will discuss this state-of-the-art
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Speaker Abstracts
technique, and it’s utility to quantify the expression of transporters in healthy adult and pediatric human livers, livers with HCV and alcoholic cirrhosis, human intestines and human kidneys. In addition, application of such proteomics data to predict drug disposition, through PBPK modeling and simulation, will be presented. Moreover, prediction of tissue concentrations will need to be verified using experimental data. My laboratory has pioneered the use of PET imaging to quantify tissue concentrations of drugs. How these data can be used to verify the predictions obtained by PBPK models will be discussed. Supported by UWRAPT through funding from Biogen, Bristol-Myers Squibb, Gilead, Merck & Co., Genentech and Takeda. S12 - CASE STUDIES SHOWING APPLICATION OF PBPK MODELLING FOR PREDICTION OF PK IN PATIENTS WITH HEPATIC AND RENAL IMPAIRMENT Karen Rowland Yeo Simcyp, Ltd. (a Certara Company), Sheffield, United Kingdom Application of in vitro – in vivo extrapolation (IVIVE), a “bottom-up” approach, in conjunction with physiologically based pharmacokinetic (PBPK) modelling can be used to predict the pharmacokinetics (PK) of drugs and potential drug-drug interactions in individual patients, including those whom cannot be investigated in formal clinical trials for ethical reasons. Although PBPK models are built using a mathematical framework, they are parameterized using known physiology and consist of a larger number of compartments which correspond to the different organs or tissues in the body. By their very nature, they can be used to extrapolate a dose in healthy volunteers to one in a disease population if the relevant physiological properties of the target population are available. The impact of renal failure and cirrhosis on the pharmacokinetics of many drugs is widely appreciated; indeed organ impairment can alter drug disposition by reducing the systemic clearance of drugs and affecting protein and tissue binding. Renal impairment not only affects elimination of the drug in the kidney, but also the non-renal route of drugs that are extensively metabolised in the liver. Prior simulation of the potential exposure of drugs in individuals with renal or hepatic impairment may help in the selection of a safe and effective dosage regimen. Methodologies relating to IVIVE and PBPK and the prediction of PK in subjects with organ impairment will be discussed in the presentation. In addition, issues relating to the prediction of PK in these individuals will be addressed. Case studies will be used to illustrate the application of PBPK modelling for assessment of the effect of renal and hepatic impairment on the PK of drugs in an industry setting. S13 - PBPK MODEL EXTRAPOLATION TO PEDIATRIC POPULATION: QUERYING UNCERTAINTY, DEFINING A ROLE FOR EXPERIMENTATION AND CURRENT PRACTICES Andrea N. Edginton School of Pharmacy, University of Waterloo, Waterloo, ON, Canada The EMA draft guideline on the qualification and reporting of PBPK models 1 and the FDA’s publication on best practices 2 have been in response to the pharmaceutical industries continued and increasing use of PBPK in regulatory submissions. Of these FDA submissions using PBPK, approximately 20% are in the area of pediatrics 3. Predominantly, pediatric PBPK models extrapolated from evaluated adult models are used to estimate pediatric doses for safety + PK trials that may or may not include efficacy. Development of a pediatric PBPK model that has utility requires the use of a structured workflow. Like any mechanistic model, model outcomes are only reasonable when a relevant model structure is used with parameter values that are appropriate. In the case of pediatrics, a workflow is adopted that first builds and evaluates the PBPK model based on preclinical and human adult information prior to using anatomical and physiological information to extrapolate to children 4. Model parameterization is an exciting challenge in pediatrics and this talk will delve into our current knowledge regarding the age-dependence of anatomy and physiology. This knowledge is varied in its certainty. While there is reasonable information on organ size as a function of age, there is less certainty on the agedependence of organ blood flows, and much less certainty surrounding the age-dependence of relevant protein concentrations within organs (e.g. OCT1 protein concentration/gram liver). The relative importance of this uncertainty to model outcomes for children begins with a process of sensitivity analyses in the adult model and, in some cases, in the pediatric model as well (sensitivity in an adult model does not necessarily equal sensitivity in the pediatric model). Usually, uncertainty in the parameters used for clearance extrapolation is a prime focus for query. Scenario planning based on relevant uncertainties can then be achieved (e.g. If I assume this transporter concentration is 10% vs. 50% of the concentration in adults, will this change my starting dose in the trial?). In the case of parameters that are both uncertain and sensitive, there is a place for experimentation. This talk will reflect on the role of experimentation/literature review in defining parameter ranges for inputs relevant to oral absorption in children. This includes aspects of mechanistic absorption models such as small intestinal transit time, gastric emptying time, solubility and membrane permeability. Examples of the application of the pediatric PBPK model development workflow and the role of relevant uncertainties in scenario planning will be included. The aim is to stimulate thinking around the significance of this modeling tool to current and potentially future applications in pediatrics.
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
References: 1. European Medicines Agency (EMA). Guideline on the qualification and reporting of physiologically based pharmacokinetic (PBPK) modelling and simulation. EMA/CHMP/458101/2016.http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2016/07/ WC500211315.pdf 2. Zhao, P., Rowland, M. & Huang, S.M. Clin Pharmacol Ther. 92,17–20 (2012). 3. Grillo JA. Pediatric applications of PBPK modeling and simulation in drug regulatory science: Where are we now? In: AAPS Meeting. San Diego, USA. (2014). https://zerista.s3.amazonaws.com/item_files/1f71/attachments/32090/original/186.pdf. 4. Maharaj AR, Edginton AN. CPT: Pharmacometrics and Systems Pharmacology. 3(11)e148 (2014). S14 - ROLE OF PHARMACOGENETICS-BASED MECHANISTIC MODELING IN EARLY AND LATE PHASE CLINICAL STUDIES Manuela Grimstein Silver Spring, MD, USA Genetic polymorphism in drug metabolizing enzymes may significantly alter drug exposure and subsequently lead to changes in the efficacy or safety of a drug. Quantifying this effect is an important initial step in determining the need for dose adjustment or implementation of risk management strategies. Physiologically based pharmacokinetic (PBPK) models may serve as a complementary tool for forecasting the effects of genetic polymorphism and drug interaction on drug exposure. The presentation endeavors to (i) provide the current perspectives on the application of PBPK in this area (ii) discuss the utility, predictive performance and best practices in the use of PBPK modeling for regulatory evaluation. Specifically, the drug eliglustat will be presented to illustrate, as an example, a successful application of PBPK during regulatory review and labeling recommendations.
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Poster Abstracts
P1 - INHIBITION OF HUMAN INTESTINAL SULFOTRANSFERASE ACTIVITY BY DIETARY COMPOUNDS Neha V Maharao and Phillip M Gerk Virginia Commonwealth University School of Pharmacy, Richmond, VA, USA Sulfotransferase (SULT) 1A3 is the predominant SULT isoform in the human intestine, metabolizing several phenolic compounds, including dopamine, 1-naphthol, and phenylephrine. Phenylephrine is taken orally as a decongestant, but its efficacy may be hampered by its low and variable oral bioavailability due to its extensive presystemic metabolism, mainly due to sulfation. Previous literature demonstrated phenylephrine sulfation by recombinant SULT1A3, which was confirmed in our lab. The purpose of this investigation was to determine the potential for certain dietary components or supplements to inhibit human intestinal sulfotransferase activity. Pooled human intestinal cytosol was mixed with the required cofactors and a PAPS regenerating system, and incubated with phenylephrine alone or with the dietary compounds propylparaben, vanillin, resveratrol, or quercetin. Incubations were terminated with acetonitrile, separated by HPLC using hydrophilic interaction chromatography. Phenylephrine 3-O-sulfate (PES) was directly quantitated by fluorescence detection using an authentic standard synthesized and chemically characterized in our lab. Data were analyzed using nonlinear regression in GraphPad Prism. The PES formation results revealed a Km of 37.4±2.4µM, Vmax of 118±2.7pmol/mg/min, and a Hill slope of 1.18±0.07. PES formation was completely inhibited by all four dietary compounds (IC50 values (mean (95%CI), in µM) of 9.84 (8.2-11.8), 7.4 (6.4-8.5), 43.5 (35.8-52.9), and 150 (129-175) for vanillin, resveratrol, quercetin, and propylparaben, respectively), while propylparaben and resveratrol demonstrated apparent positive cooperativity (Hill slope of -1.54±0.20 and -1.41±0.13, respectively). These data confirm the ability of certain dietary compounds to inhibit phenylephrine sulfation. Our ongoing work investigates the potential for these compounds to alter the bioavailability of orally-dosed medications. P2 - STRATEGIES TO INCREASE THE ORAL BIOAVAILABILITY OF PHENYLEPHRINE BY INHIBITING ITS METABOLISM THROUGH THE SULFATION PATHWAY USING PHENOLIC GRAS OR DIETARY COMPOUNDS Heta N Shah and Phillip M Gerk Virginia Commonwealth University School of Pharmacy, Richmond, VA, USA Purpose: Phenylephrine (PE) is the most commonly used over the counter (OTC) nasal decongestant. The problem associated with phenylephrine is that it undergoes extensive first pass metabolism in the intestinal gut wall leading to its poor and variable oral bioavailability. Sulfotransferase (SULT) 1A3 is responsible for sulfation of PE within the gut-wall. Hence it would be clinically important to study the PES (phenylephrine-3-O-sulfate) formation vs disappearance of PE in order to investigate the metabolism of PE. Methods: The developed and validated HILIC (hydrophilic interaction liquid chromatography) assay method as per the US-FDA guidelines for bioanalytical validation in our lab was used to detect the parent drug, phenylephrine (PE) and its sulfate metabolite (PES). The presented work involves the enzyme kinetic studies on inhibition of sulfation of PE with phenolic compounds using recombinant SULT enzymes and human intestinal cytosol (HIC). The enzymatic kinetic analysis was performed to calculate Km and Vmax by the Michaelis-Menten equation. Recombinant SULTs and human intestinal cytosol (HIC) systems were optimized regarding time, protein, and concentration range. In order to determine the mechanism of inhibition, a preliminary study was done to estimate the IC50 value of resveratrol using human intestinal cytosol (HIC). For the mechanism of inhibition study substrate concentration (3.12µM-200µM) and inhibitor concentration range (0-21µM) was used. A model selection criterion (MSC) was used to compare different models of inhibition. Results: The optimization experiments done with SULT1A3 and HIC indicated the reaction conditions to be used for the PES formation saturation studies. The K m values obtained with HIC was 73µM (95%C.I: 66.0-79.1) and SULT1A3 was 65µM (95%C.I: 58.1-71.2) were comparable, indicating that SULT1A3 is the major intestinal enzyme responsible for sulfation of PE. From the screening studies done with the inhibitors: resveretrol, isoeugenol and ethyl vanillin using SULT1A3 and LS180 cell line, resveratrol was selected in order to study the mechanism of inhibition as it showed the maximum inhibition in LS180 cell model as well as using the recombinant SULT1A3. The obtained IC50 for resveratrol was 12µM (95%C.I: 9.7-14) using HIC. Comparing the different models of inhibition using the MSC criteria, the non-competitive inhibition model gave the best fit with the lowest MSC value of -1.87 as compared to other models. The Km and Vmax values obtained using the non-competitive inhibition model were comparable with those obtained from the PES formation saturation study using HIC. Conclusions: Co-administration of phenolic GRAS (generally regarded as safe) or dietary compounds along with PE was a suitable strategy used to inhibit presystemic metabolism of PE. The studies done in vitro and by the use of appropriate scaling factors (amount of SULT1A3 in the gut, weight of the intestine and the fraction unbound for PE) will provide a good basis in order to predict in vivo intrinsic clearance through the sulfation pathway. The strategy of using GRAS or dietary inhibitors gave promising in vitro results and it is envisioned to confirm clinical feasibility of this approach.
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P3 - COMPARISON OF PRIMARY VS PROLIFERATIVE HUMAN HEPATOCYTES IN LONG-TERM CULTURE: METABOLIC CAPABILITY AND USEFULNESS FOR CLEARANCE PREDICTION Michelle Schaefer1, Asami Saito2, Gaku Morinaga2, Akiko Matsui2, Shinobu Suzuki2, Gerhard Schaenzle1, Daniel Bischoff1 and Roderich D. Suessmuth3 1Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany, 2Nippon Boehringer Ingelheim, Kobe, Japan, 3Technische Universitaet Berlin, Department of Chemistry, Berlin, Germany Primary human hepatocytes (PHH) are a well-established model for studying in vitro hepatic drug metabolism. The purpose of this study was to evaluate long-term cultured upcyte® human hepatocytes (UHH) as an alternative hepatocellular model for drug metabolism and clearance prediction of metabolically stable compounds. Derived from primary human hepatocytes, UHH provide a virtually unlimited source of non-transformed primary hepatocytes per donor, which is of general advantage for compound screening in a drug discovery setting. Differentiated UHH express adult hepatic markers and are responsive to prototypical inducers of cytochrome P450 enzymes 1,2. Compared to immortalized cell lines, confluent UHH retain expression and functionality of nuclear receptors and drug metabolizing enzymes with regard to major CYP, UGT and SULT at donor-specific levels3,4. We assessed the metabolic capability of UHH in sandwich culture for up to 21 days, focussing on functional in situ enzyme activity and relative mRNA expression of selected phase I and phase II enzymes. Absolute enzyme protein expression was determined by LC-MS/MS quantification. In vivo hepatic clearance (CLH) was scaled from in vitro intrinsic clearance (CLint) applying the physiologically based in vitro-in vivo direct scaling approach for a set of reference drugs with low (e.g. alprazolam, tolbutamide, warfarin, oxazepam) to intermediate (e.g. risperidone, lidocaine, midazolam) nonrenal clearance (CL nonrenal). The in vitro metabolite pattern was semi-quantitatively analysed for selected reference compounds. All data were compared to those obtained from sandwich cultures of cryopreserved PHH. In brief, UHH were found to be superior to PHH in reproducibly predicting the in vivo clearance for the subset of low CLnonrenal drugs, whereas PHH better predicted results for intermediate clearance drugs. References: 1. 1Burkard, A et al. (2012) Generation of proliferating human hepatocytes using Upcyte® technology: characterization and applications in induction and cytotoxicity assays. Xenobiotica 42:939-956. 2. 2Levy, G et al. (2015) Long-term culture and expansion of primary human hepatocytes. Nat.Biotechnol.33: 12641271. 3. 3Schaefer, M et al. (2016) Upcyte® Human Hepatocytes: a Potent In Vitro Tool for the Prediction of Hepatic Clearance of Metabolically Stable Compounds. Drug Metab Dispos 44:435-444. 4. 4Tolosa, L et al. (2016) Human Upcyte Hepatocytes: Characterization of the Hepatic Phenotype and Evaluation for Acute and Long-Term Hepatotoxicity Routine Testing. Tox. Sci. 152(1): 214-229. P4 - APPLYING THE EXTENDED CLEARANCE MODEL TO THE KIDNEY Gabriela Patilea-Vrana and Jashvant D. Unadkat Pharmaceutics, University of Washington, Seattle, WA, USA Unlike the well-stirred hepatic clearance model (WSHM), the extended clearance model (ECM) better describes the hepatic clearance of drugs that have permeability limitations and/or are substrates of hepatic drug transporters. The ECM can be applied to other eliminating organs such as the kidney. Typically, renal clearance is described by three clearance terms: glomerular filtration, secretion, and reabsorption. The limitation of this approach is that the active transport clearances (i.e. secretion and reabsorption) are not mechanistically described by individual transport clearance terms and thus it is difficult to interpret how the basolateral and luminal drug transporters work together to determine renal clearance. By applying the ECM to the kidney, we can describe the relationship between GFR, passive diffusion, basolateral, and luminal drug transporter clearance that determine renal clearance. We have identified conditions under which the renal ECM reduces such as renal clearance is described by specific clearance pathways. For example, for a drug with limited luminal reabsorption and low passive diffusion compared to its basolateral secretion, the basolateral secretion clearance will determine renal clearance despite having significant luminal secretion. Through theoretical simulations, we demonstrate the conditions needed to create the renal clearance rate-determining pathways and how these conditions manifest themselves in regard to systemic PK/PD and renal exposure. In particular, the sometimes confounding impact on systemic exposure versus renal exposure/toxicity is highlighted. In addition, the role of the fraction transported, particularly in the context of drug-drug interactions (DDI’s) under rate-determining conditions is discussed. Lastly, we have applied the renal ECM to explain the disposition of metformin. In particular, we demonstrate why basolateral secretion via OCTs is the rate-determining step to metformin renal clearance and why DDI’s with MATE inhibitors (luminal secretion) results in changes to systemic metformin exposure, even though basolateral secretion is the rate-determining step in metformin clearance. In conclusion, by applying the ECM to the kidney, we can mechanistically describe the renal clearance of drugs and how the relationship between basolateral and luminal drug transport clearance affects renal clearance and DDI prediction.
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Poster Abstracts
P5 - QUANTIFYING AND COMMUNICATING UNCERTAINTY IN HUMAN PK PREDICTION Douglas D Ferguson1, James Yates2, Peter Gennemark3 and Adrian Fretland1 1AstraZeneca, Waltham, MA, USA 2AstraZeneca, Cambridge, United Kingdom, 3AstraZeneca, Gothenburg, Sweden In drug discovery, prospective prediction of human pharmacokinetics facilitates the differentiation of possible clinical candidates and is a key step in the prediction of efficacious clinical dose, optimal dosing regimen and therapeutic index. Of equal importance to the prediction of point estimates, for each human PK parameter, is the accurate quantitation and communication of the uncertainty in the point estimates. This poster describes a ‘Monte-Carlo’ based approach to estimating prediction intervals for both primary PK parameters (such as Cl and Vss) and key secondary parameters such as Cmax, half-life & clinical dose. A number of PK parameter prediction methods (both IVIVe and allometry based) were investigated, using established test sets of clinical drugs, in order to characterize the distribution of measured (population mean) clinical PK parameter values relative to the point estimate predictions. For each method, the distribution of Log(measured/predicted) was characterized (in terms of shape, standard deviation σ and average bias) and used as an estimate of the prediction error distribution associated with that method. For prospective PK prediction for new clinical candidates, a Monte-Carlo approach was utilized to provide random samples to build posterior distributions of possible ‘true’ values for the population mean of each primary parameter. Each possible ‘true' value, resulting from the application of a particular PK parameter prediction method, was obtained by combining the point estimate prediction with a random sample from the associated prediction error distribution. The posterior distributions of possible ‘true’ values for key secondary parameters (such as efficacious dose and C max) were obtained by repeated random sampling of sets of primary parameter estimates (from the respective posterior distributions) and incorporation of each set of primary parameters values in the PK function of a relevant PKPD/efficacy model. The dose predicted to result in a specific extent of clinical efficacy was then determined for each set of possible PK parameter inputs and the resultant distribution of dose estimates assessed. Cumulative probability plots were created using the predicted distribution of possible 'true' values and used to estimate prediction intervals for each primary and secondary parameter. This approach has broad utility within drug discovery for the quantitation of risk associated with the inherent uncertainty in prospective PK prediction. Illustrative examples include quantifying the probability that the required clinically efficacious dose will exceed the maximum absorbable dose or that the population mean Cmax will exceed a defined threshold. P6 - IN VITRO EVIDENCE OF OATP1B1 INDUCED DRUG-SERUM PROTEIN BINDING SHIFT AND ITS IMPLICATIONS ON PREDICTING DRUG CLEARANCE AND DRUG-DRUG INTERACTIONS Xuexiang Zhang, Jason Baik, Mark Warren, Mirza Jahic and Yong Huang Optivia Biotechnology, Inc., Menlo Park, CA, USA Background: We recently proposed a Transporter-Induced Protein Binding Shift (TIPBS) hypothesis to describe the effects of serum proteins on transporter-mediated drug transport. This work provides in vitro evidence of drug- and transporter-dependent TIPBS effects that may substantiate hypothesis and potentially improve prediction of clearance and DDI for certain high-protein bound drugs. Methods: OATP1B1 and OATP1B3 mediated transport of give major statins and rifamipcin IC50s were measured in protein-free HBSS and human serum, using CHO cells stably expressing the transporters. Serum unbound fraction (fu) of each compound, measured with rapid equilibrium dialysis, was used to calculate substrate transport or inhibitor IC50s in serum from the constants measured in HBSS. The predicted values were contrasted to that measured from assays conducted in human serum. Results: The fu adjustment method generally under-estimated substrate uptake and inhibitor potency in serum. For examples, actual OATP1B1 mediated uptake of 5uM atorvastatin in serum (fu=3.95%) is 2.8x higher than that of HBSS with the same unbound drug; depending on the substrate used, rifampicin (fu=11%) OATP1B1 IC50 values in serum was 2.5x-4.5x lower than the predicted ones. Our data on various substrates and inhibitors with different fu indicated that the extent of underestimation were drug AND transporter dependent, possibly due to difference in drug binding affinities to serum proteins and transporters as predicted by our TIPBS models. Conclusion: Our work suggests that transporter-mediated drug uptake and its inhibition in serum may be under-predicted by simply applying unbound drug fraction to correct in vitro assay results performed in proteinfree buffers. This raises the question on whether/when is appropriate to use the conventional fu adjustment method for predicting in vivo drug clearance and DDIs without using empirical drug-dependent scaling factors. P7 - CHARACTERIZATION OF A NOVEL IN VITRO METABOLISM SYSTEM FOR MEASURING INTRINSIC CLEARANCE OF LONG HALF LIFE DRUGS Martin B Phillips, Jeffrey R Enders, David Billings, Pergentino Balbuena, Harvey J Clewell III and Miyoung Yoon ScitoVation, LLC, Research Triangle Park, NC, USA Low intrinsic clearance is often considered a desirable property of drugs as this contributes to reducing dosage frequency and magnitude, stabilizing tissue concentrations, and prolonging in vivo half-life. On the other hand, low intrinsic clearance can also present challenges in drug development and safety testing as it increases the likelihood of off-target effects, drug-drug interactions, and potential effects of long-lived metabolites. In vitro testing is a promising strategy to accurately 23
Poster Abstracts
Translating Preclinical Data to Human Clearance and Pharmacokinetics
estimate hepatic clearance and identify these potential safety concerns early in lead selection/optimization without relying on time- and money-intensive animal tests, while ensuring human relevance in the predicted outcomes. Currently available in vitro methods for intrinsic clearance prediction/measurement have limitations for slowly metabolized compounds, creating a great challenge for safety screening for early lead compounds. We have been optimizing a longlived 3D alginate-encapsulated cell culture model that is compatible with varying degrees of dynamic culture conditions along with in vitro biokinetic modeling capabilities in order to tackle this challenge. Our model can be used for both initial screening and higher tier toxicity testing during preclinical development. Novel and advanced in vitro approaches have been recently developed such as microfluidics or organotypic cultures. However, these alternative methods are time and recourse intensive, and difficult to scale for investigating metabolism where pmol quantities of metabolites are formed over long periods. We have characterized xenobiotic enzyme expression and activity in the alginate-encapsulated cells (aka [alginate] beads) using human primary hepatocytes. Based on the image and gene expression analyses of the beads, both 3D and dynamic culture conditions seem to be important to maintain metabolic competence of the encapsulated cells. After about a week’s incubation in dynamic conditions, both phase I and II enzyme expression levels returned to a level comparable to that of freshly isolated cells, showing promise in application of our model for low clearance prediction. In general, phase II enzymes including UGT, SULT and carboxylesterases recovered faster than phase I enzymes. Among the phase I enzymes, CYP2C9, 1A2, and 2D6 showed a faster recovery than CYP2E1 or 3A4. In its current form, our model can be used to increase the reliability of in vivo clearance predictions for low clearance compounds and yet still be able to provide a cost-effective and easy-to-use method comparable to the current gold standard of human primary hepatocyte suspension culture. Currently, we are testing other dynamic culture conditions that can be used with the alginate beads including flow-based bioreactor systems as well as putting together an in vitro biokinetic model to assist in vitro-to-in vivo extrapolation (IVIVE) of the results. With these further improved long term culture systems with an IVIVE tool, it will be possible to streamline clearance prediction and testing of repeated dose exposure effects of low clearance compounds. P8 - UPCYTE HEPATOCYTES – METABOLICALLY COMPETENT AND PROLIFERATING HUMAN HEPATOCYTES Astrid Noerenberg1 and Ramiro Jover2 1upcyte technologies GmbH, Hamburg, Germany, 2IIS Hospital La Fe, Valencia, Spain The capacity of human hepatic cell-based models to predict drug induced liver injury and hepatotoxicity depends on the functional performance of cells. The major limitations of primary human hepatocytes (pHH) include the scarce availability and rapid loss of the hepatic phenotype. Hepatoma cells are readily available and easy to handle, but are metabolically poor compared with pHH. Recently developed human upcyte hepatocytes offer the advantage of combining many features of pHH with the unlimited availability of hepatoma cells. We analyzed the phenotype of upcyte hepatocytes comparatively with HepG2 cells and adult pHH to characterize their functional features as a differentiated hepatic cell model. The transcriptomic analysis of liver characteristic genes confirmed that the upcyte hepatocytes expression profile comes closer to pHH than HepG2 cells. CYP activities were measurable and showed a similar response to prototypical CYP inducers when compared with pHH. upcyte hepatocytes from donor 653-03 expressed a number of endogenous CYP enzymes yet showed low levels (5 pmol/mL) of CYP2D6 activity. In the 653-03-2D6 cell strain, CYP2D6 was stably expressed with a basal activity of over 1600 pmol/mL. In comparison, HepaG2 cells completely lacked CYP2D6 activity. This enables complex metabolic profile analysis of CYP2D6 dependent drugs such as the breast cancer antiestrogen tamoxifen. Other key hepatic metabolic functions are ureogenesis and plasma protein synthesis. upcyte hepatocytes retained conjugating activities and key hepatic functions, e.g. albumin, urea, lipid and glycogen synthesis, at levels close to pHH. upcyte hepatocytes were able to produce urea with similar ureogenic rates in the cells from the adult donor (1003) to that of pHH, whereas the ureogenic rate in the upcyte cells from the neonate and 9-year old donors (422a-03 and 653-03, respectively) was low and comparable to that of HepG2 cells. These differences are likely related with the donor’s age, which is in accordance with reports that have shown a low expression of urea cycle enzymes in neonatal hepatocytes (Tolosa et al., 2014). In conclusion, combining the phenotype of pHH and the ease of handling of HepG2 cells, upcyte hepatocytes offer suitable properties to be potentially used for toxicological and metabolic assessments during drug development. P9 - SCALED-UP PRODUCTION OF HUMAN GLUCURONIDATED, OXIDATIVE AND GUT METABOLITES OF EPACADOSTAT, AN INVESTIGATIONAL NEW DRUG TARGETTING THE ENZYME INDOLEAMINE-2,3DIOXYGENASE 1 Frank Scheffler, Jonathan Steele, Liam Evans, Richard Phipps, Headley Williams and Ravi Manohar Hypha Discovery Ltd., Uxbridge, United Kingdom Metabolism of drugs often results in the formation of major circulating metabolites derived from mixed clearance pathways, and can include both primary and secondary metabolites. Human metabolism of Incyte's investigational new drug epacadostat (EPA) forms 3 major circulating plasma metabolites (Boer et al., 2016). Glucuronidation of EPA to form M9 is the dominant metabolic pathway, in conjunction with formation of an amidine M11 and an N-dealkylated metabolite, 24
Translating Preclinical Data to Human Clearance and Pharmacokinetics
Poster Abstracts
M12. Boer et al. showed that reductive metabolism by gut microbiota result in M11, which is then absorbed and further modified by CYP enzymes to form the secondary metabolite M12. Hypha's microbial biotransformation panel, comprising wild-type bacteria and fungi, provided a route to achieve formation of all three human metabolites, with several strains found able to effectively biotransform EPA. Different strains and dosing regimes were found to be optimal for production of each metabolite. Scale-up of the most productive biotransforming strains enabled the supply of high mg amounts of M9 and M11 at 95% purity to Incyte Corporation for further studies. M12 was synthesised in parallel by Incyte Corporation.
Reference: 1. Boer J., Young-Sciame R., Lee F., Bowman K., Yang X., Shi J., Nedza F., Frietze W., Galya L., Combs A., Yeleswaram S., Diamond S. The role of UGT, CYP and Gut Microbiota in the Metabolism of Epacadostat (EPA) in Humans. Drug Metab. Dispos. 2016 Jul 25. pii: dmd.116.070680. [Epub ahead of print] P10 - PREDICTING THE HUMAN PHARMACOKINETICS AND TARGET ENGAGEMENT FOR A COVALENT BRUTON'S TYROSINE KINASE (BTK) INHIBITOR Donavon McConn and Mark S Hixon Takeda California, San Diego, CA, USA There are many tools and techniques available to drug discovery scientists that aid in predicting human pharmacokinetic (PK) disposition. What has been increasingly more valuable in early clinical development is the ability to more accurately predict target engagement, and ideally an efficacious dose, and thus tailor the Phase 1 program in a safer, more efficient and more cost-effective manner. Whereas there exists a vast knowledge in predicting the human pharmacokinetic and pharmacodynamic (PD) parameters for a traditional small molecule asset, predicting the PK and PD for a covalent, irreversible inhibitor poses additional challenges. Our work presents one option for predicting the human PK, target engagement and proposed efficacious dose for an irreversible Bruton’s tyrosine kinase (Btk) inhibitor. We employed a hybrid approach to predicting the human PK. The human clearance was estimated via multi-species allometry, and the fraction absorbed and volume of distribution were estimated via a Physiologically-based (PB) approach. For the PD, predicting target engagement at a particular dose for an irreversible drug requires determination of its reactivity constant (kinact/KI) rather than its apparent IC50. By use of a novel first principles approach, we obtained an in vivo relevant kinact/KI from ex vivo studies. The approach was validated by benchmarking a competing drug engaging the same target in an ex vivo assay and then using the approach to successfully predict its reported in vivo target occupancy at multiple doses. Moreover, incorporating enzyme turnover was a critical component in the accurate prediction of the PD. This prediction was accurately confirmed during the Phase 1 clinical trial.
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Poster Abstracts
Translating Preclinical Data to Human Clearance and Pharmacokinetics
P11 - CREATION AND PRELIMINARY CHARACTERIZATION OF PREGNANE X RECEPTOR AND CONSTITUTIVE ANDROSTANE RECEPTOR KNOCKOUT RATS Kevin P Forbes and Xiaoxia Cui Horizon Discovery - SAGE Labs, St. Louis, MO, USA The nuclear receptors pregnane X receptor (PXR) and constitutive androstane receptor (CAR) are closely related transcription factors that regulate the expression of drug metabolizing enzymes, such as cytochrome P450 gene families as well as drug transporters, all directly involved in sensing and metabolizing xenobiotics, including prescription drugs. PXR and CAR are also involved in other endogenous processes, such as in inflammation, glucose homeostasis and lipid metabolism, and are thus potential drug targets themselves. Knockout and humanized mouse models of both nuclear receptors have proven useful. However, the rat being bigger in size, bears various advantages as a model system for testing drug metabolism and pharmacokinetics over the mouse, including larger blood volume for sampling, higher accuracy in dosage, and convenient continuation into carcinogenicity testing. Here we report the creation and preliminary characterization of pregnane X receptor (PXR) and constitutive androstane receptor (CAR) knockout rats, as well as their crossbred, PXR/CAR double knockout rats. Without exposing to drugs, the knockout rats differ from wild type rats in weight, implying the involvement in other metabolic pathways. Further, we treated 8-week old wild-type and null male SD rats with known rodent activators of PXR, pregnenolone-16α-carbonitrile (PCN) and CAR, 1,4-Bis-[2-(3,5dichloropyridyloxy)] benzene, 3,3′,5,5′-tetrachloro-1,4-bis (pyridyloxy) benzene (TCPOBOP). RNA was extracted from liver tissue of treated animals and analyzed via qRT-PCR (SYBR-arrays). In PCN treated null-PXR and null-PXR/CAR rats, there was loss of the activation of the Cyp3a4 family members (Cyp3a18, 3a23/3a1, 3a2) and Cyp2b2 as compared to treated wild-type rats. Conversely, in PCN treated null-CAR rats, Cyp2b2 was activated and another Cyp3a4 family member (Cyp3a9) lost activation as compared to treated wild-type rats. Both PXR and CAR single knockouts and the double knockout rats, lost the activation of Cyp2b2 after treatment with TCPOBOP. In the null-PXR and PXR-CAR rats, we observed higher basal levels of Cyp2b2 and Cyp3a4 family members (Cyp3a18, 3a23/3a1, 3a2) as compared to wildtype rats. In the null-CAR rats, we observed lower and higher basal levels of Cyp2b2 and Cyp3a9 respectively. This suggests that PXR and CAR play key regulatory roles in maintaining basal levels of drug metabolizing genes. These models alone should be useful for studying metabolism of xenobiotic compounds and hepatotoxicity. In addition, these models are also critical components for the humanization of the cytochrome P450 pathways in the SD rat. P12 - IN VITRO METABOLITE CHARACTERIZATION OF MAK 1616 USING LC-MS-OFFLINE MICROCOIL NMR: A STRATEGY FOR IMPROVING METABOLIC STABILITY IN LEAD OPTIMIZATION Chandrashekhar Honrao1, Xiaoyu Ma1, Shashank Kulkarni1, JodiAnne Wood1, Roger Kautz2, Alexander Zvonok1,3, Jason J Guo1, Michael Malamas1 and Alexandros Makriyannis1,3 1Center for Drug Discovery, Northeastern University, Boston, MA, USA 2Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA 3MAK Scientific, Boston, MA, USA In drug discovery, compounds often present with very good receptor affinity and selectivity, but are plagued by poor metabolic stability which diminishes their potential as prospective therapeutic candidates. In depth knowledge of metabolites can identify “soft spots” which provide crucial information for the optimization of these compounds to support successful drug discovery1 and can be used for generating new analogues with fewer metabolically accessible sites 2. MAK1616 is a CB2 selective agonist indicated for the treatment of pain and inflammation. In competition binding studies, MAK1616 showed high CB2 binding affinity and selectivity over CB1, but very poor in vitro metabolic stability which was further demonstrated by low bioavailability and short in vivo half-life. In order to identify the metabolites and to generate metabolically stable analogues, a systematic approach has been followed: 1) determination of in vitro metabolic stability in human, rat and mouse microsomes; 2) metabolite identification by LC-MS/MS showing the major metabolic pathway to be oxidation on the adamantyl moiety 3) biosynthetic generation of these metabolites for characterization using microcoil NMR; 4) stereo- and regiochemistry assignments using chemically synthesized monohydroxylated metabolite and its isomer; and 5) synthesis of second generation analogues in order to improve metabolic stability. Our results demonstrate that, in contrast to widely believed tertiary carbon, the labile position on adamantyl moiety is the secondary carbon and is the site of oxidation. Preliminary stability assessment of the first generation analogues, monofluoro and difluoro and keto, generated from monohydroxylated metabolites does not generate significant stability improvement compared with parent compound. Continued metabolic investigation reveals susceptibility of these analogues to further oxidation indicating that more than one secondary carbon on the adamantyl moiety needs to be blocked for metabolic stability. Indeed, we found that dihydroxylated metabolites are much more stable than monohydroxylated metabolites. Currently, we are synthesizing second generation analogues from the biosynthesized dihydroxylated metabolite in our quest towards generating metabolically stable CB2 selective analogues of MAK1616 with improved pharmacokinetic properties. References: 1. Kumar GN and Surpaneni S. Role of drug metabolism in drug development and drug discovery. Med Res Rev. 2001 Sep; 21(5): 397-411.
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Poster Abstracts
2. Scott Obach et al., Biosynthesis of Drug Metabolites and Quantitation Using NMR Spectroscopy for Use in Pharmacologic and Drug Metabolism Studies. Drug Metabolism and Disposition. 2014 Oct 42:1627–1639. P13 - AN EVALUATION OF THE DRUG INTERACTION POTENTIAL OF T89 (T89®), A CHINESE HERBAL MEDICINE, USING A COOPERSTOWN 5+1 COCKTAIL IN HEALTHY SUBJECTS Liu Yang1 and He Sun2 1Tasly Holding Group Co., Ltd., Tianjin, China, 2School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China Purpose The purpose of this study was to assess the drug interaction potential of T89 with the major cytochrome (CYP) 450 enzymes. Methods A single-center, open-label, two periods, crossover, cocktail study was applied. The probe used is called Cooperstown 5+1 cocktail probes[1], which included caffeine (CYP1A2), S-warfarin (CYP2C9) vitamin K, omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A). 24 healthy Americans were given a single dose of cocktail probes on Day1, and the pharmacokinetic (PK) profiles of the cocktail drugs without T89 were collected followed by a washout period until Day 14. From Days 15-24, oral T89 225mg twice daily were administered. On day 21, cocktail drugs were administered and the PK profiles of the cocktails were collected. The areas under the curve to the last measurable point (AUC0-t) of the five probes were compared with and without T89. Absence of a relevant interaction was assumed if the 90% confidence intervals (CIs) for the geometric Least-Square (GLS) mean Ratios for these probes with/without T89 were within 0.70-1.43 range. Results The GLS mean Ratios for these probes with/without T89 were close to unity for all CYPs. Furthermore, respective CIs were within the specified margins for all ratios except for CYP2C19 (90% CI 0.61, 1.33) and CYP2D6 (90% CI 0.48, 1.64). These findings were attributed to the intraindividual variability of metrics used. For CYP 2C19, a previous study of T89 effect on the steady-state Pharmacokinetics and pharmacodymamics of Warfarin(R- and S- warfarin) in healthy volunteers suggests that T89 have no effect on the steady state PD and PK of warfarin [2]. While R-warfarin is metabolized by CYP2C19, which indicates T89 have no effect on the CYP2C19 at the dose of 225 mg twice daily. For CYP2D6, several beta-blockers are metabolized by the CYP2D6[3]. However, in T89 Phase II and Phase III Angina trials in the US and globally, beta-blocker is one of the two allowed background medications, and were co-administered with T89 by more than 90% participants. None drug-drug interactions or drug-related SAE has been reported, which indicates T89 225mg b.i.d. has no clinically effect on CYP 2D6. Conclusion T89 225mg twice daily is not likely to have effect on the in vivo activity of the major CYP enzymes in human and therefore has no relevant potential to cause respective metabolic drug-drug interactions. P14 - PRIMARY HEPATOCYTE ISOLATION RESULTS DRAMATICALLY AFFECTED BY REDUCTION IN COLDISCHEMIA TIMES FOR HUMAN LIVER TISSUES Shiloh J. Barfield1, Cornelia Smith1, Edward LeCluyse2, Estephan Arrendondo3 and Zamas Lam4 1QPS Hepatic Biosciences, Durham, NC, USA 2LifeNet Health, Durham, NC, USA 3DTI Foundation, Barcelona, Spain, 4Dmpk, QPS, LLC, Newark, DE, USA Freshly isolated and cryopreserved primary human hepatocytes (PHH) are a common tool used for routine drug discovery screening as well as for critical in vitro drug development regulatory submissions. These hepatic cells are most commonly cultured on collagen type I coated multi-well plates, overlaid with extracellular matrix and most routinely used for assays that focus on drug metabolism, drug transport, gene expression, drug-drug interactions and cellular toxicity. While being the gold standard for these in vitro assays, PHH preparations vary tremendously in their quality and ability to function in culture for these aforementioned assays. These variations in quality can be the result of a wide range of factors including varying isolation experience and techniques used, cell handling and cell media, storage conditions, laboratory environments, etc., but having the ability to procure human livers rejected for transplant that are the best possible quality is key to good isolation and preparation results on a routine basis. Here we provide historical data to demonstrate that human liver tissues that have a minimal cold-ischemia time prior to processing are the ultimate rate limiting factors to processing the best possible tissues and in ultimately producing top quality PHH preparations. Through a series of clinical partnerships and laboratory expansions geographically, we have developed the ability to isolate hepatocytes from human tissues with dramatically reduced cold-ischemia times. On average and common in the industry for the last 20 years or more, hepatocyte isolation laboratories have been forced to attempt to isolate PHH from human liver tissues that have been subjected to 16-28 hours of cold-ischemia time from the time the liver tissue is recovered in the clinic to the time the actual PHH isolation begins. The subsequent effects of reducing this average cold-ischemia have never been analyzed until now, but anecdotally all hepatocyte researchers would prefer to have minimal cold-ischemia time on average for any liver to be processed. We are now able to isolate PHH in the United States that have an average cold-ischemia time of 8 hours and in Europe an average cold-ischemia time of 4 hours using the exact same isolation protocols and methodologies in all laboratories. As bench marks for “success” we list here comparable data showing initial cell viability %, cell yield per gram of tissue, and other cell biology profiling for freshly isolated cells but also our ability to increase the number of hepatic isolations that produce cryopreserved hepatocytes with cell biology profiles similar to the gold standard of freshly isolated PHH’s. 27
Poster Abstracts
Translating Preclinical Data to Human Clearance and Pharmacokinetics
P15 - RESEARCH COLLECTION OF VARIANTS OF NORMAL AND FATTY DISEASE HUMAN LIVERS Maciej Czerwinski1, Nicholas Hatfield1, Christopher Seib1, Charles Rotter1, Ben Roberts2, Steven Weinman2, Maura O'Neil2 and David B. Buckley1 1Sekisui XenoTech LLC, Kansas City, KS, USA 2Liver Center, Kansas University Medical Center, Kansas City, KS, USA Sekisui XenoTech has developed a Research BioBank that is a collection of normal, steatosis and steatohepatitis tissue samples gathered and characterized to facilitate the study of human liver disease with an emphasis on the progression of fatty liver disease. A portion of each of the human livers, which were harvested with the intent of transplantation but subsequently rejected for this purpose, and was obtained from the International Institute for the Advancement of Medicine or the National Disease Research Interchange is saved in the Research BioBank. Donor-specific data provided by the organ procurement organizations includes demographics, cause of death, BMI, and alcohol and diabetes history. Pathologist’s review of the H&E slides, in addition to classifying the samples in to normal, steatosis or hepatosteatitis categories, quantifies macrovesicular fat, inflammation, ballooning hepatocytes and fibrosis. Presence of fibrosis is confirmed with Masson's Trichrome staining. Paraffin blocks are available for additional studies. Tissues deposited in the bank are flash frozen in liquid nitrogen and stored at -80°C. Cells isolated from multiple tissues deposited in the bank are available as cryopreserved hepatocytes for culture in suspension or as an attached cell monolayer. These cells are suitable for an array of studies including in vivo/in vitro correlation of drug metabolism and biomarker expression that characterize fatty liver disease. The bank contains normal, steatosis and hepatosteatitis specimens, with and without a history of alcohol use. Photomicrographs of H&E slides of each tissue can be viewed at the www.xenotechllc.com. The levels of CYP2A6, CYP2C19 and CYP3A4 mRNA expression in normal (10), steatosis (19) and hepatosteatitis (11) specimens were analyzed by RT-PCR. The relative quantification of each of the enzymes was based on the ΔΔC T with GAPDH serving as an endogenous control. The relative quantification of the mRNAs was not affected by tissue pathology (ANOVA). This observation is in agreement with published reports. In conclusion, we have established a liver Research BioBank, derived from rejected transplant organs, that is focused on alcoholic and non-alcoholic fatty liver disease. P16 - ABSTRACT UNAVAILABLE P17 - ABSTRACT UNAVAILABLE P18 - DETERMINATION OF THE LIMIT OF DETECTION OF THE HUMAN LIVER MICROSOMAL CYP450 INACTIVATION ASSAY Andrea Whitcher-Johnstone, Naitee Ting, Mitchell Taub and Tom Chan Boehringer Ingelheim Pharmaceuticals, Ridgefield, CT, USA Mechanism-based inactivation of cytochrome P450s (MBI) is a potential cause of drug-drug interactions (DDI). In vivo prediction of MBIs is typically done using human liver microsomes (HLM) and involves preincubation of HLM with test compound for various durations, followed by evaluation of P450 enzyme activity. A test compound is determined to be an inactivator of P450s if loss of activity is NADPH-, time- and test compound concentration-dependent. An important part of the data analysis to determine if a test compound is a P450 inactivator involves comparing the rate of P450 activity loss in the presence of the test compound to the rate of activity loss in the vehicle control. It can be challenging to distinguish compound-dependent activity loss from non-specific activity loss in the vehicle control for very weak in vitro P450 inactivators. Nevertheless, the basic DDI prediction equation for inactivation recommended by regulatory agencies can still result in the prediction of inactivation-based DDIs in the clinic for very weak in vitro P450 inactivators. We describe a retrospective analysis of over 500 sets of rate constants of enzyme activity loss (k obs) in the presence of test compound compared to vehicle control to evaluate the sensitivity of the in vitro microsomal MBI assay. Based on our analysis, we have determined that typical HLM MBI assays can reliably discern a k obs difference of approximately 0.005 min-1 between the test compound and the vehicle control. Implications of this limitation are discussed in the context of current guidelines used to predict clinical DDI from in vitro inactivation data. P19 - OATP1A2-MEDIATED DRUG INTERACTION OF TELMISARTAN AND PRAVASTATIN WITH CELIPROLOL Dong-Hyeok Kang, Jisoo Lee, Sungjae Lee, Ju-Hee Oh and Young-Joo Lee College of Pharmacy, Kyung Hee University, Seoul, South Korea Drug transporters play an important role in drug absorption, disposition, and excretion; thus, pharmacokinetic drug interactions may occur via inhibition of these drug transporters. In this study, we evaluated the effects of telmisartan and pravastatin on the membrane transport of celiprolol. In the clinical setting, these combinations (celiprolol–telmisartan or celiprolol–pravastatin) are frequently administered to patients with stage III heart failure or metabolic syndrome. Celiprolol is a known co-substrate of the organic anion-transporting polypeptides (OATPs), which act as uptake transporters, and of P-glycoprotein (P-gp), which serves as an efflux transporter, whereas telmisartan is an inhibitor of OATPs and P-gp, and
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Poster Abstracts
pravastatin, an inhibitor of OATP1A2. Therefore, we investigated the effects of telmisartan and pravastatin on the membrane transport of celiprolol in vitro. The inhibitory effects of telmisartan and pravastatin on the uptake of celiprolol were evaluated using HEK293 cells expressing OATP1A2 and OATP2B1, and the inhibitory effect of telmisartan on the efflux of celiprolol was evaluated using multidrug resistance protein 1 (MDR1)-overexpressing MDCK II cells. Interestingly, the uptake ratio of celiprolol was 4.13 in OATP1A2-expressing HEK293 cells and less than 1 in OATP2B1-expressing HEK293 cells, which suggested that celiprolol is a substrate of OATP1A2, not OATP2B1. Telmisartan (10 µM) significantly reduced the uptake ratio of celiprolol to 2.05 in OATP1A2-expressing HEK293 cells; however, it did not inhibit the efflux of celiprolol from MDR1-overexpressing MDCK II cells. Pravastatin significantly reduced the membrane uptake of celiprolol in OATP1A2-expressing HEK293 cells in a dose-dependent manner, and the half-maximal inhibitory concentration (IC 50) was determined to be about 40 μM. In conclusion, our study suggested the potential OATP1A2-mediated drug interaction of celiprolol with telmisartan and pravastatin. However, additional in vivo studies are required to test the clinical meaning of these interactions. P20 - EXAMINING THE ROLE OF LYSOSOMAL SEQUESTRATION IN DESIPRAMINE CELLULAR DISPOSITION AND METABOLIC DRUG-DRUG INTERACTIONS Norikazu Matsunaga, Ayşe Ufuk, David Hallifax and Aleksandra Galetin Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, The University of Manchester, Manchester, United Kingdom Lysosomal sequestration of basic drugs results from increased drug ionisation at low lysosomal pH and inability of ionised drug to diffuse back into cytosol due to limited permeability of lysosomal membrane. In addition to potential therapeutic or toxicological consequences, lysosomal drug sequestration may play an important part in metabolic CYP2D6 drug-drug interactions due to role of this enzyme in metabolism of basic drugs. In the present study, we investigated the importance of lysosomal sequestration on cellular disposition of basic drug desipramine in the presence/absence of quinine (CYP2D6 inhibitor), NH4Cl (abolishes lysosome-cytosol pH gradient) and combined quinine and NH4Cl. Desipramine cell-to-medium ratio (Kp) was measured over a concentration range (0.1 to 300 µM) in plated rat hepatocytes in the absence or presence of agents and over 45 minutes. Concentrations of desipramine and its major metabolite 2-OH desipramine were monitored by LC-MS/MS. Following preliminary analysis, the effect of a potent CYP2D inhibitor with different lysosomotropic properties (fluoxetine) on desipramine Kp and metabolic clearance was investigated. Desipramine Kp increased up to a maximum of 300 at 3 µM and declined to ~13 (Kp,min, attributed to its membrane partitioning) at higher drug concentration. In the presence of 1 µM quinine, desipramine cellular distribution differed, as desipramine Kpdecreased in a sigmoidal manner from 400 (reached at 0.1 µM), highlighting the role of desipramine metabolic elimination in determining its Kp at low drug concentrations. Increase in lysosomal pH in the presence of 20 mM NH4Cl reduced desipramine Kp,max by 2-fold, but it did not alter its CYP2D-mediated metabolism at low concentrations. In addition, it did not alter the membrane partitioning of desipramine occurring at higher concentrations (comparable K p,min). The combined treatment of quinine and NH4Cl showed a decrease in desipramine Kp at lower concentrations relative to that in the presence of quinine alone, confirming its lysosomal sequestration and competition with metabolism at low concentrations. Changes in desipramine lysosomal sequestration in the presence of NH 4Cl marginally affected desipramine depletion and formation of its 2-OH metabolite. Both quinine and fluoxetine potently inhibited desipramine metabolism; however, fluoxetine showed more pronounced reduction in desipramine K p,max (40%), in agreement with its more pronounced lysosomotropic properties. Current data highlight the complexity in assessing the interplay between lysosomal sequestration and metabolism due to lysosomotropic nature of both CYP2D substrates and inhibitors and the need for further studies to elucidate the driving mechanism. P21 - IN VITRO METABOLITE IDENTIFICATION AND CHARACTERIZATION USING LC-MS/MS-OFFLINE MICROCOIL NMR: IMPLICATIONS FOR METABOLIC STABILITY AND LEAD OPTIMIZATION Chandrashekhar Honrao1, Xiaoyu Ma2, Shashank Kulkarni2, JodiAnne Wood2, Roger Kautz3, Alexander Zvonok4, Jason Guo2 and Alexandros Makriyannis2,4 1Center for Drug Discovery, Northeastern University, Boston, MA, USA 2Northeastern University, Boston, MA, USA 3Barnett Institute, Northeastern University, Boston, MA, USA 4MAK Scientific, Boston, MA, USA In drug discovery, we often see a compound with very good receptor affinity and selectivity, but plagued by poor metabolic stability which affects its desired pharmacokinetic and pharmacodynamic properties, thus diminishing its potential as a prospective clinical candidate. In depth knowledge of metabolites can identify soft spots which provide crucial information for the optimization of these compounds to support successful drug discovery1. Liquid Chromatography coupled with mass spectrometry is the most widely used analytical technique for metabolite identification. However, the exact position of the metabolic modification cannot be determined in all the cases. NMR can be a useful technique to enquire the structural details of metabolites but in early drug discovery its very difficult and expensive to get metabolites in large enough amounts for NMR analysis. However, recent developments in microcoil NMR probes has greatly improved mass sensitivity, (8-12 fold) over conventional 5 mm NMR probes, thus making it an attractive option to follow up LC-MS, for 29
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metabolite characterization2,3. These isolated and well characterized metabolites can further be utilised to generate new metabolically stable analogues where key functionalities can be introduce at metabolically labile sites which is often difficult, time consuming and costly using conventional synthetic approaches 4. MAK1616 is a CB2 selective agonist, which is indicated for the treatment of pain and inflammation. In radioligand binding studies, MAK1616 showed high CB2 binding affinity and good selectivity over CB1, but very poor in vitro metabolic stability which further translated into short in vivo half-life. In-order to identify metabolites and to generate metabolically stable analogues, systematic approach is been followed as follows, 1) Determination of in vitro metabolic stability in human, rat and mouse microsomes 2) determination of the major route of phase I metabolism as oxidation on adamantyl moiety and also identified the mono- and dihydroxylated metabolites using LC-MS/MS based metabolite identification approach 3) These metabolites were biosynthesized by scaling up microsomal incubations and characterized using microcoil-NMR. 4) Stereo/regio-chemistry assignments were done by synthesizing monohydroxylated metabolite and its isomer 5) further, second generation analogues of parent compound were synthesized by introducing different functionalities on biosynthesized metabolites and its synthetic isomer i.e. Monofluro, Difluro, O-methylation, keto etc. Results of these studies demonstrate that, secondary carbon is the labile position and site of oxidation on the adamantyl moiety and preliminary stability assessment of new second generation analogues shows encouraging trends in metabolic stability. Our work also underlines the importance of combining LC-MS with microcoil-NMR as a tool for metabolism guided drug design in early drug discovery. P22 - TRANSPORTER REGULATION AND ADAPTIVE RESPONSES IN THE PREVENTION OF CHOLESTATIC HEPATOTOXICITY Jonathan P. Jackson, Kimberly M Freeman, Weslyn W. Friley, Robert L. St. Claire III and Kenneth R Brouwer Qualyst Transporter Solutions, Durham, NC, USA In vivo concentrations of bile acids (BA) are tightly regulated through synthesis, metabolism and transport. Impaired BA canalicular efflux (basolateral and/or canalicular) may play a role in drug-induced liver injury (DILI). However, impaired BA efflux alone is not an adequate predictor of DILI, and adaptive responses in the regulation of bile acid disposition may be important factors. Chenodeoxycholic acid (CDCA) was used as a model BA to evaluate the time course of effects of chronic BA exposure on BA disposition in Transporter Certified™ sandwich-cultured human hepatocytes (SCHH). BCLEAR®technology was used to assess the hepatobiliary disposition of d8-TCA, d5-GCDCA (endogenously generated), and the intracellular total bile acid pool in SCHH following 1, 3, 6, 12, 24, 48 and 72 hours exposure to 100 µM CDCA or d5-CDCA. The mRNA content of key regulatory factors, synthetic enzymes, and transport proteins for BA was determined. The intracellular concentration (ICC) of both d8-TCA and d5-GCDCA following treatment with the solvent control remained relatively unchanged. However, in the presence of 100 µM CDCA, the ICC of both d8-TCA and d5-GCDCA were significantly reduced at each exposure time, to 10.7% of control and 14.4% of control, respectively, after 72 hours of exposure. The ICC of the total bile acid pool was significantly reduced to < 25% of solvent control. Exposure to CDCA decreased the CYP7A1 mRNA, and increased the mRNA content of BSEP and OSTα/β. Although BA synthesis was decreased, the primary driver for decreases in the intracellular concentration of bile acids was increased basolateral efflux of bile acids due to the rapid up regulation of OSTα/β. P23 - DIFFERENTIAL HEPATOBILIARY DISPOSITION OF MMAE ACROSS MULTIPLE SPECIES REVEALED BY BCLEAR® AND TRANSPORTER CERTIFIEDTMHEPATOCYTES TECHNOLOGIES Gauri Deshmukh1, Kenneth R. Brouwer2, Cyrus Khojasteh1, Violet Lee1, Ola Saad1, Ben Q Shen1 and Bianca M. Liederer1 1Genentech, Inc., South San Francisco, CA, USA 2Qualyst Transporter Solutions, Durham, NC, USA Monomethyl auristatin E (MMAE) is a very potent antimitotic agent that inhibits cell division by blocking the polymerisation of tubulin. As such, it has been used as payload in antibody-drug conjugate. The objective of this study was to compare the hepatobiliary disposition of MMAE in SCMH (mouse) SCRH (rat), SCMkH (monkey), and SCHH (human) using BClear® technology, which is an in vitro sandwich-cultured hepatocyte (SCH) technology that characterizes the hepatobiliary disposition (hepatic uptake, biliary excretion, and biliary clearance). A pilot study in rat hepatocytes was performed to identify appropriate incubation conditions (time and concentration) for the experiments. All experiments were performed in the presence of 4% BSA and an incubation time of 20 minutes. MMAE concentrations were 20 nM, 200 nM, 1000 nM and 2000 nM for mouse, rat, and monkey hepatocyte incubations, and 4 nM, 20 nM, 200 nM, and 1000 nM for human hepatocyte incubations. [3H]-taurocholate was used as a positive system control to evaluate hepatobiliary function. Data demonstrated that decreasing the temperature from 37°C to 4°C decreased the total accumulation of MMAE in hepatocytes from all species indicating involvement of hepatic uptake transporters. At 1000 nM, decreasing the temperature to 4°C, decreased the total accumulation of MMAE to 3.4 %, 5.7 %, 16.0 %, and 31.4 % of control (37°C) in mouse, rat, monkey and human hepatocytes, respectively. At 1000 nM in human hepatocytes, the total accumulation was 6.59 ± 0.362 pmol/mg protein, compared to 13.5 ± 4.65, 17.3 ± 7.11, and 18.5 ± 11.6 pmol/mg protein in mouse, rat and monkey hepatocytes, respectively. Accumulation of MMAE at 1000 nM in hepatocytes compared to the accumulation of taurocholate (positive control) was highest in rat hepatocytes (4.4X that of taurocholate), similar in mouse and monkey 30
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hepatocytes (0.7X and 0.9X, respectively) and lowest in human hepatocytes (0.12X). Kp (intracellular concentration/dose concentration) ratio at 1000 nM was highest in rat hepatocytes (2.39), similar in mouse and monkey hepatocytes (1.52 and 1.52, respectively) and lowest in human hepatocytes (0.656). The biliary excretion index (BEI) at the 1000 nM was lower in mouse and rat hepatocytes (12.3 and 13.6, respectively), and higher in monkey and human hepatocytes (32.5 and 24.8, respectively). The rapid and extensive uptake of MMAE into hepatocytes from mouse, rat and monkey hepatocytes suggests a high potential for elimination of MMAE into the bile, but was substantially less in human hepatocytes. The high degree of hepatic accumulation is consistent with involvement of hepatic uptake transporters. In addition, lower clearance values are consistent with the elimination being relatively slow compared to compounds eliminated rapidly in the bile (e.g. taurocholate). However, if biliary elimination is the only elimination route (i.e. limited or no metabolism) the extent of biliary elimination could be very high. This may be particularly relevant in the rat where the uptake of MMAE was the greatest relative to the uptake of taurocholate. P24 - IDENTIFICATION OF MAJOR PRIMARY AND SECONDARY METABOLITES OF SELECTED DRUGS IN DOG MICROPATTERNED HEPATOCYTE CO-CULTURES (MPCCS) USING LC/MS/MS ACQUISITION: CORRELATION WITH IN VIVO HUMAN METABOLISM Onyi Irrechukwu Ofoma, Yvonne Schaus, Jeannemarie Gaffney and Jared Broberg Ascendance Biotechnology, Inc, Medford, MA, USA Accurate prediction and identification of the biotransformation products of drugs/xenobiotics in preclinical studies is critical in elucidating the role of metabolites in drug safety assessment. Comparisons of the metabolites produced across species in vitro would enable the extrapolation of relevant data from preclinical studies to humans. Traditional in vitro models such as microsomes, S9 fractions and primary hepatocyte suspensions have limitations: 1) they do not express the full complement of phase I and phase II enzymes required to replicate in vivo drug metabolism and 2) they have short culture lifespans because of rapid decline in phenotypic function (for example, CYP450 activity), thus precluding the generation of all relevant metabolites. We have developed a novel model in which primary dog hepatocytes are seeded onto ECM-coated domains of optimized dimensions and subsequently co-cultivated with fibroblasts (i.e. micropatterned cocultures (MPCCs)), thus retaining key biochemical functions of in vivo liver. We incubated selected compounds such as betaxolol, diazepam and lorazepam that represent diverse chemical structures and biotransformation pathways in the dog MPCCs. Accurate identification of drug metabolites was performed using an LC/MS/MS system for data acquisition and analysis. Dog MPCCs produced major primary and secondary metabolites of the reference compounds, matching in vivo human and dog metabolites. Taken together, these data highlight the superiority of a longterm, functional tissue-engineered liver model such as the MPCC platform, over traditional models in correlating in vitro and in vivo species-specific metabolites and in identifying and predicting clinically-relevant metabolites. P25 - PREDICTING EFFECTS ON OXALIPLATIN CLEARANCE: IN VITRO, KINETIC AND CLINICAL STUDIES OF CALCIUM- AND MAGNESIUM-MEDIATED OXALIPLATIN DEGRADATION Catherine H Han, Prashannata Khwaounjoo, Andrew G Hill, Gordon Miskelly and Mark J. McKeage University of Auckland, Auckland, New Zealand Background: To date, there have been few previous attempts to apply in vitro-in vivo extrapolation methods to predicting effects on the in vivo clearance of oxaliplatin. Oxaliplatin is a platinum-based antitumor agent used widely in the clinical treatment of gastrointestinal cancer. The potential impact of calcium and magnesium on the in vitro degradation and in vivo clearance of oxaliplatin was previously unknown. We developed methods for predicting effects on oxaliplatin clearance in this study that sought to evaluate the potential impact of calcium and magnesium on the in vitro degradation and the in vivo clearance of oxaliplatin. Methods: Drug stability studies and kinetic modeling were used to explore reactions of oxaliplatin and its degradation products with calcium and magnesium in vitro. A clinical study was undertaken to determine changes in plasma concentrations of calcium and magnesium in cancer patients given oxaliplatin with or without infusions of calcium gluconate and magnesium sulfate, and their impact on oxaliplatin clearance. These in vitro and clinical datasets provided an opportunity to develop and exemplify experimental approaches for predicting effects on oxaliplatin clearance in vivo from oxaliplatin stability data generated in vitro. Results: We found that calcium and magnesium accelerated the degradation of oxaliplatin to Pt(DACH)Cl2 in chloride containing solutions in vitro. Kinetic models based on calcium and magnesium binding to a monochloro-monooxalato ring-opened anionic intermediate of oxaliplatin fitted to the in vitro degradation time-course data. In cancer patients, calcium and magnesium plasma concentrations varied and were increased by giving calcium gluconate and magnesium sulfate infusions, but they did not alter or correlate with oxaliplatin clearance. The intrinsic in vitro clearance of oxaliplatin attributed to calcium- and magnesium-mediated degradation, determined from the in vitro stability data, predicted that these degradation processes contributed less than 2.5% to the total in vivo clearance of oxaliplatin. Conclusions: Calcium and magnesium accelerate the in vitro degradation of oxaliplatin by binding to a monochloro-monooxalato ring-opened anionic intermediate. Kinetic analysis of in vitro oxaliplatin stability data predicted the contributions that calcium-, magnesium- and chloride-mediated
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degradation made to the total in vivo clearance of oxaliplatin in patients. In vitro-in vivo extrapolation methods can be used in future studies to predict potential effects on oxaliplatin clearance in vivo. P26 - PREDICTING IN VIVO HEPATOBILIARY CLEARANCE OF ROSUVASTATIN USING SANDWICH-CULTURED RAT HEPATOCYTES AND QUANTITATIVE PROTEOMICS Kazuya Ishida1, Mohammed Ullah2 and Jashvant D. Unadkat1 1University of Washington, Seattle, WA, USA 2F. Hoffmann-La Roche Ltd, Basel, Switzerland Hepatic drug disposition is determined by transporter-mediated uptake and efflux, metabolism or both. Predicting in vivo hepatobiliary clearance of drugs using in vitro data (IVIVE) is important for both drug development and investigation of drug-drug interactions. While IVIVE of metabolic clearance of drug has been successful, prediction of transportermediated clearance remains a challenge. Sandwich-cultured hepatocytes (SCH) are currently the gold standard for assessing hepatobiliary clearances of drugs. However, prediction of hepatic clearance based on SCH typically underestimate the drug’s in vivo hepatic clearance. One possible reason is that the expression of transporters in SCH may be lower than that in vivo. The aims of the present study were to determine: 1) whether sandwich-cultured rat hepatocytes (SCRH) from Sprague-Dawley (SD) rats can predict the in vivo transporter-mediated hepatobiliary clearance of rosuvastatin (RSV), and 2) whether this prediction is improved by the difference in expression of transporters between SCRH and the SD rat liver. SCRH (from TRL or Qualyst, 5-6 lots) were first pre-incubated with Ca2+-containing or Ca2+free buffer for 10 min followed by incubation for 20 min with [3H]-RSV (0.5 µM) in Ca2+-containing buffer. To inhibit all the transporters (Oatps) involved in the uptake and efflux of RSV, SCRH from the same lot were incubated in parallel with 1 mM unlabeled RSV throughout the above time periods. The radioactive content of cell lysate at various time points was counted. The sinusoidal uptake (CLs,uptake), sinusoidal efflux (CLs,efflux) and canalicular efflux (CLbile) clearance of RSV were estimated using Phoenix. Then, these clearances, scaled to that in vivo using fraction unbound in plasma (0.039) and blood:plasma ratio (0.67) of RSV in the rat, were compared with those obtained from our [ 11C]-RSV positron emission tomography (PET) imaging study in SD rat (He J et al., Mol Pharm, 11, 2745-2754 (2014)). In addition, using LC-MS/MS, we measured the expression of hepatic transporter proteins in several lots of SCRH used in the above transport experiments. RSV CLs,uptake was markedly decreased by 1 mM unlabeled RSV, suggesting that the Oatp transporters mediating this clearance were significantly inhibited. In contrast, the canalicular efflux of RSV was detected in only 2 lots of SCRH, where CLbile was much lower than CLs,uptake. SCRH significantly under-predicted the RSV CLs,uptake but well predicted the CLs,efflux and CLbile observed in our PET imaging study. The expression of Oatps, especially Oatp1b2, was significantly lower than that in the SD rat liver. In conclusion, SCRH significantly under-estimated (~5-fold) the observed in vivo CLs,uptake of RSV due to the lower expression of the uptake transporters, Oatps, that mediate the hepatic uptake of RSV. Supported by a grant from F. Hoffmann-La Roche Ltd. P27 - IVIVE OF METFORMIN RENAL SECRETORY CLEARANCE BASED ON ACTIVITY AND PLASMA MEMBRANE EXPRESSION OF OCT2 IN HEK293 AND MDCKII CELLS Vineet Kumar1, Jia Yin1, Sarah Billington2, Bhagwat Prasad1, Colin Brown2, Joanne Wang1 and Jashvant D. Unadkat1 1University of Washington, Seattle, WA, USA 2Newcastle University, Newcastle upon Tyne, United Kingdom Prediction of in-vivo renal secretory clearance of a drug from in-vitro studies (IVIVE) is important in drug development to predict renal DDI, kidney epithelial cell drug concentrations and thus renal and systemic toxicity liability. Recently, kidney epithelial primary cultures have become available, but there is limited published data on their ability to predict renal secretory clearance, nor are these cells readily available. For these reasons, alternative methods to predict renal secretory clearance of drugs are needed. Therefore, the goals of our study were to determine 1) if transporter-mediated in-vivo renal secretory clearance (CLr,sec) of metformin can be predicted using the expression and activity of OCT2 in OCT2-expressing cell lines (HEK293 and MDCKII) as well as OCT2 expression in the human kidney cortex; and 2) whether this prediction could be improved by quantifying OCT2 expression in the plasma membrane of OCT2-expressing cells. Total membrane expression of OCT2 in OCT2-expressing HEK293 and MDCKII cells, as well as in homogenates of human kidney cortex (n=5), were quantified in triplicate by quantitative targeted proteomics and LC-MS/MS. In the same batch of cells, OCT2 transport activity was determined by incubating the OCT2-expressing cells for 2 minute with [14C]metformin (5.5 µM) in Krebs-Ringer-HEPES buffer with and without the OCT2-inhibitor, cimetidine (1mM). Then, using a previously optimized biotinylation method, the fraction of OCT2 expressed in the plasma membrane of OCT2-expressing HEK293 and MDCKII cell lines was determined by LC-MS/MS. Total expression of OCT2 in HEK293, MDCKII cells and human kidney cortex was 377.5±26.8, 17.8±1.1 and 7.6±3.8 pmol/mg protein, respectively. The cortex yielded 0.3 mg protein/ mg cortical tissue. Approximately, 70% of a human kidney is the cortex (105 g). Assuming that OCT2 is the ratedetermining step in the in-vivo CLr,sec of metformin and 100% of OCT2 is expressed in the plasma membrane of HEK294 and MDCKII cells, the CLr,sec of metformin was predicted to be 47.6 and 50.4 mL/min respectively. These predictions under-predicted the in-vivo CLr,sec of metformin (417.6 mL/min) by ~8-fold. Using biotinylation, the fraction of OCT2 expressed in the plasma membrane of the HEK293 and MDCKII cells was determined to be 32.1% and 51.6% respectively. After correcting for plasma membrane expression of OCT2 in HEK293 and MDCKII cells, the CLr,sec of 32
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Poster Abstracts
metformin was predicted to be 148.2 and 97.7 mL/min respectively, which was closer to the observed in-vivo CLr,sec of metformin but still underpredicted the value by ~3 to 4-fold. One possible reason for this underprediction could be that the in-vitro and in-vivo activity of OCT2 is driven by membrane potential. Current literature reports that there is a difference in membrane potential between HEK293 (-20 mV), MDCKII cells (-35mV) and the human kidney epithelial cells (-70 mV). Taking these differences into consideration could lessen the gap in our IVIVE. In summary, IVIVE of transporter-mediated clearance of drugs needs to take into consideration the fraction of transporters expressed in the plasma membrane as well as the mechanism of transport. Acknowledgement: This work was supported in part by the Simcyp Grant & Partnership Scheme. P28 - IS THE VIVO-IN VITRO CORRELATION OF CLEARANCE IN PRECLINICAL SPECIES INDICATIVE FOR THE HUMAN SITUATION? Carl Petersson, Ugo Zanelli and Dominique Perrin EMD Serono, Darmstadt, Germany The prediction of human clearance is a central part of human dose predictions which was recently highlighted in several cooperate drug discovery strategies (Dolgos et al., 2016). Isolated hepatocytes provide an intact cellular system containing a full complement of drug metabolizing enzymes, transporters and cofactors, making them ideal for studying rates of drug metabolism corresponding to the industry needs. The limitations of extrapolations from in vitro to in vivo systems has become increasingly clear; 1) Compounds where the rate determining step in the elimination is related to transport rather than metabolism has been shown to be heavily underestimated by standard set ups. 2) Extrapolation of hepatocyte-derived intrinsic clearances (so called direct scaling) results in a systematic underestimation of the in vivo value, despite incorporation of established physiological scaling factors (SFs) and the unbound fractions in both blood and in vitro matrix (Stringer et al., 2008). There are a number of plausible explanations for this observation. Empirical approaches have been successfully applied to correct for the under-predictions observed across a range of drugs (Riley et al., 2005). In this study we utilized the method suggested by Riley to detect signals of extrahepatic pathways via in vitro –in vivo correlation (IVIVC) in preclinical species (Rat, Dog, and Monkey). The results indicated that several compounds that showed excellent correlation in the human system were underestimated in one or several preclinical species. This suggests that the understanding of the mechanisms responsible for the extrahepatic elimination in preclinical species is required to risk assess the human situation. References: 1. Dolgos H, Trusheim M, Gross D, Halle JP, Ogden J, Osterwalder B, Sedman E, Rossetti L (2016) Translational Medicine Guide transforms drug development processes: the recent Merck experience. Drug Discov Today. 21:517-26. 2. Riley RJ, McGinnity DF, Austin RP. (2005). A unified model for predicting human hepatic, metabolic clearance from in vitro intrinsic clearance data in hepatocytes and microsomes. Drug Metab Dispos 33:1304–1311. 3. Stringer R, Nicklin PL, Houston JB. (2008). Reliability of human cryopreserved hepatocytes and liver microsomes as in vitro systems to predict metabolic clearance. Xenobiotica 38:1313–1329 P29 - A NOVEL METHOD TO MEASURE FREE FRACTION IN HEPATOCYTE (FU,HEP) INCUBATIONS Karin M Otte Merck, Boston, MA, USA The presence of both phase 1 and phase 2 metabolizing enzymes, as well as transporters, makes hepatocytes an ideal tool to measure apparent in vitro intrinsic clearance (CLint,app; Brown et al, 2007). Establishing a drug’s unbound fraction in hepatocytes (fu,hep) under conditions used to measure CLint,app allows for the estimation of unbound intrinsic clearance (CLint,u) and the potential for improvement in an in vitro - in vivo correlation of CLint,u (Grime and Riley, 2006). Traditionally fu,hep has been measured using either chemically inactivated or non-viable hepatocytes by equilibrium dialysis (Austin et al, 2005) , simulations utilizing incubations at multiple hepatocyte concentrations (Giuliano et al, 2005), or the “oil spin” procedure (Nordell et al, 2013). These methods can be difficult, expensive, and/or labor intensive. Alternatively, fu,hep can be predicted from physical chemical properties or extrapolated from the measured unbound fraction in microsomes (f u,mic) (Austin et al, 2005; Kilford et al, 2008). In this work, we describe progress towards developing a novel method to readily measure binding in hepatocyte incubations. The approach involves spiking compound into suspensions of hepatocytes with reduced viability (which minimizes metabolism and any active transport) followed by centrifugation, in the absence of oil, to remove bound compound. Hepatocyte binding was evaluated in rat, dog, and human cryopreserved hepatocytes using compounds covering a range of physical chemical properties. The results from the hepatocyte binding studies were compared with values reported in the literature and measured rat f u,hep values were in good agreement with literature values. Our initial results are encouraging and warrant additional investigation into the assay. Work is ongoing to understand and optimize the assay further.
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References: 1. Austin RP, Barton P, Mohmed S, and Riley RJ (2005) The Binding of Drugs to Hepatocytes and Its Relationship to Physicochemical Properties Drug Metab Dispos 33 419-425. 2. Brown HS, Griffin M, and Houston JB (2007) Evaluation of Cryopreserved Human Hepatocyets as an Alternative in Vitro System to Microsomes for the Prediction of Metabolic Clearance Drug Metab Dispos 35 293-301. 3. Grime K and Riley RJ (2006) The Impact of In vitro Binding on In Vitro – In Vivo Extrapolations, Projections of Metabolic Clearance and Clinical Drug-Drug Interactions. Curr Drug Metab 7 251-264. 4. Giuliano C, Jairaj M, Zagiu CM, and Laufer R (2005) Direct Determination of Unbound Intrinsic Clearance in the Microsomal Stability Assay Drug Metab Dispos 33 1319-1324. 5. Kilford JK, Gertz M, Houston JB, and Galetin A (2008) Hepatocellular Binding of Drugs: Correction for Unbound Fraction in Hepatocyte Incubations Using Microsomal Binding or Drug Lipophilicity Data. Drug Metab Dispos 36 1194-1197. 6. Nordell P, Svanberg P, Bird J, and Grime K (2013) Predicting Metabolic Clearance for Drugs That are Actively Transported into Hepatocytes: Incubational Binding as a Consequence of in Vitro Hepatocyte Concentration Is a Key Factor. Drug Metab Dispos 41 836-843. 7. Zhang Y, Yao L, Lin J, Gao H, Wilson TC, and Giragossian C (2010) Lack of Appreciable Species Differences in Nonspecific Microsomal Binding J Pharm Sci 99 3620-3627. P30 - A NEW SYSTEM FOR REACTION PHENOTYPING AND FM DETERMINATION-SILENSOMES Christophe Chesne, David Steen, Yannick Parmentier, Fabrice Caradec, Corinne Pothier, Bouaita Belkacem and Fabrice Guillet Biopredic International, St. Gregoire, France Background: Drug-drug interactions can affect the safety and efficacy of NCEs. and determining which CYP enzyme(s) metabolize a candidate and their relative contribution to metabolism (fraction metabolized-fm) is important for candidate selection and regulatory submissions. Current methods suffer from numerous important deficiencies such as overestimation of individual CYP fm following RAF “correction”; tedious, costly, and time-consuming pretreatment of microsomes with antibody or chemical inhibitors; or complex correlation analyses using pooled human liver microsomes with different CYP phenotypes. Therefore, a direct method requiring no pretreatment of HLM and with a straightforward interpretation of results would deliver significant improvement to this important process. Methods: We treated pooled human HLM with mechanism-based inhibitors to irreversibly, potently, and specifically deactivate individual CYP enzymes. Using incubations performed under clearance conditions, we compared the metabolism profiles obtained with these MBI microsomes, which we call SilensomesTM, with their homologous control HLM on a CYP-by-CYP with known CYP substrates to assess the usefulness of the Silensomes TM to accurately determine which CYP enzymes are responsible for metabolism of the substrates, and the fm of those CYPs. Results: Following incubation of CYP3A4 SilensomesTM with CYP-specific substrates of CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 (three substrates), the results were that: (1) irreversible deactivation of CYP3A4 in the CYP3A4 SilensomesTM had no statistically significant effect on the other CYPs analyzed, in no case was an inhibition>10% of “offtarget” CYPs observed; and (2) 95% of the metabolism of CYP3A4-specific substrate testosterone was inhibited, and at least 80% of the metabolism of CYP3A4 substrates nifedipine and midazolam was observed. Conclusion: Irreversible, specific, and potent, mechanism-based inhibition of specific CYP enzymes in pooled HLM promises to significantly simplify the identification of CYPs that metabolize a candidate, and the determination of the fm of each CYP enzyme. P31 - CONVERGENCE OF PREDICTION AND DATA DRIVEN ANALYSIS FOR XENOBIOTIC METABOLISM Richard Lee1, Vitaly Lashin2, Andrey Paramonov2, Alexandr Sakharov2 and Alexey Aminov2 1ACD/Labs, Toronto, ON, Canada, 2ACD/Labs, Moscow, Russian Federation In early drug discovery and development, information acquired from metabolism studies plays a critical role to determine the viability of the new chemical entity. The site of biotransformation or “hotspots” are recognized through interpretation of mass spectrometric data, which ultimately leads to the elucidation of the biotransformation pathway. In the last 10 -15 years there have been a number of technological breakthroughs in both LCMS hardware and the software which handles the data from these types of instruments. However, there still lies challenges for structure elucidation of metabolites from the parent structures. In this work, we describe a new automated software protocol for detecting potential metabolites and their structure elucidation, which combines batch processing, prediction and data driven analysis through mass spectral investigation. The new software algorithm developed by ACD\Labs, was intended to be a vendor neutral platform to investigate batch processing mass spectrometry data. The implemented workflow was designed to work with several mass analyzers including various orbitrap and Q-Tof mass analyzers. Post-acquisition data processing was performed on a set of high resolution LC/MSn data files, representing a complete study of several incubation time points. The data and its associated parent structure file were automatically processed within the new software routine. Possible phase 1 and phase 2 metabolite structures were predicted and generated from an assembly based metabolism model. Potential 34
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Poster Abstracts
metabolites were detected based on the predicted list, and as a complement, a non-targeted unexpected metabolite extraction process was combined into the overall processing routine which employs a fractional mass filter within the component detection algorithm. Initially, metabolites were identified based on their accurate mass and theoretical isotopic distribution calculated from molecular formulae. Subsequently, their MS2 and MS3 spectra were extracted where available and later used to verify their structures. As part of spectral interpretation, the algorithm was able to assign fragment ions of the parent and metabolites to their respective MS2 spectra. Structures of metabolites were verified and scores were provided by comparing the assigned fragment pairs. For cases where a discrete structure was not provided, Markush notations were used, until further manual curating was performed to allow for changes to the substructure. Upon completion, both predicted and unexpected metabolites were combined into a single biotransformation map, where all related mass spectra were associated to each element in the map, and uploaded to a knowledge management system for easy data review. As an added benefit, all peak areas from their respective XICs across the incubation study were tabulated in a summary table and graphically displayed as a stability/kinetic plot. In addition a java script based web interface was developed for dissemination of results from the processing routine to supporting groups or collaborators. This web interface is browser independent provides an interactive interface which allows for easy navigation of the results. P32 - PREDICTING DOPAMINE D2 RECEPTOR OCCUPANCY OF ROPINIROLE IN RATS USING PET AND PHARMACOKINETIC-PHARMACODYNAMIC MODELING Ziteng Wang1, Chenrong Huang1, Bin Zhang2 and Liyan Miao1 1Clinical Pharmacology Lab, The First Affiliated Hospital of Soochow University, Suzhou, China, 2Department of Nuclear Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China Ropinirole, a non-ergoline dopamine agonist, was used as an alternative treatment drug of levodopa for Parkinson's disease. Current evaluation method of drug efficacy, Unified Parkinson's Disease Rating Scale, was relatively simple but subjective and crude. As several studies have found that clinical response of antipsychotic treatment and the presence of extrapyramidal side effects (EPS) are correlated with the degree of occupancy of dopamine D 2 receptors as measured in striatum. The occupancy range between 60 to 70 % is required to observe antipsychotic effect and EPS are likely to occur above a threshold of 80% occupancy[1, 2]. The purpose of the present study was to assess the efficacy of antiparkinsonian drug ropinirole in vivo in rodents through positron emission tomography, using 18F-fallypride as the radiotracer, and explore dopamine receptor occupancy (RO) and plasma concentration relationship by pharmacokineticpharmacodynamic (PK-PD) modeling. Rats after ropinirole treatment of four dose levels (5 mg/kg, 15 mg/kg, 30 mg/kg and 60 mg/kg) underwent series of plasma collections and 18F-fallypride PET scans using static, three-dimensional mode acquisition. Ropinirole concentrations in plasma were determined and then analyzed. Modified binding potential (BP) and receptor occupancy were calculated with PET data through a Simplified Reference Tissue Model (SRTM)[3]. Plasma concentration and receptor occupancy set as pharmacokinetic and pharmacodynamic parameters separately were then linked for model estimation by WinNonlin. Compartment models were evaluated for pharmacokinetic model. Pharmacodynamic model used in analysis was an Emax model linked to pharmacokinetic compartment via an effect compartment[4]. Plasma ropinirole eliminated fast after administration under four dose levels. Modified BP showed both dose-dependent decrease and time-dependent increase manners. Both PK and PD parameters derived from PK-PD analysis underwent bootstrap validation. Plasma concentration inducing 50% RO (EC50) calculated by PK-PD model was 1390.70 ng/mL. In summary, our data supports that ropinirole has a relative fast kinetics in plasma and can compete with the binding of 18F-fallypride to dopamine D2 receptors in the striatum. And we demonstrate dose- and concentrationdependent dopamine D2 receptor occupancy through pharmacokinetic-pharmacodynamic model. This study provides useful and fundamental information for further non-human primate and human PET experiments on the binding of agonist to D2 receptor. PK-PD modeling approaches using drug dose and concentration to predict associated receptor occupancy and clinical effect may be useful in the selection and optimization of “therapeutic window�. References: 1. Kapur, S., et al., Relationship between dopamine D-2 occupancy, clinical response, and side effects: A doubleblind PET study of first-episode schizophrenia. American Journal of Psychiatry, 2000. 157(4): p. 514-520. 2. Kegeles, L.S., et al., Dose-Occupancy Study of Striatal and Extrastriatal Dopamine D-2 Receptors by Aripiprazole in Schizophrenia with PET and F-18 Fallypride.Neuropsychopharmacology, 2008. 33(13): p. 3111-3125. 3. Lammertsma, A.A. and S.P. Hume, Simplified reference tissue model for PET receptor studies. Neuroimage, 1996. 4(3): p. 153-158. 4. Kim, E., et al., Predicting brain occupancy from plasma levels using PET: superiority of combining pharmacokinetics with pharmacodynamics while modeling the relationship. Journal of Cerebral Blood Flow and Metabolism, 2012. 32(4): p. 759-768.
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Translating Preclinical Data to Human Clearance and Pharmacokinetics
P33 - APPLICATIONS OF HARMONY SEARCH ALGORITHM FOR PK-PD PARAMETER ESTIMATION Jayant S Sancheti, Shyam S Das and R Narayanan Tata Consultancy Services, Hyderabad, India Pharmacokinetic (PK) and Pharmacodynamic (PD) parameters estimation using compartmental modeling approach employs a) in vivo data such as plasma-concentration, time-response, etc., b) a compartmental PK-PD model, c) initial PK-PD parameters and d) optimization of initial parameters using optimization algorithms. Initial parameters values play a critical role in the estimation of PK-PD parameters with minimal standard errors. The available approaches to obtain them such as non-compartmental analysis, educated guess based on PK-PD parameter information of known compounds etc. do not guarantee success all the times. We are in the process of developing software for PK-PD data analyses and as part of this initiative, became interested in the study of the applications of Harmony Search Algorithm along with optimization algorithms such as Nelder-Mead for the robust estimation of PK-PD parameters. Harmony Search Algorithm1, (HSA) is a metaheuristic algorithm, whose applications to a number of areas such as power systems, medical science, control systems, construction design, information technology etc. are documented in literature; however, it is significant to note that a) there are no reports in literature on its applications to PK-PD data analyses, specifically to problems that involve searching of parameters space, for example, initial PK-PD parameter estimation problems. An indepth analysis of the principle of the HSA optimization algorithm prompted us to believe that it can be applied to initial PKPD parameter estimation. We undertook a study on the application of HSA for initial parameter estimation, followed by optimization using known optimization method, Nelder-Mead and using a) 15 PCT data b) 3 response-concentration data and c) five response-time data. The data used in the present study is taken from literature2. The Compartmental models2 that are used in the analyses fall into following classes a) Fifteen Pharmacokinetic and eight Pharmacodynamic models b) Thirteen algebraic and ten differential equation models. The initial bounds employed in the present study are user defined and the range is intentionally chosen to be large to test the efficiency of the method. Based on the in-depth analyses of the estimated PK-PD parameters using HSA algorithm, and Nelder-Mead method, we observed that a) HSA is a promising method that can be used for the estimation of initial PK-PD parameters, which converge to optimal PK-PD parameters when used along with Nelder-Mead method b) The standard errors of the literature and HSA based parameter values are comparable c) The success rate (percentage of case studies with optimal parameter values) of the new approach is i) 80.0% in the case of Pharmacokinetic models ii) 100.0% in the case Pharmacodynamic models ii) 84.62% in the case of algebraic models iv) 90.0% in the case of differential equations models and v) 86.96% for the total case studies. References: 1. Wang X., Gao X., Zenger K. An Introduction to Harmony Search Optimization Method, Springer Briefs in Applied Sciences and Technology, 2015, P 5-11. 2. Gabrielsson, J., Weiner, D. Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications, 4th Edition, Swedish Pharmaceutical Press, Sweden, 2006. P34 - THE COMBINED USE OF ADMET AND PBPK MODELING TO PRIORITIZE BACE1 INHIBITOR LEAD MOLECULES John A. DiBella, Viera Lukacova and Michael Lawless Simulations Plus, Inc., Lancaster, CA, USA Alzheimer’s disease (AD) is a progressive neurodegenerative disease, and it has been shown that amyloid plaques are present in the brain of AD patients. ß-secretase 1 (BACE1) catalyzes the rate limiting step in amyloid ß formation, and significant research effort has recently been devoted to the study of BACE1 inhibitors to stop or reduce the production of amyloid plaques and, potentially, treat AD. When designing BACE1 inhibitor lead molecules for potential oral delivery, careful consideration needs to be given to not only potency but also “druggability” - sufficient absorption characteristics, metabolic stability, and brain penetration should also be considered. Our objective was to utilize the combination of quantitative structure-activity relationship (QSAR) and physiologically-based pharmacokinetic (PBPK) modeling to screen literature BACE1 inhibitors and prioritize the best lead molecules according to predicted ADME properties and brain concentration levels. The ChEMBL database was first queried for compounds targeting BACE1, which resulted in 7,700 records. The data set was then filtered so that only compounds without peptide backbones and with valid BACE1 IC50 values remained, reducing the size of the data set to below 1,000. Next, compounds which contained non-druglike fragments, e.g. Michael acceptors, quinones, and aromatic nitro, were eliminated, and the compounds which remained were clustered into families with the same scaffold. Artificial neural network ensemble (ANNE) models in ADMET Predictor™ were applied to predict key physicochemical and cytochrome P450 metabolism parameters (aqueous and biorelevant solubility, logD vs.pH, pKa(s), gastrointestinal permeability, plasma protein binding, CLint, etc.) for input into the PBPK models. Oral absorption for the compounds was simulated using the GastroPlus™ Advanced Compartmental Absorption and Transit™ (ACAT™) model in humans under fasted conditions, with systemic distribution and elimination modeled using the GastroPlus PBPKPlus™ Module. The in silico PBPK simulations predicted oral bioavailability, along
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Poster Abstracts
with total and unbound concentrations in brain and plasma. The predicted unbound brain concentrations were then compared with the measured BACE1 IC50 values in order to prioritize lead candidates. P35 - PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODEL FOR INTRAMUSCULAR INJECTION OF ARIPIPRAZOLE Azar Shahraz, Jessica Spires, John A. DiBella and Viera Lukacova Simulations Plus, Inc., Lancaster, CA, USA Aripiprazole is an atypical antipsychotics drug that is widely used in the treatment of agitation associated with schizophrenia, schizoaffective disorder, schizophreniform disorder or bipolar I disorder. It has been reported [1] that intramuscular injection of aripiprazole was more effective than placebo in these patient populations. It is also valuable for patients who are unable or unwilling to take oral medication. A mechanistic model was developed to describe the disposition of aripiprazole at the site of intramuscular injection. Local binding, clearance, and blood flow can be specified, with other muscle characteristics similar to those described for muscle tissue by the PBPK model. An absorption/PBPK model for aripiprazole pharmacokinetics (PK) after intravenous (IV) and intramuscular (IM) administration was developed using GastroPlus™ 9.0 (Simulations Plus, Inc.). The program’s Advanced Compartmental Absorption and Transit (ACAT™) model described the intestinal absorption of the drug, while PK was simulated with its PBPKPlus™ module. Physiologies were generated by the program’s internal Population Estimates for Age-Related (PEAR) Physiology™ module. The perfusion-limited tissue model was used to describe drug distribution in all tissues. Tissue/plasma partition coefficients (Kps) were predicted using Lukacova (default) method. The physicochemical properties of the drug were collected from the experimental published studies or estimated by ADMET predictor v7.2 (Simulations Plus, Inc.). Aripiprazole PBPK model was fitted against reported plasma concentration-time (Cp-time) profile after 2mg IV administration [2]. The distribution was predicted from tissue volumes and Kps, the clearance was fitted to match the Cptime profile. The same PBPK model was then used to predict aripiprazole PK after various of IM doses (1 mg-7.5 mg) and the predictions were compared to observed data [2]. Majority of the predicted Cmax and AUCs were within 20% of the observed data. The Cmax for 5mg dose had higher prediction error (39%). The results show that the model for intramuscular injection provides adequate prediction of aripiprazole’s pharmacokinetics. References: 1. Sanford, M., Scott, L. J., Intramuscular Aripiprazole: A Review of its Use in the Management of Agitation in Schizophrenia and Bipolar I Disorder, CNS Drugs 2008; 22 (4): 335-352. 2. Boulton, D. W., Kollia, G., Mallikaarjun, S., Komoroski, B., Sharma, A., Kovalick, L. J., and Reeves, R. A., Pharmacokinetics and Tolerability of Intramuscular, Oral and Intravenous Aripiprazole in Healthy Subjects and in Patients with Schizophrenia, Clin Pharmacokinet 2008; 47 (7): 475-485. P36 - IN VITRO EVALUATION OF OATP1B1- AND OATP1B3-MEDIATED DRUG-DRUG INTERACTIONS USING STATINS AS PROBE SUBSTRATES Beáta Tóth1, Viktória Juhász1, Ildikó Nagy1, Zsuzsanna Gáborik1, Emese Kis1, Joseph K. Zolnerciks2 and Erzsébet Beéry1 1SOLVO Biotechnology, Budaörs, Hungary, 2SOLVO Biotechnology USA, Seattle, WA, USA HMG-CoA inhibitors (statins) are among the most prescribed medications in the United States. As a result, it is almost unavoidable that drugs in development will ultimately be co-administered with statins. Statins are generally well tolerated in humans, but adverse effects associated with myopathy have been reported, and range from muscle pain to fatal rhabdomyolysis. Because of this risk, any drug-drug interaction (DDI) that might cause an increase in statin systemic exposure is of particular clinical importance, and should be identified early in the drug development process. There are numerous reports of clinically relevant DDIs involving statins, the majority of which are ascribed to OATP interactions, with or without contributions from other transporters and drug metabolizing enzymes. OATPs are also among the most often cited transporters mediating clinically relevant DDIs, often due to interaction with statins. Preclinical evaluation of the potential DDI risk between statins and drugs in development is therefore of particular importance. In order to further characterize the current in vitro tools used to assess the risk of OATP-mediated DDIs, we have validated the use of stable OATP1B1- and OATP1B3-expressing HEK293 cell lines using the range of commercially available statins. Seven statins were utilized in this study: lovastatin, simvastatin, pravastatin, fluvastatin, atorvastatin, rosuvastatin and pitavastatin. Active uptake of selected statins was studied in HEK293-OATP1B1 and HEK293-OATP1B3 cell lines. Time-dependent and transporter-specific transport was measured using atorvastatin, pravastatin, rosuvastatin and pitavastatin as probe substrates in both OATP1B1-and OATP1B3-expressing cell lines. However, when fluvastatin was used as a probe, only moderate OATP-specific transport was observed, due to high passive diffusion in a mock-transduced control cell line. Similarly, OATP-mediated transport could not be detected using lovastatin or simvastatin due to high passive diffusion. Subsequently, concentration-dependent transport kinetics were evaluated using pravastatin, fluvastatin, pitavastatin, rosuvastatin and atorvastatin. Furthermore, the utility of the assay to assess DDI risk was determined using a variety of high- and low-affinity inhibitors with atorvastatin or pitavastatin utilized as probe substrates. All IC50 values obtained were 37
Poster Abstracts
Translating Preclinical Data to Human Clearance and Pharmacokinetics
within the expected range. In summary, the use of one or more statins as probe substrates in the OATP1B1 and OATP1B3 transporter inhibition assay can be a useful tool for the in vitro study of potential drug-drug interactions and substrate-dependent inhibition involving this clinically important class of drugs. P37 - CHRONOPHARMACOKINETICS OF RHODAMINE 123: CIRCADIAN RHYTHM OF BILIARY EXCRETION IN RATS Lee Jisoo Kyunghee University, Seoul, South Korea The administration of the drug at an appropriate time based on the chronopharmacokinetics studies increases the efficiency and decreases side effects, because the ADME of drug vary depending on biological circadian rhythm. Recently it was reported that biliary efflux transporter such as P-glycoprotein and Multidrug resistance protein 2 is regulated by clock gene and fluctuated with 24-hour period. The purpose of this study was to investigate the chronopharmacokinetic properties of Rhodamine 123, a representative substrate of P-glycoprotein (P-gp) and Multidrug resistance protein 2 (Mrp2). Rats and mice maintained under a 12 h light (Zeitgeber time (ZT) 0~ ZT 12), 12 h dark cycle with ad lib feeding for 3 weeks. After entrainment, rats received i.v. administration of 2 mg/kg of Rhodamine 123 at ZT 0, ZT 6, ZT 12 and ZT 18. Plasma and bile were collected for 2h after each dosing and tissue samples (liver, heart, kidney, small intestine) were taken at 2 h after administration. Rhodamine 123 was quantified using HPLC with fluorescence detection. Quantitative PCR was performed for an expression of mRNA of P-gp and Mrp2 at each ZT times in mice. The plasma concentration profile, AUC and total CL of Rhodamine 123 showed a weak daily rhythm but were not statistical significance with ZT times (ANOVA, P>0.05) The heart, small intestine, and kidney concentration and K p,heart, Kp,small intestine of Rhodamine 123 were not statistically different also with ZT times. However, the liver concentration, Kp,liver, and CLbile, l-b of Rhodamine 123 showed clear circadian oscillation with 24-hour period. The CLbile, l-b of Rhodamine 123 was significantly lower and the liver concentration and Kp,liver were significantly higher at ZT 12 in rats (Table 1). In additions, as reported, mRNA expression of P-gp and Mrp2 in the liver showed a circadian rhythm with a peak level at ZT 12. Considering a time lag between the mRNA and protein expression profiles for efflux transporters (about 6 hour), these results suggested that circadian oscillation of liver concentration of Rhodamine 123 may be attributed to biliary excretion of Rhodamine 123 with daily rhythm by circadian expression of biliary efflux transporters. Table 1
Liver concentration (ng/ml) Kp,Liver, CLbile, l-b (ml/min/kg)
Light period ZT 0 1031.6±289.1
ZT 6 1292.3±210.7
Dark period ZT 12 2151.7±208.9
ZT 18 898.6±71.3
34.59±10.83 0.147±0.045
47.87±8.845 0.115±0.017
83.91±14.04 0.062±0.020
37.45±1.76 0.184±0.016
Reference: 1. Murakami Y, Higashi Y, Matsunaga N, Koyanagi S, and Ohdo S (2008) Circadian clock-controlled intestinal expression of the multidrug-resistance gene mdr1a in mice. Gastroenterology 135:1636–1644.
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Translating Preclinical Data to Human Clearance and Pharmacokinetics BIOAVAILABILITY, P1, P2
INTRINSIC CLEARANCE, P29
CLEARANCE PREDICTION, S2, S9, S13, P3, P4, P5, P6, P7
LC-MS, MICROCOIL NMR, P12
CONJUGATION REACTIONS AND ENZYMES, P1, P2, P8, P9 COVALENT, P10 CYTOCHROME P450, P8, P9, P11, P12, P13, P14 DIFFERENCES IN METABOLISM (DISEASE), P15 DIFFERENCES IN METABOLISM (SPECIES, GENDER, AGE, DISEASES), P8 DISPOSITION, P4 DOPAMINE AGONIST; POSITRON EMISSION TOMOGRAPHY; RECEPTOR OCCUPANCY; PHARMACOKINETICS AND PHARMACODYNAMICS; PHARMACOKINETIC MODELLING, P32 DRUG DISCOVERY AND DEVELOPMENT, S1, S4, S10, P5, P12, P14 DRUG INTERACTION, S10, P6, P13, P14, P18, P19, P20 DRUG METABOLISM, LC/MSMICROCOIL NMR, LEAD OPTIMIZATION, METABOLIC STABILITY, LEAD DIVERSIFICATION, P21
METID, DATA-PROCESSING, PREDICTION, PLATFORMAGNOSTIC, P31 METABOLISM, S7, P9, P12, P14, P24, P30, P31 NEXT GENERATION LIVER MODELS, P24 NON-P450 PHASE I ENZYMES, S7 PHARMACOKINETIC MODELLING, S3, S5, S14, P4, P5, P32 PHARMACOKINETIC PREDICTION, S7, S9, S10, P4, P10 PHARMACOKINETICS AND PHARMACODYNAMICS, P9, P32, P33 PHYSIOLOGICALLY-BASED PHARMACOKINETIC (PBPK), S5, S13, P10, P34, P35 PROTEIN BINDING, S5 RECEPTORS, P11 T89, P13 TRANSPORTERS, S9, S10, S11, P4, P6, P19, P22, P36, P37 VOLUME PREDICTION, S5, P5
ENZYME INDUCTION, P8 ENZYME INHIBITION/ INACTIVATION, P1, P2, P10 EXTRAHEPATIC METABOLISM, P1, P2 GLUCURONIDATION, PBPK MODELLING, S6 GUT METABOLITES, P9 HEPATIC UPTAKE, S10, P22 HEPATOCYTES, S9, P3, P8, P14, P22, P23, P24 IN VITRO TECHNIQUES, S7, P12, P22, P24 IN VITRO–IN VIVO EXTRAPOLATION (IVIVE), S6, S7, S9, P6, P22, P24, P25, P26, P27, P28
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Abstract Keyword Index
Abstract Author Index Aminov, Alexey, P31 Arrendondo, Estephan, P14 Baik, Jason, P6 Balbuena, Pergentino, P7 Barfield, Shiloh, P14 Beéry, Erzsébet, P36 Belkacem, Bouaita, P30 Billings, David, P7 Billington, Sarah, P27 Bischoff, Daniel, P3 Broberg, Jared, P24 Brouwer, Kenneth R., P22, P23 Brouwer, Kim L. R., S9 Brown, Colin, P27 Buckley, David B., P15 Caradec, Fabrice, P30 Chan, Tom, P18 Chesne, Christophe, P30 Chu, X., S10 Clewell, Harvey, P7 Cui, Xiaoxia, P11 Czerwinski, Maciej, P15 Das, Shyam, P33 Deshmukh, Gauri, P23 Di, Li, S8 DiBella, John A., P34, P35 Edginton, Andrea N., S13 Enders, Jeffrey, P7 Evans, Liam, P9 Ferguson, Douglas, P5 Forbes, Kevin, P11 Freeman, Kimberly, P22 Fretland, Adrian, P5 Friley, Weslyn W., P22 Gáborik, Zsuzsanna, P36 Gaffney, Jeannemarie, P24 Galetin, Aleksandra, S6, P20 Gennemark, Peter, P5 Gerk, Phillip, P1, P2 Grimstein, Manuela, S14 Guillet, Fabrice, P30 Guo, Jason, P12, P21 Hallifax, David, P20 Han, Catherine, P25 Hatfield, Nicholas, P15 Hill, Andrew, P25 Hixon, Mark, P10 Honrao, Chandrashekhar, P12, P21 Huang, Chenrong, P32 Huang, Yong, P6 Ishida, Kazuya, P26
Translating Preclinical Data to Human Clearance and Pharmacokinetics Jackson, Jonathan P., P22 Jahic, Mirza, P6 Jisoo, Lee, P37 Jones, Jeffrey P., S7 Jover, Ramiro, P8 Juhász, Viktória, P36 Kang, Dong-Hyeok, P19 Kautz, Roger, P12, P21 Khojasteh, Cyrus, P23 Khwaounjoo, Prashannata, P25 Kis, Emese, P36 Kulkarni, Shashank, P12, P21 Kumar, Vineet, P27 Lam, Zamas, P14 Lashin, Vitaly, P31 Lawless, Michael, P34 LeCluyse, Edward, P14 Lee, Jisoo, P19 Lee, Richard, P31 Lee, Sungjae, P19 Lee, Violet, P23 Lee, Young-Joo, P19 Liederer, Bianca M., P23 Lukacova, Viera, P34, P35 Ma, Xiaoyu, P12, P21 Maharao, Neha, P1 Makriyannis, Alexandros, P12, P21 Malamas, Michael, P12 Manohar, Ravi, P9 Matsui, Akiko, P3 Matsunaga, Norikazu, P20 McConn, Donavon, P10 McKeage, Mark J., P25 Miao, Liyan, P32 Miskelly, Gordon, P25 Morinaga, Gaku, P3 Mudra, Daniel, S2 Nagar, Swati, S5 Nagy, Ildikó, P36 Narayanan, R, P33 Noerenberg, Astrid, P8 Obach, R. Scott, S4 Ofoma, Onyi, P24 Oh, Ju-Hee, P19 O'Neil, Maura, P15 Otte, Karin, P29 Paramonov, Andrey, P31 Parmentier, Yannick, P30 Patilea-Vrana, Gabriela, P4 Perrin, Dominique, P28 Petersson, Carl, P28 Phillips, Martin, P7 Phipps, Richard, P9 Pothier, Corinne, P30
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Prasad, Bhagwat, P27 Roberts, Ben, P15 Rotter, Charles, P15 Rowland-Yeo, Karen, S12 Saad, Ola, P23 Saito, Asami, P3 Sakharov, Alexandr, P31 Sancheti, Jayant, P33 Schaefer, Michelle, P3 Schaenzle, Gerhard, P3 Schaus, Yvonne, P24 Scheffler, Frank, P9 Seib, Christopher, P15 Shah, Heta, P2 Shahraz, Azar, P35 Shen, Ben, P23 Smith, Cornelia, P14 Spires, Jessica, P35 St. Claire III, Robert L., P22 Steele, Jonathan, P9 Steen, David, P30 Suessmuth, Roderich, P3 Sun, He, P13 Suzuki, Shinobu, P3 Taub, Mitchell, P18 Ting, Naitee, P18 Tóth, Beáta, P36 Ufuk, Ayşe, P20 Ullah, Mohammed, P26 Unadkat, Jashvant D., S1, S11, P4, P26, P27 Wang, Joanne, P27 Wang, Ziteng, P32 Warren, Mark, P6 Weinman, Steven, P15 Whitcher-Johnstone, Andrea, P18 Williams, Headley, P9 Wood, JodiAnne, P12, P21 Yang, Liu, P13 Yates, James, P5 Yin, Jia, P27 Yoon, Miyoung, P7 Zanelli, Ugo, P28 Zhang, Bin, P32 Zhang, Xuexiang, P6 Zhao, Ping, S3 Zolnerciks, Joseph, P36 Zvonok, Alexander, P12, P21
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