bioinformatics

Of Collecting And Analyzing Complex Biological Data Such As Genetic Codes

characteristics of the infecting bacterium to develop an artificial intelligence algorithm to help clinicians prescribe precision therapeutics that could save more lives from these dangerous infections.

“One out of three people with bloodstream infection caused by the bacterium Staphylococcus will continue to grow the bacterium in the blood, which is problematic because it not only gets seeded into other organs, but such patients also have a much higher likelihood of death,” Wong-Beringer notes. “By better understanding the biomarkers of host and pathogen interaction most predictive of outcome, we can improve how we identify at-risk patients and direct treatment with precision for each individual patient.”

Closing the Omics Divide

Rapid advances in omics technologies have created unprecedented amounts of biological data—along with an increased dependence on computational analysis to properly harness this information for medical research.

Serghei Mangul applies his bioinformatics expertise to help close the digital divide between biomedical researchers’ lack of computational expertise and the rising importance of reproducible data science. In addition to teaching computational techniques to life sciences and medical researchers, Mangul devises ways of accelerating the accurate applications of genomics and biomedical data to translational research and education. His team is also currently developing robust yet easy-to-use open-source software to study adaptive immune repertoires across diverse populations.

Investigating Policy Consequences

For more than a decade, the USC Schaeffer Center has been at the forefront of developing pioneering economic demographic microsimulation tools to effectively model future trends in health and longevity and answer salient questions in health policy. The centerpiece effort is the Future Elderly Model (FEM), which projects a rich set of health and economic outcomes for the U.S. population age 50 and older. The Schaeffer Center is building a network of global collaborators to develop country-level, FEM-based models in nations around the world, an effort that will allow researchers to compare demographic, health and economic trends on a global scale. This project is especially important since the number of individuals age 65 and over is projected to double by 2050.

Researchers recently used the FEM to forecast long-term trends in disease dynamics from 20 countries. Focusing on investigating the consequences of policy and behavioral factors in healthy aging—including trends in chronic disease and education, and behavioral factors like smoking—the researchers produced forecasting models that can be used by policymakers and stakeholders in deciding where to most effectively deploy resources. Models have also gone local, with simulations conducted for California and Los Angeles County to help policymakers at the state and county levels understand trends and the impact of policy decisions.

Predicting Molecular Associations

Ian Haworth develops computational methods for predicting molecular associations to enhance our understanding of biochemical and pharmacological mechanisms. His laboratory’s advances include improving solvation methods to make them more widely applicable for clinical research. He also leads research aimed at expanding the use of artificial intelligence for more sophisticated analyses of data from computational predictions. Haworth’s methodologies enable a deeper understanding of the molecular events underlying drug design and delivery. His collaborations span structural biology, immunology and computer sciences, and students are partners in all of his projects. This includes recruiting science-oriented PharmD students for his laboratory team.

Valuing Care

Rising healthcare expenses mean that economists have an increasingly important role to play in advancing cost-effective care. Yet economic models overwhelmingly fail to predict the value people place on treating dangerous or rare diseases. Darius Lakdawalla, the Quintiles Chair in Pharmaceutical and Regulatory Innovation, focuses on identifying why economic theory mischaracterizes the value of treating severe illness and on finding solutions that promote valuebased care. With a colleague, he devised the revolutionary Generalized Risk-Adjusted Cost-Effectiveness (GRACE) approach, which seeks to remedy the failure of current economic methods by incorporating the concept of diminishing returns in terms of quality of life and not just life expectancy.

Enhancing Pharmacy Training

The increasing reliance on technology and big data is a key trend affecting pharmacy education and the success of the field’s future practitioners. “Leaders from healthcare systems, government, the pharmacy supply chain, venture capital and academia urge that students become equipped with programming and computational skills for the collection, management and analysis of large data sets and the understanding of artificial intelligence and machine learning,” says Assistant Dean for Assessment Maryann Wu. She and several colleagues at the Mann School are working to utilize technology to push the boundaries of education, assessment and student success.

Findings using the Schaeffer Center’s Future Elderly Model and the related Future Adult Model have been published in top journals and cited or commissioned by government agencies, the White House, the National Academy of Sciences and private organizations interested in policy relating to aging.

75+ STUDIES PUBLISHED THAT LEVERAGE THE SCHAEFFER CENTER’S MICROSIMULATION MODELS

290+

CITATIONS OF SCHAEFFER CENTER EXPERTS IN GOVERNMENT DOCUMENTS SINCE 2009, INCLUDING EIGHT OF THE LAST NINE ANNUAL VERSIONS OF THE ECONOMIC REPORT OF THE PRESIDENT