Report Information More information from: https://www.wiseguyreports.com/reports/1474113
OpportunityAnalyzer: Cystic Fibrosis - Opportunity Analysis and Forecasts to 2025 Report / Search Code: WGR1474113
Price
1-user PDF : $ 10995.0
Description:
Publish Date: 1 April, 2017
Site PDF : $ 21990.0
Enterprise PDF : $ 32985.0
OpportunityAnalyzer: Cystic Fibrosis - Opportunity Analysis and Forecasts to 2025 Summary Cystic fibrosis (CF) is an autosomal recessive disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, which codes for the CFTR protein. As a multisystem condition, CF patients show great heterogeneity in presenting clinical symptoms. CF mainly affects the respiratory and gastrointestinal tracts. Three classes of drugs have been used to for treatment in CF patients: inhaled antibiotics for bacterial and fungal respiratory infections, mucolytic drugs for mucociliary clearance of the airways, and pancreatic enzyme replacement therapies (PERTs) for treatment of CF induced exocrine pancreatic insufficiency (EPI). During the last five years, a new class of drugs was launched into the market, specifically treating the underlying cause of CF. These CFTR modulators help restore function of the insufficient CFTR protein. GlobalData projects the global cystic fibrosis marketplace to experience tremendous growth during the forecast period. This growth will be driven primarily by the highly anticipated arrival of the CFTR modulator, Vertex Pharmaceuticals' ivacaftor/tezacaftor. Insmed's inhaled antibiotic Arikace (liposomal amikacin) is also expected to launch during the forecast period but is not expected to drive CF market growth as much as the CFTR modulator, since it will be competing with other inhaled antibiotics. Key Questions Answered - Inhaled antibiotics, mucolytic drugs, and PERTs have been the cornerstone of CF treatment. The introduction of CFTR modulators have contributed to better treatment of CF patients; nevertheless, the overall life expectancy in CF patients is still 20-25 years less than in the healthy population. Therefore, there are considerably high unmet needs within the indication. What are the main unmet needs in this market? Will the drugs under development fulfil the unmet needs of the CF market? - The current late-stage CF pipeline encompasses one CFTR modulating combination therapy and an inhaled antibiotic. Will the late-stage drugs make a significant impact on the CF market? Which of these drugs will have the highest peak sales at the highest CAGR, and why? - CFTR modulators treat the cause of the CF disease. How will the entrance of CFTR modulators into the CF therapy market affect the other classes of drugs? Scope - Overview of cystic fibrosis, including epidemiology, etiology, pathophysiology, symptoms, diagnosis, and treatment guidelines. - Annualized CF therapeutics market revenue, annual cost of therapy and treatment usage pattern data from 2015 and forecast for ten years to 2025. - Key topics covered include strategic competitor assessment, market characterization, unmet needs, clinical trial mapping and implications for the CF therapeutics market. - Pipeline analysis: comprehensive data split across different phases, emerging novel trends under development, and detailed analysis of late-stage pipeline drugs. - Analysis of the current and future market competition in the global CF therapeutics market. Insightful review of the key industry drivers, restraints and challenges. Each trend is independently researched to provide qualitative analysis of its implications. Reasons to buy The report will enable you to - Develop and design your in-licensing and out-licensing strategies through a review of pipeline products and technologies, and by identifying the companies with the most robust pipeline. Additionally a list of acquisition targets included in the pipeline product company list. - Develop business strategies by understanding the trends shaping and driving the global CF therapeutics market. - Drive revenues by understanding the key trends, innovative products and technologies, market
segments, and companies likely to impact the global CF therapeutics market in future. - Formulate effective sales and marketing strategies by understanding the competitive landscape and by analysing the performance of various competitors. - Identify emerging players with potentially strong product portfolios and create effective counterstrategies to gain a competitive advantage. - Track drug sales in the global CF therapeutics market from 2015-2025. - Organize your sales and marketing efforts by identifying the market categories and segments that present maximum opportunities for consolidations, investments and strategic partnerships.
Contents:
1 Table of Contents 1 Table of Contents 2 1.1 List of Tables 6 1.2 List of Figures 7 2 Cystic Fibrosis: Executive Summary 9 2.1 CF Transmembrane Conductance Regulator Modulators Expected to Drive Substantial Growth in the Cystic Fibrosis Market from 2015-2025 9 2.2 Licensing Activity and the Formation of New Partnerships Will Steer Small Companies to Continue Research of Novel Compounds 11 2.3 Marketed and Pipeline CF Transmembrane Conductance Regulator Modulators Will Provide Appropriate Treatment for the Majority of the CF Population, but the High Unmet Needs Will Remain 12 2.4 Opportunities Will Remain for the Development of New CF Transmembrane Conductance Regulator Modulators 12 2.5 What Do Physicians Think? 13 3 Introduction 15 3.1 Catalyst 15 3.2 Related Reports 15 3.3 Upcoming Related Reports 15 4 Disease Overview 16 4.1 Etiology and Pathophysiology 16 4.1.1 Etiology 16 4.1.2 Pathophysiology 16 4.2 Classification 20 4.3 Symptoms 21 4.4 Prognosis 22 4.5 Quality of Life 23 5 Epidemiology 24 5.1 Disease Background 24 5.2 Risk Factors and Comorbidities 25 5.3 Global Trends 26 5.3.1 Diagnosed Incidence and Diagnosed Prevalence 27 5.4 Forecast Methodology 29 5.4.1 Sources Used 29 5.4.2 Forecast Assumptions and Methods 37 5.4.3 Sources Not Used 49 5.5 Epidemiological Forecast for CF (2015-2025) 50 5.5.1 Diagnosed Incident Cases, Based on Registry Data 50 5.5.2 Diagnosed Prevalent Cases, Based on Registry Data 53 5.5.3 CF Mortality, Based on Registry Data 62 5.5.4 Diagnosed Incident Cases, Adjusted for Underestimation 65 5.5.5 Diagnosed Prevalent Cases, Adjusted for Underestimation 68 5.5.6 CF Mortality, Adjusted for Underestimation 76 5.6 Discussion 79 5.6.1 Epidemiological Forecast Insight 79 5.6.2 Limitations of the Analysis 80 5.6.3 Strengths of the Analysis 81 6 Current Treatment Options 82 6.1 Overview 82 6.2 Diagnosis and Treatment 83 6.2.1 Diagnosis 83 6.2.2 Treatment Guidelines and Leading Prescribed Drugs 84 6.3 Clinical Practice 85 6.4 Product Profiles - Major Brands, Inhaled Antibiotics 86 6.4.1 TOBI (tobramycin) 86 6.4.2 TOBI Podhaler (tobramycin) 89 6.4.3 Quinsair (levofloxacin) 93 6.4.4 Cayston (aztreonam) 95
6.4.5 Bramitob/Bethkis (tobramycin) 99 6.4.6 Colobreathe (colistimethate sodium) 102 6.5 Product Profiles - Major Brands, Mucolytics 105 6.5.1 Pulmozyme (dornase alfa) 105 6.5.2 Bronchitol (mannitol) 109 6.6 Product Profiles - Major Brands, CF Transmembrane Conductance Regulator Modulators 113 6.6.1 Kalydeco (ivacaftor) 113 6.6.2 Orkambi (ivacaftor + lumacaftor) 118 6.7 Product Profiles - Major Brands, Other Therapies 121 6.7.1 Pancreatic Enzyme Replacement Therapies 121 7 Unmet Needs Assessment and Opportunity Analysis 124 7.1 Overview 124 7.2 Development of More Effective or Curative Therapies 125 7.2.1 Unmet Need 125 7.2.2 Gap Analysis 126 7.2.3 Opportunity 127 7.3 Development of Chronic Lung Infection Therapies 127 7.3.1 Unmet Need 127 7.3.2 Gap Analysis 128 7.3.3 Opportunity 130 7.4 Increased Treatment Compliance 131 7.4.1 Unmet Need 131 7.4.2 Gap Analysis 132 7.4.3 Opportunity 132 7.5 Development of Mucolytic Therapies 133 7.5.1 Unmet Need 133 7.5.2 Gap Analysis 133 7.5.3 Opportunity 134 8 R&D Strategies 135 8.1 Overview 135 8.1.1 Reformulation Strategies 135 8.1.2 Personalized Treatment Approach 136 8.1.3 Development of Agents with Novel Mechanisms of Action 138 8.1.4 Licensing and Alliances 139 8.2 Clinical Trial Design 139 8.2.1 Current Clinical Trials 139 8.2.2 CF Transmembrane Conductance Regulator Modulator Clinical Trials 140 9 Pipeline Assessment 142 9.1 Overview 142 9.2 Promising Drugs in Clinical Development 142 9.3 Promising Drugs in Clinical Development, Inhaled Antibiotics 144 9.3.1 Arikace (liposomal amikacin) 144 9.4 Promising Drugs in Clinical Development, CF Transmembrane Conductance Regulator Modulators 148 9.4.1 Ivacaftor/Tezacaftor 148 9.5 Innovative Early-Stage Approaches 153 10 Pipeline Valuation Analysis 158 10.1 Clinical Benchmark of Key Pipeline Drugs 158 10.2 Commercial Benchmark of Key Pipeline Drugs 159 10.3 Competitive Assessment 161 10.4 Top-Line 10-Year Forecast 162 10.4.1 US 167 10.4.2 5EU 169 10.4.3 Canada 171 11 Appendix 174 11.1 Bibliography 174 11.2 Abbreviations 186 11.3 Methodology 190 11.4 Forecasting Methodology 190 11.4.1 Diagnosed CF Patients 190 11.4.2 Percent Drug-Treated Patients 190 11.4.3 Drugs Included in Each Therapeutic Class 191 11.4.4 Launch and Patent Expiry Dates 192 11.4.5 General Pricing Assumptions 193 11.4.6 Drug Assumptions 194 11.4.7 Pricing of Pipeline Agents 196 11.5 Primary Research - Key Opinion Leaders Interviewed for This Report 198
11.6 Primary Research - Prescriber Survey 202 11.7 About the Authors 203 11.7.1 Analyst 203 11.7.2 Reviewer 203 11.7.3 Therapy Area Director 203 11.7.4 Epidemiologist 204 11.7.5 Managing Epidemiologist 205 11.7.6 Global Director of Therapy Analysis and Epidemiology 206 11.7.7 Global Head of Healthcare 207 11.8 About GlobalData 208 11.9 Contact Us 208 11.10 Disclaimer 208 1.1 List of Tables Table 1: Cystic Fibrosis: Key Metrics in the Seven Major Pharmaceutical Markets 9 Table 2: Onset of CF by Approximate Age 18 Table 3: Classification and Criteria of the CFTR Gene Mutations in CF 20 Table 4: Symptoms of CF 22 Table 5: Risk Factors and Comorbidities of CF 26 Table 6: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of CF (Based on Registry Data) 30 Table 7: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of CF (Based on Registry Data) 31 Table 8: 7MM, Sources Used for Segmentation of Diagnosed Prevalent Cases of CF by Specific Mutations (Based on Registry Data) 32 Table 9: 7MM, Sources Used to Forecast the Proportion of Diagnosed Prevalent Cases of CF by Chronic MRSA Infection (Based on Registry Data) 35 Table 10: 7MM, Sources Used to Forecast CF Deaths (Based on Registry Data) 36 Table 11: 7MM, Proportion of CF Cases Reported to Respective CF Registries (Primary Research) 36 Table 12: 7MM, Sources Not Used in the Epidemiological Analysis of CF 49 Table 13: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, Selected Years 20152025 (Based on Registry Data) 50 Table 14: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N (Row %), 2015 (Based on Registry Data) 52 Table 15: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 20152025 (Based on Registry Data) 54 Table 16: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N (Row %), 2015 (Based on Registry Data) 55 Table 17: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N (Row %), 2015 (Based on Registry Data) 57 Table 18: 7MM, Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, All Ages, Both Sexes, N, Selected Years 2015-2025 (Based on Registry Data) 61 Table 19: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015-2025 (Based on Registry Data) 62 Table 20: 7MM, Sex-Specific CF Deaths, All Ages, N (Row %), 2015 (Based on Registry Data) 64 Table 21: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, Selected Years 20152025 (Adjusted for Underestimation) 66 Table 22: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N (Row %), 2015 (Adjusted for Underestimation) 67 Table 23: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 20152025 (Adjusted for Underestimation) 69 Table 24: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N (Row %), 2015 (Adjusted for Underestimation) 70 Table 25: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N (Row %), 2015 (Adjusted for Underestimation) 72 Table 26: 7MM, Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, All Ages, Both Sexes, N, Selected Years 2015-2025 (Adjusted for Underestimation) 75 Table 27: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015-2025 (Adjusted for Underestimation) 76 Table 28: 7MM, Sex-Specific CF Deaths, All Ages, N (Row %), 2015 (Adjusted for Underestimation) 78 Table 29: Treatment Guidelines for CF 84 Table 30: Leading Treatments for CF, 2016 85 Table 31: Product Profile - TOBI 87 Table 32: TOBI SWOT Analysis, 2016 88 Table 33: Product Profile - TOBI Podhaler 90 Table 34: TOBI Podhaler SWOT Analysis, 2016 92 Table 35: Product Profile - Quinsair 94
Table 36: Quinsair SWOT Analysis, 2016 95 Table 37: Product Profile - Cayston 96 Table 38: Cayston SWOT Analysis, 2016 99 Table 39: Product Profile - Bramitob 100 Table 40: Bramitob SWOT Analysis, 2016 102 Table 41: Product Profile - Colobreathe 103 Table 42: Colobreathe SWOT Analysis, 2016 105 Table 43: Product Profile - Pulmozyme 107 Table 44: Pulmozyme SWOT Analysis, 2016 109 Table 45: Product Profile - Bronchitol 111 Table 46: Bronchitol SWOT Analysis, 2016 113 Table 47: Product Profile - Kalydeco 115 Table 48: Kalydeco SWOT Analysis, 2016 118 Table 49: Product Profile - Orkambi 119 Table 50: Orkambi SWOT Analysis, 2016 121 Table 51: Pancreatic Enzyme Replacement Therapies (PERTs) SWOT Analysis, 2016 123 Table 52: Unmet Need and Opportunity in CF, 2016 125 Table 53: Key Late-Stage Pipeline Agents for CF, 2016 143 Table 54: Comparison of Therapeutic Classes in Development for CF, 2015-2025 143 Table 55: Product Profile - Arikace 145 Table 56: Insmed’s Arikace - Phase III Clinical Trials 146 Table 57: Arikace SWOT Analysis, 2016 148 Table 58: Product Profile - ivacaftor/tezacaftor 149 Table 59: Vertex’s ivacaftor/tezacaftor - Phase III Clinical Trials 150 Table 60: Efficacy of Ivacaftor + Tezacaftor 151 Table 61: Ivacaftor + Tezacaftor SWOT Analysis, 2016 153 Table 62: Drugs in Development for CF, 2016 156 Table 63: Clinical Benchmark of Key Pipeline Drugs - Inhaled Antibiotics 159 Table 64: Clinical Benchmark of Key Pipeline Drugs - CFTR Modulators 159 Table 65: Commercial Benchmark of Key Pipeline Drugs - Inhaled Antibiotics 160 Table 66: Commercial Benchmark of Key Pipeline Drugs - CFTR Modulators 160 Table 67: Top-Line Sales Forecasts ($m) for CF, 2015-2025 163 Table 68: Key Events Impacting Sales for CF, 2015-2025 166 Table 69: CF Market - Global Drivers and Barriers, 2015‒2025 167 Table 70: Key Historical and Projected Launch Dates 192 Table 71: Key Historical and Projected Patent Expiry Dates 193 Table 72: High-Prescribing Physicians (Non-KOLs) Surveyed, By Country 202 1.2 List of Figures Figure 1: Global Sales for CF by Country/Region, 2015 and 2025 11 Figure 2: Classes of CFTR Gene Mutations in CF 21 Figure 3: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, 2015-2025 (Based on Registry Data) 51 Figure 4: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N, 2015 (Based on Registry Data) 53 Figure 5: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 20152025 (Based on Registry Data) 54 Figure 6: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N, 2015 (Based on Registry Data) 56 Figure 7: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N, 2015 (Based on Registry Data) 58 Figure 8: 7MM, Age-Standardized Diagnosed Prevalence of CF, All Ages, N, 2015 (Based on Registry Data) 59 Figure 9: 7MM, Diagnosed Prevalent Cases of CF with Specific Mutations, Both Sexes, All Ages, N, 2015 (Based on Registry Data) 60 Figure 10: 7MM, Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, Both Sexes, All Ages, N, 2015 (Based on Registry Data) 61 Figure 11: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015-2025 (Based on Registry Data) 63 Figure 12: 7MM, Sex-Specific CF Deaths, All Ages, N, 2015 (Based on Registry Data) 65 Figure 13: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, 2015-2025 (Adjusted for Underestimation) 66 Figure 14: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N, 2015 (Adjusted for Underestimation) 68 Figure 15: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 2015-2025 (Adjusted for Underestimation) 69 Figure 16: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N, 2015 (Adjusted for Underestimation) 71 Figure 17: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N, 2015 (Adjusted for
Underestimation) 73 Figure 18: 7MM, Diagnosed Prevalent Cases of CF with Specific Mutations, Both Sexes, All Ages, N, 2015 (Adjusted for Underestimation) 74 Figure 19: 7MM, Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, Both Sexes, All Ages, N, 2015 (Adjusted for Underestimation) 75 Figure 20: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015-2025 (Adjusted for Underestimation) 77 Figure 21: 7MM, Sex-Specific CF Deaths, All Ages, N, 2015 (Adjusted for Underestimation) 79 Figure 22: Competitive Assessment of Marketed and Pipeline Agents in CF, 2015-2025 161 Figure 23: Competitive Assessment of Marketed and Pipeline Agents in CF, 2015-2025 162 Figure 24: Top-Line Sales for CF by Country/Region, 2015 and 2025 164 Figure 25: Global Sales for CF by Drug Class, 2015 and 2025 165 Figure 26: Sales for CF by Drug Class in the US, 2015 and 2025 169 Figure 27: Sales for CF by Drug Class in the 5EU, 2015 and 2025 171 Figure 28: Sales for CF by Drug Class in Canada, 2015 and 2025 173
wiseguyreports.com / Phone (US) + 1-646-845-9349 (UK) +44 208 133 9349