OpportunityAnalyzer: Cystic Fibrosis – Opportunity Analysis and Forecasts to 2025

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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 counter-strategies 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.

AbbVie
Chiesis USA
Forest Laboratories
Gilead
Insmed Therapeutics
Johnson & Johnson
Novartis
Pharmaxis
Raptor Pharmaceuticals
Roche
Vertex Pharmaceuticals

Table of Contents

Table of Contents

1 Table of Contents

1.1 List of Tables

1.2 List of Figures

2 Cystic Fibrosis: Executive Summary

2.1 CF Transmembrane Conductance Regulator Modulators Expected to Drive Substantial Growth in the Cystic Fibrosis Market from 2015–2025

2.2 Licensing Activity and the Formation of New Partnerships Will Steer Small Companies to Continue Research of Novel Compounds

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

2.4 Opportunities Will Remain for the Development of New CF Transmembrane Conductance Regulator Modulators

2.5 What Do Physicians Think?

3 Introduction

3.1 Catalyst

3.2 Related Reports

3.3 Upcoming Related Reports

4 Disease Overview

4.1 Etiology and Pathophysiology

4.1.1 Etiology

4.1.2 Pathophysiology

4.2 Classification

4.3 Symptoms

4.4 Prognosis

4.5 Quality of Life

5 Epidemiology

5.1 Disease Background

5.2 Risk Factors and Comorbidities

5.3 Global Trends

5.3.1 Diagnosed Incidence and Diagnosed Prevalence

5.4 Forecast Methodology

5.4.1 Sources Used

5.4.2 Forecast Assumptions and Methods

5.4.3 Sources Not Used

5.5 Epidemiological Forecast for CF (2015–2025)

5.5.1 Diagnosed Incident Cases, Based on Registry Data

5.5.2 Diagnosed Prevalent Cases, Based on Registry Data

5.5.3 CF Mortality, Based on Registry Data

5.5.4 Diagnosed Incident Cases, Adjusted for Underestimation

5.5.5 Diagnosed Prevalent Cases, Adjusted for Underestimation

5.5.6 CF Mortality, Adjusted for Underestimation

5.6 Discussion

5.6.1 Epidemiological Forecast Insight

5.6.2 Limitations of the Analysis

5.6.3 Strengths of the Analysis

6 Current Treatment Options

6.1 Overview

6.2 Diagnosis and Treatment

6.2.1 Diagnosis

6.2.2 Treatment Guidelines and Leading Prescribed Drugs

6.3 Clinical Practice

6.4 Product Profiles – Major Brands, Inhaled Antibiotics

6.4.1 TOBI (tobramycin)

6.4.2 TOBI Podhaler (tobramycin)

6.4.3 Quinsair (levofloxacin)

6.4.4 Cayston (aztreonam)

6.4.5 Bramitob/Bethkis (tobramycin)

6.4.6 Colobreathe (colistimethate sodium)

6.5 Product Profiles – Major Brands, Mucolytics

6.5.1 Pulmozyme (dornase alfa)

6.5.2 Bronchitol (mannitol)

6.6 Product Profiles – Major Brands, CF Transmembrane Conductance Regulator Modulators

6.6.1 Kalydeco (ivacaftor)

6.6.2 Orkambi (ivacaftor + lumacaftor)

6.7 Product Profiles – Major Brands, Other Therapies

6.7.1 Pancreatic Enzyme Replacement Therapies

7 Unmet Needs Assessment and Opportunity Analysis

7.1 Overview

7.2 Development of More Effective or Curative Therapies

7.2.1 Unmet Need

7.2.2 Gap Analysis

7.2.3 Opportunity

7.3 Development of Chronic Lung Infection Therapies

7.3.1 Unmet Need

7.3.2 Gap Analysis

7.3.3 Opportunity

7.4 Increased Treatment Compliance

7.4.1 Unmet Need

7.4.2 Gap Analysis

7.4.3 Opportunity

7.5 Development of Mucolytic Therapies

7.5.1 Unmet Need

7.5.2 Gap Analysis

7.5.3 Opportunity

8 R&D Strategies

8.1 Overview

8.1.1 Reformulation Strategies

8.1.2 Personalized Treatment Approach

8.1.3 Development of Agents with Novel Mechanisms of Action

8.1.4 Licensing and Alliances

8.2 Clinical Trial Design

8.2.1 Current Clinical Trials

8.2.2 CF Transmembrane Conductance Regulator Modulator Clinical Trials

9 Pipeline Assessment

9.1 Overview

9.2 Promising Drugs in Clinical Development

9.3 Promising Drugs in Clinical Development, Inhaled Antibiotics

9.3.1 Arikace (liposomal amikacin)

9.4 Promising Drugs in Clinical Development, CF Transmembrane Conductance Regulator Modulators

9.4.1 Ivacaftor/Tezacaftor

9.5 Innovative Early-Stage Approaches

10 Pipeline Valuation Analysis

10.1 Clinical Benchmark of Key Pipeline Drugs

10.2 Commercial Benchmark of Key Pipeline Drugs

10.3 Competitive Assessment

10.4 Top-Line 10-Year Forecast

10.4.1 US

10.4.2 5EU

10.4.3 Canada

11 Appendix

11.1 Bibliography

11.2 Abbreviations

11.3 Methodology

11.4 Forecasting Methodology

11.4.1 Diagnosed CF Patients

11.4.2 Percent Drug-Treated Patients

11.4.3 Drugs Included in Each Therapeutic Class

11.4.4 Launch and Patent Expiry Dates

11.4.5 General Pricing Assumptions

11.4.6 Drug Assumptions

11.4.7 Pricing of Pipeline Agents

11.5 Primary Research – Key Opinion Leaders Interviewed for This Report

11.6 Primary Research – Prescriber Survey

11.7 About the Authors

11.7.1 Analyst

11.7.2 Reviewer

11.7.3 Therapy Area Director

11.7.4 Epidemiologist

11.7.5 Managing Epidemiologist

11.7.6 Global Director of Therapy Analysis and Epidemiology

11.7.7 Global Head of Healthcare

11.8 About GlobalData

11.9 Contact Us

11.10 Disclaimer

Table

Table 1: Cystic Fibrosis: Key Metrics in the Seven Major Pharmaceutical Markets

Table 2: Onset of CF by Approximate Age

Table 3: Classification and Criteria of the CFTR Gene Mutations in CF

Table 4: Symptoms of CF

Table 5: Risk Factors and Comorbidities of CF

Table 6: 7MM, Sources Used to Forecast the Diagnosed Incident Cases of CF (Based on Registry Data)

Table 7: 7MM, Sources Used to Forecast the Diagnosed Prevalent Cases of CF (Based on Registry Data)

Table 8: 7MM, Sources Used for Segmentation of Diagnosed Prevalent Cases of CF by Specific Mutations (Based on Registry Data)

Table 9: 7MM, Sources Used to Forecast the Proportion of Diagnosed Prevalent Cases of CF by Chronic MRSA Infection (Based on Registry Data)

Table 10: 7MM, Sources Used to Forecast CF Deaths (Based on Registry Data)

Table 11: 7MM, Proportion of CF Cases Reported to Respective CF Registries (Primary Research)

Table 12: 7MM, Sources Not Used in the Epidemiological Analysis of CF

Table 13: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, Selected Years 2015–2025 (Based on Registry Data)

Table 14: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N (Row %), 2015 (Based on Registry Data)

Table 15: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 2015–2025 (Based on Registry Data)

Table 16: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N (Row %), 2015 (Based on Registry Data)

Table 17: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N (Row %), 2015 (Based on Registry Data)

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)

Table 19: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015–2025 (Based on Registry Data)

Table 20: 7MM, Sex-Specific CF Deaths, All Ages, N (Row %), 2015 (Based on Registry Data)

Table 21: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, Selected Years 2015–2025 (Adjusted for Underestimation)

Table 22: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N (Row %), 2015 (Adjusted for Underestimation)

Table 23: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 2015–2025 (Adjusted for Underestimation)

Table 24: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N (Row %), 2015 (Adjusted for Underestimation)

Table 25: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N (Row %), 2015 (Adjusted for Underestimation)

Table 26: 7MM, Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, All Ages, Both Sexes, N, Selected Years 2015–2025 (Adjusted for Underestimation)

Table 27: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015–2025 (Adjusted for Underestimation)

Table 28: 7MM, Sex-Specific CF Deaths, All Ages, N (Row %), 2015 (Adjusted for Underestimation)

Table 29: Treatment Guidelines for CF

Table 30: Leading Treatments for CF, 2016

Table 31: Product Profile – TOBI

Table 32: TOBI SWOT Analysis, 2016

Table 33: Product Profile – TOBI Podhaler

Table 34: TOBI Podhaler SWOT Analysis, 2016

Table 35: Product Profile – Quinsair

Table 36: Quinsair SWOT Analysis, 2016

Table 37: Product Profile – Cayston

Table 38: Cayston SWOT Analysis, 2016

Table 39: Product Profile – Bramitob

Table 40: Bramitob SWOT Analysis, 2016

Table 41: Product Profile – Colobreathe

Table 42: Colobreathe SWOT Analysis, 2016

Table 43: Product Profile – Pulmozyme

Table 44: Pulmozyme SWOT Analysis, 2016

Table 45: Product Profile – Bronchitol

Table 46: Bronchitol SWOT Analysis, 2016

Table 47: Product Profile – Kalydeco

Table 48: Kalydeco SWOT Analysis, 2016

Table 49: Product Profile – Orkambi

Table 50: Orkambi SWOT Analysis, 2016

Table 51: Pancreatic Enzyme Replacement Therapies (PERTs) SWOT Analysis, 2016

Table 52: Unmet Need and Opportunity in CF, 2016

Table 53: Key Late-Stage Pipeline Agents for CF, 2016

Table 54: Comparison of Therapeutic Classes in Development for CF, 2015–2025

Table 55: Product Profile – Arikace

Table 56: Insmed’s Arikace – Phase III Clinical Trials

Table 57: Arikace SWOT Analysis, 2016

Table 58: Product Profile – ivacaftor/tezacaftor

Table 59: Vertex’s ivacaftor/tezacaftor – Phase III Clinical Trials

Table 60: Efficacy of Ivacaftor + Tezacaftor

Table 61: Ivacaftor + Tezacaftor SWOT Analysis, 2016

Table 62: Drugs in Development for CF, 2016

Table 63: Clinical Benchmark of Key Pipeline Drugs – Inhaled Antibiotics

Table 64: Clinical Benchmark of Key Pipeline Drugs – CFTR Modulators

Table 65: Commercial Benchmark of Key Pipeline Drugs – Inhaled Antibiotics

Table 66: Commercial Benchmark of Key Pipeline Drugs – CFTR Modulators

Table 67: Top-Line Sales Forecasts ($m) for CF, 2015–2025

Table 68: Key Events Impacting Sales for CF, 2015–2025

Table 69: CF Market – Global Drivers and Barriers, 2015‒2025

Table 70: Key Historical and Projected Launch Dates

Table 71: Key Historical and Projected Patent Expiry Dates

Table 72: High-Prescribing Physicians (Non-KOLs) Surveyed, By Country

Figures

Figure 1: Global Sales for CF by Country/Region, 2015 and 2025

Figure 2: Classes of CFTR Gene Mutations in CF

Figure 3: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, 2015–2025 (Based on Registry Data)

Figure 4: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N, 2015 (Based on Registry Data)

Figure 5: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 2015–2025 (Based on Registry Data)

Figure 6: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N, 2015 (Based on Registry Data)

Figure 7: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N, 2015 (Based on Registry Data)

Figure 8: 7MM, Age-Standardized Diagnosed Prevalence of CF, All Ages, N, 2015 (Based on Registry Data)

Figure 9: 7MM, Diagnosed Prevalent Cases of CF with Specific Mutations, Both Sexes, All Ages, N, 2015 (Based on Registry Data)

Figure 10: 7MM, Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, Both Sexes, All Ages, N, 2015 (Based on Registry Data)

Figure 11: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015–2025 (Based on Registry Data)

Figure 12: 7MM, Sex-Specific CF Deaths, All Ages, N, 2015 (Based on Registry Data)

Figure 13: 7MM, Diagnosed Incident Cases of CF, All Ages, Both Sexes, N, 2015–2025 (Adjusted for Underestimation)

Figure 14: 7MM, Sex-Specific Diagnosed Incident Cases of CF, All Ages, N, 2015 (Adjusted for Underestimation)

Figure 15: 7MM, Diagnosed Prevalent Cases of CF, All Ages, Both Sexes, N, Selected Years 2015–2025 (Adjusted for Underestimation)

Figure 16: 7MM, Age-Specific Diagnosed Prevalent Cases of CF, Both Sexes, N, 2015 (Adjusted for Underestimation)

Figure 17: 7MM, Sex-Specific Diagnosed Prevalent Cases of CF, All Ages, N, 2015 (Adjusted for Underestimation)

Figure 18: 7MM, Diagnosed Prevalent Cases of CF with Specific Mutations, Both Sexes, All Ages, N, 2015 (Adjusted for Underestimation)

Figure 19: 7MM, Diagnosed Prevalent Cases of CF with Chronic MRSA Infection, Both Sexes, All Ages, N, 2015 (Adjusted for Underestimation)

Figure 20: 7MM, CF Deaths, All Ages, Both Sexes, N, Selected Years 2015–2025 (Adjusted for Underestimation)

Figure 21: 7MM, Sex-Specific CF Deaths, All Ages, N, 2015 (Adjusted for Underestimation)

Figure 22: Competitive Assessment of Marketed and Pipeline Agents in CF, 2015–2025

Figure 23: Competitive Assessment of Marketed and Pipeline Agents in CF, 2015–2025

Figure 24: Top-Line Sales for CF by Country/Region, 2015 and 2025

Figure 25: Global Sales for CF by Drug Class, 2015 and 2025

Figure 26: Sales for CF by Drug Class in the US, 2015 and 2025

Figure 27: Sales for CF by Drug Class in the 5EU, 2015 and 2025

Figure 28: Sales for CF by Drug Class in Canada, 2015 and 2025

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