Heart Failure: Seven-Market Drug Forecast and Market Analysis - Update

Table of Contents

Table of Contents

• About GlobalData

1 Heart Failure: Executive Summary - Updated October 2024, Based on Events up to October 24, 2024

• 1.1 The HF market will exhibit strong growth between 2022 and 2032
• 1.2 Label expansions of CV drugs will fuel market growth
• 1.3 Unmet needs remain in the HF market despite the availability of well-established therapies
• 1.4 Injectable agents will dominate the HF market
• 1.5 What do physicians think?

2 Introduction - Updated October 2024, Based on Events up to October 24, 2024

• 2.1 Catalyst
• 2.2 Related reports

3 Disease Overview

• 3.1 Etiology and pathophysiology
  • 3.1.1 Etiology
  • 3.1.2 Pathophysiology
  • 3.1.3 Biomarkers/targets of interest
• 3.2 Classification or staging systems
• 3.3 Prognosis

4 Epidemiology

• 4.1 Disease background
• 4.2 Risk factors and comorbidities
• 4.3 Global and historical trends
• 4.4 Forecast methodology
  • 4.4.1 Sources
  • 4.4.2 Forecast assumptions and methods
  • 4.4.3 Forecast assumptions and methods: diagnosed incident cases of HF - 7MM
  • 4.4.4 Forecast assumptions and methods: diagnosed incident cases of HF by ejection fraction
  • 4.4.5 Forecast assumptions and methods: hospitalizations for acute HF
  • 4.4.6 Forecast assumptions and methods: acute HF hospitalizations based on presentation
  • 4.4.7 Forecast assumptions and methods: hospital length of stay days for acute HF hospitalizations
  • 4.4.8 Forecast assumptions and methods: re-admissions within 30 days post-discharge after acute HF hospitalization
  • 4.4.9 Forecast assumptions and methods: diagnosed prevalent cases of HF - 7MM
  • 4.4.10 Forecast assumptions and methods: diagnosed prevalent cases of HF by ejection fraction
  • 4.4.11 Forecast assumptions and methods: diagnosed prevalent cases of HF by New York Heart Association classes
  • 4.4.12 Forecast assumptions and methods: diagnosed prevalent cases of HF with preserved ejection fraction (left ventricular ejection fraction >=50%) by New York Heart Association class
  • 4.4.13 Forecast assumptions and methods: diagnosed prevalent cases of HF with mid-range ejection fraction (left ventricular ejection fraction 40-49%) by New York Heart Association class
  • 4.4.14 Forecast assumptions and methods: diagnosed prevalent cases of HF with reduced ejection fraction (left ventricular ejection fraction <40%) by New York Heart Association class
  • 4.4.15 Forecast assumptions and methods: diagnosed prevalent cases of HF by American College of Cardiology Foundation/American Heart Association stages
• 4.5 Epidemiological forecast for HF (2022-32)
  • 4.5.1 Diagnosed incident cases of HF
  • 4.5.2 Age-specific diagnosed incident cases of HF
  • 4.5.3 Sex-specific diagnosed incident cases of HF
  • 4.5.4 Diagnosed incident cases of HF by ejection fraction
  • 4.5.5 Hospitalizations for acute HF
  • 4.5.6 Acute HF hospitalizations based on presentation
  • 4.5.7 Hospital length of stay for acute HF
  • 4.5.8 Re-admissions within 30 days post-discharge after acute HF
  • 4.5.9 Diagnosed prevalent cases of HF
  • 4.5.10 Age-specific diagnosed prevalent cases of HF
  • 4.5.11 Sex-specific diagnosed prevalent cases of HF
  • 4.5.12 Diagnosed prevalent cases of HF by ejection fraction
  • 4.5.13 Diagnosed prevalent cases of HF by New York Heart Association class
  • 4.5.14 Diagnosed prevalent cases of HF with preserved ejection fraction (left ventricle ejection fraction >=50%) by New York Heart Association class
  • 4.5.15 Diagnosed prevalent cases of HF with mid-range ejection fraction (left ventricle ejection fraction 40-49%) by New York Heart Association class
  • 4.5.16 Diagnosed prevalent cases of HF with reduced ejection fraction (left ventricle ejection fraction <40%) by New York Heart Association class
  • 4.5.17 Diagnosed prevalent cases of HF by American College of Cardiology Foundation/American Heart Association stages
• 4.6 Discussion
  • 4.6.1 Epidemiological forecast insight
  • 4.6.2 COVID-19 impact
  • 4.6.3 Limitations of the analysis
  • 4.6.4 Strengths of the analysis

5 Disease Management - Updated October 2024, Based on Events up to October 24, 2024

• 5.1 Diagnosis and treatment overview
• 5.2 KOL insights on disease management

6 Current Treatment Options - Updated October 2024, Based on Events up to October 24, 2024

• 6.1 Overview

7 Unmet Needs and Opportunity Assessment - Updated October 2024, Based on Events up to October 24, 2024

• 7.1 Overview
• 7.2 Lack of therapies for HF with preserved ejection fraction patients
• 7.3 Lack of therapies for acute HF
• 7.4 Compliance and optimal management of HF treatments
• 7.5 Preventative therapies for patients at risk of developing HF

8 R&D Strategies - Updated October 2024, Based on Events up to October 24, 2024

• 8.1 Overview
  • 8.1.1 Label expansion for therapies approved for other indications
  • 8.1.2 Mergers and acquisitions to expand the product pipeline
• 8.2 Clinical trials design
  • 8.2.1 Clinical endpoints for HF
  • 8.2.2 Inclusion and exclusion criteria

9 Pipeline Assessment - Updated October 2024, Based on Events up to October 24, 2024

• 9.1 Overview
• 9.2 Promising drugs in clinical development

10 Pipeline Valuation Analysis - Updated October 2024, Based on Events up to October 24, 2024

• 10.1 Overview
• 10.2 Competitive assessment

11 Current and Future Players - Updated October 2024, Based on Events up to October 24, 2024

• 11.1 Overview
• 11.2 Deal-making trends

12 Market Outlook - Updated October 2024, Based on Events up to October 24, 2024

• 12.1 Global markets
  • 12.1.1 Forecast
  • 12.1.2 Drivers and barriers - global issues
• 12.2 US
  • 12.2.1 Forecast
  • 12.2.2 Key events
  • 12.2.3 Drivers and barriers
• 12.3 5EU
  • 12.3.1 Forecast
  • 12.3.2 Key events
  • 12.3.3 Drivers and barriers
• 12.4 Japan
  • 12.4.1 Forecast
  • 12.4.2 Key events
  • 12.4.3 Drivers and barriers

13 Appendix

• 13.1 Bibliography
• 13.2 Abbreviations
• 13.3 Methodology
  • 13.3.1 Forecasting methodology
• 13.4 Primary research - KOLs interviewed for this report
  • 13.4.1 KOLs
• 13.5 Primary research - prescriber survey
• 13.6 About the authors
  • 13.6.1 Analyst
  • 13.6.2 Therapy Area Director
  • 13.6.3 Epidemiologist
  • 13.6.4 Vice President of Disease Intelligence and Epidemiology
  • 13.6.5 Global Head of Pharma Research, Analysis, and Competitive Intelligence
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List of Tables

• Table 1: Heart failure: key metrics in the 7MM
• Table 2: Types of chronic HF
• Table 3: Causes of HF
• Table 4: Compensatory mechanisms in HF patients
• Table 5: Symptoms of HF
• Table 6: Types of chronic HF
• Table 7: Comparison of two HF classification systems
• Table 8: Risk factors and comorbidities for HF
• Table 9: Treatment guidelines for HF
• Table 10: Top 10 deals by value, 2019-24
• Table 11: HF market - global drivers and barriers, 2022-32
• Table 12: Key events impacting sales for HF in the US, 2022-32
• Table 13: HF market - drivers and barriers in the US, 2022-32
• Table 14: Key events impacting sales for HF in the 5EU, 2022-32
• Table 15: HF market - drivers and barriers in the 5EU, 2022-32
• Table 16: Key events impacting sales for HF in Japan, 2022-32
• Table 17: HF market - drivers and barriers in Japan, 2022-32
• Table 18: High-prescribing physicians (non-KOLs) surveyed, by country

List of Figures

• Figure 1: Global sales forecast by country for HF in 2022 and 2032
• Figure 2: Analysis of the company portfolio gap in HF during the forecast period
• Figure 3: Competitive assessment of the injectable late-stage pipeline agents that GlobalData expects to be licensed for the treatment of HF during the forecast period
• Figure 4: Competitive assessment of the oral late-stage pipeline agents that GlobalData expects to be licensed for the treatment of HF during the forecast period
• Figure 5: Changes in cardiac structure in HF
• Figure 6: 7MM, diagnosed incidence of HF (cases per 100,000 population), men and women, all ages, 2022
• Figure 7: 7MM, diagnosed prevalence of HF (%), men and women, all ages, 2022
• Figure 8: 7MM, sources used and not used to forecast the diagnosed incident cases of HF
• Figure 9: 7MM, sources used to forecast the diagnosed incident cases of HF by EF
• Figure 10: 7MM, sources used to forecast the hospitalization for acute HF
• Figure 11: 7MM, sources used to forecast the hospitalizations for acute HF by presentation
• Figure 12: 7MM, sources used to forecast the hospital LoS for acute HF
• Figure 13: 7MM, sources used to forecast the re-admissions within 30 days post-discharge after acute HF hospitalization
• Figure 14: 7MM, sources used to forecast the diagnosed prevalent cases of HF
• Figure 15: 7MM, sources used to forecast the diagnosed prevalent cases of HF by EF
• Figure 16: 7MM, sources used to forecast the diagnosed prevalent cases of HF by NYHA class
• Figure 17: 7MM, sources used to forecast the diagnosed prevalent cases of HF-PEF, HF-mrEF, and HF-REF by NYHA class
• Figure 18: 7MM, sources used to forecast the diagnosed prevalent cases of HF by EF
• Figure 19: 7MM, diagnosed incident cases of HF, N, both sexes, all ages, 2022
• Figure 20: 7MM, diagnosed incident cases of HF by age, N, both sexes, 2022
• Figure 21: 7MM, diagnosed incident cases of HF by sex, N, all ages, 2022
• Figure 22: 7MM, diagnosed incident cases of HF by EF, N, both sexes, all ages, 2022
• Figure 23: 7MM, hospitalizations for acute HF, N, both sexes, all ages, 2022
• Figure 24: 7MM, acute HF hospitalizations based on presentation, N, both sexes, all ages, 2022
• Figure 25: 7MM, hospital LoS for acute HF, days, both sexes, all ages, 2022
• Figure 26: 7MM, re-admissions within 30 days post-discharge after acute HF hospitalization, N, both sexes, all ages, 2022
• Figure 27: 7MM, diagnosed prevalent cases of HF, N, both sexes, all ages, 2022
• Figure 28: 7MM, diagnosed prevalent cases of HF by age, N, both sexes, 2022
• Figure 29: 7MM, diagnosed prevalent cases of HF by sex, N, all ages, 2022
• Figure 30: 7MM, diagnosed prevalent cases of HF by sex, N, all ages, 2022
• Figure 31: 7MM, diagnosed prevalent cases of HF by NYHA classes, N, both sexes, all ages, 2022
• Figure 32: 7MM, diagnosed prevalent cases of HF-PEF (LVEF >=50%) by NYHA class, N, both sexes, all ages, 2022
• Figure 33: 7MM, diagnosed prevalent cases of HF-mrEF (LVEF = 40-49%) by NYHA class, N, both sexes, all ages, 2022
• Figure 34: 7MM, diagnosed prevalent cases of HF-REF (LVEF <40%) by NYHA class, N, both sexes, all ages, 2022
• Figure 35: 7MM, diagnosed prevalent cases of HF by ACCF/AHA stages, N, both sexes, all ages, 2022
• Figure 36: Diagnosis algorithm for chronic HF
• Figure 37: Unmet needs and opportunities in chronic and acute HF
• Figure 38: Overview of the development pipeline in HF
• Figure 39: Key late-stage trials for the promising pipeline agents that GlobalData expects be licensed for HF in the 7MM during the forecast period
• Figure 40: Competitive assessment of the late-stage pipeline agents that GlobalData expects to be licensed for the treatment of HF during the forecast period
• Figure 41: Competitive assessment of the oral pipeline drugs benchmarked against the standard of care (SOC)
• Figure 42: Competitive assessment of the injectable pipeline drugs benchmarked against the standard of care (SOC)
• Figure 43: Analysis of the company portfolio gap in HF during the forecast period
• Figure 44: Global (7MM) sales forecast by country for HF in 2022 and 2032
• Figure 45: Sales forecast by class for HF in the US in 2022 and 2032
• Figure 46: Sales forecast by class for HF in the 5EU in 2022 and 2032
• Figure 47: Sales forecast by class for HF in Japan in 2022 and 2032