Atrial Fibrillation: Eight-Market Drug Forecast and Market Analysis - Update

1.1 Summary of changes
1.2 Executive summary
1.3 AF market will decline at a negative CAGR of 3.2%
1.4 Bayer and Bristol Myers Squibb will continue to lead the AF market over the forecast period
1.5 While outlook in AF improves, opportunities remain to improve patient outcomes
1.6 BMS and Johnson & Johnson’s (J&J) milvexian will be a key driver of growth
1.7 What do physicians think?

2.1 Catalyst
2.2 Related reports
2.3 Upcoming reports

3.1 Etiology and pathophysiology
3.1.1 Etiology
3.1.2 Pathophysiology
3.2 Classification

4.1 Disease background
4.2 Risk factors and comorbidities
4.3 Global and historical trends
4.4 8MM forecast methodology
4.4.1 Sources
4.4.2 Forecast assumptions and methods
4.4.3 Forecast assumptions and methods: total prevalent cases of AF - 8MM
4.4.4 Forecast assumptions and methods: diagnosed prevalent cases of AF
4.4.5 Forecast assumptions and methods: diagnosed prevalent cases of AF by temporal patterns of arrhythmia
4.4.6 Forecast assumptions and methods: diagnosed prevalent cases of AF by CHADS2 stroke risk score
4.4.7 Forecast assumptions and methods: diagnosed prevalent cases of AF by CHA2DS2 - VASc stroke risk score in men
4.4.8 Forecast assumptions and methods: diagnosed prevalent cases of AF by CHA2DS2 - VASc stroke risk score in women
4.4.9 Forecast assumptions and methods: diagnosed prevalent cases of AF with/without moderate-to-severe mitral stenosis and/or an artificial (mechanical) heart valve
4.4.10 Forecast assumptions and methods: diagnosed prevalent cases of AF with CKD by stage
4.4.11 Forecast assumptions and methods: diagnosed prevalent cases of AF with major bleeding risk by HAS-BLED score
4.4.12 Forecast assumptions and methods: diagnosed prevalent cases of AF admitted to ED
4.5 Epidemiological forecast for atrial fibrillation
4.5.1 Total prevalent cases of AF
4.5.2 Diagnosed prevalent cases of AF
4.5.3 Age-specific diagnosed prevalent cases of AF
4.5.4 Sex-specific diagnosed prevalent cases of AF
4.5.5 Diagnosed prevalent cases of AF by temporal pattern of arrhythmia
4.5.6 Diagnosed prevalent cases of AF by CHADS2 stroke risk score
4.5.7 Diagnosed prevalent cases of AF by CHA2DS2 - VASc stroke risk score in men
4.5.8 Diagnosed prevalent cases of AF by CHA2DS2 - VASc stroke risk score in women
4.5.9 Diagnosed prevalent cases of AF with or without moderate-to-severe mitral stenosis and/or an artificial (mechanical) heart valve
4.5.10 Diagnosed prevalent cases of AF with CKD by stage
4.5.11 Diagnosed prevalent cases of AF with major bleeding risk by HAS-BLED score
4.5.12 Diagnosed prevalent cases of AF admitted to ED
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

5.1 Diagnosis and treatment overview
5.1.1 Diagnosis
5.1.2 Treatment
5.2 KOL insights on disease management

6.1 Overview

7.1 Overview
7.2 Development of anticoagulants with reduced risk of bleeding
7.3 Therapies for atrial fibrillation patients with ESRD
7.4 Safer antiarrhythmic drugs for the maintenance of sinus rhythm
7.5 Effective and rapid-acting cardioversion drugs

8.1 Overview
8.1.1 Development of anticoagulants with novel MOAs to reduce bleeding risk
8.1.2 FXI/FXIa inhibitor modalities
8.1.3 Development of non-invasive and fast-acting cardioversion agents
8.2 Clinical trials design
8.2.1 Exclusion criteria for AF clinical trials

9.1 Overview
9.2 Promising drugs in clinical development

10.1 Overview
10.2 Competitive assessment
10.2.1 Anticoagulant agents
10.2.2 Pharmacological calcium channel blockers

11.1 Overview
11.2 Deal-making trends

12.1 Market outlook - updated August 2025, based on events up to July 2025
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
12.5 Canada
12.5.1 Forecast
12.5.2 Key events
12.5.3 Drivers and barriers

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 Epidemiologist reviewers
13.6.5 Vice President of Disease Analysis and Intelligence
13.6.6 Global Head of Pharma Research, Analysis and Competitive Intelligence

• About the Analyst
• Contact the Publisher

Table 1: Summary of changes to AF: Eight-Market Drug Forecast and Analysis report
Table 2: Atrial fibrillation: key metrics in the 8MM
Table 3: Common cardiac and non-cardiac causes of AF
Table 4: Classification of AF
Table 5: Risk factors and comorbidities for AF
Table 6: CHA2DS2-VA score for stroke risk assessment
Table 7: CHA2DS2-VASc score for stroke risk assessment
Table 8: Treatment guidelines for atrial fibrillation
Table 9: Top 10 deals by value, 2020-25
Table 10: Atrial fibrillation market - global drivers and barriers, 2022-32
Table 11: Key events impacting sales for atrial fibrillation in the US, 2022-32
Table 12: Atrial fibrillation market - drivers and barriers in the US, 2022-32
Table 13: Key events impacting sales for atrial fibrillation in the 5EU, 2022-32
Table 14: Atrial fibrillation market - drivers and barriers in the 5EU, 2022-32
Table 15: Key events impacting sales for atrial fibrillation in Japan, 2022-32
Table 16: Atrial fibrillation market - drivers and barriers in Japan, 2022-32
Table 17: Key events impacting sales for atrial fibrillation in Canada, 2022-32
Table 18: Atrial fibrillation market - drivers and barriers in Canada, 2022-32
Table 19: High-prescribing physicians (non-KOLs) surveyed, by country

Figure 1: Global sales forecast by country for atrial fibrillation in 2022 and 2032
Figure 2: Analysis of the company portfolio gap in atrial fibrillation during the forecast period
Figure 3: Competitive assessment of the pipeline anticoagulant drugs benchmarked against the current SOC
Figure 4: Competitive assessment of the pipeline drugs for pharmacological cardioversion benchmarked against the SOC
Figure 5: 8MM, diagnosed prevalence of AF (%), men and women, ages =40 years, 2022
Figure 6: 8MM, sources used and not used to forecast the diagnosed prevalent cases of AF
Figure 7: 8MM, sources used to forecast the diagnosed prevalent cases of AF by temporal pattern of arrhythmia
Figure 8: 8MM, sources used to forecast the diagnosed prevalent cases of AF by CHADS2 stroke risk score
Figure 9: 8MM, sources used to forecast the diagnosed prevalent cases of AF by CHA2DS2 - VASc score in men
Figure 10: 8MM, sources used to forecast the diagnosed prevalent cases of AF by CHA2DS2 - VASc score in women
Figure 11: 8MM, sources used to forecast the diagnosed prevalent cases of AF with/without moderate-to-severe mitral stenosis and/or an artificial (mechanical) heart valve
Figure 12: 8MM, sources used to forecast the diagnosed prevalent cases of AF with CKD
Figure 13: 8MM, sources used to forecast the diagnosed prevalent cases of AF with major bleeding risk by HAS-BLED score
Figure 14: 8MM, sources used to forecast the diagnosed prevalent cases of AF admitted to the ED
Figure 15: 8MM, sources used to forecast the diagnosis rate of AF
Figure 16: 8MM, total prevalent cases of AF, N, both sexes, ages =40 years, 2022
Figure 17: 8MM, diagnosed prevalent cases of AF, N, both sexes, ages =40 years, 2022
Figure 18: 8MM, diagnosed prevalent cases of AF by age, N, both sexes, 2022
Figure 19: 8MM, diagnosed prevalent cases of AF by sex, N, ages =40 years, 2022
Figure 20: 8MM, diagnosed prevalent cases of AF by temporal pattern of arrhythmia, N, both sexes, ages =40 years, 2022
Figure 21: 8MM, diagnosed prevalent cases of AF by CHADS2 stroke risk score, N, both sexes, ages =40 years, 2022
Figure 22: 8MM, diagnosed prevalent cases of AF by CHA2DS2 - VASc stroke risk score in men, N, men, ages =40 years, 2022
Figure 23: 8MM, diagnosed prevalent cases of AF by CHA2DS2 - VASc stroke risk score in women, N, women, ages =40 years, 2022
Figure 24: 8MM, diagnosed prevalent cases of AF with and without moderate-to-severe mitral stenosis and/or an artificial (mechanical) heart valve, N, both sexes, =40 years, 2022
Figure 25: 8MM, diagnosed prevalent cases of AF with CKD by stage, N, both sexes, ages =40 years, 2022
Figure 26: 8MM, diagnosed prevalent cases of AF by HAS-BLED score, N, both sexes, ages =40 years, 2022
Figure 27: 8MM, diagnosed prevalent cases of AF admitted to ED, N, both sexes, ages =40 years, 2022
Figure 28: General treatment algorithm for stroke prevention in AF
Figure 29: CCS guideline recommendations for choosing an anticoagulant
Figure 30: General treatment algorithm for long-term ventricular rate control in AF patients
Figure 31: Treatment algorithm for the maintenance of sinus rhythm in AF patients
Figure 32: Unmet needs and opportunities in AF
Figure 33: Overview of the development pipeline in atrial fibrillation
Figure 34: Key late-stage trials for the promising pipeline agents that the analyst expects to be licensed for atrial fibrillation in the 8MM during the forecast period
Figure 35: Competitive assessment of the marketed and pipeline drugs for anticoagulation benchmarked against the SOC
Figure 36: Competitive assessment of the marketed and pipeline drugs for calcium channel blocker benchmarked against diltiazem
Figure 37: Analysis of the company portfolio gap in AF during the forecast period
Figure 38: Global (8MM) sales forecast by country for atrial fibrillation in 2022 and 2032
Figure 39: Sales forecast by class for atrial fibrillation in the US in 2022 and 2032
Figure 40: Sales forecast by class for atrial fibrillation in the 5EU in 2022 and 2032
Figure 41: Sales forecast by class for atrial fibrillation in Japan in 2022 and 2032
Figure 42: Sales forecast by class for atrial fibrillation in Canada in 2022 and 2032