The world AI on the clinical trial market tends to current partnerships

By Mathini IlancheranMain analyst, R&D, Beroe Inc.

Currently, the pharmaceutical industry has adopted a conservative approach to the adoption of LIA on a large scale due to the prudence necessary to treat human life, regulatory uncertainties and substantial capital requirements. The AI ​​-based models have been used to complete traditional experimental methods, ensuring the safety and efficiency of drugs. The integration of AI maintains the potential to accelerate the creation of new treatments, reduce costs and improve patient results. However, to fully exploit the potential of AI in pharmaceutical research and development, the challenges linked to data accessibility, the interpretability of algorithms and regulatory frameworks must be noted.

AI trends in the development of clinical drugs

Market growth and potential

The global AI on the clinical trial market is estimated at around $ 1.35 billion in 2025. It is expected to increase at an annual growth rate (TCAC) by 12.4%, reaching $ 2.74 billion D ‘here 2030 (Figure 2)¹.

The generative AI is particularly transformative, with the potential to generate $ 13 billion at 25 billion dollars of annual value specifically at the level of clinical trials².

Application and feedback

AI applications in clinical research are mainly concentrated in oncology, especially in patient recruitment – one of the most difficult aspects of clinical trials. The AI ​​improves efficiency by reducing the size of the samples, improving registration rates and allowing faster and more optimized adaptive trials. In December 2022, the 800 main Pharmaceutical companies focused on AI collectively received approximately more than $ 59.3 billion in funding, reflecting a significant increase compared to the $ 37 billion reported the previous year ³. This increase in investment highlights the AI ​​transformer potential to reshape both clinical trials and the discovery of drugs, promising revolutionary therapies and substantial economic benefits for the pharmaceutical industry during the next decade.

Clinical trials using AI technologies have the potential to considerably improve results in several key areas. Some examples include:

• Approval at a lower cost – According to IQVIA, a clinical research site has operated the technology fueled by AI- and ML to rationalize the supplements of the feasibility survey, achieving a 90% reduction in the required time.
• Faster time to market – A biopharmaceutical company has shortened the test periods from 15% to 30% by substituting the traditional evaluation criterion with a rare disease with more frequent assessment criteria or those measurable through blood tests⁴.
• Improvement of patient results – ML prediction models allowed a decrease of 15% to 25% of cancer mortality rates in several clinical trials⁵.
• Optimization of cancer medication trials – Take advantage of the AI ​​in partnership with Immunai, Astrazeneca reduced the test periods to 25%, optimizing the selection of the dose and improving the identification of biomarkers in the tests of drug cancer drugs¹¹.

Partnerships of the clinical trials led by AI

From 2022 to 2025, pharmaceutical companies have become more and more associated with technological companies to apply AI in clinical research, drug development and manufacturing. These collaborations aim to optimize the design of clinical trials, to improve the recruitment and retention of patients, to improve the analysis of real world evidence and to rationalize manufacturing processes. Investments in these areas are between $ 2 billion and $ 4 billion USD, reflecting the accent put by the sector to integration of AI to reduce costs, accelerate deadlines and improve efficiency^6.7.

The following table describes the main partnerships established between pharmaceutical and technological companies from 2023 to the present day.

Conclusion

The growing adoption of AI, with a 30% increase in partnerships from 2022 to 2024, underlines the recognition by the AI ​​transformer potential industry. AI technologies allow the integration of real world data, improving test design and promoting decentralized trials, paved the way for more accessible and patient drug development processes. In addition, the progress of manufacturing led by AI tackle the scalability and efficiency of production, essential to respond^8.9.

While AI continues to mature, the adoption of the pharmaceutical industry about this technology reflects a commitment to innovation and efficiency, ultimately promising faster administration of safer and more effective therapies for patients around the world. Trends and partnerships have highlighted not only a turning point in clinical research, but also establish a solid basis for the future of precision medicine and value -based health care.

References:

1. Research and Markets, “www.globenewswire.com”, www.globenewswire.com, January 6, 2025. (Online). Available: https://www.globenewswire.com/news-release/2025/01/06/3004773/28124/en/ai-in-clinical-strials-market-research-2024-2030-with-in-epth- Sessment- strategies and services of the growth of market acts.
2. MCKINSEY & COMPANY, “Generative AI in the Pharmaceutical Industry: Moving of Hype to Reality”, MCKINSEY & COMPANY, January 4, 2024.
3. Nr Narain, “a new era of drug discovery with an AI focused on biology”, Forbes, February 14, 2024. (Online).
4. C. Anagnostopoulos, D. Champagne, T. Devenyns, A. Devereson and H. Tarkkila, “How Artificial Intelligence Can Power Clinical Development”, McKinsey & Company, November 22, 2023.
5. A. S, B. D and C. G, “Artificial intelligence applied to clinical trials: opportunities and challenges”, Health Technol Springer, February 28, 2023.
6. Fiercebiotech, “Big Pharma’s Bari on clinical trials and development based on AI”, 2024.
7. Pharmaceutical technology, “AI adoption in Pharma Clinical Operations”, 2023.
8. Marketwatch, “AI in the development and manufacture of clinical drugs”, 2024.
9. Evolveetfs, “AI Partnerships Revolutioning Healthcare Sector Investments”, 2023.
10. Novo Nordisk and Valo Health, “expanded collaboration to develop treatments for obesity, type 2 diabetes and cardiovascular diseases using AI,” Press Lippère, 2025.
11. C. Hale, “Astrazeneca extends an Immuno-Oncology R & D pact with Immunai”, Fierce Biotech, September 26, 2024. (Online). Available: Astrazeneca extends the Immuno-Oncology R&D pact with Immunaï. (Accessed February 15, 2025).
12. JW Pharmaceutical and Oncocross, “Research spouse to develop anticancer and regenerative drugs using AI to identify new indications”, JW Pharmaceutical, 2024.
13. Sanofi and Owkin, “entered an alliance to use AI in oncology to discover biomarkers and therapeutic targets”, Sanofi, 2023.
14. Amgen and Amazon Web Services, “Collaborated to Use AI in the discovery and manufacturing processes”, AMGEN, 2023.
15. Advanced Micro Devices (AMD) and ABSCI Corp., “invested $ 20 million to support the discovery of IA -run medicines, aimed at improving therapeutic development antibodies”, Press Lippère, 2025.
16. Janssen and Komodo Health, “have joined forces to improve clinical trials in oncology using the real world data focused on AI”, Globaldata, 2023.
17. Bristol Myers Squibb and Tempus, “collaborated to use AI for the discovery of biomarkers and the stratification of patients in oncology”, Pharmatimes, 2023.
18. Merck and Deepmind, “entered a partnership to apply AI in the discovery of drugs, focusing on the folding of proteins and the prediction of the structure”, Deepmind, 2023.
19. Roche and Unkearn.ai, “collaborated to use AI in clinical trials, aimed at reducing the need for control groups through synthetic controls”, Roche Press Lippère, 2023.
20. Bayer and sensyne Health, “associated to apply AI in the discovery and development of drugs, focusing on cardiovascular and oncology indications”, Bayer News, 2023.
21. Eli Lilly and Médable, “collaborated to use AI in decentralized clinical trials, aimed at improving the recruitment and retention of patients”, Médable, 2023.

About the author:

Mathini Ilancheran is an expert in market intelligence and industry analysis, specializing in the supply of strategic information that helps Fortune 500 companies make informed decisions. By focusing on global pharmaceutical, biotechnological and medical devices, it provides in -depth expertise in the analysis of the value chain, industry and technology trends, competitive intelligence and strategy. A prolific opinion leader, Mathini is the author of more than 35 publications on the outsourcing of R&D, offering exploitable perspectives that guide global companies in the optimization of outsourcing practices, management of categories and long -term planning.