Archive · 22 Aug 2026
India’s Pharma Industry Embraces AI Amid Regulatory Concerns
Pharmaceutical companies in India are starting to use artificial intelligence in many parts of healthcare.
AI can help researchers find possible medicines faster and identify problems in clinical trials earlier.
It can also summarize patient records, write clinical notes and examine medical scans.
The drug regulator said these tools create difficult questions about safety and responsibility.
For example, it may be unclear who is responsible if an app tells a person what medicine to take.
AI can also change frequently, while regulators usually approve products that are expected to stay consistent.
Industry leaders said doctors should remain involved and that AI should help them rather than replace them.
They believe AI could give doctors more time with patients and improve early detection.
India’s top drug regulator warned that AI healthcare tools could create accountability and regulatory challenges.
Rajeev Raghuvanshi said continuously changing AI systems are difficult to regulate under rules designed for stable products.
AI adoption remains concentrated among roughly the top 10% of pharmaceutical companies, especially in discovery research.
Pankaj Patel said AI could shorten drug development, improve clinical-trial selection and reduce paperwork for doctors.
Industry leaders said AI should support clinicians through early detection, monitoring and decision-making rather than replace them.
- Who
- Drugs Controller General of India Rajeev Raghuvanshi, Zydus Lifesciences chairman Pankaj Patel and Abbott India executive vice president Vivek Mohan discussed the issue.
- What
- The IIMA Healthcare Summit examined the pharmaceutical industry’s growing use of AI and the regulatory risks associated with it.
- When
- The summit discussion took place on a Saturday; the article was published on August 22, 2026.
- Where
- The summit was held in Ahmedabad, India.
- Why
- AI is being adopted because it can reduce research and clinical timelines, analyze data and support doctors, while its changing behavior raises questions about safety and accountability.
Regulatory Caution
Industry Opportunity
Accountability for AI recommendations
Regulatory Caution
Rajeev Raghuvanshi warned that responsibility may be unclear if a mobile application directly tells consumers what treatment or medicine to use.
Industry Opportunity
Industry speakers emphasized clinician-supported AI, with tools intended to improve decision-making and enable more informed conversations between patients and doctors.
Regulating continuously changing systems
Regulatory Caution
The regulator said conventional approval systems are designed to keep a product’s quality, safety and performance consistent, while AI can change daily.
Industry Opportunity
Pharma leaders argued that AI’s ability to reduce research timelines, identify failures earlier and assist clinical work can significantly improve healthcare efficiency.
Replacement versus assistance
Regulatory Caution
Regulatory concerns center on AI making recommendations independently of doctors, potentially weakening existing medical accountability.
Industry Opportunity
Pankaj Patel and Vivek Mohan said AI should assist clinicians, return time to doctors and provide early warnings rather than replace medical professionals.
- Event
- Third edition of the IIMA Healthcare Summit
- Summit theme
- Advancing AI in Healthcare
- Regulatory concern
- It is unclear whether some AI systems fit the definition of medical devices and who is accountable for consumer-facing recommendations.
- AI adoption
- The regulator estimated that adoption is concentrated among approximately the top 10% of pharmaceutical companies.
- Research uses
- AI is being used to predict molecule behavior, propose drug candidates, analyze data and identify clinical-trial patients.
- Clinical uses
- Examples include AI scribes, discharge-summary drafting, patient-history summaries and analysis of chest X-rays or retinal scans.
- Industry position
- Speakers said AI should support clinicians in decision-making rather than replace them.