Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products Guidance for Industry and Other Interested Parties; Draft Guidance

Eigen Bio, a biotechnology company, supports the draft guidance and suggests several improvements to enhance its scope and practical application. They recommend including preclinical AI models, providing specific guidance for federated learning, creating accelerated pathways for orphan drugs, and establishing a centralized AI advisory point for early-stage sponsors.

The EU Innovative Health Initiative (IHI) VICT3R project, a public-private consortium, supports the draft guidance and recommends expanding the AI definition to include Virtual Control Groups (VCGs). They also suggest clarifying the definition of "credibility" using established frameworks and providing more diverse case studies and examples.

Flagship Pioneering, a biotechnology company, supports the FDA's draft guidance but urges the Agency to balance patient safety with the need to foster innovation by avoiding overregulation. They recommend narrowing the scope of oversight to AI applications that directly impact patient safety, providing clearer risk-based requirements, and establishing a centralized AI council to facilitate early engagement with developers.

Cruelty Free International supports the proposed guidance but urges the FDA to explicitly emphasize and include examples of AI applications that can replace, rather than just reduce, animal testing. They argue that prioritizing human-relevant data and modern AI models will improve drug development outcomes, reduce costs, and align with ethical standards.

The Association for Accessible Medicines (AAM), representing generic and biosimilar pharmaceutical manufacturers, supports the draft guidance on using AI in regulatory decision-making. They suggest specific improvements to enhance the guidance's utility, including adding more technical examples, clarifying transparency vs. intellectual property protections, and refining requirements for performance metrics and confidence intervals.

TriApex Laboratories Co., Ltd., a contract research organization (CRO), supports the draft guidance but suggests improvements regarding third-party AI validation and non-clinical AI adoption. They propose a "Partial Disclosure + Third-Party Certification" model for proprietary "black-box" AI tools and suggest creating a "Preclinical AI Consultation" process to provide clearer pathways for non-clinical applications.

Joe argues that current animal testing methods are outdated and economically unsustainable due to high drug failure rates. He advocates for the FDA to rapidly adopt AI and machine learning technologies to modernize the drug commercialization process.