Regulating the AI-enabled ecosystem for human therapeutics.

Area of Science:

• Biopharmaceutical industry
• Drug discovery and development
• Regulatory science

Background:

• Artificial intelligence (AI) offers transformative potential for pharmaceutical innovation.
• The biopharmaceutical sector requires stringent regulatory oversight for drug quality, efficacy, and safety.

Purpose of the Study:

• To examine the challenges in regulating AI-driven technologies within drug discovery and development.
• To provide recommendations for effective regulatory frameworks for AI in the biopharmaceutical industry.

Main Methods:

• Evaluation of current global drug regulatory practices.
• Identification of gaps and unknowns in AI regulation.
• Analysis of AI's role in drug discovery, development, manufacturing, and delivery.

Main Results:

• AI is poised to significantly impact pharmaceutical R&D timelines and costs.
• Effective regulation is crucial for harnessing AI's benefits while ensuring safety.
• Existing regulatory frameworks may need adaptation for AI-driven innovations.

Conclusions:

• The focus should be on *how* to regulate AI in pharmaceuticals, not *if*.
• Addressing regulatory gaps is essential for fostering AI innovation.
• Proactive regulatory strategies are needed to support AI in the biopharmaceutical industry.