Artificial Intelligence and the Transformation of Cell and Gene Therapy Development

Area of Science:

• Biotechnology
• Medical Innovation
• Computational Biology

Background:

• Cell and Gene Therapy (CGT) offers curative potential but faces significant accessibility challenges due to complexity and high costs.
• Current CGT development, manufacturing, and administration processes are often inefficient and costly, limiting patient access.

Purpose of the Study:

• To review the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) across the entire Cell and Gene Therapy (CGT) lifecycle.
• To analyze how AI/ML approaches overcome barriers in CGT discovery, manufacturing, clinical translation, and regulatory processes.
• To outline a roadmap for realizing the full potential of AI-enabled CGT.

Main Methods:

• Review of current literature and AI/ML applications in CGT.
• Analysis of AI-driven methodologies in construct design, manufacturing, and translational modeling.
• Examination of AI's impact on pharmacovigilance and regulatory oversight.

Main Results:

• AI/ML accelerates CGT construct optimization and improves translational model predictability.
• AI enables autonomous, digital-twin-driven smart manufacturing for CGT.
• AI establishes new paradigms for CGT pharmacovigilance and regulatory compliance.

Conclusions:

• AI integration is a foundational transformation, shifting CGT towards scalable, accessible, and personalized medicine.
• Addressing data scarcity and regulatory uncertainty is crucial for AI-enabled CGT.
• AI is key to unlocking the full potential of CGT for treating intractable diseases.