R&D Partnerships: Insights from Innovators
Amid the shifting and uncertain landscape of gene therapies, navigating uncharted territory on AI-guided design, AAV immunogenicity, and the predictive trends for viral and non-viral gene therapies with an AAV gene therapy expert. Read through for insight into integrating AI-guided design with drug discovery, for the effective development of gene therapies
The AI/ML Frontier in AAV Gene Therapy, & Predictive Trends for Viral & Non-Viral Therapies
Q. AI/ML approaches to capsid design and engineering, and drug discovery as a whole, have been intriguing to the field. Could you speak to the major areas of utility for this approach, i.e, does AI-guided design allow for selection of capsids more suited for specific indications, or are we focused more on AI-guided design to accelerate discovery of lead candidates?
A. It is hard to overstate the promise and hype surrounding AI/ML approaches in drug discovery. A fundamental aspect of the methods’ power is how more data can be used to create better models. The rate of data generation has expanded quickly since more resources have been utilized towards AI/ML approaches. Therefore it is reasonable to expect ML models to keep improving and producing even better capsids in this positive feedback loop.
Most past capsid engineering approaches have relied on generation of large and complex gene libraries where random mutations…
