Accelerating CGTX Discovery and Development through Advanced Phenotypic Models and Machine Learning

This panel will explore the ways in which next-generation engineered in-vitro models can be combined with innovations in machine learning applications to drive more rational development of complex cell and gene therapy products. Leveraging advances in in-vitro model development (ex. engineered iPSC-derived tissues) as a starting point for discovery, AI/ML platforms can help make connections and correlations between cause and effect in CGTx development at a rapid pace, ultimately driving towards faster, cheaper, and more accurate therapeutic outputs. This model is already established in the small molecule space, and this panel will explore how this will translate to the CGTx industry.

Chair:
Adam Roose, Vice President, Cell and Gene Commercial Strategy, Adjuvant Partners

Speakers:
Isaac Bentwich, M.D., Founder and CEO, Quris Technologies
Robert Deans, Ph.D., Chief Scientific Officer, Synthego
Keith James, Ph.D., Senior Vice President, Drug Discovery, insitro
Emmanouil Metzakopian, Ph.D., Vice President, Research and Development, bit.bio