Exploring AI Impact on Drug Design and Genetic Experiments

This chapter delves into the impact of AI on drug design within pharmaceutical R&D, discussing the significance of genetic databases and machine learning in identifying disease-related variations and predicting protein changes. It also explores conducting experiments in genetics, challenges in discovering continuous traits, and the necessity for machine learning in processing vast amounts of data. The conversation emphasizes the importance of unique data for startups, controlling sampling biases, and the significance of robustness and reliability criteria in evaluating machine learning models.