2023 - Using AI in Drug Development to Enhance Preclinical Translatability

Drug developers are increasingly turning to computational / in silico tools and methods to enhance novel drug investigation, as well as reduce costs and improve translation throughout the development lifecycle, from lead optimization through validation.
But despite the infusion of computational models and the improvements gained from their use, the drug failure rate remains the same (if not greater). Workflows leveraging key datasets are often siloed, as are traditional computational models, which also suffer from being overfit, error-prone and limited in their extensibility.
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Join this webinar to learn how exactly AI and ML techniques are taking computational modeling and informatics to new domains of applicability in the drug development lifecycle. Through illustrative examples of AI in drug development, attendees will gain a better understanding of how these techniques can be applied to enhance decision-making and increase the chances of clinical success.
Register today!