Cambridge Healthtech Institute’s 6th Annual

AI/Machine Learning for Early Drug Discovery – Part 1

AI-Driven Decision-Making for Drug Design, Screening, and Lead Optimization

April 2-3, 2024

Artificial Intelligence (AI)/Machine Learning (ML) for Early Drug Discovery is a two-part conference that brings together a diverse group of experts from chemistry, target discovery, pharmacology, and bioinformatics to talk about the increasing use of computational tools, models, algorithms, and data analytics for drug development. The talks will highlight the pros and cons of AI/ML-driven decision-making using relevant case studies from small molecule and peptide drug development. The first part of the conference will focus on how AI/ML can help improve drug design, hit identification, and lead optimization.

Coverage will likely include:

AI-driven molecular modeling and virtual screening for drug design, reaction kinetics, and specificity
AI and ML-enabled hit identification, drug candidate prioritization, and lead optimization
Case studies highlighting the use of quantum chemistry and computational modeling
Improving compound efficacy based on AI/ML predictions and data analytics

The deadline for priority consideration is September 15, 2023.

All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge Healthtech Institute’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.

We hope you can join us for the 5 concurrent day-and-a-half conferences during each half of our 19th Annual Drug Discovery Chemistry event. Registering for this conference lets you also move back and forth among parallel programs to create your own agenda.

Opportunities for Participation: