Cambridge Healthtech Institute’s 2nd Annual

AI/ML-Enabled Drug Discovery

Part 1: AI/ML for Identifying Novel Targets and Pathways

September 26-27, 2023

Part 2: AI/ML for Drug Design, Screening, and Lead Optimization

September 27-28, 2023


Cambridge Healthtech Institute’s two-part conference on Artificial Intelligence (AI)/Machine Learning (ML)-Enabled Drug Discovery will highlight the increasing use of computational tools, AI modeling, algorithms, and data science for identifying novel drug targets, drug design, virtual screening, lead optimization, and ADME/toxicology assessments. Relevant case studies and research findings will show how and where AI/ML can be successfully integrated and implemented in drug discovery. It will bring together chemists, biologists, pharmacologists, and bioinformaticians to talk about hope versus hype, and to understand the caveats of AI-enabled decision-making.


Who should attend: Scientist in Computational Chemistry, Computational Biology, Bioinformatics, Data Sciences, IT, Target Discovery, Drug Design, Medicinal Chemistry, Lead Discovery, Proteomics, Genomics, Assay Development and  Screening, Pharmacology, Toxicology.


Part 1:

Part 1 of the AI/ML-Enabled Drug Discovery conference will focus on use of AI and ML predictions and modeling for identifying and prioritizing drug targets and cellular pathways to pursue.     


Coverage will include, but is not limited to:


  • AI for accelerating target identification and validation
  • AI/ML for understanding cellular pathways and disease pathogenesis
  • AI/ML for predicting induced proximity and targeted degradation
  • AI/ML for genomics and proteomics-driven drug discovery


Part 2:

Part 2 of the AI/ML-Enabled Drug Discovery conference will highlight growing use of AI and ML for drug design, compound screening, hit-to-lead identification, lead optimization, and predicting drug-like properties.


Coverage will include, but is not limited to:


  • AI/ML for drug design and lead optimization
  • Expanding chemical space using ML
  • AI-enabled screening and drug candidate prioritization
  • ML approaches to predict binding and drug-like properties
  • AI/ML for predicting ADME and safety profiles


The deadline for priority consideration is March 17, 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.


Opportunities for Participation:



For more details on the conference, please contact:

Tanuja Koppal, PhD

Senior Conference Director

Cambridge Healthtech Institute



For sponsorship information, please contact:

Kristin Skahan

Senior Business Development Manager

Cambridge Healthtech Institute

Phone: (+1) 781-972-5431