Due to unprecedented interest in this workshop, we are no longer accepting registrations. However you may view this workshop live on the NIH VideoCast site:

Day 1: Wednesday, October 23, 2024, 11:00 AM – 5:15 PM ET (UTC -4)

Day 2: Thursday, October 24, 2024, 11:00 AM – 5:15 PM ET (UTC -4)

Please note: If you have already registered, you will be sent a Zoom link. On Zoom you will be able to participate in the Q&A sessions. The Zoom is limited to 1,000 concurrent users. If you are not able to join on Zoom due to the capacity limit, you should click to join the VideoCast using the links here and also in the email you will receive.

About the Workshop

The National Center for Advancing Translational Sciences (NCATS) Assay Guidance Manual (AGM) program is hosting a two-day workshop that will cover a broad range of critical concepts, including practical approaches and best practices, to successfully develop and integrate accurate, robust, and rigorous AI/ML methods/models into drug discovery pipelines and to facilitate discussions around utilization of such methodologies. Many of the speakers are pioneers of covered scientific topics and the listed workshop sessions aim to share the fundamentals and modern knowledge to facilitate learning for both novice and established practitioners. This workshop is jointly organized by NCATS, Biomedical Advanced Research and Development Authority (BARDA), University of California San Diego (UCSD), and The University of North Carolina at Chapel Hill (UNC).

Goals and Objectives

This workshop aims to provide scientists with best practices and standards for rigor in the field of computational drug discovery to enable accurate and reproducible results. This workshop will also cover case studies for AI-driven drug discovery campaigns as well as an overview of new trends and gaps in the field.

Specific learning goals and objectives of this workshop include:

Provide participants with data sources and best practices in building and maintaining databases used for developing robust and rigorous AI based drug discovery models/methods.
Introduce participants to the available computational methodologies utilized in drug discovery and discuss their utility and limitations.
Provide case studies for digital drug discovery and an overview of new trends in the field.
Provide guidelines and considerations for developing robust and reproducible in silico models.
Discuss challenges in data quality and data sharing as well as affordability, accessibility, transferability, accuracy, and reproducibility of AI-driven computational techniques.
Identify gaps in translation of these in silico models to therapies and seed discussions around best practices to help bridge the gaps in the field.

Agenda

Download the agenda

About the Assay Guidance Manual Program

The AGM program is a world-class source of guidelines and best practices for advancing translational science and research in the preclinical development of novel therapeutics and offers training and insight for those desiring to become translational scientists. This program provides scientists with community-developed best laboratory practices in early translational research, including robust assay development, analytical technologies, data analysis tools and preclinical drug discovery standards. The program also aims to help the preclinical drug discovery workforce understand the value of robust, reproducible and replicable results.

The AGM program provides multiple resources, including the AGM eBook. This manual contains best practices in preclinical drug discovery and is free and publicly available from the National Library of Medicine; its editorial board has members from both the private and public sectors.

The program offers in-person and virtual multiday training workshops and conferences. It also hosts an AGM Preclinical Translational Science Webinar Series. This series highlights distinguished translational scientists who share case studies and information about preclinical translational science.

Workshop Organizing Committee

Rommie Amaro, University of California San Diego (UCSD)

Hanna Baskir, NCATS

Kyle Brimacombe, NCATS

Abigail Grossman, NCATS

Matthew D. Hall, NCATS

Sarine Markossian, NCATS

Shyam Rele, Biomedical Advanced Research and Development Authority (BARDA)

Morgan Sherer, BARDA

Alexander Tropsha, University of North Carolina at Chapel Hill

Alexey Zakharov, NCATS

In silico Drug Discovery Workshop