Assay Guidance Workshop for High-Throughput Screening and Lead Discovery

This full-day workshop will cover a broad range of critical concepts underlying assay development and implementation for high-throughput screening (HTS) and lead discovery projects. This workshop is designed to disseminate critical information about the implementation of robust assay methods and is particularly relevant for researchers developing molecular probes or clinical candidates. Many of the instructors have 20 to 30 years of experience in the field of drug discovery and will share information not readily found in a classroom or published material outside of the Assay Guidance Manual (AGM) eBook.

Who Should Attend?

Scientists from academia, industry, and government involved in bioassay development for drug discovery and development are encouraged to attend. The AGM eBook and this workshop will be a valuable resource for individuals planning or beginning to develop methods for high- or low-throughput screening that are amenable to automation using appropriate statistical and operational concepts. The workshop will be useful for everyone from early career researchers to experienced investigators who wish to learn about the latest assay concepts for HTS and lead optimization.

Course Benefits

Participants will learn best practices for the development and implementation of robust assays and gain a broad, practical perspective on assay development and data analysis. Additionally, participants will have the opportunity to seek practical advice about individual research challenges.

Course Objectives

• Gain an overview of the AGM eBook as an important resource for detailed information about robust assay methods and best practices in quantitative biology.
• Learn practical approaches for developing robust assays for small molecule discovery and validation, including biochemical, biophysical, and cell-based assays.
• Identify and develop optimal assay reagents and assay instrumentation.
• Gain an overview of sources of assay artifacts and strategies to identify artifacts through the development and implementation of counter assays.
• Interpret important statistical and data analysis concepts with an emphasis on using these concepts to collect the best possible data and make go/no go decisions based on experimental results.

Course Instructors

Michelle Arkin, University of California San Francisco
Nathan P. Coussens, Frederick National Laboratory for CancerResearch
Thomas D.Y. Chung, Sanford Burnham Prebys Medical Discovery Institute
Jayme Dahlin, Agios Pharmaceuticals
Stefan Grotegut, Eli Lilly
Sam Hoare, Pharmechanics LLC
Sarine Markossian, National Center for Advancing Translational Sciences, National Institutes of Health
Samarjit Patnaik, National Center for Advancing Translational Sciences, National Institutes of Health
Terry Riss, Promega Corporation