Assay Guidance Manual for Drug Discovery: Technologies That Matter

Advancements in technologies accompanied by rigorous experimental and data analysis standards not only help accelerate drug discovery but also address the growing emphasis on reproducibility in basic and preclinical research. ¹ This SLAS Technology special collection complements the special issue in SLAS Discovery ² that focuses on the Assay Guidance Workshop for High-Throughput Screening and Lead Discovery series conducted by the Assay Guidance Manual (AGM) program of the National Center for Advancing Translational Sciences (NCATS). ³ The AGM program is part of a disease-agnostic translational science education program that helps to bridge the gap between discoveries and the delivery of new therapies by establishing and disseminating standards for rigor in early translational research. As a component of this program, the AGM ⁴ is a free and publicly available e-book of best practices for the design, development, and implementation of robust assays for preclinical research. The workshops, conducted by AGM editorial board members, authors, and other subject matter experts, highlight key concepts from the AGM. The goal of the AGM workshop series is to improve the design, rigor, and execution of assays supporting preclinical discovery by providing participants with a broad, practical perspective on assay development and data analysis. The articles in this SLAS Technology special collection expand on workshop lecture concepts by describing the incorporation of best practices into new assay methodologies that enable reproducible results as well as illustrating how the underlying principles are critical to the entire drug discovery and development process.

This special collection of SLAS Technology contains three peer-reviewed articles, including two original research articles and one perspective. The first original research article, by Gonzales et al., ⁵ provides recommended best practices in compound management and handling for researchers performing biological assays. The authors emphasize the importance of a close collaboration and an open dialogue between screening and sample handling groups for successful drug discovery campaigns. The other two articles in this collection describe emerging technologies related to high-throughput screening (HTS) and lead optimization. An original research article by Elder et al. ⁶ was contributed by NCATS scientists in collaboration with an industrial partner, Kebotix, and is focused on remote-controlled autonomous bioassay optimization using Bayesian statistical approaches. The other perspective, by Morato et al., ⁷ was written by an academic group and describes exciting new applications of desorption electrospray ionization (DESI) mass spectrometry (MS) for high-throughput synthetic chemistry, chemical reaction screening, and label-free biological assays amenable to HTS. These two articles highlight major areas of technological development, including remote assay design and optimization using machine learning, as well as the power of evolving MS methodologies to advance both chemistry and biological applications. An interesting opportunity is to utilize the Bayesian statistical tools to not only remotely design and optimize the DESI MS technology but also rapidly develop applications such as high-content imaging and optogenetics to study tissue and single-cell genomics, proteomics, and metabolomics (see the recent Defense Advanced Research Projects Agency announcement in the Related Links section below). Remote assay development and optimization enable global collaborations with multiple institutions that might or might not have access to expensive and specialized instrumentation or expertise. We will continue to add articles that are relevant to the AGM in upcoming SLAS Technology special issues on breakthroughs in instrumentation and automation.

We thank the contributing authors, the SLAS staff, and editors who helped assemble this special collection, as well as the scientific reviewers for their valuable and thoughtful evaluations of the science. There is a critical need to continue an open dialogue regarding best practices in preclinical research to avoid irreproducible results, increase efficiency in drug discovery, and save billions of dollars on biomedical research. To that end, we hope that this SLAS Technology special collection, along with the SLAS Discovery special issue, will help scientists to recognize the importance of performing rigorous preclinical research. We also hope that the readers are aware of the tremendous technological advances that are currently emerging, particularly in remote assay design and optimization, which can have powerful implications for future drug discovery campaigns.