In this Webinar, you will learn:
• How AI-driven technologies enhance High-Throughput Screening for faster drug discovery.
• How combining silico and high-throughput screening methods can enhance hit identification, hit-to-lead, and lead optimization stages of a drug discovery program.
• The requirements for applying this approach, along with examples of successful implementations will be covered.
About this Webinar:
High throughput screening (HTS) and artificial intelligence (AI) drug discovery are mutually beneficial and are being used to accelerate the drug discovery process. On one hand, the vast amount of experimental data generated through assays performed in HTS format is an invaluable source of training data for AI models. On the other hand, for precision hit discovery, AI and other in silico approaches can be used to select screening collections based on the likelihood of target specificity and phenotypic activity. In the case of iterative drug discovery, AI models can be trained on the previous round of HTS data and can then prioritize a new set of screening collections for the next round of HTS. The biological data that are used for in silico models must be generated from robust assays and will ideally represent a broad chemical space with quantitative parameters (e.g. IC50 values). In addition, agile processes that support experimentally testing the output from AI models must be in place to realize the full benefit of the HTS-AI pairing. We will highlight one example from a collaborative project that involved the identification of novel agents against alphaviruses, a family of tropic mosquito-borne viruses that currently lack effective vaccine and drugs. We developed a deep learning AI model using cell-based antiviral assay data including a previously performed 150K in-house HTS alphavirus inhibition campaign. We used this AI model to prioritize a new screening collection that would be likely to impart the desired phenotypic activity of alphavirus inhibition. We also predicted the viral protein target binding to aid the prioritization of the new screening collection. After screening a new collection of prioritized compounds, we were able to quickly identify novel target-specific antiviral inhibitors with a significantly higher hit rate than the previous HTS efforts without prioritization of screening collection.
About Paige N. Vinson, Ph.D.
Dr. Vinson earned her Ph.D. in Analytical Chemistry from Emory University, where she applied innovative approaches to address key questions in neuroscience. She brings this expertise and her passion for data-driven science to her role at Southern Research, where her team integrates HTS with cell-based and biochemical assays, providing essential support for hit identification and advancing drug discovery efforts.
With her deep understanding of the drug discovery process and a proven track record of leading multidisciplinary teams, Dr. Vinson continues to make significant contributions to advancing scientific discovery in both academia and industry.
Dr. Paige N. Vinson is the Director of High-Throughput Screening (HTS) at Southern Research, where she leads a team possessing expertise in assay technologies, compound management, and data analytics. With the aid of automated instruments and processes, the Southern Research HTS Center produces high volumes of biological data to inform drug discovery projects spanning multiple therapeutic areas including oncology, infectious diseases, diabetes, cystic fibrosis, among others. With over 20 years of experience in both academic and industry settings, Dr. Vinson has played a critical role in translating early-stage research into therapeutic discoveries. Her extensive background includes directing the HTS core at Vanderbilt University, where she was pivotal in bridging basic research with drug discovery efforts. Her work in the molecular pharmacology group at the Warren Center for Neuroscience Drug Discovery allowed her to contribute to multiple projects, including collaborations with pharmaceutical companies, focusing on early drug discovery and in vitro assay support.
Dr. Vinson earned her Ph.D. in Analytical Chemistry from Emory University, where she applied innovative approaches to expand temporal and detection boundaries to address key questions in neuroscience. Her postdoctoral training involved developing a recombinant expression system for monoamine oxidase and characterizing the purified enzyme. She combined her scientific background with automation while working with ThermoFisher Scientific as an application scientist and product manager in their Laboratory Automation Division. She brings this expertise and her passion for data-driven science to her role at Southern Research, where her team integrates HTS with cell-based and biochemical assays, providing essential support for hit identification, hit-to-lead, and lead optimization stages of and advancing drug discovery efforts. She is part of the broader drug discovery community through her involvement with the Academic Drug Discovery Consortium (serving as President) and the Society for Laboratory Automation and Screening (co-chair of the Screen Design and Assay Technology topical interest group). With her deep understanding of the drug discovery process and a proven track record of leading multidisciplinary teams, Dr. Vinson continues to make significant contributions to advancing scientific discovery in both academia and industry.
About Sixue Zhang, Ph.D.
Dr. Sixue Zhang is the Head of A.I. Drug Discovery at Southern Research, where he leads the integration of artificial intelligence into drug discovery pipelines. With over 10 years of experience in computer-aided drug discovery, Dr. Zhang has collaborated on more than 50 drug discovery projects across various therapeutic areas, including oncology, neurology, and infectious diseases. His work focuses on leveraging AI and next-generation molecular modeling to streamline and accelerate the discovery of novel therapeutics.
Dr. Zhang earned his Ph.D. in Computational Chemistry from the University of Illinois Urbana-Champaign, where he received the prestigious J. & M. Witt Fellowship and worked under the supervision of Prof. Sharon Hammes-Schiffer. His expertise spans multidisciplinary collaborations, partnering with academic institutions and industry to drive innovative drug discovery solutions. His team plays a key role in Southern Research’s integrated Design-Make-Test-Analyze platform, utilizing AI models developed with in-house assay data to quickly identify potent compounds that would otherwise take years to discover.
In addition to his leadership role at Southern Research, Dr. Zhang serves on the editorial boards of several scientific journals and is an active member of professional committees. He is a frequent speaker at national and international conferences, sharing insights on AI's transformative impact on drug discovery.
Recent Publications:
[1] Jimenez-Torres, A. C, et al. J. Pharmacol. Exp. Ther. 2024 Sep. JPET-AR-2024-002138.
[2] Zhang, S, et al. PLOS One. 2021 Jan. 22;16(1):e0245013. [Content Brief]
[3] Zhang, F, et al. Sci. Transl. Med. 2020 Jan. 15;12(526):eaay6931. [Content Brief]
[4] Rasmussen, L, et al. SLAS Discov. 2024 Jul;29(5):100160. [Content Brief]
[5] Martinez-Gzegozewska, Y, et al. SLAS Discov. 2024 Jan;29(1):66-76. [Content Brief]
[6] Garrison, A. T, et al. J Med Chem. 2022 Apr. 28;65(8):6273-6286. [Content Brief]
