SPARK: Harnessing Human-Centered Workflows with Biomedical Foundation Models for Drug Discovery

Bum Chul Kwon, Simona Rabinovici-Cohen, Beldine Moturi, Ruth Mwaura, Kezia Wahome, Oliver Njeru, Miguel Shinyenyi, Catherine Wanjiru, Sekou Remy, William Ogallo, Itai Guez, Partha Suryanarayanan, Joseph Morrone, Shreyans Sethi, Seung Gu Kang, Tien Huynh, Kenney Ng, Diwakar Mahajan, Hongyang Li, Matan NinioShervin Ayati, Efrat Hexter, Wendy Cornell

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Biomedical foundation models, trained on diverse sources of small molecule data, hold great potential for accelerating drug discovery. However, their complex nature often presents a barrier for researchers seeking scientific insights and drug candidate generation. SPARK addresses this challenge by providing a user-friendly, web-based interface that empowers researchers to leverage these powerful models in their scientific workflows. Through SPARK, users can specify target proteins and desired molecule properties, adjust pre-trained models for tailored inferences, generate lists of potential drug candidates, analyze and compare molecules through interactive visualizations, and filter candidates based on key metrics (e.g., toxicity). By seamlessly integrating human knowledge and biomedical AI models' capabilities through an interactive web-based system, SPARK can improve the efficiency of collaboration between human experts and AI, thereby accelerating drug candidate discovery and ultimately leading to breakthroughs in finding cures for various diseases.

Original languageEnglish
Title of host publicationProceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
EditorsKate Larson
PublisherInternational Joint Conferences on Artificial Intelligence
Pages8713-8716
Number of pages4
ISBN (Electronic)9781956792041
StatePublished - 2024
Externally publishedYes
Event33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 - Jeju, Korea, Republic of
Duration: 3 Aug 20249 Aug 2024

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
Country/TerritoryKorea, Republic of
CityJeju
Period3/08/249/08/24

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