Changing the HTS Paradigm: AI-Driven Iterative Screening for Hit Finding.

ABSTRACT: Iterative screening is a process in which screening is done in batches, with each batch filled by using machine learning to select the most promising compounds from the library based on the previous results. We believe iterative screening is poised to enhance the screening process by improving hit finding while at the same time reducing the number of compounds screened. In addition, we see this process as a key enabler of next-generation high-throughput screening (HTS), which uses more complex assays that better describe the biology but demand more resource per screened compound. To demonstrate the utility of these methods, we retrospectively analyze HTS data from PubChem with a focus on machine learning-based screening strategies that can be readily implemented in practice. Our results sh

SUBMITTER: Dreiman GHS 

PROVIDER: S-EPMC7838329 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature