An Automated Robotic Interface for Assays: Facilitating Machine Learning in Drug Discovery by the Automation of Physicochemical Property Assays.
| Autor: | Wu NP; Analytical Research, Discovery Chemistry Department, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States., Wang W; Drug Metabolism and Pharmacokinetics, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States., Gadiagellan D; UK Robotics, Inc., Manchester BL5 3EH, United Kingdom., Counsell M; UK Robotics, Inc., Manchester BL5 3EH, United Kingdom., Hamidi NK; Analytical Research, Discovery Chemistry Department, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States., Koike Y; Analytical Research, Discovery Chemistry Department, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States., Nguyen HQ; Analytical Research, Discovery Chemistry Department, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States. |
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| Jazyk: | angličtina |
| Zdroj: | ACS omega [ACS Omega] 2024 May 24; Vol. 9 (23), pp. 24948-24958. Date of Electronic Publication: 2024 May 24 (Print Publication: 2024). |
| DOI: | 10.1021/acsomega.4c02003 |
| Abstrakt: | Measuring the physicochemical properties of molecules is an iterative but integral process in the drug development process. A strategy to overcome the challenges in maximizing assay throughput relies on the usage of in silico machine learning (ML) prediction models trained on experimental data. Consequently, the performance of these in silico models are dependent on the quality of the utilized experimental data. To improve the data quality, we have designed and implemented an automated robotic system to prepare and run physicochemical property assays ( A utomated R obotic I nterface for A ssays, ARIA) with an increase in sample throughput of 6 to10-fold. Through this process, we overcame major challenges and achieved consistent reproducible assay data compared to semiautomated assay preparation. Competing Interests: The authors declare no competing financial interest. (© 2024 The Authors. Published by American Chemical Society.) |
| Databáze: | MEDLINE |
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