The Impact of Computational Drug Discovery on Society

Jianxin Wang; Min Li; Edwin Wang; Jing Tang; Bin Hu

doi:10.1109/TCSS.2023.3313208

The Impact of Computational Drug Discovery on Society

Jianxin Wang, Min Li, Edwin Wang, Jing Tang, Bin Hu

School of Medical and Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Network pharmacology and deep learning-based approaches have significantly advanced the field of drug discovery. With the improved prediction accuracy on drug targets, a logical next step would be the modeling of the complexity of human biology to understand the heterogeneity of drug response across individual patients and suggest novel treatment options for non responders. To ensure the successful translation of the computer-aided models into drug development and treatment decision-making, it is imperative to refine our models to predict drug-target interactions within specific disease contexts and ultimately to personalize these predictions for each patient.

Original language	English
Pages (from-to)	2148-2159
Number of pages	12
Journal	IEEE Transactions on Computational Social Systems
Volume	10
Issue number	5
DOIs	https://doi.org/10.1109/TCSS.2023.3313208
Publication status	Published - 1 Oct 2023

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Wang, J., Li, M., Wang, E., Tang, J., & Hu, B. (2023). The Impact of Computational Drug Discovery on Society. IEEE Transactions on Computational Social Systems, 10(5), 2148-2159. https://doi.org/10.1109/TCSS.2023.3313208

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The Impact of Computational Drug Discovery on Society

Abstract

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