ArticleBioanalysis
Transforming drug discovery: the impact of AI and molecular simulation on R&D efficiency.
Article in Bioanalysis. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Computational Prediction of the Therapeutic Mechanisms From the Turmeric-Pueraria-Coix Seed Botanical Formula in Rheumatoid Arthritis.Food science & nutrition · 2026Article
- Molecular dynamics simulation in traditional Chinese medicine research: from molecular mechanisms to multiscale validation.Frontiers in chemistry · 2026Review
- Examining hybridization-based LC-MS methodologies for the bioanalysis of siRNA analytes.Bioanalysis · 2025Article
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Authors and funding
1 author.
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Abstract
The process of developing new drugs in the pharmaceutical industry is both time-consuming and costly, making efficiency crucial. Recent advances in hardware and computational methods have led to the widespread application of computational science approaches in drug discovery. These approaches, including artificial intelligence and molecular simulations, span from target identification to pharmacokinetics research, aiming to reduce the likelihood of failure and present lower costs. Machine learning-based methods predict new applications for developing new drugs based on accumulated knowledge, while molecular simulations estimate interactions between drugs and target proteins at the atomic level based on physical laws. Each approach has its advantages and disadvantages, and they complement each other. As a result, the future of computational science approaches in drug discovery is expected to focus on developing new methodologies that integrate these two techniques to enhance the efficiency of drug discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.