Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction.

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ID: 280739
2024
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Abstract
The attrition rate of drugs in clinical trials is generally quite high, with estimates suggesting that approximately 90% of drugs fail to make it through the process. The identification of unexpected toxicity issues during preclinical stages is a significant factor contributing to this high rate of failure. These issues can have a major impact on the success of a drug and must be carefully considered throughout the development process. These late-stage rejections or withdrawals of drug candidates significantly increase the costs associated with drug development, particularly when toxicity is detected during clinical trials or after market release. Understanding drug-biological target interactions is essential for evaluating compound toxicity and safety, as well as predicting therapeutic effects and potential off-target effects that could lead to toxicity. This will enable scientists to predict and assess the safety profiles of drug candidates more accurately. Evaluation of toxicity and safety is a critical aspect of drug development, and biomolecules, particularly proteins, play vital roles in complex biological networks and often serve as targets for various chemicals. Therefore, a better understanding of these interactions is crucial for the advancement of drug development. The development of computational methods for evaluating protein-ligand interactions and predicting toxicity is emerging as a promising approach that adheres to the 3Rs principles (replace, reduce, and refine) and has garnered significant attention in recent years. In this review, we present a thorough examination of the latest breakthroughs in drug toxicity prediction, highlighting the significance of drug-target binding affinity in anticipating and mitigating possible adverse effects. In doing so, we aim to contribute to the development of more effective and secure drugs.
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amorim2024advancingchemical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Amorim, Ana M B;Piochi, Luiz F;Gaspar, Ana T;Preto, António J;Rosário-Ferreira, Nícia;Moreira, Irina S;
Journal Chemical research in toxicology
Year 2024
DOI
10.1021/acs.chemrestox.3c00352
URL
Keywords Keywords not found

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