Recent Advances in Omics, Computational Models, and Advanced Screening Methods for Drug Safety and Efficacy.

Area of Science:

• Toxicology
• Pharmacology
• Biotechnology

Background:

• Drug-induced toxicity poses a significant challenge in therapeutic development.
• Novel drug safety and efficacy rely on understanding underlying toxicity mechanisms.

Purpose of the Study:

• To review advancements in technologies and methodologies for predicting and assessing drug toxicity.
• To highlight the synergy between omics, computational tools, and advanced modeling for improved drug safety.

Main Methods:

• Omics technologies (transcriptomics, proteomics, metabolomics) for pathway identification.
• Computational tools like quantitative structure-activity relationship (QSAR) and machine learning for toxicity prediction.
• Physiologically based pharmacokinetic (PBPK) modeling and micro-physiological systems (MPS) for preclinical-to-clinical translation.

Main Results:

• Omics technologies enable early identification of potential adverse effects.
• In silico models accurately predict toxicity endpoints.
• PBPK and MPS enhance preclinical-to-clinical translation for better drug safety assessments.

Conclusions:

• The integration of screening technologies, in silico modeling, and omics data reduces late-stage drug development failures.
• Overcoming challenges in data integration and interpretation is crucial.
• Collaboration among researchers, clinicians, and regulatory bodies is essential for developing standardized predictive toxicology methodologies.