Advances in molecular biomarkers for pharmacovigilance: Early detection of drug toxicity

Sharma, Debobrata and Farid, Farhad Bin and Ferdouszzaman, Ferdouszzaman and Khan, Tania (2025) Advances in molecular biomarkers for pharmacovigilance: Early detection of drug toxicity. World Journal of Biology Pharmacy and Health Sciences, 21 (2). 071-081. ISSN 2582-5542

The importance of molecular biomarkers leading to early drug toxicity detection as well as drug safety monitoring leading to the strengthening of pharmacovigilance. Hence, spontaneous reporting systems and cohort studies commonly used for the purposes of traditional pharmacovigilance are not effective and timely enough in identifying Adverse Drug reaction (ADR). Molecular biomarkers (genomic, transcriptomic, proteomic or metabolomic and epigenetic) lastly provide a more targeted and mechanistic understanding of drug induced toxicities. There has been evolution in the last few years in discovering biomarkers by next generation sequencing (NGS), artificial intelligence (AI), by organ on a chip technology, allowing us to go beyond personalized medicine/toxicology to predict its outcomes. The organ specific toxicities, i.e., hepatotoxicity, nephrotoxicity, cardiotoxicity and neurotoxicity are assessed by biomarkers and can be used as basis to institute early intervention and choice of strategy thus. Though the first of these seem to be advancements, they have done much on the surface in standardization, validation, ethical issues, etc. and most of all, all this has to do with the cost. Biomarker analysis with AI and machine learning, however, helps to integrate the higher drug safety assessment accuracy and efficiency. Like in the case of pharmacovigilance, global collaboration and regulatory framework for harmonized biomarker applications and routine clinical applications are also needed in the biomarker applications. In the future, predictive toxicology will be made by improving the prediction of toxicology through personalized biomarkers, the second improvement of its AI based biomarker discovery and the span between biomarker research and clinical practice. Placed in future, the assumption of pharmacovigilance can transition to a reactive, data driven discipline from reactive, and become another proactive, safer discipline to enhance global patient safety and therapeutic outcomes.