Anti-infective agents are some of the most widely used therapeutic drugs worldwide. Overall, the most common serious adverse events attributable to antiinfective agents include liver injury, nephrotoxicity, hypersensitivity reactions, cardiac arrhythmias, drug-drug interactions and therapeutic failure. In clinical practice, serious problems of toxicity limit the usefulness of antimicrobial drugs.
In order to improve the design of clinical trials and better conceptualize research plans for the development of anti-infective drugs, it is important to take into consideration cutting-edge drug safety approaches that can be implemented during discovery and early phase studies, as well as promising methods and models for clinical research advancement. In the present text, we describe a holistic perspective inspired by chemoinformatics, systems biology, and predictive clinical pharmacology, to discuss the utility of in silico methods, preclinical models, genomics, translational biomarkers and postmarketing surveillance strategies for safety evaluation and risk detection during anti-infective drug development.
Keywords: Adverse effect, adverse reaction, AMES test, animal model, antiinfective drug, biomarkers, cardiotoxicity, chemoinformatics, clinical trial, Cramer rules, drug development, drug discovery, drug-induced toxicity, environmental risk assessment, hepatotoxicity, humanized mice, nephrotoxicity, pharmacogenomics, pharmacovigilance, preclinical study, quantitative structure-activity relationship (QSAR), systems toxicology, translational medicine, verhaar scheme, zebrafish.