A pharmacist-led framework for antibiotic-associated liver injury: from pharmacovigilance signals to bedside surveillance with the updated RUCAM and susceptibility markers.

Antibiotics account for more cases of idiosyncratic drug-induced liver injury (DILI) than any other drug class. At the bedside, attributing injury to a particular antibiotic is difficult: there is no confirmatory test, and latency and biochemical pattern vary markedly among agents. Spontaneous-reporting databases add a second kind of evidence. Disproportionality analyses repeatedly identify strong reporting signals for amoxicillin-clavulanate and nitrofurantoin, but these describe reporting patterns rather than incidence, rest on reports that are seldom assessed by a validated causality method, and cannot establish causation in an individual patient. This review considers how clinical pharmacists might use such population-level information, together with the globally used updated Roussel Uclaf Causality Assessment Method (RUCAM), without overstating what either can show. We bring together evidence on culprit antibiotics and their characteristic phenotypes, the mechanistic basis of susceptibility markers including HLA-B*57:01 and slow NAT2 acetylator status, the methods and limits of disproportionality analysis, and the pharmacist's role in medication review and monitoring. On that basis we propose a closed surveillance cycle. A pharmacovigilance signal first informs risk stratification and the timing of laboratory monitoring; suspected cases then undergo updated RUCAM assessment, which yields a quantitative causality score at no marginal cost, with genotyping reserved for patients in whom the result would change interpretation; intervention and structured reporting close the loop. Published antibiotic-associated cases are tabulated with their RUCAM scores and susceptibility results. Research priorities include prospective validation of composite risk scores, agreed monitoring intervals, multicenter evaluation of pharmacist-led detection, and appraisal of emerging biomarkers.