Role of Automation in Clinical Bacteriology: Enhancing “Actionable” Antibiograms

Abstract

Antimicrobial resistance (AMR) has emerged as one of the most critical public health threats of the 21st century, with projections estimating up to 10 million annual deaths and substantial global economic losses by 2050. Conventional antimicrobial susceptibility testing (AST) methods—such as disk diffusion, broth microdilution, and E-test—remain reliable but are constrained by labor intensity and long turnaround times, often delaying the initiation of effective therapy in critically ill patients. Recent advances in laboratory automation, including pre-analytical robotics, automated identification/AST platforms, digital imaging, and middleware solutions, are transforming clinical bacteriology workflows. These innovations enhance reproducibility, minimize human error, and enable the creation of “actionable antibiograms”—dynamic, real-time, unit-specific, and resistance-mechanism-linked reports that provide clinicians with timely, relevant, and context-specific guidance for empirical therapy and antimicrobial stewardship. This review highlights the evolution from traditional static antibiograms to actionable, data-driven tools, examines the clinical benefits of reduced time-to-effective therapy, and emphasizes their potential in strengthening AMR surveillance and improving patient outcomes, particularly within the Indian healthcare context where multidrug resistance poses a growing challenge.