Bioinformatics in anaesthesia: A new era of personalised and predictive perioperative care

Bioinformatics represents a powerful tool for advancing personalised and predictive anaesthesia care. By integrating genomic information, machine learning techniques, and multi-omics analytics, it enhances our understanding of interindividual variability in drug responses, supports early identification of perioperative risks, and improves intraoperative decision-making. Key applications include real-time clinical decision support systems, biomarker discovery, AI-based monitoring, pharmacogenomics-guided anaesthetic dosing, and the prediction of complications such as malignant hyperthermia and postoperative pain. Despite these promising developments, several challenges remain. Limited clinician training, concerns regarding data privacy, inadequate digital infrastructure, and uncertainties in regulatory frameworks continue to hinder widespread adoption. Addressing these gaps- through stronger interoperability, ethical data governance, and enhanced education is essential to ensure safe and equitable implementation. With these foundations in place, bioinformatics has the potential to transform modern anaesthetic practice in meaningful ways.