Dalbavancin is a long-acting lipoglycopeptide antibiotic increasingly off-label used for the management of complex and chronic Gram-positive infections, including osteoarticular, prosthetic, and cardiovascular device-related infections. While its prolonged half-life enables infrequent dosing, marked inter-individual pharmacokinetic variability has been documented during extended treatment courses, potentially resulting in suboptimal exposure. This narrative review explores the role of proactive therapeutic drug monitoring (TDM) as a strategy to individualize dalbavancin dosing in patients requiring long-term therapy. We summarized current evidence on pharmacokinetic determinants of dalbavancin exposure, including renal function, body weight, and hypoalbuminemia, and discussed proposed pharmacokinetic/pharmacodynamic targets to support TDM implementation. Available analytical methods for dalbavancin quantification and clinical experiences with TDM-guided dosing are reviewed, highlighting their impact on optimizing injection timing and maintaining adequate drug concentrations over prolonged periods. In addition, emerging model-informed precision dosing approaches, such as Bayesian forecasting and machine learning-based tools, are discussed as promising strategies to further refine exposure prediction and re-dosing decisions. Overall, proactive TDM represents a valuable tool for optimizing dalbavancin therapy in chronic infections, although prospective multicenter studies are needed to validate target thresholds and standardized implementation strategies.
Cattaneo et al. (Sun,) studied this question.