Population Pharmacokinetics of Tigecycline and Implications for Individualized Therapy Optimization: A Systematic...

Tigecycline, owing to its broad-spectrum antimicrobial activity, has emerged as an important option in the treatment of infections. However, its optimal dosing strategy remains controversial in clinical practice. Recent studies have provided valuable insights into the population pharmacokinetics (PopPK) of tigecycline. This review aims to synthesize the current literature to offer theoretical guidance for individualized clinical management.

A systematic search of PopPK studies on tigecycline published from inception to April 2025 was conducted in the PubMed and Web of Science databases. The pharmacokinetics of tigecycline in different populations were systematically reviewed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

16 studies were included, of which 11 focused on critically ill populations (such as those with severe infections, sepsis, renal replacement therapy, multi-drug resistant Gram-negative infections, and impaired liver function, etc). The majority of studies (12/16) adopted a two-compartment model, with the typical parameter ranges as follows: clearance (CL) 3.09-25.2 L/h, intercompartmental clearance (Q) 31.9-85.1 L/h, central volume of distribution (V1) 30.9-162 L, and peripheral volume of distribution (V2) 87.9-1030 L. This systematic analysis suggested that covariates influencing tigecycline pharmacokinetics were primarily classified into three categories: hepatic function indicators, renal function markers, and body weight-related parameters. All included models underwent internal validation.

Based on the existing evidence, it is recommended to use high-dose tigecycline (100mg, q12h) for drug-resistant bacterial infections, cSSI and VAP, and consider combination therapy. Individualized dose adjustment should be based on liver function and the degree of drug resistance of the pathogen, without considering renal function. The application of other covariates and the model needs to be further verified.