Limited sampling strategies for therapeutic drug monitoring of anti-tuberculosis medications: A systematic review of their feasibility and clinical utility

Therapeutic drug monitoring (TDM) is recommended for medications with high inter-individual variability, narrow therapeutic index drugs, possible drug-drug interactions, drug toxicity, and subtherapeutic concentrations, as well as to assess noncompliance. The area under the plasma concentration-time curve (AUC) is a significant pharmacokinetic parameter since it calculates the drug's total systematic exposure in the body. However, multiple blood samples from the patient are required to calculate the area under the curve, which is inconvenient for both the patient and the healthcare professional. To alleviate the issue, the limited sampling strategy (LSS) was devised, in which sampling is minimized while obtaining complete and precise findings to anticipate the area under the curve. One can reduce costs, labor, and discomfort for patients and healthcare workers by applying this limited sampling strategy. This article examines a systematic evaluation of all the limited sampling done in anti-tuberculosis (anti-TB) medications resulting from the literature search of several research papers. This article also briefly describes the two methodologies: Multiple regression analysis (MRA) and the Bayesian approach used to develop a limited sampling strategy model. Anti-TB medications have been found to have considerable inter-individual variability, and isoniazid has a narrow therapeutic index, both of which are criteria for therapeutic drug monitoring. To avoid multi-drug resistance and therapy failure, it is proposed that limited sampling strategy-based therapeutic drug monitoring of anti-TB medications be undertaken to generate an individualized dose regimen, particularly for individuals at high risk of treatment failure or delayed response.