Abstract Background Directly Observed Treatment Short Course for Tuberculosis (TB) (DOTS) treatment currently produces a cure rate of 80%. Rifampicin (RMP) and isoniazid (INH) are the main bactericides; both show wide inter-individual pharmacokinetics and narrow therapeutic range. Therapeutic drug monitoring (TDM) of antiTB drugs is a strategy to improve the response to treatment. The aim of this work was to optimize and individualize antiTB treatment based on plasma concentrations of RMP and INH, NAT2 genotyping and the Bayesian estimation of PK parameters. Methods A prospective and analytical study including TB patients under DOTS scheme was performed. Venous blood samples were drawn 2 and 4 hours after last dose; INH and RMP were quantified by liquid chromatography coupled to tandem mass spectrometry. Anthropometric and clinical information was retrieved from medical records. Acetylator phenotype was determined based on NAT2 genotyping by real-time PCR. Bayesian estimation of the PK parameters was performed using NONMEM and dosing scheme was proposed to achieve therapeutic concentrations of RIF and INH. Results A total 62 patients were included from 18 to 80 years and 35 to 117 kg of total body weight. The most frequent was pulmonary infection (40%), 25% of patients had type 2 diabetes mellitus and 58.5% were slow acetylators for the NAT2 gene. Lower INH and RMP plasma concentrations were related to adverse clinical outcome, compared to those patients classified with early clinical success [1.9 vs 3.7 mg/L and 16.9 vs 10.0 mg/L (p< 0.05)]. Results indicate the need to adjust anti-TB drugs dose to more than 50% of the patients who show plasma concentrations outside the range for both drugs. Bayesian dosing performed was validated after individualization by quantification and interpretation of INH and RMP plasma concentrations followed by a narrow medical follow up. Conclusion Even with standard anti-TB treatment, great proportion of patients show subtherapeutic concentrations of RMP and INH which is associated with overall therapeutic failure. TDM is a useful tool to individualize antimicrobials dose and improve clinical outcomes at early stages of active TB. Disclosures All Authors: No reported disclosures.
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