Individualizing Tuberculosis (TB) Treatment: Are TB Programs in High Burden Settings Ready for Prime Time Therapeutic Drug Monitoring?

Exposure to Rifampicin and its Metabolite 25-Deacetylrifampicin Rapidly Decreases During Tuberculosis Therapy

BACKGROUND AND OBJECTIVE

Limited information is available on the pharmacokinetics of rifampicin (RIF) along with that of its active metabolite, 25-deacetylrifampicin (25-dRIF). This study aimed to analyse the pharmacokinetic data of RIF and 25-dRIF collected in adult patients treated for tuberculosis.

METHODS

In adult patients receiving 10 mg/kg of RIF as part of a standard regimen for drug-susceptible pulmonary tuberculosis enrolled in the Opti-4TB study, plasma RIF and 25-dRIF concentrations were measured at various occasions. The RIF and 25-dRIF concentrations were modelled simultaneously by using a population approach. The area under the concentration-time curves of RIF and 25-dRIF were estimated on each occasion of therapeutic drug monitoring. Optimal RIF exposure, defined as an area under the concentration-time curve over 24 hours/minimum inhibitory concentration > 435, was assessed.

RESULTS

Concentration data (247 and 243 concentrations of RIF and 25-dRIF, respectively) were obtained in 35 patients with tuberculosis (10 women, 25 men). Mycobacterium tuberculosis minimum inhibitory concentration ranged from 0.06 to 0.5 mg/L (median = 0.25 mg/L). The final model was a two-compartment model including RIF metabolism into 25-dRIF and auto-induction. Exposure to 25-dRIF was low, with a mean area under the concentration-time curve over 24 h ratio of 25-dRIF/RIF of 14 ± 6%. The area under the concentration-time curve over 24 h of RIF and 25-dRIF rapidly decreased during therapy, with an auto-induction half-life of 1.6 days. Optimal RIF exposure was achieved in only six (19.3%) out of 31 patients upon first therapeutic drug monitoring.

CONCLUSIONS

Exposure to both RIF and 25-dRIF rapidly decreased during tuberculosis therapy. The contribution of 25-dRIF to overall drug exposure was low. Attainment of the target area under the concentration-time curve over 24 hours/minimum inhibitory concentration for RIF was poor, supporting an increased RIF dosage as an option to compensate for auto-induction.

Toward a Clinical Decision Support System for Monitoring Therapeutic Antituberculosis Medical Drugs in Tanzania (Project TuberXpert): Protocol for an Algorithm' Development and Implementation

BACKGROUND

The end tuberculosis (TB) strategy requires a novel patient treatment approach contrary to the one-size-fits-all model. It is well known that each patient's physiology is different and leads to various rates of drug elimination. Therapeutic drug monitoring (TDM) offers a way to manage drug dosage adaptation but requires trained pharmacologists, which is scarce in resource-limited settings.

OBJECTIVE

We will develop an automated clinical decision support system (CDSS) to help practitioners with the dosage adaptation of rifampicin, one of the essential medical drugs targeting TB, that is known for large pharmacokinetic variability and frequent suboptimal blood exposure. Such an advanced system will encourage the spread of a dosage-individualization culture, including among practitioners not specialized in pharmacology. Thus, the objectives of this project are to (1) develop the appropriate population pharmacokinetic (popPK) model for rifampicin for Tanzanian patients, (2) optimize the reporting of relevant information to practitioners for drug dosage adjustment, (3) automate the delivery of the report in line with the measurement of drug concentration, and (4) validate and implement the final system in the field.

METHODS

A total of 3 teams will combine their efforts to deliver the first automated TDM CDSS for TB. A cross-sectional study will be conducted to define the best way to display information to clinicians. In parallel, a rifampicin popPK model will be developed taking advantage of the published literature, complemented with data provided by existing literature data from the Pan-African Consortium for the Evaluation of Antituberculosis Antibiotics (panACEA), and samples collected within this project. A decision tree will be designed and implemented as a CDSS, and an automated report generation will be developed and validated through selected case studies. Expert pharmacologists will validate the CDSS, and finally, field implementation in Tanzania will occur, coupled with a prospective study to assess clinicians' adherence to the CDSS recommendations.

RESULTS

The TuberXpert project started in November 2022. In July 2024, the clinical study in Tanzania was completed with the enrollment of 50 patients to gather the required data to build a popPK model for rifampicin, together with a qualitative study defining the report design, as well as the CDSS general architecture definition.

CONCLUSIONS

At the end of the TuberXpert project, Tanzania will possess a new tool to help the practitioners with the adaptation of drug dosage targeting complicated TB cases (TB or HIV, TB or diabetes mellitus, and TB or malnutrition). This automated system will be validated and used in the field and will be proposed to other countries affected by endemic TB. In addition, this approach will serve as proof of concept regarding the feasibility and suitability of CDSS-assisted TDM for further anti-TB drugs in TB-burdened areas deprived of TDM experts, including second-line treatments considered important to monitor.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/58720.