Pharmacometrics in tuberculosis: progress and opportunities.

Area of Science:

• Pharmacometrics and mathematical modeling in infectious diseases.
• Clinical pharmacology and drug development.
• Computational modeling for tuberculosis treatment.

Background:

• Tuberculosis (TB) is a major global health threat, particularly in underserved populations.
• Pharmacometrics utilizes quantitative models to link drug exposure to effects (pharmacokinetics/pharmacodynamics).
• Existing pharmacometric methods have improved population-level dosing for anti-TB drugs and antiretrovirals.

Purpose of the Study:

• To review the current applications of pharmacometrics in tuberculosis pharmacotherapy.
• To explore emerging opportunities for pharmacometrics to advance TB treatment.
• To highlight the role of advanced modeling in optimizing anti-TB drug regimens.

Main Methods:

• Review of existing literature on pharmacometric applications in TB.
• Discussion of advanced modeling frameworks: physiologically based pharmacokinetics (PBPK), quantitative systems pharmacology (QSP), and machine learning.
• Analysis of opportunities for in-silico drug-drug interaction quantification and personalized dosing.

Main Results:

• Pharmacometric approaches have successfully informed population-level dosing strategies for TB and HIV co-infections.
• Advanced modeling offers potential for predicting drug interactions and optimizing doses for special populations.
• Understanding complex exposure-response relationships is crucial for multi-drug regimens.

Conclusions:

• Pharmacometrics provides a robust framework for optimizing tuberculosis pharmacotherapy.
• Future directions include leveraging advanced modeling for personalized dosing, drug interaction assessment, and novel regimen design.
• Pharmacometrics is essential for improving the efficacy and safety of TB treatments globally.