Individualized Dosing With High Inter-Occasion Variability Is Correctly Handled With Model-Informed Precision...

Area of Science:

• Pharmacokinetics and Pharmacodynamics
• Tuberculosis Treatment
• Computational Pharmacology

Background:

• Rifampicin dosing is complex due to high inter-occasion variability (IOV) in its pharmacokinetics (PK).
• This variability poses challenges for individualizing rifampicin doses in tuberculosis (TB) patients.
• Model-informed precision dosing (MIPD) offers a potential solution for optimizing individual drug regimens.

Purpose of the Study:

• To quantify the magnitude of IOV in rifampicin PK exposure.
• To assess the impact of ignoring IOV in MIPD for dose prediction accuracy.
• To determine the minimum number of sampling occasions required for reliable dose forecasting.

Main Methods:

• A simulation-based study using a previously established population PK model for rifampicin.
• Simulated 1,000 sampling occasions at steady-state to assess IOV in AUC0-24h.
• Compared prediction errors between MIPD approaches with and without IOV consideration.

Main Results:

• Rifampicin AUC0-24h demonstrated substantial IOV (25.8%), comparable to inter-individual variability (25.4%).
• MIPD incorporating IOV yielded more accurate dose predictions with narrower prediction intervals.
• Including a second sampling occasion significantly improved dose prediction precision and reduced bias.

Conclusions:

• Significant inter-occasion variability in rifampicin exposure necessitates its inclusion in dosing models.
• Accurate individual dose forecasting using MIPD requires accounting for IOV.
• At least two sampling occasions are recommended for effective MIPD of rifampicin.