Individualised dosing algorithm and personalised treatment of high-dose rifampicin for tuberculosis.

ABSTRACT:

Aims

To propose new exposure targets for Bayesian dose optimisation suited for high-dose rifampicin and to apply them using measured plasma concentrations coupled with a Bayesian forecasting algorithm allowing predictions of future doses, considering rifampicin's auto-induction, saturable pharmacokinetics and high interoccasion variability.

Methods

Rifampicin exposure targets for Bayesian dose optimisation were defined based on literature data on safety and anti-mycobacterial activity in relation to rifampicin's pharmacokinetics i.e. highest plasma concentration up to 24 hours and area under the plasma concentration-time curve up to 24 hours (AUC_0-24h ). Targets were suggested with and without considering minimum inhibitory concentration (MIC) information. Individ

SUBMITTER: Svensson RJ 

PROVIDER: S-EPMC6783589 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature