Translational learning from clinical studies predicts drug pharmacokinetics across patient populations.

ABSTRACT: Early indication of late-stage failure of novel candidate drugs could be facilitated by continuous integration, assessment, and transfer of knowledge acquired along pharmaceutical development programs. We here present a translational systems pharmacology workflow that combines drug cocktail probing in a specifically designed clinical study, physiologically based pharmacokinetic modeling, and Bayesian statistics to identify and transfer (patho-)physiological and drug-specific knowledge across distinct patient populations. Our work builds on two clinical investigations, one with 103 healthy volunteers and one with 79 diseased patients from which we systematically derived physiological information from pharmacokinetic data for a reference probe drug (midazolam) at the single-patient level. Ta

SUBMITTER: Krauss M 

PROVIDER: S-EPMC5460240 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature