title: An Exposure-Response Modeling Approach to Examine the Relationship Between Potency of CYP3A Inducer and Plasma 4β-Hydroxycholesterol in Healthy Subjects.
abstract: The objectives of this analysis were to establish the exposure-response relationship between plasma rifampicin and 4β-hydroxycholesterol (4βHC) concentration and to estimate the effect of weak, moderate, and potent CYP3A induction. Plasma rifampicin and 4βHC concentration-time data from a drug-drug interaction study with rifampicin 600 mg were used for model development. An indirect response model with an effect compartment described the relationship between rifampicin and 4βHC concentrations. The model predicted that the equilibration t1/2and 4βHC t1/2were 72.8 and 142 hours, respectively. EM50and Emaxof rifampicin induction were 32.6 μg and 8.39-fold, respectively. The population PK-PD model was then used to simulate the effects of rifampicin 10, 20, and 100 mg on plasma 4βHC for up to 21 days, in which rifampicin 10, 20, and 100 mg were used to represent weak, moderate, and strong inducers, respectively. The model-predicted median (5th, 95th percentiles) 1.13 (1.04, 1.44)-, 1.28 (1.10, 1.71)-, and 2.10 (1.45, 3.49)-fold increases in plasma 4βHC after 14-day treatment with rifampicin 10, 20, and 100 mg, respectively. A new drug candidate can likely be classified as a weak, moderate, or strong inducer if baseline-normalized plasma 4βHC increases by <1.13-, 1.13- to 2.10-, or >2.10-fold, respectively, after 14 days of dosing.
authors.affiliation: Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, NJ, USA.
authors.forename: Xuemin
authors.initials: X
authors.lastname: Jiang
authors.affiliation: Oncology Clinical Pharmacology, Novartis Pharma AG, Basel, Switzerland.
authors.forename: Catherine
authors.initials: C
authors.lastname: Dutreix
authors.affiliation: Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, NJ, USA.
authors.forename: Venkateswar
authors.initials: V
authors.lastname: Jarugula
authors.affiliation: Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, NJ, USA.
authors.forename: Sam
authors.initials: S
authors.lastname: Rebello
authors.affiliation: Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, NJ, USA.
authors.forename: Christina S
authors.initials: CS
authors.lastname: Won
authors.affiliation: Drug Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, East Hanover, NJ, USA.
authors.forename: Haiying
authors.initials: H
authors.lastname: Sun
mesh_terms: D000328:Adult; D065701:Cytochrome P-450 CYP3A Inducers / Q000008:administration & dosage* / Q000097:blood / Q000493:pharmacokinetics; D004347:Drug Interactions; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D006888:Hydroxycholesterols / Q000008:administration & dosage / Q000097:blood* / Q000494:pharmacology; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D012293:Rifampin / Q000008:administration & dosage* / Q000097:blood / Q000493:pharmacokinetics; D055815:Young Adult
chemical_list: D065701:Cytochrome P-450 CYP3A Inducers; D006888:Hydroxycholesterols; C099828:cholest-5-ene-3,4-diol; D012293:Rifampin
keywords: 4β-hydroxycholesterol; CYP3A; endogenous biomarker; population pharmacokinetics and pharmacodynamics; rifampicin