Compelling Relationship of CYP3A Induction to Levels of the Putative Biomarker 4β-Hydroxycholesterol and Changes in Midazolam Exposure

Drug-Drug Interactions With the Hepatitis B Virus Capsid Assembly Modulator JNJ-56136379 (Bersacapavir)

The capsid assembly modulator JNJ-56136379 (bersacapavir) disrupts hepatitis B virus replication. It is metabolized via cytochrome P450 (CYP) 3A, but little is known about the drug-drug interactions of JNJ-56136379 when combined with drugs that inhibit or are metabolized by CYP3A. In a phase 1, open-label trial (NCT03945539), healthy adults received 1 dose of JNJ-56136379 with and without 21 days of prior exposure to itraconazole 200 mg (CYP3A inhibitor). In a second phase 1, open-label trial (NCT03111511), healthy women received 1 dose of drospirenone/ethinyl estradiol and midazolam before and after 15 days of JNJ-56136379. Itraconazole increased the area under the plasma concentration-time curve (AUC) of JNJ-56136379 by 38%. JNJ-56136379 reduced the maximum observed concentration and AUC of midazolam (CYP3A substrate) by 42%-54%, increased AUC of ethinyl estradiol by 1.6-fold, but had no effect on drospirenone pharmacokinetics. Overall, these results demonstrated that a strong CYP3A inhibitor (itraconazole) modestly increased JNJ-56136379 exposure. Furthermore, JNJ-56136379 was a weak inducer of CYP3A (midazolam) and increased ethinyl estradiol exposure; coadministration of high-dose estrogen-based contraceptives and JNJ-56136379 is not recommended.

Evaluation of hepatic CYP3A enzyme activity using endogenous markers in lung cancer patients treated with cisplatin, dexamethasone, and aprepitant

PURPOSE

Aprepitant is used with dexamethasone and 5-HT₃ receptor antagonists as an antiemetic treatment for chemotherapy, including cisplatin. Aprepitant is a substrate of cytochrome P450 (CYP) 3A4 and is known to cause its inhibition and induction. In addition, dexamethasone is a CYP3A4 substrate that induces CYP3A4 and CYP3A5 expression. In this study, we aimed to quantitatively evaluate the profile of CYP3A activity using its endogenous markers in non-small cell lung cancer patients receiving a standard cisplatin regimen with antiemetics, including aprepitant.

METHODS

Urinary 11β-hydroxytestosterone (11β-OHT)/testosterone concentration ratio and plasma 4β-hydroxycholesterol (4β-OHC) concentrations were measured before and after cisplatin treatment (days 1, 4, and 8). CYP3A5 was genotyped, and plasma aprepitant concentrations were measured on day 4 to examine its influence on CYP3A endogenous markers.

RESULTS

The urinary 11β-OHT/testosterone concentration ratio in the 35 patients included in this study increased by 2.65-fold and 1.21-fold on days 4 and 8 compared with day 1, respectively. Their plasma 4β-OHC concentration increased by 1.46-fold and 1.66-fold, respectively. The mean plasma aprepitant concentration on day 4 was 1,451 ng/mL, which is far lower than its inhibitory constant. The allele frequencies of CYP3A5*1 and CYP3A5*3 were 0.229 and 0.771, respectively. In patients with the CYP3A5*1 allele, the plasma 4β-OHC concentration was significantly lower at baseline but more potently increased with chemotherapy.

CONCLUSION

CYP3A activity was significantly induced from day 4 to day 8 in patients receiving cisplatin and three antiemetic drugs.

Current Practices, Gap Analysis, and Proposed Workflows for PBPK Modeling of Cytochrome P450 Induction: An Industry Perspective

The International Consortium for Innovation and Quality (IQ) Physiologically Based Pharmacokinetic (PBPK) Modeling Induction Working Group (IWG) conducted a survey across participating companies around general strategies for PBPK modeling of induction, including experience with its utility to address various questions, regulatory interactions, and regulatory acceptance. The results highlight areas where PBPK modeling is used with high confidence and identifies opportunities where confidence is lower and further evaluation is needed. To enhance the survey results, the PBPK-IWG also collected case studies and analyzed recent literature examples where PBPK models were applied to predict CYP3A induction-mediated drug-drug interactions. PBPK modeling of induction has evolved and progressed significantly, proving to have great potential to accelerate drug discovery and development. With the aim of enabling optimal use for new molecular entities that are either substrates and/or inducers of CYP3A, the PBPK-IWG proposes initial workflows for PBPK application, discusses future trends, and identifies gaps that need to be addressed.

Recovery of CYP3A Phenotype after Kidney Transplantation

End-stage renal disease impairs drug metabolism via cytochrome P450 CYP3A; however, it is unclear whether CYP3A activity recovers after kidney transplantation. Therefore, the aim of this study was to evaluate the change in CYP3A activity measured as 4β-hydroxycholesterol (4βOHC) concentration after kidney transplantation. In total, data from 58 renal transplant recipients with 550 prospective 4βOHC measurements were included in the study. One sample per patient was collected before transplantation, and 2-12 samples per patient were collected 1-82 days after transplantation. The measured pretransplant 4βOHC concentrations ranged by >7-fold, with a median value of 22.8 ng/ml. Linear mixed-model analysis identified a 0.16-ng/ml increase in 4βOHC concentration per day after transplantation (P < 0.001), indicating a regain in CYP3A activity. Increasing estimated glomerular filtration rate after transplantation was associated with increasing 4βOHC concentration (P < 0.001), supporting that CYP3A activity increases with recovering uremia. In conclusion, this study indicates that CYP3A activity is regained subsequent to kidney transplantation.

A Physiologically-Based Pharmacokinetic Modeling Approach To Predict Drug-Drug Interactions of Sonidegib (LDE225) with Perpetrators of CYP3A in Cancer Patients

Sonidegib (Odomzo) is an orally available Smoothened inhibitor for the treatment of advanced basal cell carcinoma. Sonidegib was found to be metabolized primarily by cytochrome P450 (CYP)3A in vitro. The effect of multiple doses of the strong CYP3A perpetrators, ketoconazole (KTZ) and rifampin (RIF), on sonidegib pharmacokinetics (PK) after a single 800 mg dose in healthy subjects was therefore assessed. These data were used to verify a physiologically-based pharmacokinetic (PBPK) model developed to 1) bridge the clinical drug-drug interaction (DDI) study of sonidegib with KTZ and RIF in healthy subjects to the marketed dose (200 mg) in patients 2) predict acute (14 days) versus long-term dosing of the perpetrators with sonidegib at steady state and 3) predict the effect of moderate CYP3A perpetrators on sonidegib exposure in patients. Treatment of healthy subjects with KTZ resulted in an increased sonidegib exposure of 2.25- and 1.49-fold (area under the curve_0-240h and maximal concentration respectively), and RIF decreased exposure by 72% and 54%, respectively. The model simulated the single- and/or multiple-dose PK of sonidegib (healthy subjects and patients) within ∼50% of observed values. The effect of KTZ and RIF on sonidegib in healthy subjects was also simulated well, and the predicted DDI in patients was slightly less and independent of sonidegib dose. At steady state, sonidegib was predicted to have a higher DDI magnitude with strong or moderate CYP3A perpetrators compared with a single dose. Different dosing regimens of sondigeb with the perpetrators were also simulated and provided guidance to the current dosing recommendations incorporated in the product label.

Impact of genetic and nongenetic factors on interindividual variability in 4β-hydroxycholesterol concentration

PURPOSE

Individual variability in the endogenous CYP3A metabolite 4β-hydroxycholesterol (4βOHC) is substantial, but to which extent this is determined by genetic and nongenetic factors remains unclear. The aim of the study was to evaluate the explanatory power of candidate genetic variants and key nongenetic factors on individual variability in 4βOHC levels in a large naturalistic patient population.

METHODS

We measured 4βOHC concentration in serum samples from 655 patients and used multiple linear regression analysis to estimate the quantitative effects of CYP3A4*22, CYP3A5*3, and POR*28 variant alleles, comedication with CYP3A inducers, inhibitors and substrates, sex, and age on individual 4βOHC levels.

RESULTS

4βOHC concentration ranged >100-fold in the population, and the multiple linear regression model explained about one fourth of the variability (R ² = 0.23). Only comedication with inducers or inhibitors, sex, and POR genotype were significantly associated with individual variability in 4βOHC level. The estimated quantitative effects on 4βOHC levels were greatest for inducer comedication (+>313%, P < 0.001), inhibitor comedication (-34%, P = 0.021), and female sex (+30%, P < 0.001), while only a modestly elevated 4βOHC level was observed in carriers vs. noncarriers of POR*28 (+11%, P = 0.023).

CONCLUSIONS

These findings suggest that the CYP3A4*22, CYP3A5*3, and POR*28 variant alleles are of limited importance for overall individual variability in 4βOHC levels compared to nongenetic factors.