Prediction of CYP-mediated DDIs involving inhibition: Approaches to address the requirements for system qualification of the Simcyp Simulator.

Physiologically-based pharmacokinetic (PBPK) modeling is being increasingly used in drug development to avoid unnecessary clinical drug-drug interaction (DDI) studies and inform drug labels. Thus, regulatory agencies are recommending, or indeed requesting, more rigorous demonstration of the prediction accuracy of PBPK platforms in the area of their intended use. We describe a framework for qualification of the Simcyp Simulator with respect to competitive and mechanism-based inhibition (MBI) of CYP1A2, CYP2D6, CYP2C8, CYP2C9, CYP2C19, and CYP3A4/5. Initially, a DDI matrix, consisting of a range of weak, moderate, and strong inhibitors and substrates with varying fraction metabolized by specific CYP enzymes that were susceptible to different degrees of inhibition, were identified. Simulations were run with 123 clinical DDI studies involving competitive inhibition and 78 clinical DDI studies involving MBI. For competitive inhibition, the overall prediction accuracy was good with an average fold error (AFE) of 0.91 and 0.92 for changes in the maximum plasma concentration (Cmax ) and area under the plasma concentration (AUC) time profile, respectively, as a consequence of the DDI. For MBI, an AFE of 1.03 was determined for both Cmax and AUC. The prediction accuracy was generally comparable across all CYP enzymes, irrespective of the isozyme and mechanism of inhibition. These findings provide confidence in application of the Simcyp Simulator (V19 R1) for assessment of the DDI potential of drugs in development either as inhibitors or victim drugs of CYP-mediated interactions. The approach described herein and the identified DDI matrix can be used to qualify subsequent versions of the platform.

Estimation of brain receptor occupancy for trazodone immediate release and once a day formulations.

Trazodone is approved for the treatment of major depressive disorders, marketed as immediate release (IR), prolonged release, and once a day (OAD) formulation. The different formulations allow different administration schedules and may be useful to facilitate patients' compliance to the antidepressant treatment. A previously verified physiologically-based pharmacokinetic model based on in vitro and in vivo information on trazodone pharmacokinetics was applied, aiming at predicting brain receptor occupancy (RO) after single and repeated dosing of the IR formulation and repeated dosing of the OAD formulation in healthy subjects. Receptors included in the simulations were selected using static calculations of RO based on the maximum unbound brain concentration (Cmax,brain,u ) of trazodone for each formulation and dosing scheme, resulting in 16 receptors being simulated. Seven receptors were simulated for the IR low dose formulation (30 mg), with similar tonset and duration of coverage (range: 0.09-0.25 h and 2.1->24 h, respectively) as well as RO (range: 0.64-0.92) predicted between day 1 and day 7 of dosing. The 16 receptors evaluated for the OAD formulation (300 mg) showed high RO (range: 0.97-0.84 for the receptors also covered by the IR formulation and 0.73-0.48 for the remaining) correlating with affinity and similar duration of time above the target threshold to the IR formulation (range: 2->24 h). The dose-dependent receptor coverage supports the multimodal activity of trazodone, which may further contribute to its fast antidepressant action and effectiveness in controlling different symptoms in depressed patients.

A physiologically based pharmacokinetic - pharmacodynamic modelling approach to predict incidence of neutropenia as a result of drug-drug interactions of paclitaxel in cancer patients.

Paclitaxel is the backbone of standard chemotherapeutic regimens used in a number of malignancies and is frequently given with concomitant medications. Newly developed oncolytic agents, including tyrosine kinase inhibitors are often shown to be CYP3A4 and P-gp inhibitors. The aim of this study was to develop a PBPK model for intravenously administered paclitaxel in order to predict the incidence of neutropenia and to estimate the DDI potential as a victim drug. The dose-dependent effects on paclitaxel plasma protein binding, volume of distribution and drug clearance were considered for dose levels of 80 mg/m2, 135 mg/m2 and 175 mg/m2. A pharmacodynamics model that incorporate the impact of paclitaxel on the neutrophil was developed. The relative metabolic clearance via CYP3A4 and CYP2C8, the renal clearance as well as P-gp mediated biliary clearance were incorporated in the model in order to assess the neutropenia in the presence of DDI. The developed PBPK-PD model was able to recover the drop in neutrophils observed after the administration of 175mg/m2 of paclitaxel over a 3-h duration. The mean nadir observed was 1.9 × 109 neutrophils/L and was attained after 10 days of treatment, and a fraction of 47% of the population was predicted to have at some point a neutropenia including 12% with severe neutropenia. In the case of concomitant administration of ketoconazole, 39% of the population was predicted to suffer from severe neutropenia. In summary, PBPK-PD modeling allows a priori prediction of DDIs and safety events involving complex combination therapies which are often utilized in an oncology setting.

Evaluation of Maternal Drug Exposure Following the Administration of Antenatal Corticosteroids During Late Pregnancy Using Physiologically-Based Pharmacokinetic Modeling.

Betamethasone and dexamethasone are the most widely studied antenatal corticosteroids (ACS) administered to pregnant women, just prior to the birth of a preterm neonate, to accelerate fetal lung maturation. Although betamethasone, predominantly used in developed countries, has been shown to be an effective and safe intervention for reducing neonatal mortality, the choice of ACS and optimal dosing in low and middle income countries (LMICs) remains unclear. This is primarily because the exposure-response relationships have not been established for ACS despite the long history of use. As the first step toward the optimal use of ACS in LMICs, we developed physiologically-based pharmacokinetic (PBPK) models to describe the kinetics of ACS following i.v., p.o., or i.m. dosing. In vitro data describing the cytochrome P450 3A4 enzyme contribution were incorporated and this was refined using clinical data. The models can be applied prospectively to predict kinetics of ACS in pregnant women receiving various dosing regimens.

Drug Dosing in Pregnant Women: Challenges and Opportunities in Using Physiologically Based Pharmacokinetic Modeling and Simulations.

The unmet medical need of providing evidence-based pharmacotherapy for pregnant women is recognized by the regulatory bodies. Physiologically based pharmacokinetic (PBPK) modeling offers an attractive platform to quantify anticipated changes in the pharmacokinetics (PKs) of drugs during pregnancy. Recent publications applying a pregnancy PBPK module to the prediction of maternal and fetal exposure of drugs are summarized. Future opportunities to use PBPK models to predict breast milk exposure and assess human fetotoxicity risks are presented.

Assessment of the persistence of anacetrapib and evacetrapib concentrations using two pharmacokinetic modeling approaches.

Anacetrapib, a cholesterol ester transfer protein (CETP) inhibitor, has been reported to have longer elimination half-life after longer treatment. Two pharmacokinetic model-based approaches were used to assess whether evacetrapib, another CETP inhibitor, could behave similarly. Using population pharmacokinetic (PopPK) modeling, evacetrapib and anacetrapib pharmacokinetics were characterized using available concentration-time data, and steady-state conditions were simulated. Published 2-compartment models for each compound were adapted to include a hypothetical third compartment representing a depot into which drug could partition. Physiologically based pharmacokinetic (PBPK) modeling was used to predict steady-state conditions and terminal half-life based on known physicochemical and dispositional properties. The PopPK model described the anacetrapib data well, showing a likely third compartment with estimated apparent volume of 40,700 L. Anacetrapib's estimated half-life for this compartment was 550 days. Simulations for evacetrapib using a hypothetical 3-compartment model, the third compartment being consistent with that of the anacetrapib model, produced predictions inconsistent with reported results, indicating that evacetrapib did not substantially accumulate into a large compartment. The PBPK simulations were consistent with PopPK results, predicting accumulation for anacetrapib (but not evacetrapib) followed by very slow elimination. Based on available data and known physicochemical properties, evacetrapib is not expected to accumulate substantially during long-term treatment.

Pharmacometrics in pregnancy: An unmet need.

Pregnant women and their fetuses are orphan populations with respect to the safety and efficacy of drugs. Physiological and absorption, distribution, metabolism, and excretion (ADME) changes during pregnancy can significantly affect drug pharmacokinetics (PK) and may necessitate dose adjustment. Here, the specific aspects related to the design, execution, and analysis of clinical studies in pregnant women are discussed, underlining the unmet need for top-down pharmacometrics analyses and bottom-up modeling approaches. The modeling tools that support data analysis for the pregnancy population are reviewed, with a focus on physiologically based pharmacokinetics (PBPK) and population pharmacokinetics (POP-PK). By integrating physiological data, preclinical data, and clinical data (e.g., via POP-PK) to quantify anticipated changes in the PK of drugs during pregnancy, the PBPK approach allows extrapolation beyond the previously studied model drugs to other drugs with well-characterized ADME characteristics. Such a systems pharmacology approach can identify drugs whose PK may be altered during pregnancy, guide rational PK study design, and support dose adjustment for pregnant women.

Expansion of a PBPK model to predict disposition in pregnant women of drugs cleared via multiple CYP enzymes, including CYP2B6, CYP2C9 and CYP2C19.

AIM: Conducting PK studies in pregnant women is challenging. Therefore, we asked if a physiologically-based pharmacokinetic (PBPK) model could be used to predict the disposition in pregnant women of drugs cleared by multiple CYP enzymes. METHODS: We expanded and verified our previously published pregnancy PBPK model by incorporating hepatic CYP2B6 induction (based on in vitro data), CYP2C9 induction (based on phenytoin PK) and CYP2C19 suppression (based on proguanil PK), into the model. This model accounted for gestational age-dependent changes in maternal physiology and hepatic CYP3A, CYP1A2 and CYP2D6 activity. For verification, the pregnancy-related changes in the disposition of methadone (cleared by CYP2B6, 3A and 2C19) and glyburide (cleared by CYP3A, 2C9 and 2C19) were predicted. RESULTS: Predicted mean post-partum to second trimester (PP : T2 ) ratios of methadone AUC, Cmax and Cmin were 1.9, 1.7 and 2.0, vs. observed values 2.0, 2.0 and 2.6, respectively. Predicted mean post-partum to third trimester (PP : T3 ) ratios of methadone AUC, Cmax and Cmin were 2.1, 2.0 and 2.4, vs. observed values 1.7, 1.7 and 1.8, respectively. Predicted PP : T3 ratios of glyburide AUC, Cmax and Cmin were 2.6, 2.2 and 7.0 vs. observed values 2.1, 2.2 and 3.2, respectively. CONCLUSIONS: Our PBPK model integrating prior physiological knowledge, in vitro and in vivo data, allowed successful prediction of methadone and glyburide disposition during pregnancy. We propose this expanded PBPK model can be used to evaluate different dosing scenarios, during pregnancy, of drugs cleared by single or multiple CYP enzymes.

A physiologically based pharmacokinetic model to predict disposition of CYP2D6 and CYP1A2 metabolized drugs in pregnant women.

Conducting pharmacokinetic (PK) studies in pregnant women is challenging. Therefore, we asked if a physiologically based pharmacokinetic (PBPK) model could be used to evaluate different dosing regimens for pregnant women. We refined and verified our previously published pregnancy PBPK model by incorporating cytochrome P450 CYP1A2 suppression (based on caffeine PK) and CYP2D6 induction (based on metoprolol PK) into the model. This model accounts for gestational age-dependent changes in maternal physiology and hepatic CYP3A activity. For verification, the disposition of CYP1A2-metabolized drug theophylline (THEO) and CYP2D6-metabolized drugs paroxetine (PAR), dextromethorphan (DEX), and clonidine (CLO) during pregnancy was predicted. Our PBPK model successfully predicted THEO disposition during the third trimester (T3). Predicted mean postpartum to third trimester (PP:T3) ratios of THEO area under the curve (AUC), maximum plasma concentration, and minimum plasma concentration were 0.76, 0.95, and 0.66 versus observed values 0.75, 0.89, and 0.72, respectively. The predicted mean PAR steady-state plasma concentration (Css) ratio (PP:T3) was 7.1 versus the observed value 3.7. Predicted mean DEX urinary ratio (UR) (PP:T3) was 2.9 versus the observed value 1.9. Predicted mean CLO AUC ratio (PP:T3) was 2.2 versus the observed value 1.7. Sensitivity analysis suggested that a 100% induction of CYP2D6 during T3 was required to recover the observed PP:T3 ratios of PAR Css, DEX UR, and CLO AUC. Based on these data, it is prudent to conclude that the magnitude of hepatic CYP2D6 induction during T3 ranges from 100 to 200%. Our PBPK model can predict the disposition of CYP1A2, 2D6, and 3A drugs during pregnancy.

Modeling cyclosporine A inhibition of the distribution of a P-glycoprotein PET ligand, 11C-verapamil, into the maternal brain and fetal liver of the pregnant nonhuman primate: impact of tissue blood flow and site of inhibition.

UNLABELLED: Through PET imaging, our laboratory has studied the dynamic biodistribution of (11)C-verapamil, a P-gp substrate, in the nonhuman primate Macaca nemestrina. To gain detailed insight into the kinetics of verapamil transport across the blood-brain barrier (BBB) and the blood-placental barrier (BPB), we analyzed these dynamic biodistribution data by compartmental modeling. METHODS: Thirteen pregnant macaques (gestational age, 71-159 d; term, ∼172 d) underwent PET imaging with (11)C-verapamil before and during infusion (6, 12, or 24 mg/kg/h) of cyclosporine A (CsA, a P-glycoprotein [P-gp] inhibitor). Dynamic (11)C-verapamil brain or fetal liver (reporter of placental P-gp function) activity was assessed by a 1- or 2-tissue-compartment model. RESULTS: The 1-tissue-compartment model best explained the observed brain and fetal liver distribution of (11)C-radioactivity. When P-gp was completely inhibited, the brain and fetal liver distribution clearance (K1) approximated tissue blood flow (Q); that is, extraction ratio (K1/Q) was approximately 1, indicating that in the absence of P-gp function, the distribution of (11)C-verapamil radioactivity into these compartments is limited by blood flow. The potency of CsA to inhibit P-gp was tissue-independent (maternal BBB half-maximal inhibitory concentration [IC50], 5.67 ± 1.07 µM, vs. BPB IC50, 7.63 ± 3.16 µM). CONCLUSION: We propose that on deliberate or inadvertent P-gp inhibition, the upper boundary of increase in human brain (or fetal) distribution of lipophilic drugs such as verapamil will be limited by tissue blood flow. This finding provides a means to predict the magnitude of P-gp-based drug interactions at the BBB and BPB when only the baseline distribution of the drug (i.e., in the absence of P-gp inhibition) across these barriers is available through PET. Our data suggest that P-gp-based drug interactions at the human BBB and BPB can be clinically significant, particularly for those P-gp substrate drugs for which P-gp plays a significant role in excluding the drug from these privileged compartments.