Physiologically based pharmacokinetic modeling of tadalafil to inform pediatric dose selection in children with pulmonary arterial hypertension.

Tadalafil, a phosphodiesterase 5 inhibitor, is being investigated as a treatment for pulmonary arterial hypertension (PAH) in children aged 6 months to less than 18 years. Tadalafil pharmacokinetic (PK) data in children less than 2 years old are unavailable, therefore a physiologically based pharmacokinetic (PBPK) model was developed to enable estimation of tadalafil doses in children less than 2 years old. The model was verified in adults and extended for use in children by modifying CYP3A-mediated intrinsic clearance to include CYP3A7. To account for co-dosing of the commonly prescribed moderate CYP3A4 inducer bosentan, predicted exposures were increased by a factor of 1.54 based on changes in exposure in adults with PAH. This factor was predictable using a bosentan PBPK model. The tadalafil model was verified in children aged greater than or equal to 2 years by comparing predicted and observed exposures. Tadalafil doses for children less than 2 years old were calculated as target area under the concentration curve from zero to 24 h (AUC0-24 )/predicted AUC0-24 , with target AUC0-24 of 10,000 ng*h/ml based on adult 40 mg single dose exposures determined in patients without bosentan background treatment. These doses were 2 mg, 3 mg, 4 mg, and 6 mg, respectively, for children aged birth to less than 1 month, 1 month to less than 6 months, 6 months to less than 1 year, and 1 to less than 2 years. Due to uncertainties in CYP maturation, a nonmechanistic steady-state volume scalar, and lack of PK data in children less than 2 years old, accumulation of tadalafil to steady-state in children less than 2 years was not verifiable. Safety of proposed doses is supported by postmarketing research and investigator-led trials.

Predicting Clinical Effects of CYP3A4 Modulators on Abemaciclib and Active Metabolites Exposure Using Physiologically Based Pharmacokinetic Modeling.

Abemaciclib, a selective inhibitor of cyclin-dependent kinases 4 and 6, is metabolized mainly by cytochrome P450 (CYP)3A4. Clinical studies were performed to assess the impact of strong inhibitor (clarithromycin) and inducer (rifampin) on the exposure of abemaciclib and active metabolites. A physiologically based pharmacokinetic (PBPK) model incorporating the metabolites was developed to predict the effect of other strong and moderate CYP3A4 inhibitors and inducers. Clarithromycin increased the area under the plasma concentration-time curve (AUC) of abemaciclib and potency-adjusted unbound active species 3.4-fold and 2.5-fold, respectively. Rifampin decreased corresponding exposures 95% and 77%, respectively. These changes influenced the fraction metabolized via CYP3A4 in the model. An absolute bioavailability study informed the hepatic and gastric availability. In vitro data and a human radiolabel study determined the fraction and rate of formation of the active metabolites as well as absorption-related parameters. The predicted AUC ratios of potency-adjusted unbound active species with rifampin and clarithromycin were within 0.7- and 1.25-fold of those observed. The PBPK model predicted 3.78- and 7.15-fold increases in the AUC of the potency-adjusted unbound active species with strong CYP3A4 inhibitors itraconazole and ketoconazole, respectively; and 1.62- and 2.37-fold increases with the concomitant use of moderate CYP3A4 inhibitors verapamil and diltiazem, respectively. The model predicted modafinil, bosentan, and efavirenz would decrease the AUC of the potency-adjusted unbound active species by 29%, 42%, and 52%, respectively. The current PBPK model, which considers changes in unbound potency-adjusted active species, can be used to inform dosing recommendations when abemaciclib is coadministered with CYP3A4 perpetrators.

Quantitative Prediction of CYP3A4- and CYP3A5-Mediated Drug Interactions.

We verified a physiologically-based pharmacokinetic (PBPK) model to predict cytochrome P450 3A4/5-mediated drug-drug interactions (DDIs). A midazolam (MDZ)-ketoconazole (KTZ) interaction study in 24 subjects selected by CYP3A5 genotype, and liquid chromatography and mass spectroscopy quantification of CYP3A4/5 abundance from independently acquired and genotyped human liver (n = 136) and small intestinal (N = 12) samples, were conducted. The observed CYP3A5 genetic effect on MDZ systemic and oral clearance was successfully replicated by a mechanistic framework incorporating the proteomics-informed CYP3A abundance and optimized small intestinal CYP3A4 abundance based on MDZ intestinal availability (FG ) of 0.44. Furthermore, combined with a modified KTZ PBPK model, this framework recapitulated the observed geometric mean ratio of MDZ area under the curve (AUCR) following 200 or 400 mg KTZ, which was, respectively, 2.7-3.4 and 3.9-4.7-fold in intravenous administration and 11.4-13.4 and 17.0-19.7-fold in oral administration, with AUCR numerically lower (P > 0.05) in CYP3A5 expressers than nonexpressers. In conclusion, the developed mechanistic framework supports dynamic prediction of CYP3A-mediated DDIs in study planning by bridging DDIs between CYP3A5 expressers and nonexpressers.

Physiologically-Based Pharmacokinetic Modeling of Atorvastatin Incorporating Delayed Gastric Emptying and Acid-to-Lactone Conversion.

The drug-drug interaction profile of atorvastatin confirms that disposition is determined by cytochrome P450 (CYP) 3A4 and organic anion transporting polypeptides (OATPs). Drugs that affect gastric emptying, including dulaglutide, also affect atorvastatin pharmacokinetics (PK). Atorvastatin is a carboxylic acid that exists in equilibrium with a lactone form in vivo. The purpose of this work was to assess gastric acid-mediated lactone equilibration of atorvastatin and incorporate this into a physiologically-based PK (PBPK) model to describe atorvastatin acid, lactone, and their major metabolites. In vitro acid-to-lactone conversion was assessed in simulated gastric fluid and included in the model. The PBPK model was verified with in vivo data including CYP3A4 and OATP inhibition studies. Altering the gastric acid-lactone equilibrium reproduced the change in atorvastatin PK observed with dulaglutide. The model emphasizes the need to include gastric acid-lactone conversion and all major atorvastatin-related species for the prediction of atorvastatin PK.

Physiologically Based Pharmacokinetic Model Qualification and Reporting Procedures for Regulatory Submissions: A Consortium Perspective.

This work provides a perspective on the qualification and verification of physiologically based pharmacokinetic (PBPK) platforms/models intended for regulatory submission based on the collective experience of the Simcyp Consortium members. Examples of regulatory submission of PBPK analyses across various intended applications are presented and discussed. European Medicines Agency (EMA) and US Food and Drug Administration (FDA) recent draft guidelines regarding PBPK analyses and reporting are encouraging, and to advance the use and acceptability of PBPK analyses, more clarity and flexibility are warranted.

Population Pharmacokinetics of LY2623091 in Patients With Hypertension and Chronic Kidney Disease.

LY2623091 is a selective, orally active, nonsteroidal, competitive mineralocorticoid receptor antagonist that blocks the actions of aldosterone and other mineralocorticoid receptor ligands at the receptor level. The aim of this work was to explore and establish a population pharmacokinetic model, quantify the degree of interindividual variability, and identify significant disease-, patient-, and study-specific covariates that alter the disposition of LY2623091. The data included concentrations from 294 healthy subjects and patients with hypertension and/or chronic kidney disease (CKD), sampled in 5 phase 1 and 2 studies. The pharmacokinetics of LY2623091 was well described by a 2-compartment model with first-order absorption and elimination. Formulation (on oral bioavailability) as well as weight and age (both on apparent central volume of distribution) were found to be significant covariates. The relative bioavailability of the capsule formulation was 68.4% compared to that of the solution. Hypertension and CKD status were not significant covariates. The pharmacokinetic model suggests that given the same dose, patients with hypertension and/or CKD would receive a similar exposure compared to subjects without these disease conditions.

Receptor Occupancy of the κ-Opioid Antagonist LY2456302 Measured with Positron Emission Tomography and the Novel Radiotracer 11C-LY2795050.

The κ-opioid receptor (KOR) is thought to play an important therapeutic role in a wide range of neuropsychiatric and substance abuse disorders, including alcohol dependence. LY2456302 is a recently developed KOR antagonist with high affinity and selectivity and showed efficacy in the suppression of ethanol consumption in rats. This study investigated brain penetration and KOR target engagement after single oral doses (0.5-25 mg) of LY2456302 in 13 healthy human subjects. Three positron emission tomography scans with the KOR antagonist radiotracer (11)C-LY2795050 were conducted at baseline, 2.5 hours postdose, and 24 hours postdose. LY2456302 was well tolerated in all subjects without serious adverse events. Distribution volume was estimated using the multilinear analysis 1 method for each scan. Receptor occupancy (RO) was derived from a graphical occupancy plot and related to LY2456302 plasma concentration to determine maximum occupancy (rmax) and IC50. LY2456302 dose dependently blocked the binding of (11)C-LY2795050 and nearly saturated the receptors at 10 mg, 2.5 hours postdose. Thus, a dose of 10 mg of LY2456302 appears well suited for further clinical testing. Based on the pharmacokinetic (PK)-RO model, the rmax and IC50 of LY2456302 were estimated as 93% and 0.58 ng/ml to 0.65 ng/ml, respectively. Assuming that rmax is 100%, IC50 was estimated as 0.83 ng/ml.

Safety, tolerability, and pharmacokinetic evaluation of single- and multiple-ascending doses of a novel kappa opioid receptor antagonist LY2456302 and drug interaction with ethanol in healthy subjects.

Accumulating evidence indicates that selective antagonism of kappa opioid receptors may provide therapeutic benefit in the treatment of major depressive disorder, anxiety disorders, and substance use disorders. LY2456302 is a high-affinity, selective kappa opioid antagonist that demonstrates >30-fold functional selectivity over mu and delta opioid receptors. The safety, tolerability, and pharmacokinetics (PK) of LY2456302 were investigated following single oral doses (2-60 mg), multiple oral doses (2, 10, and 35 mg), and when co-administered with ethanol. Plasma concentrations of LY2456302 were measured by liquid chromatography-tandem mass spectrometry method. Safety analyses were conducted on all enrolled subjects. LY2456302 doses were well-tolerated with no clinically significant findings. No safety concerns were seen on co-administration with ethanol. No evidence for an interaction between LY2456302 and ethanol on cognitive-motor performance was detected. LY2456302 displayed rapid oral absorption and a terminal half-life of approximately 30-40 hours. Plasma exposure of LY2456302 increased proportionally with increasing doses and reached steady state after 6-8 days of once-daily dosing. Steady-state PK of LY2456302 were not affected by coadministration of a single dose of ethanol. No clinically important changes in maximum concentration (Cmax ) or AUC of ethanol (in the presence of LY2456302) were observed.

A framework for assessing inter-individual variability in pharmacokinetics using virtual human populations and integrating general knowledge of physical chemistry, biology, anatomy, physiology and genetics: A tale of 'bottom-up' vs 'top-down' recognition of covariates.

An increasing number of failures in clinical stages of drug development have been related to the effects of candidate drugs in a sub-group of patients rather than the 'average' person. Expectation of extreme effects or lack of therapeutic effects in some subgroups following administration of similar doses requires a full understanding of the issue of variability and the importance of identifying covariates that determine the exposure to the drug candidates in each individual. In any drug development program the earlier these covariates are known the better. An important component of the drive to decrease this failure rate in drug development involves attempts to use physiologically-based pharmacokinetics 'bottom-up' modeling and simulation to optimize molecular features with respect to the absorption, distribution, metabolism and elimination (ADME) processes. The key element of this approach is the separation of information on the system (i.e. human body) from that of the drug (e.g. physicochemical characteristics determining permeability through membranes, partitioning to tissues, binding to plasma proteins or affinities toward certain enzymes and transporter proteins) and the study design (e.g. dose, route and frequency of administration, concomitant drugs and food). In this review, the classical 'top-down' approach in covariate recognition is compared with the 'bottom-up' paradigm. The determinants and sources of inter-individual variability in different stages of drug absorption, distribution, metabolism and excretion are discussed in detail. Further, the commonly known tools for simulating ADME properties are introduced.

The use of mechanistic DM-PK-PD modelling to assess the power of pharmacogenetic studies -CYP2C9 and warfarin as an example.

AIM: To assess the power of in vivo studies needed to discern the effect of genotype on pharmacokinetics (PK) and pharmacodynamics (PD) using CYP2C9 and (S)-warfarin as an example. METHODS: Information on the in vitro metabolism of (S)-warfarin and genetic variation in CYP2C9 was incorporated into a mechanistic population-based PK-PD model. The influence of study design on the ability to detect significant differences in PK (AUC(0-12 h)) and PD (AUEC(0-12 h) INR) between CYP2C9 genotypes was investigated. RESULTS: A study size of 90 (based on the natural abundance of genotypes and uniform dosage) was required to achieve 80% power to discriminate the PK of (S)-warfarin between wild type (*1/*1) and the combination of all other genotypes. About 250 subjects were needed to detect a difference in anticoagulant response. The power to detect differences between specific genotypes was much lower. Analysis of experimental comparisons of the PK or PD between wild-type and other individual genotypes indicated that only 21% of cases (20 of 95 comparisons within 11 PD and four PK-PD studies) reported statistically significant differences. This was similar to the percentage expected from our simulations (20%, chi(2) test, P = 0.80). Simulations of studies enriched with specific genotypes indicated that only three and five subjects were required to detect differences in PK and PD between wild type and the *3/*3 genotype, respectively. CONCLUSION: The utilization of prior information (including in vivo enzymology) in clinical trial simulations can guide the design of subsequent in vivo studies of the impact of genetic polymorphisms, and may help to avoid costly, inconclusive outcomes.

Incorporating in vitro information on drug metabolism into clinical trial simulations to assess the effect of CYP2D6 polymorphism on pharmacokinetics and pharmacodynamics: dextromethorphan as a model application.

In vitro-in vivo extrapolation of clearance, embedded in a clinical trial simulation, was used to investigate differences in the pharmacokinetics and pharmacodynamics of dextromethorphan between CYP2D6 poor and extensive metabolizer phenotypes. Information on the genetic variation of CYP2D6, as well as the in vitro metabolism and pharmacodynamics of dextromethorphan and its active metabolite dextrorphan, was integrated to assess the power of studies to detect differences between phenotypes. Whereas 6 subjects of each phenotype were adequate to achieve 80% power in showing pharmacokinetic differences, the power required to detect a difference in antitussive response was less than 80% with 500 subjects in each study arm. Combining in vitro-in vivo extrapolation with a clinical trial simulation is useful in assessing different elements of study design and could be used a priori to avoid inconclusive pharmacogenetic studies.