Population PK/PD modeling of low-density lipoprotein cholesterol response in hypercholesterolemic participants following administration of bococizumab, a potent anti-PCSK9 monoclonal antibody.

We sought to characterize the population pharmacokinetic/pharmacodynamic (PK/PD) relationship of bococizumab (RN316/PF-04950615), a humanized IgG2Δa monoclonal antibody that binds to secreted human proprotein convertase subtilisin kexin type 9 (PCSK9), using data derived from 16 phase I, II, and III clinical studies (36,066 bococizumab observations, 46,790 low-density lipoprotein cholesterol [LDL-C] measurements, 3499 participants). A two-compartment disposition model with parallel linear and Michaelis-Menten elimination and an indirect response model was used to characterize the population PK and LDL-C response of bococizumab. Potential model parameters and covariate relationships were explored, and visual predictive checks were used for model assessment and validation. Key covariates included the effect of anti-drug antibodies (ADAs) on exposure through impact on clearance and bioavailability; impact of statins on bococizumab elimination (maximal rate of metabolism); and impact of statins, Asian race, and male sex on LDL-C efficacy (maximum effect). ADAs and neutralizing ADAs did not have additional effects on LDL-C beyond the influence on bococizumab exposure. In conclusion, the population PK/PD model adequately describes bococizumab concentration and LDL-C efficacy. The covariate effects are consistent with the presumed mechanism of action of PCSK9 inhibitors. With increasing availability of antibody-based therapeutics, improved understanding of the effect of ADAs and statins on bococizumab PK/PD adds to the literature and enhances our pharmacological understanding of how immunogenicity and concomitant medications may impact the PK/PD of biotherapeutics.

Pharmacokinetics, pharmacodynamics, and safety of bococizumab, a monoclonal antibody against proprotein convertase subtilisin/kexin type 9, in healthy subjects when administered in co-mixture with recombinant human hyaluronidase: A phase 1 randomized trial.

AIM: Prior to the discontinuation of bococizumab's clinical development, it was considered advantageous to develop an infrequent dosing regimen (eg, monthly). Therefore, we conducted a phase 1 study to evaluate the pharmacokinetics, pharmacodynamics, and safety of bococizumab when administered in co-mixture with recombinant human hyaluronidase (rHuPH20). METHOD: Healthy subjects (N = 60) were randomized equally among 4 groups that received a single subcutaneous dose of either bococizumab 150, 300, or 450 mg co-mixed with rHuPH20 or bococizumab 300 mg alone. Bioavailability and lipid-lowering effect of bococizumab were evaluated by using ANCOVA models. RESULTS: In the groups administered bococizumab co-mixed with rHuPH20, dose-normalized C max and AUCinf were 26.6 to 39.1% and 18.3 to 36.6% greater, respectively, compared with bococizumab 300 mg alone. Despite these increases, mean percent reductions from baseline in low-density lipoprotein cholesterol were smaller in the bococizumab 300 mg + rHuPH20 group than in the bococizumab 300-mg group at Day 21 (52.2% and 59.5%, respectively) and were similar at Day 29 (51.7% and 49.6%, respectively). Compared with the group administered bococizumab 300 mg alone, the bococizumab 300 mg + rHuPH20 group did not show a significantly altered AUEC85 (ratio of adjusted means: 102.5%, 90% confidence interval: 96.1-109.3%) but did show a higher MaxELDL-C (ratio of adjusted means: 125.4%, 90% confidence interval: 103.3-152.2%), indicating diminution of efficacy. The most frequent adverse events were injection-site erythema, injection-site bruising, and nasopharyngitis; all injection-site adverse events were mild. CONCLUSION: Co-mixture with rHuPH20 increased the bioavailability of bococizumab without proportional increase in pharmacodynamic effect. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02667223.

Results of bococizumab, a monoclonal antibody against proprotein convertase subtilisin/kexin type 9, from a randomized, placebo-controlled, dose-ranging study in statin-treated subjects with hypercholesterolemia.

Bococizumab is a humanized monoclonal antibody binding proprotein convertase subtilisin/kexin type 9, which may be a potential therapeutic option for reducing low-density lipoprotein cholesterol (LDL-C) levels in patients with hypercholesterolemia. In this 24-week, multicenter, double-blind, placebo-controlled, dose-ranging study (NCT01592240), subjects with LDL-C levels≥80 mg/dl on stable statin therapy were randomized to Q14 days subcutaneous placebo or bococizumab 50, 100, or 150 mg or Q28 days subcutaneous placebo or bococizumab 200 or 300 mg. Doses of bococizumab were reduced if LDL-C levels persistently decreased to ≤25 mg/dl. The primary end point was the absolute change in LDL-C levels from baseline to week 12 after placebo or bococizumab administration. Continuation of bococizumab administration through to week 24 enabled the collection of safety data over an extended period. Of the 354 subjects randomized, 351 received treatment (placebo [n=100] or bococizumab [n=251]). The most efficacious bococizumab doses were 150 mg Q14 days and 300 mg Q28 days. Compared with placebo, bococizumab 150 mg Q14 days reduced LDL-C at week 12 by 53.4 mg/dl and bococizumab 300 mg Q28 days reduced LDL-C by 44.9 mg/dl; this was despite dose reductions in 32.5% and 34.2% of subjects at week 10 or 8, respectively. Pharmacokinetic/pharmacodynamic model-based simulation assuming no dose reductions predicted that bococizumab would lower LDL-C levels by 72.2 and 55.4 mg/dl, respectively. Adverse events were similar across placebo and bococizumab groups. Few subjects (n=7; 2%) discontinued treatment because of treatment-related adverse events. In conclusion, bococizumab significantly reduced LDL-C across all doses despite dose reductions in many subjects. Model-based simulations predicted greater LDL-C reduction in the absence of bococizumab dose reduction. The Q14 days regimen is being evaluated in phase 3 clinical trials.

Novel, selective vitamin D analog suppresses parathyroid hormone in uremic animals and postmenopausal women.

BACKGROUND: The use of 1α-hydroxylated vitamin D therapy to control secondary hyperparathyroidism in renal failure patients has been a success story, culminating with the demonstration of increased life expectancy in patients treated with these compounds. However, hypercalcemic episodes have been a recurrent problem with these therapies and have resulted in the added use of calcium mimetics. Clearly there is good reason to search for improved vitamin D therapy. In our inventory of vitamin D compounds, 2-methylene-19-nor-(20S)-1α,25-dihydroxyvitamin D3 (2MD) surfaced as a potential candidate. This was based on its preferential localization in the parathyroid gland and a clear suppression of serum parathyroid hormone (PTH) levels without a change in serum calcium in a clinical trial in postmenopausal women. METHODS: 2MD has now been tested in the rat 5/6-nephrectomy model of renal failure, and in postmenopausal women to determine if it can suppress serum PTH at doses that do not elevate serum calcium and serum phosphorus concentrations. RESULTS: Daily oral treatment of uremic rats on 2.5 ng/bw/day of 2MD dramatically suppressed PTH without a change in serum calcium or serum phosphorus. Further, PTH was suppressed in postmenopausal women after only 3 daily oral doses of 2MD that continued for 4 weeks with no change in serum calcium or serum phosphorus. CONCLUSION: These results coupled with a pharmacokinetic half-life of ~24 h suggest that 2MD given either daily or at the time of dialysis may be a superior therapy for secondary hyperparathyroidism in chronic renal failure patients.

Drug metabolites as cytochrome p450 inhibitors: a retrospective analysis and proposed algorithm for evaluation of the pharmacokinetic interaction potential of metabolites in drug discovery and development.

Understanding drug-drug interactions (DDIs) is a key component of clinical practice ensuring patient safety and efficacy of medicines. The role of drug metabolites in DDIs is a developing area of science, and has been recently highlighted in a draft regulatory guidance. The guidance states that metabolites representing ≥25% of the parent drug's area under the plasma concentration/time curve and/or >10% of exposure of total drug-related material should trigger in vitro characterization of metabolites for cytochrome P450 inhibition and propensity for DDIs. The relationship between in vitro cytochrome P450 inhibitory potency, systemic exposure, and DDI potential of drug metabolites was examined using the Pfizer development database to identify compounds with pre-existing in vivo biotransformation data, where circulating metabolites were identified in humans. The database yielded 33 structurally diverse compounds with collectively 115 distinct circulating metabolites. Of these, 52% (60/115) achieved exposures >25% of parent drug levels as judged from mass balance/metabolite identification studies. It was noted that 14 metabolite standards for 12 parent drugs had been synthesized, monitored in clinical studies, and examined for cytochrome P450 inhibition. For the 14 metabolite/parent drug pairs, no clinically relevant DDIs were expected to occur against the major human cytochrome P450 isoforms. A review of the literature for parent/metabolite DDI information was also conducted to examine trends using a larger data set. Leveraging the analysis of both internal and literature-based data sets, an algorithm was devised for use in drug discovery/early development to assess cytochrome P450 inhibitory potential of drug metabolites and the propensity to cause a clinically relevant DDI.

Prediction of drug clearance in a smoking population: modeling the impact of variable cigarette consumption on the induction of CYP1A2.

PURPOSE: To derive estimates of CYP1A2 abundance as a function of daily cigarette consumption and use these values to predict the clearances of CYP1A2 substrates in smokers. METHODS: Smoking-induced changes in hepatic CYP1A2 abundance were extrapolated from reported in vivo caffeine clearance data for sub-groups of a smoking population that were categorized according to their daily cigarette consumption. These abundance values together with in vitro-in vivo extrapolation (IVIVE) within the Simcyp population-based Simulator were used to predict the clearances of caffeine, theophylline, and clozapine in smokers. The model was used subsequently to predict differences in oral clearance between smoker and non-smoker cohorts in a Phase 1 clinical trial involving PF-2400013, a drug metabolized by CYP1A2. RESULTS: Estimated hepatic CYP1A2 abundance values were 52, 64, 79, 90, and 94 pmol/mg microsomal protein for subjects smoking 0, 1-5, 6-10, 11-20, and >20 cigarettes/day respectively. Predicted -fold increases in oral clearance of caffeine, theophylline and clozapine in smokers relative to non-smokers were consistent with observed data. The validated model was able to recover the smoking-induced increase in oral clearance of PF-2400013; predicted and observed mean (CV%) values in male nonsmokers and smokers were 90 L/h (40%) and 141 L/h (34%) respectively, and 100 L/h (58%) and 131 L/h (33%) respectively. CONCLUSIONS: This study demonstrates that it may be possible to predict the clearance of CYP1A2 substrates in smoking populations using quantitative estimates of CYP1A2 abundance based on daily cigarette consumption in conjunction with an IVIVE approach.

Simulation of human intravenous and oral pharmacokinetics of 21 diverse compounds using physiologically based pharmacokinetic modelling.

BACKGROUND: The importance of predicting human pharmacokinetics during compound selection has been recognized in the pharmaceutical industry. To this end there are many different approaches that are applied. METHODS: In this study we compared the accuracy of physiologically based pharmacokinetic (PBPK) methodologies implemented in GastroPlus™ with the one-compartment approach routinely used at Pfizer for human pharmacokinetic plasma concentration-time profile prediction. Twenty-one Pfizer compounds were selected based on the availability of relevant preclinical and clinical data. Intravenous and oral human simulations were performed for each compound. To understand any mispredictions, simulations were also performed using the observed clearance (CL) value as input into the model. RESULTS: The simulation results using PBPK were shown to be superior to those obtained via traditional one-compartment analyses. In many cases, this difference was statistically significant. Specifically, the results showed that the PBPK approach was able to accurately predict passive distribution and absorption processes. Some issues and limitations remain with respect to the prediction of CL and active transport processes and these need to be improved to further increase the utility of PBPK modelling. A particular advantage of the PBPK approach is its ability to accurately predict the multiphasic shape of the pharmacokinetic profiles for many of the compounds tested. CONCLUSION: The results from this evaluation demonstrate the utility of PBPK methodology for the prediction of human pharmacokinetics. This methodology can be applied at different stages to enhance the understanding of the compounds in a particular chemical series, guide experiments, aid candidate selection and inform clinical trial design.

Comparison of different algorithms for predicting clinical drug-drug interactions, based on the use of CYP3A4 in vitro data: predictions of compounds as precipitants of interaction.

Cytochrome P450 3A4 (CYP3A4) is the most important enzyme in drug metabolism and because it is the most frequent target for pharmacokinetic drug-drug interactions (DDIs) it is highly desirable to be able to predict CYP3A4-based DDIs from in vitro data. In this study, the prediction of clinical DDIs for 30 drugs on the pharmacokinetics of midazolam, a probe substrate for CYP3A4, was done using in vitro inhibition, inactivation, and induction data. Two DDI prediction approaches were used, which account for effects at both the liver and intestine. The first was a model that simultaneously combines reversible inhibition, time-dependent inactivation, and induction data with static estimates of relevant in vivo concentrations of the precipitant drug to provide point estimates of the average magnitude of change in midazolam exposure. This model yielded a success rate of 88% in discerning DDIs with a mean -fold error of 1.74. The second model was a computational physiologically based pharmacokinetic model that uses dynamic estimates of in vivo concentrations of the precipitant drug and accounts for interindividual variability among the population (Simcyp). This model yielded success rates of 88 and 90% (for "steady-state" and "time-based" approaches, respectively) and mean -fold errors of 1.59 and 1.47. From these findings it can be concluded that in vivo DDIs for CYP3A4 can be predicted from in vitro data, even when more than one biochemical phenomenon occurs simultaneously.

Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Numerous retrospective analyses have shown the utility of in vitro systems for predicting potential drug-drug interactions (DDIs). Prediction of DDIs from in vitro data is commonly obtained using estimates of enzyme K(i), inhibitor and substrate concentrations and absorption rate for substrate and inhibitor. WHAT THIS STUDY ADDS: Using a generic approach for all test compounds, the findings from the current study showed the use of recombinant P450s provide a more robust in vitro measure of P450 contribution (fraction metabolized, f(m)) than that achieved when using chemical inhibitors in combination with human liver microsomes, for the prediction of potential CYP3A4 drug-drug interactions prior to clinical investigation. The current study supported the use of SIMCYP(R), a modelling and simulation software in utilizing the in vitro measures in the prediction of potential drug-drug interactions. AIMS: The aim of this study was to explore and optimize the in vitro and in silico approaches used for predicting clinical DDIs. A data set containing clinical information on the interaction of 20 Pfizer compounds with ketoconazole was used to assess the success of the techniques. METHODS: The study calculated the fraction and the rate of metabolism of 20 Pfizer compounds via each cytochrome P450. Two approaches were used to determine fraction metabolized (f(m)); 1) by measuring substrate loss in human liver microsomes (HLM) in the presence and absence of specific chemical inhibitors and 2) by measuring substrate loss in individual cDNA expressed P450s (also referred to as recombinant P450s (rhCYP)) The fractions metabolized via each CYP were used to predict the drug-drug interaction due to CYP3A4 inhibition by ketoconazole using the modelling and simulation software SIMCYP. RESULTS: When in vitro data were generated using Gentest supersomes, 85% of predictions were within two-fold of the observed clinical interaction. Using PanVera baculosomes, 70% of predictions were predicted within two-fold. In contrast using chemical inhibitors the accuracy was lower, predicting only 37% of compounds within two-fold of the clinical value. Poorly predicted compounds were found to either be metabolically stable and/or have high microsomal protein binding. The use of equilibrium dialysis to generate accurate protein binding measurements was especially important for highly bound drugs. CONCLUSIONS: The current study demonstrated that the use of rhCYPs with SIMCYP provides a robust in vitro system for predicting the likelihood and magnitude of changes in clinical exposure of compounds as a consequence of CYP3A4 inhibition by a concomitantly administered drug.

The sulfonylurea glipizide does not inhibit ischemic preconditioning in anesthetized rabbits.

The K(ATP) channel blocker glibenclamide inhibits cardioprotection afforded by ischemic preconditioning (IPC), raising concern about sulfonylurea use by patients with cardiovascular disease. We examined the effects of the widely prescribed sulfonylurea glipizide (Glucotrol XL(R) ) on IPC in anesthetized rabbits. Initially, in parallel studies in pentobarbital-anesthetized rabbits, we identified doses of glipizide (GLIP, 0.17 mg/kg + 0.12 mg/kg/h, IV) and glibenclamide (GLIB, 0.05 mg/kg + 0.03 mg/kg/h, IV) that produced steady-state, clinically relevant plasma levels of both drugs; these doses also significantly increased plasma insulin by 51 +/- 17% (GLIP) and by 57 +/- 17% (GLIB, both p < 0.05 vs. their respective baseline levels). Subsequent parallel studies in ketamine-xylazine-anesthetized rabbits examined the effects of these doses of GLIP and GLIB on IPC. Myocardial injury (30 min coronary occlusion/120 min reperfusion), either with or without IPC (5 min occlusion/10 min reperfusion) was induced midway during a 2 h infusion of vehicle (VEH), GLIP or GLIB (n = 10-11 each). Infarct area (IA) normalized to area-at-risk (%IA/AAR) was 62 +/- 3% in the VEH group, and was significantly reduced to 39 +/- 5% by IPC (p < 0.05 vs. VEH). Neither GLIP nor GLIB treatment had any effect on %IA/AAR in the absence of IPC (p > 0.05). IPC-induced cardioprotection was preserved in the GLIP + IPC treatment group (45 +/- 4%) when compared to VEH alone (p < 0.05), but was attenuated in the presence of GLIB (GLIB+IPC: 53 +/- 4% IA/AAR, p > 0.05 vs. VEH). Thus, at a clinically relevant plasma concentration, glipizide did not limit the cardioprotective effects of IPC, and is unlikely to increase the severity of cardiac ischemic injury.

Development of a physiologically based pharmacokinetic model for estradiol in rats and humans: a biologically motivated quantitative framework for evaluating responses to estradiol and other endocrine-active compounds.

A physiologically based pharmacokinetic (PBPK) model for estradiol (E2) in rats and humans (male and female) was developed to provide a quantitative tool for evaluating the importance of physiological parameters on E2 blood and tissue concentration time-course and for predicting blood and tissue concentrations in rats and humans. A hepatic extraction model was developed to evaluate the significance of plasma protein binding on the hepatic extraction of E2 and the approach was integrated into the E2 model. Sufficient data was available to parameterize and validate oral and iv routes. The E2 model simulations of E2 blood and tissue concentrations compared well to experimental values. Estrogen receptor content strongly impacts distribution and elimination kinetics of E2 as well as tissue concentrations. The prolonged terminal elimination phase seen after iv bolus administration reflects the slow release of receptor bound E2 from tissues. E2 uptake behavior in the ovariectomized, but not intact rat uterus, was best described as diffusion-limited. Simulations with the hepatic extraction model predicted extensive binding of E2 to albumin (rat) and SHBG (sex-hormone binding globulin humans), although hepatic extraction does not appear to be restricted to the unbound fraction, implying that the total plasma E2 concentration is important when considering hepatic uptake. Important determinants of E2 disposition are tissue ER content and binding affinity, nonreceptor binding proteins, vascular permeability, partition coefficients, hepatic blood flow, and extrahepatic metabolism. As an integral part of a research program, the quantitative framework developed for E2 can be extended to other endocrine-active compounds (EACs) and used to evaluate the biological activity of EACs.