John P. Gibbs

Effects of AMG 145 on low-density lipoprotein cholesterol levels: results from 2 randomized, double-blind, placebo-controlled, ascending-dose phase 1 studies in healthy volunteers and hypercholesterolemic subjects on statins.

OBJECTIVES The aim of this study was to evaluate the safety, tolerability, and effects of AMG 145 on low-density lipoprotein cholesterol (LDL-C) in healthy and hypercholesterolemic subjects on statin therapy. BACKGROUND Proprotein convertase subtilisin/kexin type 9 (PCSK9) down-regulates surface expression of the low-density lipoprotein receptor (LDL-R), increasing serum LDL-C. AMG 145, a fully human monoclonal antibody to PCSK9, prevents PCSK9/LDL-R interaction, restoring LDL-R recycling. METHODS Healthy adults (phase 1a) were randomized to 1 dose of AMG 145: 7, 21, 70, 210, or 420 mg SC; 21 or 420 mg IV; or matching placebo. Hypercholesterolemic adults (phase 1b) receiving low- to moderate-dose statins were randomized to multiple SC doses of AMG 145: 14 or 35 mg once weekly (QW) ×6, 140 or 280 mg every 2 weeks (Q2W) ×3, 420 mg every 4 weeks ×2, or matching placebo. Eleven subjects receiving high-dose statins and 6 subjects with heterozygous familial hypercholesterolemia were randomized to SC AMG 145 140 mg or placebo Q2W ×3. RESULTS In the trials (AMG 145 n = 85, placebo n = 28), AMG 145 reduced LDL-C up to 64% (p < 0.0001) versus placebo after 1 dose ≥21 mg and up to 81% (p < 0.001) with repeated doses ≥35 mg QW. No serious adverse events (AEs) occurred. Overall incidence of treatment-emergent AEs was similar in AMG 145 versus placebo groups: 69% versus 71% (phase 1a); 65% versus 64% (phase 1b). CONCLUSIONS In phase 1 studies, AMG 145 significantly reduced serum LDL-C in healthy and hypercholesterolemic statin-treated subjects, including those with heterozygous familial hypercholesterolemia or taking the highest doses of atorvastatin or rosuvastatin, with an overall AE profile similar to placebo.

Evaluation of Cerebrospinal Fluid Concentration and Plasma Free Concentration As a Surrogate Measurement for Brain Free Concentration

This study was designed to evaluate the use of cerebrospinal fluid (CSF) drug concentration and plasma unbound concentration (Cu,plasma) to predict brain unbound concentration (Cu,brain). The concentration-time profiles in CSF, plasma, and brain of seven model compounds were determined after subcutaneous administration in rats. The Cu,brain was estimated from the product of total brain concentrations and unbound fractions, which were determined using brain tissue slice and brain homogenate methods. For theobromine, theophylline, caffeine, fluoxetine, and propranolol, which represent rapid brain penetration compounds with a simple diffusion mechanism, the ratios of the area under the curve of Cu,brain/CCSF and Cu,brain/Cu,plasma were 0.27 to 1.5 and 0.29 to 2.1, respectively, using the brain slice method, and were 0.27 to 2.9 and 0.36 to 3.9, respectively, using the brain homogenate method. A P-glycoprotein substrate, CP-141938 (methoxy-3-[(2-phenyl-piperadinyl-3-amino)-methyl]-phenyl-N-methyl-methane-sulfonamide), had Cu,brain/CCSF and Cu,brain/Cu,plasma ratios of 0.57 and 0.066, using the brain slice method, and 1.1 and 0.13, using the brain homogenate method, respectively. The slow brain-penetrating compound, N[3-(4′-fluorophenyl)-3-(4′-phenylphenoxy)propyl-]sarcosine, had Cu,brain/CCSF and Cu,brain/Cu,plasma ratios of 0.94 and 0.12 using the brain slice method and 0.15 and 0.018 using the brain homogenate method, respectively. Therefore, for quick brain penetration with simple diffusion mechanism compounds, CCSF and Cu,plasma represent Cu,brain equally well; for efflux substrates or slow brain penetration compounds, CCSF appears to be equivalent to or more accurate than Cu,plasma to represent Cu,brain. Thus, we hypothesize that CCSF is equivalent to or better than Cu,plasma to predict Cu,brain. This hypothesis is supported by the literature data.

Quantitative Prediction of Human Pharmacokinetics for Monoclonal Antibodies

Background and ObjectivesPrediction of human pharmacokinetics for monoclonal antibodies (mAbs) plays an important role for first-in-human (FIH) dose selection. This retrospective analysis compares observed FIH pharmacokinetic data for 16 mAbs to those predicted in humans based on allometric scaling of Cynomolgus monkey pharmacokinetic data.MethodsTen mAbs exhibited linear pharmacokinetics in monkeys based on non-compartmental analysis. For these, simple allometric scaling based on bodyweight was applied to predict human clearance (CL) and volume of distribution (Vd) from those obtained in monkeys. Six mAbs exhibited nonlinear pharmacokinetics in monkeys based on population modelling. For these, a population modelling approach using nonlinear mixed-effects modelling software, NONMEM®, was applied to describe monkey data by a two-compartment pharmacokinetic model with parallel linear and nonlinear elimination from the central compartment. The pharmacokinetic parameters in monkeys were then scaled to humans based on simple allometry. Human concentrationtime profiles of these mAbs were then simulated and compared with those observed in the FIH studies.ResultsAntibodies with linear elimination in monkeys also exhibited linear elimination in humans. For these, observed CL and Vd were predicted within 2.3-fold by allometry. The predictability of human peak serum concentration (Cmax) and area under the serum concentration-time curve (AUC) for mAbs with nonlinear pharmacokinetics in monkeys was, however, concentration dependent. Cmax was consistently overestimated (up to 5.3-fold higher) when below the predicted Michaelis-Menten constant (Km; range 0.3–4 μg/mL). The prediction of human Cmax was within 2.3-fold when concentrations greatly exceeded Km. Similarly, differences between predicted human AUCs and those observed in the FIH studies were much greater at low doses/concentrations. Consequently, predicted drug exposure in humans at low starting doses (range 0.01–0.3 mg/kg) in FIH studies was poorly estimated for three of six mAbs with nonlinear pharmacokinetics.ConclusionsAllometric prediction of human pharmacokinetics may be sufficient for mAbs that exhibit linear pharmacokinetics. For mAbs that exhibited nonlinear pharmacokinetics, the best predictive performance was obtained after doses that achieved target-saturating concentrations.

Reaction Phenotyping in Drug Discovery: Moving Forward with Confidence?

For the pharmaceutical industry, one of the challenges in evaluating the risk of future compound attrition at the discovery stage is the successful prediction of the major routes of clearance in humans. For compounds cleared by metabolism, such information will help to avoid the development of compounds that will exhibit large interpatient differences in pharmacokinetics via 1). routes of metabolism catalyzed by functionally polymorphic enzymes and/or 2). clinically significant metabolic drug-drug interactions, in the later stages of development. The degree of intersubject variability that is acceptable for a drug candidate is uncertain in the discovery stage where knowledge of other important factors is limited or unavailable (i.e. therapeutic index, pharmacodynamic variability, etc). Reaction phenotyping is the semi-quantitative in vitro estimation of the relative contributions of specific drug-metabolizing enzymes to the metabolism of a test compound. However, reaction phenotyping in the discovery stage of drug development is complicated by the absence of radiolabelled parent compound or metabolite bioanalytical standards relative to later stages of development. In this commentary, some of the approaches, based on published data, which can be taken to overcome these challenges are discussed. In addition, knowledge of the molecular structure (i.e. specific chemical substituents), physicochemical properties, and routes of clearance in animals can all help in making a successful prediction for the routes of clearance in humans. In combination, the objective of these studies should be to reduce to a minimum the risk of finding significant inter-patient differences in pharmacokinetics at a later stage in development due to significant metabolism by polymorphic enzymes or drug-drug interactions. Consequently, this data should be used to avoid costly late stage attrition.

Population Pharmacokinetic/Pharmacodynamic Model of Subcutaneous Adipose 11β‐Hydroxysteroid Dehydrogenase Type 1 (11β‐HSD1) Activity After Oral Administration of AMG 221, a Selective 11β‐HSD1 Inhibitor

Inhibition of 11β‐HSD1 is hypothesized to improve measures of insulin sensitivity and hepatic glucose output in patients with type II diabetes. AMG 221 is a potent, small molecule inhibitor of 11β‐HSD1. The objective of this analysis is to describe the pharmacokinetic/pharmacodynamic (PK/PD) relationship between AMG 221 and 11β‐HSD1 inhibition in ex vivo adipose tissue samples. Healthy, obese subjects were administered a single dose of 3, 30, or 100 mg of oral AMG 221 (n = 44) or placebo (n = 11). Serial blood samples were collected over 24 hours. Subcutaneous adipose tissue samples were collected by open biopsy. Population PK/PD analysis was conducted using NONMEM. The inhibitory effects (mean ± standard error of the estimate) of AMG 221 on 11β‐HSD1 activity were directly related to adipose concentrations with Imax (the maximal inhibition of 11β‐HSD1 activity) and IC50 (the plasma AMG 221 concentration associated with 50% inhibition of enzyme activity) of 0.975 ± 0.003 and 1.19 ± 0.12 ng/mL, respectively. The estimated baseline 11β‐HSD1 enzyme activity was 755 ± 61 pmol/mg. An equilibration rate constant (keo) of 0.220 ± 0.021 h–1 described the delay between plasma and adipose tissue AMG 221 concentrations. AMG 221 potently blocked 11β‐HSD1 activity producing sustained inhibition for the 24‐hour study duration as measured in ex vivo adipose samples. Early characterization of concentration‐response relationships can support rational selection of dose and regimen for future studies.

Prediction of Exposure–Response Relationships to Support First-in-Human Study Design

In drug development, phase 1 first-in-human studies represent a major milestone as the drug moves from preclinical discovery to clinical development activities. The safety of human subjects is paramount to the conduct of these studies and regulatory considerations guide activities. Forces of evolution on the pharmaceutical industry are re-shaping the first-in-human dose selection strategy. Namely, high attrition rates in part due to lack of efficacy have led to the re-organization of research and development organizations around the umbrella of translational research. Translational research strives to bring basic research advances into the clinic and support the reverse transfer of information to enhance compound selection strategies. Pharmacokinetic/pharmacodynamic (PK/PD) modeling holds a unique position in translational research by attempting to integrate diverse sets of information. PK/PD modeling has demonstrated utility in dose selection and trial design for later stages of drug development and is now being employed with greater prevalence in the translational research setting to manage risk (i.e., oncology and inflammation/immunology). Moving from empirical Emax models to more mechanistic representations of the biological system, a higher fidelity of human predictions is expected. Strategies that have proven useful for PK predictions are being applied to PK/PD predictions. This review article examines examples of the application of PK/PD modeling in establishing target concentrations for supporting first-in-human study design.

Quantitative Model of the Relationship Between Dipeptidyl Peptidase‐4 (DPP‐4) Inhibition and Response: Meta‐Analysis of Alogliptin, Saxagliptin, Sitagliptin, and Vildagliptin Efficacy Results

Dipeptidyl peptidase‐4 (DPP‐4) inhibition is a well‐characterized treatment for type 2 diabetes mellitus (T2DM). The objective of this model‐based meta‐analysis was to describe the time course of HbA1c response after dosing with alogliptin (ALOG), saxagliptin (SAXA), sitagliptin (SITA), or vildagliptin (VILD). Publicly available data involving late‐stage or marketed DPP‐4 inhibitors were leveraged for the analysis. Nonlinear mixed‐effects modeling was performed to describe the relationship between DPP‐4 inhibition and mean response over time. Plots of the relationship between metrics of DPP‐4 inhibition (ie, weighted average inhibition [WAI], time above 80% inhibition, and trough inhibition) and response after 12 weeks of daily dosing were evaluated. The WAI was most closely related to outcome, although other metrics performed well. A model was constructed that included fixed effects for placebo and drug and random effects for intertrial variability and residual error. The relationship between WAI and outcome was nonlinear, with an increasing response up to 98% WAI. Response to DPP‐4 inhibitors could be described with a single drug effect. The WAI appears to be a useful index of DPP‐4 inhibition related to HbA1c. Biomarker to response relationships informed by model‐based meta‐analysis can be leveraged to support study designs including optimization of dose, duration of therapy, and patient population.

EFFECTS OF AMG 145, A FULLY HUMAN MONOCLONAL ANTIBODY AGAINST PCSK9, ON LOW-DENSITY LIPOPROTEIN CHOLESTEROL IN SUBJECTS TAKING STATINS: A PHASE 1, RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, ASCENDING MULTIPLE-DOSE STUDY

Proprotein convertase subtilisin/kexin type 9 (PCSK9) downregulates surface expression of the low density lipoprotein (LDL) receptor (LDL-R), increasing circulating LDL cholesterol (LDL-C). Statins increase LDL-R and PCSK9 levels. AMG 145, a fully human monoclonal antibody against PCSK9, has been

Impact of Target-Mediated Elimination on the Dose and Regimen of Evolocumab, a Human Monoclonal Antibody Against Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9).

Understanding the pharmacokinetic (PK) and pharmacodynamic (PD) relationship of a therapeutic monoclonal antibody against proprotein convertase subtilisin/kexin type 9 (PCSK9) exhibiting target‐mediated drug disposition (TMDD) is critical for selecting optimal dosing regimens. We describe the PK/PD relationship of evolocumab using a mathematical model that captures evolocumab binding and removal of unbound PCSK9 as well as reduction in circulating low‐density lipoprotein cholesterol (LDL‐C). Data were pooled from 2 clinical studies: a single‐dose escalation study in healthy subjects (7‐420 mg SC; n = 44) and a multiple‐dose escalation study in statin‐treated hypercholesterolemic patients (14 mg weekly to 420 mg monthly [QM] SC; n = 57). A TMDD model described the time course of unbound evolocumab concentrations and removal of unbound PCSK9. The estimated linear clearance and volume of evolocumab were 0.256 L/day and 2.66 L, respectively, consistent with other monoclonal antibodies. The time course of LDL‐C reduction was described by an indirect response model with the elimination rate of LDL‐C being modulated by unbound PCSK9. The concentration of unbound PCSK9 associated with half‐maximal inhibition (IC50) of LDL‐C elimination was 1.46 nM. Based on simulations, 140 mg every 2 weeks (Q2W) and 420 mg QM were predicted to achieve a similar time‐averaged effect of 69% reduction in LDL‐C in patients on statin therapy, suggesting that an approximate 3‐fold dose increase is required for a 2‐fold extension in the dosing interval. Evolocumab dosing regimens of 140 mg Q2W or 420 mg QM were predicted to result in comparable reductions in LDL‐C over a monthly period, consistent with results from recently completed phase 3 studies.

Application of In Vivo Animal Models to Characterize the Pharmacokinetic and Pharmacodynamic Properties of Drug Candidates in Discovery Settings

A goal of preclinical discovery is the identification of drug candidates suitable for clinical testing. Successful integration of in vitro and in vivo experimental data sets can afford projections of human dose regimens anticipated to be safe and therapeutically beneficial. While in vitro experiments guide new chemical syntheses and are essential to understanding drug action and disposition, in vivo characterizations provide unique insight into complex biological systems that control concentrations at the site of action and pharmacologic response. Pharmacokinetic and pharmacodynamic (PK/PD) concepts underlying drug disposition and response provide a quantitative framework with which to identify potential clinical candidates. To improve throughput in earlier stages of drug discovery, in vivo pharmacokinetic study designs such as cassette dosing and sparse sampling schemes have been utilized. In later stages of discovery, pharmacokinetic studies using chemical inhibitors or surgical and genetic animal models are used to characterize the underlying determinants of drug disposition. In a complimentary fashion, modeling of in vivo pharmacodynamic effects may quantitatively link biomarkers to pharmacological response, validate in vitro to in vivo correlations and underwrite predictions of efficacious exposure targets. When applied to in vivo discovery data, PK/PD models have aided in understanding mechanisms of pharmacological response such as receptor theory in the central nervous system and cell turnover concepts in infectious disease and oncology. This review considers the role of in vivo testing toward understanding the pharmacokinetic and pharmacodynamic attributes of lead candidates in drug discovery.