Translational Modeling Predicts Efficacious Therapeutic Dosing Range of Teclistamab for Multiple Myeloma.

BACKGROUND: Teclistamab (JNJ-64007957), a B-cell maturation antigen × CD3 bispecific antibody, displayed potent T-cell-mediated cytotoxicity of multiple myeloma cells in preclinical studies. OBJECTIVE: A first-in-human, Phase I, dose escalation study (MajesTEC-1) is evaluating teclistamab in patients with relapsed/refractory multiple myeloma. PATIENTS AND METHODS: To estimate the efficacious therapeutic dosing range of teclistamab, pharmacokinetic (PK) data following the first cycle doses in the low-dose cohorts in the Phase I study were modeled using a 2-compartment model and simulated to predict the doses that would have average and trough serum teclistamab concentrations in the expected therapeutic range (between EC50 and EC90 values from an ex vivo cytotoxicity assay). RESULTS: The doses predicted to have average serum concentrations between the EC50 and EC90 range were validated. In addition, simulations showed that weekly intravenous and subcutaneous doses of 0.70 mg/kg and 0.72 mg/kg, respectively, resulted in mean trough levels comparable to the maximum EC90. The most active doses in the Phase I study were weekly intravenous doses of 0.27 and 0.72 mg/kg and weekly subcutaneous doses of 0.72 and 1.5 mg/kg, with the weekly 1.5 mg/kg subcutaneous doses selected as the recommended Phase II dose (RP2D). With active doses, exposure was maintained above the mean EC90. All patients who responded to the RP2D of teclistamab had exposure above the maximum EC90 in both serum and bone marrow on cycle 3, Day 1 of treatment. CONCLUSIONS: Our findings show that PK simulations of early clinical data together with ex vivo cytotoxicity estimates can inform the identification of a bispecific antibody's therapeutic range. CLINICAL TRIAL REGISTRATION: NCT03145181, date of registration: May 9, 2017.

Population pharmacokinetics and exposure-response modeling analyses of guselkumab in patients with psoriatic arthritis.

Guselkumab is an anti-interleukin-23 human monoclonal antibody effective in treating psoriatic arthritis (PsA). To characterize the pharmacokinetics (PKs) and exposure-response relationship of guselkumab in PsA, population PKs, and exposure-response modeling, analyses were conducted using data from pivotal phase III studies of subcutaneous guselkumab in patients with PsA. The observed serum concentration-time data of guselkumab were adequately described by a one-compartment linear PK model with first-order absorption and elimination. Covariates identified as contributing to the observed guselkumab PK variability were body weight and diabetes comorbidity; however, the magnitude of the effects of these covariates was not considered clinically relevant, and dose adjustment was not warranted for the patient population investigated. Positive exposure-response relationships were demonstrated with landmark and longitudinal exposure-response analyses between guselkumab exposure and clinical efficacy end points (American College of Rheumatology [ACR] 20%, 50%, and 70% improvement criteria and Investigator's Global Assessment [IGA] of psoriasis) at weeks 20 and/or 24, with no clinically relevant differences observed in improvement of PsA signs and symptoms between the two guselkumab treatment regimens evaluated (100 mg every 4 weeks or 100 mg at weeks 0 and 4, then every 8 weeks). Baseline Disease Activity Score in 28 joints (DAS28), Psoriasis Area and Severity Index (PASI) score, and/or C-reactive protein level were identified as influencing covariates on guselkumab exposure-response model parameters. These results provide a comprehensive evaluation of subcutaneous guselkumab PKs and exposure-response relationship that supports the dose regimen of 100 mg at weeks 0 and 4, then every 8 weeks in patients with PsA.

Population Pharmacokinetics and Exposure-Response Modeling of Daratumumab Subcutaneous Administration in Patients With Light-Chain Amyloidosis.

The purpose of this study is to characterize the population pharmacokinetics (popPK) of subcutaneous (SC) daratumumab in combination with bortezomib, cyclophosphamide, and dexamethasone and explore the relationship between daratumumab systemic exposure and selected efficacy and safety end points in patients with newly diagnosed systemic amyloid light-chain amyloidosis. The popPK analysis included pharmacokinetic and immunogenicity data from patients receiving daratumumab SC in combination with bortezomib, cyclophosphamide, and dexamethasone in the ANDROMEDA study (AMY3001; safety run-in, n = 28; randomized phase, n = 183). Nonlinear mixed-effects modeling was used to characterize the popPK and quantify the impact of potential covariates. The exposure-response (E-R) analysis included data from all patients in the randomized phase of ANDROMEDA (n = 388). Logistic regression and survival analysis were used to evaluate the relationships between daratumumab systemic exposure and efficacy end points. The E-R analysis on safety was conducted using quartile comparison and logistic regression analysis. The observed concentration-time data of daratumumab SC were well described by a 1-compartment popPK model with first-order absorption and parallel linear and nonlinear Michaelis-Menten elimination pathways. None of the investigated covariates were determined to be clinically meaningful. Daratumumab systemic exposure was generally similar across subgroups that achieved different levels of hematologic response, and there was no apparent relationship between daratumumab systemic exposure and the investigated safety end points. In conclusion, the popPK and E-R analyses supported the selected 1800-mg flat dose of daratumumab SC in combination with the bortezomib, cyclophosphamide, and dexamethasone regimen for the treatment of light-chain amyloidosis. No dose adjustment was recommended for investigated covariates.

Extrapolating Pharmacodynamic Effects From Adults to Pediatrics: A Case Study of Ustekinumab in Pediatric Patients With Moderate to Severe Plaque Psoriasis.

Ustekinumab (STELARA) is a human monoclonal antibody against interleukins-12 and -23 for the treatment of adult and adolescent (≥ 12 to < 18 years of age) patients with moderate-to-severe plaque psoriasis. A phase III study was recently completed in pediatric patients (≥ 6 to < 12 years of age) with psoriasis. The objectives of the current analysis were to develop a population pharmacokinetic (PK) model and a joint longitudinal exposure-response model using ordered categorial end points derived from Psoriasis Area and Severity Index (PASI) and Physician's Global Assessment (PGA) scores (namely a joint PASI response criteria (PRC) and PGA model) to characterize the PK and exposure-response relationship of ustekinumab in pediatric patients with psoriasis. The developed pediatric models reasonably predicted the PK of ustekinumab, as well as the PRC and PGA clinical response in pediatric patients with psoriasis. In addition, the joint PRC and PGA modeling framework was able to adequately extrapolate clinical response in pediatric patients using data collected from clinical studies in adult patients with psoriasis.

Pharmacokinetics and Pharmacodynamics of JNJ-55920839, an Antibody Targeting Interferon α/ω, in Healthy Subjects and Subjects with Mild-to-Moderate Systemic Lupus Erythematosus.

BACKGROUND: The interferon (IFN) pathway has been correlated with clinical and serological markers of disease activity in patients with systemic lupus erythematosus (SLE). OBJECTIVE: The pharmacokinetics and pharmacodynamics of JNJ-55920839, a fully human immunoglobulin G1κ antibody targeting IFNα/ω, were investigated. METHODS: In a double-blind, first-in-human study, Part A enrolled 48 healthy adults who received a single dose of placebo/JNJ-55920839 between 0.3 and 15 mg/kg intravenous (IV) or at 1 mg/kg subcutaneous (SC). Part B enrolled 26 adults with SLE who received placebo or JNJ-55920839 10 mg/kg IV 6 times biweekly. Pharmacokinetic parameters were calculated by noncompartmental analysis (NCA) and estimated by nonlinear mixed-effects modeling. RESULTS: JNJ-55920839 pharmacokinetics following a single IV infusion exhibited a biphasic disposition in healthy subjects. Maximum plasma concentration (Cmax) and area under the concentration-time curve values increased dose-proportionally. Mean clearance (CL) after a single IV infusion ranged between 2.28 and 3.09 mL/kg/day. Absolute bioavailability after a single SC injection was ≥ 80.0%. Mean terminal elimination half-life (t1/2) was similar after IV (20.7 to 24.6 days) and SC administration (22.6 days). Steady state of JNJ-55920839 was achieved 6 weeks after multiple 10 mg/kg IV doses in subjects with SLE. Mean steady-state CL and t1/2 were 4.73 mL/kg/day and 14.8 days, respectively. A linear 2-compartment population pharmacokinetic model with 1st-order absorption and elimination adequately characterized the pharmacokinetics; parameters were consistent with NCA estimates. Higher CL was estimated in subjects with SLE compared with healthy subjects, after correcting for body weight. A trend of increased total IFNα/ω levels was observed after treatment with JNJ-55920839. CONCLUSION: Pharmacokinetic and pharmacodynamic analyses of the data from this study demonstrated that there was biphasic disposition in both healthy subjects and subjects with SLE, CL was faster in subjects with SLE, and increases in total IFNα/ω levels were observed in both healthy subjects and subjects with SLE after treatment with JNJ-55920839, thus further development is supported. The study is registered at ClinicalTrials.gov NCT02609789.

Application of Beta-Distribution and Combined Uniform and Binomial Methods in Longitudinal Modeling of Bounded Outcome Score Data.

Disease status is often measured with bounded outcome scores (BOS) which takes a discrete set of values on a finite range. The distribution of such data is often skewed, rendering the standard analysis methods assuming normal distribution inappropriate. Among the methods used for BOS analyses, two of them have the ability to predict the data within its natural range and accommodate data skewness: (1) a recently proposed beta-distribution based approach and (2) a mixture model known as CUB (combined uniform and binomial). This manuscript compares the two approaches, using an established mechanism-based longitudinal exposure-response model to analyze data from a phase 2 clinical trial in psoriatic patients. The beta-distribution-based approach was confirmed to perform well, and CUB also showed potential. A separate issue of modeling clinical trial data is that the collected baseline disease score range may be more limited than that of post-treatment disease score due to clinical trial inclusion criteria, a fact that is typically ignored in longitudinal modeling. The effect of baseline disease status restriction should in principle be adjusted for in longitudinal modeling.

Facilitating Longitudinal Exposure-Response Modeling of a Composite Endpoint Using the Joint Modeling of Sparsely and Frequently Collected Subcomponents.

Longitudinal exposure-response modeling plays an important role in optimizing dose and dosing regimens in clinical drug development. Certain clinical trials contain induction and maintenance phases where the maintenance treatment depends on the subjects' achieving the main endpoint outcome in the induction phase. Due to logistic difficulties and cost considerations, the main endpoint is usually collected more sparsely than a subcomponent (or other related endpoints). The sparse collection of the main endpoint hampers its longitudinal modeling. In principle, the frequent collection of a subcomponent allows its longitudinal modeling. However, the model evaluation via the visual predictive check (VPC) in the maintenance phase is difficult due to the requirement of the main-endpoint model to identify the treatment subgroups. This manuscript proposes a solution to this dilemma via the joint modeling of the main endpoint and the subcomponent. The challenges are illustrated by analyzing the data collected up to 60 weeks from a phase III trial of ustekinumab in patients with moderate-to-severe ulcerative colitis (UC). The main endpoint Mayo score, a commonly used composite endpoint to measure the severity of UC, was collected only at baseline, the end of the induction phase, and the end of the maintenance phase. The partial Mayo score, which is a major subset of the Mayo score, was collected at nearly every 4 weeks. A longitudinal joint exposure-response model, developed under a latent-variable Indirect Response modeling framework, described the Mayo score time course and facilitated the VPC model evaluation under a response-adaptive trial design.

Evaluating Potential Disease-Mediated Protein-Drug Interactions in Patients With Moderate-to-Severe Plaque Psoriasis Receiving Subcutaneous Guselkumab.

This open-label, multicenter, phase I therapeutic protein-drug interaction study was designed to evaluate the potential effect of guselkumab, a fully human anti-interleukin-23 immunoglobulin G1 lambda monoclonal antibody, on the pharmacokinetics of a cocktail of representative cytochrome P450 (CYP) probe substrates (midazolam (CYP3A4), S-warfarin (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and caffeine (CYP1A2)). Fourteen participants with psoriasis received a single subcutaneous dose of guselkumab 200 mg on day 8 and an oral probe cocktail on days 1, 15, and 36. Blood samples were collected for measuring plasma concentrations of these probe substrates on days 1, 15, and 36. No consistent trends in observed maximum plasma concentration and area under the curve from time 0 to infinity values of each probe CYP-substrate before (day 1) and after guselkumab treatment (days 15 and 36) could be identified in each individual patient, suggesting that the use of guselkumab in patients with psoriasis is unlikely to influence the systemic exposure of drugs metabolized by CYP isozymes (CYP3A4, CYP2C9, CYP2C19, CYP2D6, and CYP1A2). The probe cocktail was generally well-tolerated when administered in combination with guselkumab in patients with psoriasis. Clinicaltrials.gov Identifiers: NCT02397382.

Applying Beta Distribution in Analyzing Bounded Outcome Score Data.

Disease status is often measured with bounded outcome scores (BOS) which report a discrete set of values on a finite range. The distribution of such data is often non-standard, such as J- or U-shaped, for which standard analysis methods assuming normal distribution become inappropriate. Most BOS analysis methods aim to either predict the data within its natural range or accommodate data skewness, but not both. In addition, a frequent modeling objective is to predict clinical response of treatment using derived disease endpoints, defined as meeting certain criteria of improvement from baseline in disease status. This objective has not yet been addressed in existing BOS data analyses. This manuscript compares a recently proposed beta distribution-based approach with the standard continuous analysis approach, using an established mechanism-based longitudinal exposure-response model to analyze data from two phase 3 clinical studies in psoriatic patients. The beta distribution-based approach is shown to be superior in describing the BOS data and in predicting the derived endpoints, along with predicting the response time course of a highly sensitive subpopulation.

Population Pharmacokinetics and Exposure-Response Modeling Analyses of Ustekinumab in Adults With Moderately to Severely Active Ulcerative Colitis.

To characterize the pharmacokinetics (PK) and exposure-response (E-R) relationship of ustekinumab, an anti-interleukin-12/interleukin-23 (IL-12/IL-23) human monoclonal antibody, in the treatment of moderately to severely active ulcerative colitis (UC), population PK and E-R modeling analyses were conducted based on the data from the pivotal phase 3 induction and maintenance studies in UC patients. The observed serum concentration-time data of ustekinumab were adequately described by a 2-compartment linear PK model with first-order absorption and first-order elimination. Body weight, baseline serum albumin, sex, and antibodies to ustekinumab were the covariates to influence ustekinumab PK, but the magnitudes of the effects of these covariates were not considered clinically relevant, and dose adjustment was not warranted. Positive E-R relationships were demonstrated between ustekinumab exposure metrics and clinical endpoints (including clinical response, clinical remission, and endoscopic healing based on Mayo score) at induction week 8 and maintenance week 44, consistent with the effectiveness of ustekinumab in the induction and maintenance treatment of patients with UC. E-R modeling results suggest that ustekinumab ∼6 mg/kg intravenous induction and 90-mg subcutaneous every-8-week maintenance dose would produce greater efficacy than the 130 mg intravenous induction and the 90-mg subcutaneous every-12-week maintenance regimen, respectively. Our work provides a comprehensive evaluation of ustekinumab PK and E-R in a modeling framework to support ustekinumab dose recommendations in patients with UC.

Influence of model-predicted rivaroxaban exposure and patient characteristics on efficacy and safety outcomes in patients with acute coronary syndrome.

BACKGROUND: This analysis aimed to evaluate the impact of rivaroxaban exposure and patient characteristics on efficacy and safety outcomes in patients with acute coronary syndrome (ACS) and to determine whether therapeutic drug monitoring might provide additional information regarding rivaroxaban dose, beyond what patient characteristics provide. METHODS: A post hoc exposure-response analysis was conducted using data from the phase III ATLAS ACS 2 Thrombolysis in Myocardial Infarction (TIMI) 51 study, in which 15,526 randomized ACS patients received rivaroxaban (2.5 mg or 5 mg twice daily) or placebo for a mean of 13 months (maximum follow up: 31 months). A multivariate Cox model was used to correlate individual predicted rivaroxaban exposures and patient characteristics with time-to-event clinical outcomes. RESULTS: For the incidence of myocardial infarction (MI), ischemic stroke, or nonhemorrhagic cardiovascular death, hazard ratios (HRs) for steady-state maximum plasma concentration (Cmax) in the 5th and 95th percentiles versus the median were statistically significant but close to 1 for both rivaroxaban doses. For TIMI major bleeding events, a statistically significant association was observed with Cmax [HR, 1.08; 95% CI, 1.06-1.11 (95th percentile versus median, 2.5 mg twice daily)], sex [HR, 0.56; 95% CI, 0.38-0.84 (female versus male)], and previous revascularization [HR, 0.62; 95% CI, 0.44-0.87 (no versus yes)]. CONCLUSIONS: The shallow slopes of the exposure-response relationships and the lack of a clear therapeutic window render it unlikely that therapeutic drug monitoring in patients with ACS would provide additional information regarding rivaroxaban dose beyond that provided by patient characteristics.

Pharmacokinetics, Pharmacodynamics, Immunogenicity, Safety, and Tolerability of JNJ-61178104, a Novel Tumor Necrosis Factor-Alpha and Interleukin-17A Bispecific Antibody, in Healthy Subjects.

The safety, tolerability, pharmacokinetics, pharmacodynamics, and immunogenicity of JNJ-61178104, a novel anti-tumor necrosis factor-alpha (TNFα) and anti-interleukin-17A (IL-17A) bispecific antibody, were investigated in a placebo-controlled, first-in-human study. Healthy subjects (n = 54) received a single dose of JNJ-61178104 by either intravenous infusion (0.1, 0.3, 1, 3, and 10 mg/kg) or subcutaneous injection (1 mg/kg). Blood samples for measurement of serum JNJ-61178104 concentrations, total IL-17A, total TNFα, and detection of antidrug antibodies were collected for up to 16 weeks after dosing and assessed using electrochemiluminescence immunoassays. PK parameters were calculated by noncompartmental analysis and estimated by nonlinear mixed-effects modeling. JNJ-61178104 was generally well tolerated in healthy subjects. For the intravenous cohorts, mean maximum concentration, and area under the concentration-time curve values increased in a dose-proportional manner. Mean clearance ranged from 6.73 to 9.99 mL/day/kg, mean volume of distribution at terminal phase after intravenous administration ranged from 51.0 to 91.9 mL/kg, and mean half-life ranged from 4.3 to 9.7 days following intravenous administration. After a single subcutaneous dose of 1 mg/kg, median time to maximum concentration was 4.0 days, mean bioavailability was 52.0% and mean half-life was 5.3 days. A linear 2-compartment population model with first-order elimination adequately characterized the pharmacokinetics with parameters consistent with noncompartmental analysis estimates. Body weight and antidrug antibodies were significant covariates on JNJ-61178104 clearance. The time to reach mean maximum serum total TNFα and total IL-17A concentrations appeared to be dose dependent across the 0.1 mg/kg to 10 mg/kg IV dose groups. All subjects who received active treatment were antidrug antibody positive after dosing with JNJ-61178104.

Modeling near-continuous clinical endpoint as categorical: application to longitudinal exposure-response modeling of Mayo scores for golimumab in patients with ulcerative colitis.

Accurate characterization of exposure-response relationship of clinical endpoints is important in drug development to identify optimal dose regimens. Endpoints with ≥ 10 ordered categories are typically analyzed as continuous. This manuscript aims to show circumstances where it is advantageous to analyze such data as ordered categorical. The results of continuous and categorical analyses are compared in a latent-variable based Indirect Response modeling framework for the longitudinal modeling of Mayo scores, ranging from 0 to 12, which is commonly used as a composite endpoint to measure the severity of ulcerative colitis (UC). Exposure response modeling of Mayo scores is complicated by the fact that studies typically include induction and maintenance phases with re-randomizations and other response-driven dose adjustments. The challenges are illustrated in this work by analyzing data collected from 3 phase II/III trials of golimumab in patients with moderate-to-severe UC. Visual predictive check was used for model evaluations. The ordered categorical approach is shown to be accurate and robust compared to the continuous approach. In addition, a disease progression model with an empirical bi-phasic rate of onset was found to be superior to the commonly used placebo model with one onset rate. An application of this modeling approach in guiding potential dose-adjustment was illustrated.

Risk-Based Comparability Assessment for Monoclonal Antibodies During Drug Development: A Clinical Pharmacology Perspective.

Due to complexities in the structure, function, and manufacturing process of antibody-based therapeutic proteins, comparability assessment for supporting manufacturing changes can sometimes be a challenging task. Regulatory guidance recommends a hierarchical risk-based approach, starting with Chemistry, Manufacturing, and Controls (CMC) analytical characterizations, followed by non-clinical and/or clinical studies to ensure that any potential changes in quality attributes have no adverse impact on efficacy and safety of the product. This review focuses on the changes in quality attributes which may potentially affect the pharmacokinetics (PK), pharmacodynamics (PD), and immunogenicity of a monoclonal antibody (mAb) product, and provides general guidelines in designing non-clinical and clinical PK/PD studies to help support comparability assessments. A decision tree for comparability assessment is proposed depending on the nature of the changes in quality attributes, the potential impact of such changes, and the timing of the manufacturing change relative to the development process. Ideally, the optimization of manufacturing process should take place in the early stage of drug development (i.e., preclinical to phase 2a) as more stringent comparability criteria would have to be met if manufacturing changes occur in the late stage of drug development (i.e., phase 2b and after), and consequently, major changes in manufacturing process should be avoided during confirmatory phase 3 studies and post-approval of drug products.

Joint longitudinal model development: application to exposure-response modeling of ACR and DAS scores in rheumatoid arthritis patients treated with sirukumab.

Exposure-response modeling is important to optimize dose and dosing regimen in clinical drug development. The joint modeling of multiple endpoints is made possible in part by recent progress in latent variable indirect response (IDR) modeling for ordered categorical endpoints. This manuscript presents the results of joint modeling of continuous and ordered categorical endpoints in the latent variable IDR modeling framework through the sharing of model parameters, with an application to the exposure-response modeling of sirukumab. Sirukumab is a human anti- interleukin-6 (IL-6) monoclonal antibody that binds soluble human IL-6 thus blocking IL-6 signaling, which plays a major role in the pathophysiology of rheumatoid arthritis (RA). A phase 2 clinical trial was conducted in patients with active RA despite methotrexate therapy, who received subcutaneous (SC) administration of either placebo or sirukumab of 25, 50 or 100 mg every 4 weeks (q4w) or 100 mg every 2 weeks (q2w). Major efficacy endpoints were the 20, 50, and 70% improvement in the American College of Rheumatology (ACR20, ACR50, and ACR70) disease severity criteria, and the 28-joint disease activity score using C-reactive protein (DAS28). The ACR endpoints were treated as ordered categorical and DAS28 as continuous. The results showed that, compared with the common approach of separately modeling the endpoints, the joint model could describe the observed data better with fewer parameters through the sharing of random effects, and thus more precisely characterize the dose-response relationship. The implications on future dose and dosing regimen optimization are discussed in contrast with those from landmark analysis.

Exposure-Response Modeling Analyses for Sirukumab, a Human Monoclonal Antibody Targeting Interleukin 6, in Patients With Moderately to Severely Active Rheumatoid Arthritis.

To characterize the dose-exposure-response relationship of sirukumab, an anti-interleukin 6 human monoclonal antibody, in the treatment of moderately to severely active rheumatoid arthritis (RA), we conducted exposure-response (E-R) modeling analyses based on data from two pivotal phase 3 placebo-controlled trials of sirukumab in patients with RA who were inadequate responders to nonbiologic disease-modifying antirheumatic drugs or anti-tumor necrosis factor α agents. A total of 2176 patients were included for the analyses and received subcutaneous administration of either placebo or sirukumab 50 mg every 4 weeks or 100 mg every 2 weeks. The clinical endpoints were 20%, 50%, and 70% improvement in the American College of Rheumatology response criteria (ie, ACR20, ACR50, and ACR70), and 28-joint Disease Activity Index Score (DAS28) using C-reactive protein. To provide a thorough assessment of the sirukumab E-R relationship, 2 pharmacokinetic/pharmacodynamic modeling approaches were implemented, including joint longitudinal modeling (ie, indirect response modeling of the time course of the 2 clinical endpoints) and landmark analyses (ie, direct linking of selected pharmacokinetic parameters to response at week 16 or 24). Results from both modeling analyses were generally consistent, and collectively suggested that the sirukumab subcutaneous dose of 50 mg every 4 weeks would produce near-maximal efficacy. No covariates identified in the E-R modeling analyses would have a significant impact on dose-response. Despite body weight and comorbid diabetes having significant effect on sirukumab exposure, simulations suggested that their effect on efficacy was small. Our work provides a comprehensive evaluation of sirukumab E-R to support dose recommendations in patients with RA.

Why Drugs Fail in Late Stages of Development: Case Study Analyses from the Last Decade and Recommendations.

New drug development is both resource and time intensive, where later clinical stages result in significant costs. We analyze recent late-stage failures to identify drugs where failures result from inadequate scientific advances as well as drugs where we believe pitfalls could have been avoided. These can be broadly classified into two categories: 1) where science is mature and the failures can be avoided through rigorous and prospectively determined decision-making criteria, scientific curiosity, and discipline to follow up on emerging findings; and 2) where problems encountered in Phase 3 failures cannot be explained at this time, as the science is not sufficiently advanced and companies/investigators need to recognize the possibility of deficiency of our knowledge. Through these case studies, key themes critical for successful drug development emerge-understanding the therapeutic pathway including receptor and signaling biology, pharmacological responses related to safety and efficacy, pharmacokinetics of the drug and exposure at target site, optimum dose, and dosing regimen; and identification of patient sub-populations likely to respond and will have a favorable benefit-risk profile, design of clinical trials, and a quantitative framework that can guide data-driven decision making. It is essential that the right studies are conducted early in the development process to answer the key questions, with the emphasis on learning in the early stages of development, whereas Phase 3 should be reserved for confirming the safety and efficacy. Utilization of innovative technology in identifying patients based on molecular signature of their disease, rapid assessment of pharmacological response, mechanistic modeling of emerging data, seamless operational processes to reduce start-up and wind-down time for clinical trials through use of electronic health records and data mining, and development of novel and objective clinical efficacy endpoints are some concepts for improving the success rate.

A comprehensive evaluation of exposure-response relationships in clinical trials: application to support guselkumab dose selection for patients with psoriasis.

Guselkumab, a human IgG1 monoclonal antibody that blocks interleukin-23, has been evaluated in one Phase 2 and two Phase 3 trials in patients with moderate-to-severe psoriasis, in which disease severity was assessed using Psoriasis Area and Severity Index (PASI) and Investigator's Global Assessment (IGA) scores. Through the application of landmark and longitudinal exposure-response (E-R) modeling analyses, we sought to predict the guselkumab dose-response (D-R) relationship using data from 1459 patients who participated in these trials. A recently developed novel latent-variable Type I Indirect Response joint model was applied to PASI75/90/100 and IGA response thresholds, with placebo effect empirically modeled. An effect of body weight on E-R, independent of pharmacokinetics, was identified. Thorough landmark analyses also were implemented using the same dataset. The E-R models were combined with a population pharmacokinetic model to generate D-R predictions. The relative merits of longitudinal and landmark analysis also are discussed. The results provide a comprehensive and robust evaluation of the D-R relationship.

Population Pharmacokinetic Modeling of Guselkumab, a Human IgG1λ Monoclonal Antibody Targeting IL-23, in Patients with Moderate to Severe Plaque Psoriasis.

Psoriasis is a common inflammatory skin disorder that requires chronic treatment and is associated with multiple comorbidities. Guselkumab, a human immunoglobulin-G1-lambda monoclonal antibody, binds to interleukin-23 with high specificity and affinity and is effective in treating moderate to severe plaque psoriasis. As part of the guselkumab psoriasis clinical trial program, using a confirmatory approach, a population pharmacokinetics (PopPK) model was established using 13 014 PK samples from 1454 guselkumab-treated patients across 3 phase 2/3 trials. Observed serum guselkumab concentrations were adequately described by a 1-compartment linear PK model with first-order absorption and elimination. The final PK model was robust and stable, with apparent clearance (CL/F), apparent volume of distribution (V/F), and absorption rate constant (ka) estimates of 0.516 L/day, 13.5 L, and 1.11 day-1 , respectively. A model-derived elimination half-life of 18.1 days indicated achievement of steady-state serum guselkumab concentrations within 12-14 weeks. The primary covariate contributing to the observed PK variability was body weight, which accounted for only 28% (CL/F) and 32% (V/F) of the interindividual proportion of variance. Diabetes was identified to marginally reduce guselkumab exposure, owing to 12% higher CL/F in diabetic versus nondiabetic patients, but its contribution was not clinically relevant. None of the other covariates tested (eg, age, sex, ethnicity, immune response to guselkumab, or concomitant medications) had a clinically relevant effect on guselkumab exposure.