Novel endpoints based on tumor size ratio to support early clinical decision-making in oncology drug-development.

In oncology drug development, overall response rate (ORR) is commonly used as an early endpoint to assess the clinical benefits of new interventions; however, ORR benefit may not always translate into a long-term clinical benefit such as overall survival (OS). Most of the work on developing endpoints based on tumor growth dynamics relies on empirical validation, leading to a lack of generalizability of the endpoints across indications and therapeutic modalities. Additionally, many of these metrics are model-based and do not use data from all the patients.

Visual predictive check of longitudinal models and dropout.

Visual predictive checks (VPC) are commonly used to evaluate pharmacometrics models. However their performance may be hampered if patients with worse outcomes drop out earlier, as often occurs in clinical trials, especially in oncology. While methods accounting for dropouts have appeared in literature, they vary in assumptions, flexibility, and performance, and the differences between them are not widely understood.

Likelihood comparisons in bounded outcome score analysis must be internally consistent.

Clinical trial endpoints are often bounded outcome scores (BOS), which are variables having restricted values within finite intervals. Common analysis approaches may treat the data as continuous, categorical, or a mixture of both. The appearance of BOS data being simultaneously continuous and categorical easily leads to confusions in pharmacometrics regarding the appropriate domain for model evaluation and the circumstances under which data likelihoods can be compared.

Latent variable indirect response modeling of clinical efficacy endpoints with combination therapy: application to guselkumab and golimumab in patients with ulcerative colitis.

Accurate characterization of longitudinal exposure-response of clinical trial endpoints is important in optimizing dose and dosing regimens in drug development. Clinical endpoints are often categorical, for which much progress has been made recently in latent variable indirect response (IDR) modeling with single drugs. However, such applications have not yet been used for trials employing multiple drugs administered concurrently.

Variability and uncertainty: interpretation and usage of pharmacometric simulations and intervals.

Variability and estimation uncertainty are important sources of variation in pharmacometric simulations. Different combinations of uncertainty and the variability components lead to a variety types of simulation intervals, and many realized and unrealized confusions exist among pharmacometricians on their interpretation and usage. This commentary aims to clarify some of the important underlying concepts and provide a convenient guideline on pharmacometric simulation conduct and interpretation.

Population Pharmacokinetic and Exposure-Response Model Simulations: Predicted Exposure and Efficacy for Maintenance Doses of Intravenous Golimumab Every 6 or 8 Weeks in Patients With Moderately to Severely Active Rheumatoid Arthritis.

Purpose: Golimumab is approved to treat moderate-to-severe active rheumatoid arthritis when given intravenously at weeks 0 and 4, then every 8 weeks (Q8W) with concomitant methotrexate. These analyses assessed whether a shorter dosing interval could ameliorate diminished efficacy experienced by a small proportion of patients toward the end of the dosing interval.

Methods: Population pharmacokinetic and exposure-response modeling simulations were performed for intravenous golimumab 2 mg/kg at weeks 0 and 4, then Q8W or every 6 weeks (Q6W) through 1 year.

Improving categorical endpoint longitudinal exposure-response modeling through the joint modeling with a related endpoint.

Exposure-response modeling is important to optimize dose and dosing regimens in clinical drug development. While primary clinical trial endpoints often have few categories and thus provide only limited information, sometimes there may be additional, more informative endpoints. Benefits of fully incorporating relevant information in longitudinal exposure-response modeling through joint modeling have recently been shown.

Pharmacokinetic/Pharmacodynamic Analysis of Guselkumab for Treatment of Palmoplantar Pustulosis: Clinical Implications of Guselkumab Dose, Disease Severity, and Smoking in Japanese Patients.

Guselkumab is a human IgG1λ monoclonal antibody that has been approved for treatment of multiple immunologic diseases including palmoplantar pustulosis in Japan. The efficacy of guselkumab in reducing disease severity as compared with placebo has been demonstrated in phase 2 and 3 clinical studies. In some patients assigned to the placebo treatment, worsening of Palmoplantar Pustulosis Area and Severity Index (PPPASI) score was noted.

Pharmacokinetic Modeling and Predictive Performance: Practical Considerations for Therapeutic Monoclonal Antibodies.

Population pharmacokinetic (PopPK) model parameter estimation and predictive performance depend on the data adequacy for model building. PopPK models of therapeutic monoclonal antibodies (mAbs) may not be well supported by commonly used sparse sampling in late-stage development because of the slow absorption (days) and long half-life (weeks) of mAbs, affecting accuracy of predicted exposure metrics which are often used to support drug development. A case study was presented for a representative mAb to compare the predictive performance of two established PopPK models from their respective data.

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.

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).

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).

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.

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.

On the Comparison of Methods in Analyzing Bounded Outcome Score Data.

Clinical trial endpoints often take the form of bounded outcome scores (BOS) which report a discrete set of values on a finite range. Conceptually such endpoints are ordered categorical in nature, but in practice they are often analyzed as continuous variables, which may result in data range violations and difficulties to handle data skewness. Analysis methods dedicated for BOS data have been proposed; however, much confusion exists among pharmacometricians on how to compare the possible methods.

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

Population pharmacokinetics (PK) and exposure-response (E-R) analyses were conducted to compare the PK and E-R relationships of golimumab between children and adults with ulcerative colitis. PK data following subcutaneous golimumab administration to children with ulcerative colitis (6-17 years) in the PURSUIT-PEDS-PK study, adults with ulcerative colitis in the PURSUIT study, and children with pediatric polyarticular juvenile idiopathic arthritis (2-17 years) in the GO-KIDS study, were included in the population PK analysis. E-R analysis was conducted using logistic regression to link serum golimumab concentration and Mayo score-based efficacy outcomes in pediatric and adult ulcerative colitis.

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.

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.

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.

Confirmatory Population Pharmacokinetic Analysis for Sirukumab, a Human Monoclonal Antibody Targeting Interleukin-6, in Patients With Moderately to Severely Active Rheumatoid Arthritis.

The population pharmacokinetics of sirukumab, a human immunoglobulin G1κ monoclonal antibody against interleukin-6, were characterized in patients with moderately to severely active rheumatoid arthritis in 4 phase 3 studies (SIRROUND-D, -T, -H, and -M). A total of 17 034 serum concentrations were analyzed from 1991 rheumatoid arthritis patients who received subcutaneous administration of sirukumab 50 mg every 4 weeks or 100 mg every 2 weeks. A stepwise confirmatory population PK analysis was conducted to accommodate the staged data release and the sparse sampling nature of phase 3 studies and to assess the potential covariate influences in an unbiased and timely manner.

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.

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.

Integrated pharmacokinetic/viral dynamic model for daclatasvir/asunaprevir in treatment of patients with genotype 1 chronic hepatitis C.

In order to develop an integrated pharmacokinetic/viral dynamic (PK/VD) model to predict long-term virological response rates to daclatasvir (DCV) and asunaprevir (ASV) combination therapy in patients infected with genotype 1 (GT1) chronic hepatitis C virus (HCV), a systematic publication search was conducted for DCV and ASV administered alone and/or in combination in healthy subjects or patients with GT1 HCV infection. On the basis of a constructed meta-database, an integrated PK/VD model was developed, which adequately described both DCV and ASV PK profiles and viral load time curves. The IC values of DCV and ASV were estimated to be 0.