Model-informed Evidence for Clinical Non-inferiority of Every-2-Weeks Versus Standard Weekly Dosing Schedule of Cetuximab in Metastatic Colorectal Cancer.

Cetuximab was initially developed and approved as a first-line treatment in patients with unresectable metastatic colorectal cancer (mCRC) for weekly administration (250 mg/m2 Q1W with 400 mg/m2 loading dose). An every-2-weeks schedule (500 mg/m2 Q2W) was approved recently by several health authorities. Being synchronized with chemotherapy, Q2W administration should improve patients' convenience and healthcare resource utilization. Herein, we present evidence of non-inferiority of Q2W cetuximab, compared with Q1W dosing using pharmacometrics modeling and clinical trial simulation (CTS). Pooled data from five phase I-III clinical trials in 852 patients with KRAS wild-type mCRC treated with Q1W or Q2W cetuximab were modeled using a population exposure-tumor size (TS) model linked to overall survival (OS); exposure was derived from a previously established population pharmacokinetic model. A semi-mechanistic TS model adapted from the Claret model incorporated killing rate proportional to cetuximab area under the concentration-time curve over 2 weeks (AUC) with Eastern Cooperative Oncology Group (ECOG) status as covariate on baseline TS. The OS was modeled with Weibull hazard using ECOG, baseline TS, primary tumor location, and predicted percent change in TS at 8 weeks as covariates. Model-based simulations revealed indistinguishable early tumor shrinkage and survival between Q2W vs. Q1W cetuximab. CTS evaluated OS non-inferiority (predefined margin of 1.25) in 1,000 trials, each with 2,000 virtual patients receiving Q2W or Q1W cetuximab (1:1), and demonstrated non-inferiority in 94% of cases. Taken together, these analyses provide model-based evidence for clinical non-inferiority of Q2W vs. Q1W cetuximab in mCRC with potential benefits to patients and healthcare providers.

Tumor growth inhibition modeling in patients with second line biliary tract cancer and first line non-small cell lung cancer based on bintrafusp alfa trials.

This analysis aimed to quantify tumor dynamics in patients receiving either bintrafusp alfa (BA) or pembrolizumab, by population pharmacokinetic (PK)-pharmacodynamic modeling, and investigate clinical and molecular covariates describing the variability in tumor dynamics by pharmacometric and machine-learning (ML) approaches. Data originated from two clinical trials in patients with biliary tract cancer (BTC; NCT03833661) receiving BA and non-small cell lung cancer (NSCLC; NCT03631706) receiving BA or pembrolizumab. Individual drug exposure was estimated from previously developed population PK models. Population tumor dynamics models were developed for each drug-indication combination, and covariate evaluations performed using nonlinear mixed-effects modeling (NLME) and ML (elastic net and random forest models) approaches. The three tumor dynamics' model structures all included linear tumor growth components and exponential tumor shrinkage. The final BTC model included the effect of drug exposure (area under the curve) and several covariates (demographics, disease-related, and genetic mutations). Drug exposure was not significant in either of the NSCLC models, which included two, disease-related, covariates in the BA arm, and none in the pembrolizumab arm. The covariates identified by univariable NLME and ML highly overlapped in BTC but showed less agreement in NSCLC analyses. Hyperprogression could be identified by higher tumor growth and lower tumor kill rates and could not be related to BA exposure. Tumor size over time was quantitatively characterized in two tumor types and under two treatments. Factors potentially related to tumor dynamics were assessed using NLME and ML approaches; however, their net impact on tumor size was considered as not clinically relevant.

A multistate modeling and simulation framework to learn dose-response of oncology drugs: Application to bintrafusp alfa in non-small cell lung cancer.

The dose/exposure-efficacy analyses are often conducted separately for oncology end points like best overall response, progression-free survival (PFS) and overall survival (OS). Multistate models offer to bridge these dose-end point relationships by describing transitions and transition times from enrollment to response, progression, and death, and evaluating transition-specific dose effects. This study aims to apply the multistate pharmacometric modeling and simulation framework in a dose optimization setting of bintrafusp alfa, a fusion protein targeting TGF-ß and PD-L1. A multistate model with six states (stable disease [SD], response, progression, unknown, dropout, and death) was developed to describe the totality of endpoints data (time to response, PFS, and OS) of 80 patients with non-small cell lung cancer receiving 500 or 1200 mg of bintrafusp alfa. Besides dose, evaluated predictor of transitions include time, demographics, premedication, disease factors, individual clearance derived from a pharmacokinetic model, and tumor dynamic metrics observed or derived from tumor size model. We found that probabilities of progression and death upon progression decreased over time since enrollment. Patients with metastasis at baseline had a higher probability to progress than patients without metastasis had. Despite dose failed to be statistically significant for any individual transition, the combined effect quantified through a model with dose-specific transition estimates was still informative. Simulations predicted a 69.2% probability of at least 1 month longer, and, 55.6% probability of at least 2-months longer median OS from the 1200 mg compared to the 500 mg dose, supporting the selection of 1200 mg for future studies.

Variable or variate? A conundrum in pharmacometrics exposure-response models.

Key elements of scientific writing-consistency and clarity-can be compromised in case of inaccurate use of methodological terms, especially in complex and multidisciplinary scientific fields. Such is the case in reports of pharmacometrics exposure-response analyses with the use of the terms univariate/multivariate and univariable/multivariable. This perspective outlines the issues in the use of these terms, clarifies their definitions, provides examples, and makes recommendations for authors, reviewers, and journals in the fields of clinical pharmacology and pharmacometrics.

Model-informed approach for risk management of bleeding toxicities for bintrafusp alfa, a bifunctional fusion protein targeting TGF-ß and PD-L1.

PURPOSE: Bintrafusp alfa (BA) is a bifunctional fusion protein composed of the extracellular domain of the transforming growth factor-ß (TGF-ß) receptor II fused to a human immunoglobulin G1 antibody blocking programmed death ligand 1 (PD-L1). The recommended phase 2 dose (RP2D) was selected based on phase 1 efficacy, safety, and pharmacokinetic (PK)-pharmacodynamic data, assuming continuous inhibition of PD-L1 and TGF-ß is required. Here, we describe a model-informed dose modification approach for risk management of BA-associated bleeding adverse events (AEs). METHODS: The PK and AE data from studies NCT02517398, NCT02699515, NCT03840915, and NCT04246489 (n = 936) were used. Logistic regression analyses were conducted to evaluate potential relationships between bleeding AEs and BA time-averaged concentration (Cavg), derived using a population PK model. The percentage of patients with trough concentrations associated with PD-L1 or TGF-ß inhibition across various dosing regimens was derived. RESULTS: The probability of bleeding AEs increased with increasing Cavg; 50% dose reduction was chosen based on the integration of modeling and clinical considerations. The resulting AE management guidance to investigators regarding temporary or permanent treatment discontinuation was further refined with recommendations on restarting at RP2D or at 50% dose, depending on the grade and type of bleeding (tumoral versus nontumoral) and investigator assessment of risk of additional bleeding. CONCLUSION: A pragmatic model-informed approach for management of bleeding AEs was implemented in ongoing clinical trials of BA. This approach is expected to improve benefit-risk profile; however, its effectiveness will need to be evaluated based on safety data generated after implementation.

Avelumab Dose Selection for Clinical Studies in Pediatric Patients with Solid Tumors.

BACKGROUND AND OBJECTIVE: A phase I/II trial evaluated the safety, antitumor activity, and pharmacokinetics of avelumab (anti-PD-L1 antibody) in pediatric patients with refractory/relapsed solid tumors (NCT03451825). This study aimed to inform avelumab dose selection in pediatric populations using population pharmacokinetic modeling and simulations. METHODS: Patients aged < 18 years with refractory/relapsed solid tumors enrolled in phase I received avelumab 10 or 20 mg/kg intravenously every 2 weeks. A pediatric population pharmacokinetic model was developed via the frequentist prior approach. RESULTS: Pharmacokinetic parameters from 21 patients who received avelumab 10 mg/kg (n = 6) or 20 mg/kg (n = 15) were analyzed. Patients had a wide range of weights and ages (medians, 37.3 kg and 12 years). Exposures with 10-mg/kg dosing were lower vs adult dosing, particularly in patients weighing < 40 kg, whereas 20-mg/kg dosing achieved or exceeded adult exposures, irrespective of body weight. A two-compartment linear model with time-varying clearance using body weight as a covariate, with the frequentist prior approach, best described pediatric data. In this model, optimal overlap in exposure with adult data was achieved with 800 mg every 2 weeks for patients aged ≥ 12 years and weighing ≥ 40 kg, and 15 mg/kg every 2 weeks for patients aged < 12 years or weighing < 40 kg. CONCLUSIONS: Based on exposure matching, the recommended doses for further avelumab studies, including combination studies, are 15 mg/kg every 2 weeks for pediatric patients aged < 12 years or weighing < 40 kg and the adult flat dose of 800 mg every 2 weeks for pediatric patients aged ≥ 12 years and weighing ≥ 40 kg. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT03451825.

Model-Based Characterization of the Bidirectional Interaction Between Pharmacokinetics and Tumor Growth Dynamics in Patients with Metastatic Merkel Cell Carcinoma Treated with Avelumab.

PURPOSE: Empirical time-varying clearance models have been reported for several immune checkpoint inhibitors, including avelumab (anti-programmed death ligand 1). To investigate the exposure-response relationship for avelumab, we explored semimechanistic pharmacokinetic (PK)-tumor growth dynamics (TGD) models. PATIENTS AND METHODS: Plasma PK data were pooled from three phase I and II trials (JAVELIN Merkel 200, JAVELIN Solid Tumor, and JAVELIN Solid Tumor JPN); tumor size (TS) data were collected from patients with metastatic Merkel cell carcinoma (mMCC) enrolled in JAVELIN Merkel 200. A PK model was developed first, followed by TGD modeling to investigate interactions between avelumab exposure and TGD. A PK-TGD feedback loop was evaluated with simultaneous fitting of the PK and TGD models. RESULTS: In total, 1,835 PK observations and 338 TS observations were collected from 147 patients. In the final PK-TGD model, which included the bidirectional relationship between PK and TGD, avelumab PK was described by a two-compartment model with a positive association between clearance and longitudinal TS, with no additional empirical time-varying clearance identified. TGD was described by first-order tumor growth/shrinkage rates, with the tumor shrinkage rate decreasing exponentially over time; the exponential time-decay constant decreased with increasing drug concentration, representing the treatment effect through tumor shrinkage inhibition. CONCLUSIONS: We developed a TGD model that mechanistically captures the prevention of loss of antitumor immunity (i.e., T-cell suppression in the tumor microenvironment) by avelumab, and a bidirectional interaction between PK and TGD in patients with mMCC treated with avelumab, thus mechanistically describing previously reported time variance of avelumab elimination.

Quantitative relationship between infliximab exposure and inhibition of C-reactive protein synthesis to support inflammatory bowel disease management.

AIM: Quantitative and kinetic insights into the drug exposure-disease response relationship might enhance our knowledge on loss of response and support more effective monitoring of inflammatory activity by biomarkers in patients with inflammatory bowel disease (IBD) treated with infliximab (IFX). This study aimed to derive recommendations for dose adjustment and treatment optimisation based on mechanistic characterisation of the relationship between IFX serum concentration and C-reactive protein (CRP) concentration. METHODS: Data from an investigator-initiated trial included 121 patients with IBD during IFX maintenance treatment. Serum concentrations of IFX, antidrug antibodies (ADA), CRP, and disease-related covariates were determined at the mid-term and end of a dosing interval. Data were analysed using a pharmacometric nonlinear mixed-effects modelling approach. An IFX exposure-CRP model was generated and applied to evaluate dosing regimens to achieve CRP remission. RESULTS: The generated quantitative model showed that IFX has the potential to inhibit up to 72% (9% relative standard error [RSE]) of CRP synthesis in a patient. IFX concentration leading to 90% of the maximum CRP synthesis inhibition was 18.4 µg/mL (43% RSE). Presence of ADA was the most influential factor on IFX exposure. With standard dosing strategy, ≥55% of ADA+ patients experienced CRP nonremission. Shortening the dosing interval and co-therapy with immunomodulators were found to be the most beneficial strategies to maintain CRP remission. CONCLUSIONS: With the generated model we could for the first time establish a robust relationship between IFX exposure and CRP synthesis inhibition, which could be utilised for treatment optimisation in IBD patients.

Infliximab clearance decreases in the second and third trimesters of pregnancy in inflammatory bowel disease.

BACKGROUND: Infliximab therapy during pregnancy in inflammatory bowel disease is challenged by a dilemma between maintaining adequate maternal disease control while minimizing fetal infliximab exposure. We investigated the effects of pregnancy on infliximab pharmacokinetics. METHODS: The study population comprised 23 retrospectively identified pregnancies. Patients with inflammatory bowel disease were generally in clinical remission at pregnancy conception (74%) and received steady infliximab maintenance therapy (5 mg/kg q8w n = 17; q6w n = 4; q10w n = 1; 10 mg/kg q8w n = 1). Trough blood samples had been obtained in the same patients prior to pregnancy (n = 119), the first trimester (n = 16), second trimester (n = 18), third trimester (n = 7), and postpregnancy (n = 12). Data were analyzed using nonlinear mixed-effects population pharmacokinetic modeling. RESULTS: Dose-normalized infliximab concentrations were significantly higher during the second trimester (median 15 mg/ml/kg, interquartile range 10-21) compared to prepregnancy (7, 2-12; p = 0.003), the first trimester (9, 1-12; p = 0.04), or postpregnancy (6, interquartile range 3-11; p > 0.05) in patients with inflammatory bowel disease. Similar trends were observed in the third trimester (13, 7-36; p > 0.05). A one-compartment model with linear elimination described the pharmacokinetics of infliximab (volume of distribution n = 18.2 L; clearance 0.61 L/day). Maternal infliximab exposure was influenced by the second and third trimester of pregnancy and anti-infliximab antibodies, and not by pregnancy-imposed physiological changes in, for example, body weight or albumin. Infliximab clearance decreased significantly during the second and third trimesters by up to 15% as compared to pre- and postpregnancy and the first trimester. The increased maternal infliximab exposure was weakly associated with lowered clinical disease activity. Pharmacokinetic model simulations of virtual patients indicated the increased maternal infliximab trough concentrations imposed by pregnancy will not completely counteract the decrease in infliximab concentration if therapy is paused in the third trimester. CONCLUSION: Infliximab clearance decreases significantly in the second and third trimesters, leading to increasing maternal infliximab concentrations in any given regimen. Maternal infliximab levels may thus be maintained as constant in a de-intensified regimen by therapeutic drug monitoring guidance in inflammatory bowel disease.

Semimechanistic Clearance Models of Oncology Biotherapeutics and Impact of Study Design: Cetuximab as a Case Study.

This study aimed to explore the currently competing and new semimechanistic clearance models for monoclonal antibodies and the impact of clearance model misspecification on exposure metrics under different study designs exemplified for cetuximab. Six clearance models were investigated under four different study designs (sampling density and single/multiple-dose levels) using a rich data set from two cetuximab clinical trials (226 patients with metastatic colorectal cancer) and using the nonlinear mixed-effects modeling approach. A two-compartment model with parallel Michaelis-Menten and time-decreasing linear clearance adequately described the data, the latter being related to post-treatment response. With respect to bias in exposure metrics, the simplified time-varying linear clearance (CL) model was the best alternative. Time-variance of the linear CL component should be considered for biotherapeutics if response impacts pharmacokinetics. Rich sampling at steady-state was crucial for unbiased estimation of Michaelis-Menten elimination in case of the reference (parallel Michaelis-Menten and time-varying linear CL) model.

Absence of Relationship Between Crohn's Disease Activity Index or C-Reactive Protein and Infliximab Exposure Calls for Objective Crohn's Disease Activity Measures for the Evaluation of Treatment Effects at Treatment Failure.

BACKGROUND: Circulating infliximab (IFX) concentrations correlate with clinical outcomes, forming the basis of the IFX concentration monitoring in patients with Crohn's disease. This study aims to investigate and refine the exposure-response relationship by linking the disease activity markers "Crohn's disease activity index" (CDAI) and C-reactive protein (CRP) to IFX exposure. In addition, we aim to explore the correlations between different disease markers and exposure metrics. METHODS: Data from 47 Crohn's disease patients of a randomized controlled trial were analyzed post hoc. All patients had secondary treatment failure at inclusion and had received intensified IFX of 5 mg/kg every 4 weeks for up to 20 weeks. Graphical analyses were performed to explore exposure-response relationships. Metrics of exposure included area under the concentration-time curve (AUC) and trough concentrations (Cmin). Disease activity was measured by CDAI and CRP values, their change from baseline/last visit, and response/remission outcomes at week 12. RESULTS: Although trends toward lower Cmin and lower AUC in nonresponders were observed, neither CDAI nor CRP showed consistent trends of lower disease activity with higher IFX exposure across the 30 evaluated relationships. As can be expected, Cmin and AUC were strongly correlated with each other. Contrarily, the disease activity markers were only weakly correlated with each other. CONCLUSIONS: No significant relationship between disease activity, as evaluated by CDAI or CRP, and IFX exposure was identified. AUC did not add benefit compared with Cmin. These findings support the continued use of Cmin and call for stringent objective disease activity (bio-)markers (eg, endoscopy) to form the basis of personalized IFX therapy for Crohn's disease patients with IFX treatment failure.