Immunogenicity of avelumab in patients with metastatic Merkel cell carcinoma or advanced urothelial carcinoma.

Like other monoclonal antibodies, immune checkpoint inhibitors may be immunogenic in some patients, potentially affecting pharmacokinetics (PKs) and clinical outcomes. In post hoc analyses, we characterized antidrug antibody (ADA) development with avelumab monotherapy in patients with metastatic Merkel cell carcinoma (mMCC) from the JAVELIN Merkel 200 trial (first-line [1L; N = 116] and second-line or later [≥2L; N = 88] cohorts) or with advanced urothelial carcinoma (aUC) from the JAVELIN Bladder 100 (1L maintenance [N = 350]) and JAVELIN Solid Tumor (≥2L [N = 249]) trials. Treatment-emergent ADAs developed in a numerically higher proportion of patients with aUC (1L maintenance, 19.1%; ≥2L, 18.1%) versus mMCC (1L, 8.2%; ≥2L, 8.9%); incidences within tumor types were similar by line of therapy. In PK analyses, numerically lower avelumab trough concentration and higher baseline clearance were observed in treatment-emergent ADA+ versus ADA- subgroups; however, differences were not clinically relevant. Numerical differences in overall survival, progression-free survival, or objective response rate by ADA status were observed; however, no clinically meaningful trends were identified. Proportions of patients with treatment-emergent adverse events (TEAEs; any grade or grade 3/4), serious TEAEs, TEAEs leading to treatment discontinuation, or infusion-related reactions were similar, with overlapping 80% confidence intervals between ADA subgroups. Efficacy and safety observations were similar in subgroups defined by early development of ADA+ status during treatment. In conclusion, no meaningful differences in PKs, efficacy, and safety were observed between subgroups of avelumab-treated patients with different ADA status. Overall, these data suggest that ADAs are not relevant for treatment decisions with avelumab.

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.

Semi-mechanistic population pharmacokinetic/pharmacodynamic modeling of a Plasmodium elongation factor 2 inhibitor cabamiquine for prevention and cure of malaria.

Cabamiquine is a novel antimalarial agent that demonstrates the potential for chemoprevention and treatment of malaria. In this article, the dose-exposure-response relationship of cabamiquine was characterized using a population pharmacokinetic (PK)/pharmacodynamic (PD) model, incorporating the effects of cabamiquine on parasite dynamics at the liver and blood stages of malaria infection. Modeling was performed sequentially. First, a three-compartmental population PK model was developed, comprising linear elimination, a transit absorption model in combination with first-order absorption, and a recirculation model. Second, this model was expanded into a PK/PD model using parasitemia data from an induced blood stage malaria (IBSM) human challenge model. To describe the parasite growth and killing in the blood, a turnover model was used. Finally, the liver stage parasite dynamics were characterized using data from a sporozoite challenge model (SpzCh), and system parameters were fixed based on biological plausibility. Cabamiquine concentration in the central compartment was used to drive parasite killing at the blood and liver stages. Blood stage minimum inhibitory concentrations (MICb) were estimated at 7.12 ng/mL [95% confidence interval (CI95%): 6.26-7.88 ng/mL] and 1.28 ng/mL (CI95%: 1.12-1.43 ng/mL) for IBSM and SpzCh populations, respectively, while liver stage MICl was lower (0.61 ng/mL; CI95%: 0.24-0.96 ng/mL). In conclusion, a population PK/PD model was developed by incorporating parasite dynamics and drug activity at the blood and liver stages based on clinical data and biological knowledge. This model can potentially facilitate antimalarial agent development by supporting the efficient selection of the optimal dosing regimen.

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.

Nontubercular bacterial and fungal infections in patients of chronic obstructive pulmonary disease.

Introduction: Acute exacerbation of chronic obstructive pulmonary disease (COPD), frequently due to respiratory tract infection is the major cause of morbidity and mortality, and estimate suggests that it is currently the third leading cause of death worldwide. Aims and Objectives: This study aims to study the prevalence of nontubercular bacterial and fungal infections in patients of COPD. Materials and Methods: It is an observational study done for 1-year period from August 2017 to July 2018. A total of 100 COPD patients who fulfilled the inclusion and exclusion criteria were analyzed in the present study. These cases were classified according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) combined assessment criteria and subjected to sputum or in some cases Bronchoalveolar lavage (BAL) fluid examination for nontubercular bacterial and fungal pathogens. Serum galactomannan assay, bronchoscopy, and computed tomography chest were done in selected cases. Results: The age of the study population ranged from 40 to 85 years and the mean age was 60.01 ± 9.85 years. Majority of the patients were male (81.0%) and most (78.0%) of them were smokers. Most of the patients belonged to GOLD Grades 2 and 3. Forty-six percent of the patients did show pathogenic organisms in sputum examination. Out of these, 80.4% were bacterial, mainly Gram-negative organisms (Acinetobacter, Pseudomonas, Escherichia coli, Enterobacter, Proteus, and Citrobacter) and 19.6% of cases were having fungal infections (Candida and Aspergillus). Conclusions: Increasing patient age, smoking habit, and severity of COPD were related to an increasing frequency of bacterial and fungal infections. Early detection and proper treatment could help in preventing the morbidity and mortality related to COPD.

Résumé Introduction: L'exacerbation aiguë de la maladie pulmonaire obstructive chronique (MPOC), souvent en raison de l'infection des voies respiratoires, est la principale cause de morbidité et de mortalité, et l'estimation suggère qu'il s'agit actuellement de la troisième cause de décès dans le monde. Objectifs et objectifs: Cette étude vise à étudier la prévalence des infections bactériennes et fongiques non tubulaires chez les patients de la MPOC. Matériaux et méthodes: Il s'agit d'une étude d'observation réalisée pour une période de 1 an d'août 2017 à juillet 2018. Un total de 100 patients atteints de MPOC qui remplissaient les critères d'inclusion et d'exclusion ont été analysés dans la présente étude. Ces cas ont été classés selon l'initiative globale des critères d'évaluation combinés chroniques obstructifs (OR) et soumis à des expectorations ou dans certains cas examen des liquides de lavage bronchoalvéolaire (BAL) pour les agents pathogènes bactéries et fongiques non tubulaires. Le test de galactomannane sérique, la bronchoscopie et le poitrine de tomodensitométrie ont été effectués dans certains cas. Résultats: L'âge de la population d'étude variait de 40 à 85 ans et l'âge moyen était de 60,01 ± 9,85 ans. La majorité des patients étaient des hommes (81,0%) et la plupart (78,0%) d'entre eux étaient des fumeurs. La plupart des patients appartenaient à GOLD GRADES 2 et 3. Quarante-six pour cent des patients ont montré des organismes pathogènes à l'examen des expectorations. Parmi ceux-ci, 80,4% étaient des organismes bactériens, principalement à Gram - négatifs (Acinetobacter, Pseudomonas, Escherichia coli, Enterobacter, Proteus et Citrobacter) et 19,6% des cas avaient des infections fongiques (Candida et 23 aspergillus). Conclusions: L'âge croissant du patient, l'habitude du tabagisme et la gravité de la MPOC étaient liés à une fréquence croissante des infections bactériennes et fongiques. La détection précoce et le traitement approprié pourraient aider à prévenir la morbidité et la mortalité liées à la MPOC. Mots-clés: Maladie pulmonaire obstructive chronique, infection fongique, initiative mondiale pour la maladie pulmonaire obstructive chronique, infection bactérienne non tuberculeuse.

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.

COVID-19 infection in patients with haematological disease - A tertiary centre experience from north India.

This retrospective study was aimed to understand the clinical, laboratory, radiological parameters and the outcome of COVID-19 patients with underlying haematological disease. All patients with known haematological disease admitted with COVID-19-positive status from April to August 2020 in the COVID-19 facility of a tertiary care centre in north India, were included. Their medical records were analyzed for outcome and mortality risk factors. Fifty four patients, 37 males, were included in the study. Of these, 36 patients had haematological malignancy and 18 had benign disorder. Fever (95.5%), cough (59.2%) and dyspnoea (31.4%) were the most common symptoms. Nine patients had severe disease at diagnosis, mostly malignant disorders. Overall mortality rate was 37.0 per cent, with high mortality seen in patients with aplastic anaemia (50.0%), acute myeloid (46.7%) and lymphoblastic leukaemia (40.0%). On univariate analysis, Eastern Cooperative Oncology Group performance status >2 [odd ratio (OR) 11.6], COVID-19 severity (OR 8.2), dyspnoea (OR 5.7) and blood product transfusion (OR 6.4) were the predictors of mortality. However, the presence of moderate or severe COVID-19 (OR 16.6, confidence interval 3.8-72.8) was found significant on multivariate analysis. The results showed that patients with haematological malignancies and aplastic anaemia might be at increased risk of getting severe COVID-19 infection and mortality as compared to the general population.

Translation of liver stage activity of M5717, a Plasmodium elongation factor 2 inhibitor: from bench to bedside.

BACKGROUND: Targeting the asymptomatic liver stage of Plasmodium infection through chemoprevention could become a key intervention to reduce malaria-associated incidence and mortality. METHODS: M5717, a Plasmodium elongation factor 2 inhibitor, was assessed in vitro and in vivo with readily accessible Plasmodium berghei parasites. In an animal refinement, reduction, replacement approach, the in vitro IC99 value was used to feed a Population Pharmacokinetics modelling and simulation approach to determine meaningful effective doses for a subsequent Plasmodium sporozoite-induced volunteer infection study. RESULTS: Doses of 100 and 200 mg would provide exposures exceeding IC99 in 96 and 100% of the simulated population, respectively. CONCLUSIONS: This approach has the potential to accelerate the search for new anti-malarials, to reduce the number of healthy volunteers needed in a clinical study and decrease and refine the animal use in the preclinical phase.

Applying Modeling and Simulations for Rational Dose Selection of Novel Toll-Like Receptor 7/8 Inhibitor Enpatoran for Indications of High Medical Need.

Dual toll-like receptor (TLR) 7 and TLR8 inhibitor enpatoran is under investigation as a treatment for lupus and coronavirus disease 2019 (COVID-19) pneumonia. Population pharmacokinetic/pharmacodynamic (PopPK/PD) model-based simulations, using PK and PD (inhibition of ex vivo-stimulated interleukin-6 (IL-6) and interferon-α (IFN-α) secretion) data from a phase I study of enpatoran in healthy participants, were leveraged to inform dose selection for lupus and repurposed for accelerated development in COVID-19. A two-compartment PK model was linked to sigmoidal maximum effect (Emax ) models with proportional decrease from baseline characterizing the PD responses across the investigated single and multiple doses, up to 200 mg daily for 14 days (n = 72). Concentrations that maintain 50/60/90% inhibition (IC50/60/90 ) of cytokine secretion (IL-6/IFN-α) over 24 hours were estimated and stochastic simulations performed to assess target coverage under different dosing regimens. Simulations suggested investigating 25, 50, and 100 mg enpatoran twice daily (b.i.d.) to explore the anticipated therapeutic dose range for lupus. With 25 mg b.i.d., > 50% of subjects are expected to achieve 60% inhibition of IL-6. With 100 mg b.i.d., most subjects are expected to maintain almost complete target coverage for 24 hours (> 80% subjects IC90,IL-6  = 15.5 ng/mL; > 60% subjects IC90,IFN-α  = 22.1 ng/mL). For COVID-19, 50 and 100 mg enpatoran b.i.d. were recommended; 50 mg b.i.d. provides shorter IFN-α inhibition (median time above IC90  = 13 hours/day), which may be beneficial to avoid interference with the antiviral immune response. Utilization of PopPK/PD models initially developed for lupus enabled informed dose selection for the accelerated development of enpatoran in COVID-19.

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-informed drug development supporting the approval of the avelumab flat-dose regimen in patients with advanced renal cell carcinoma.

Avelumab is an anti-PD-L1 monoclonal antibody approved as monotherapy for Merkel cell carcinoma (MCC) and urothelial carcinoma (UC), and in combination with axitinib for advanced renal cell carcinoma (aRCC). Although initially approved with weight-based dosing (10 mg/kg intravenously [IV] every 2 weeks [Q2W]), avelumab was subsequently approved for flat dosing (800 mg IV Q2W) based on population pharmacokinetic (PopPK), exposure-efficacy, and exposure-safety modeling in MCC and UC. Here, through modeling and simulation, we provide justification for a flat-dose regimen of avelumab plus axitinib in aRCC. Simulated exposure metrics from the previous monotherapy PopPK model (1827 patients) for both weight-based and flat-dose regimens were compared with exposure metrics from treatment-naive patients with aRCC who received avelumab plus axitinib (488 patients). The aRCC population exposures were derived from a fit-for-purpose PopPK model developed using data from monotherapy and combination studies and the existing base structural PopPK model. Exposure-response relationships for safety were analyzed, including grade ≥3 treatment-emergent adverse events (TEAEs), any-grade infusion-related reactions, and TEAE any-grade immune-related adverse events (irAEs). Weight-based dosing of avelumab in the aRCC population yielded similar PK exposures to the flat-dose regimen reference exposures in the monotherapy population. Increased avelumab exposure was not associated with increased probabilities of grade ≥3 TEAEs or any-grade IRRs, although there was a weak association with an increased probability of any-grade irAEs. Overall, models in aRCC suggest that the avelumab 800-mg Q2W flat-dose regimen would provide similar benefits compared with weight-based dosing with no meaningful change in the probability of AEs.

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.

Pharmacometric modeling and machine learning analyses of prognostic and predictive factors in the JAVELIN Gastric 100 phase III trial of avelumab.

Avelumab (anti-PD-L1) is an approved anticancer treatment for several indications. The JAVELIN Gastric 100 phase III trial did not meet its primary objective of demonstrating superior overall survival (OS) with avelumab maintenance versus continued chemotherapy in patients with advanced gastric cancer/gastroesophageal junction cancer; however, the OS rate was numerically higher with avelumab at timepoints after 12 months. Machine learning (random forests, SIDEScreen, and variable-importance assessments) was used to build models to identify prognostic/predictive factors associated with long-term OS and tumor growth dynamics (TGDs). Baseline, re-baseline, and longitudinal variables were evaluated as covariates in a parametric time-to-event model for OS and Gompertzian population model for TGD. The final OS model incorporated a treatment effect on the log-logistic shape parameter but did not identify a treatment effect on OS or TGD. Variables identified as prognostic for longer OS included older age; higher gamma-glutamyl transferase (GGT) or albumin; absence of peritoneal carcinomatosis; lower neutrophil-lymphocyte ratio, lactate dehydrogenase, or C-reactive protein (CRP); response to induction chemotherapy; and Eastern Cooperative Oncology Group performance status of 0. Among baseline and time-varying covariates, the largest effects were found for GGT and CRP, respectively. Liver metastasis at re-baseline predicted higher tumor growth. Tumor size after induction chemotherapy was associated with number of metastatic sites and stable disease (vs. response). Asian region did not impact OS or TGD. Overall, an innovative workflow supporting pharmacometric modeling of OS and TGD was established. Consistent with the primary trial analysis, no treatment effect was identified. However, potential prognostic factors were identified.

Tele-Medicine Services in Hematological Practice During Covid Pandemic: Its Feasibility and Difficulties.

In COVID 19 pandemic, delivery and access of health care services have become challenging. Telemedicine services can be considered for management of patients with hematological diseases. This study included all patients who enrolled for telemedicine facility for hematology from May 15 to July 15, 2020. Patient's demographic and disease related parameters were recorded during the teleconsultation call. Overall satisfaction of attending doctor and patients were also recorded. A total of 1187 teleconsultation appointments were taken, of which 944 (79.6%) were successfully attended. Median age of patients was 38 years (range- 0.5-78 years), with 38% females. 55% of successful calls were from patients suffering a malignant hematological disorder. 24% had an active complaint pertaining to their disease or treatment. Of these, 162 (17%) were asked for a physical consultation. A significant association was found between the requirement of physical consultation and diagnosis (p < 0.001), absence of active complaint (< 0.0001) and education level of responder (p = 0.008). Patients understand that teleconsultation is helpful in preventing COVID-19 infection (71.4%) and avoids outpatient department rush (14.5%) associated with physical appointments; and around 80% patients were satisfied with the teleconsult. With the emergence of COVID 19, many localities under partial lockdown with constant fear of contacting virus amongst patients and health care providers, we can clearly see the advantages as well as feasibility of telemedicine services for our patients. The acute surge in telemedicine could be harnessed in the future to provide comprehensive and integrated care to patients of hematological disorders.

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.

Selection of the Recommended Phase 2 Dose for Bintrafusp Alfa, a Bifunctional Fusion Protein Targeting TGF-ß and PD-L1.

Bintrafusp alfa, a first-in-class bifunctional fusion protein composed of the extracellular domain of the TGF-ßRII receptor (TGF-ß "trap") fused to a human IgG1-blocking PD-L1, showed a manageable safety profile and clinical activity in phase I studies in patients with heavily pretreated advanced solid tumors. The recommended phase 2 dose (RP2D) was selected based on integration of modeling, simulations, and all available data. A 1,200-mg every 2 weeks (q2w) dose was predicted to maintain serum trough concentration (Ctrough ) that inhibits all targets of bintrafusp alfa in circulation in > 95% of patients, and a 2,400-mg every 3 weeks (q3w) dose was predicted to have similar Ctrough . A trend toward an association between exposure and efficacy variables and a relatively stronger inverse association between clearance and efficacy variables were observed. Exposure was either weakly or not correlated with probability of adverse events. The selected intravenous RP2D of bintrafusp alfa is 1,200 mg q2w or 2,400 mg q3w.

Changing Body Weight-Based Dosing to a Flat Dose for Avelumab in Metastatic Merkel Cell and Advanced Urothelial Carcinoma.

Avelumab, an anti-programmed death-ligand 1 monoclonal antibody approved for the treatment of metastatic Merkel cell carcinoma and platinum-treated urothelial carcinoma, was initially approved with a 10 mg/kg weight-based dose. We report pharmacokinetic (PK)/pharmacodynamic analyses for avelumab comparing weight-based dosing and a flat 800 mg dose, developed using data from 1,827 patients enrolled in 3 clinical trials (NCT01772004, NCT01943461, and NCT02155647). PK metrics were simulated for weight-based and flat-dosing regimens and summarized by quartiles of weight. Derived exposure metrics were used in simulations of exposure-safety (various tumors) and exposure-efficacy (objective responses; Merkel cell or urothelial carcinoma). Flat dosing was predicted to provide similar exposure to weight-based dosing, with slightly lower variability. Exposure-safety and exposure-efficacy simulations suggested similar benefit:risk profiles for the two dosing regimens. These pharmacometric analyses provided the basis for the US Food and Drug Administration approval of a flat dose of avelumab 800 mg every 2 weeks in approved indications.

Population Pharmacokinetic Analysis of Bintrafusp Alfa in Different Cancer Types.

INTRODUCTION: Bintrafusp alfa, an innovative first-in-class bifunctional fusion protein composed of the extracellular domain of the TGF-ßRII receptor (a TGF-ß "trap") fused to a human IgG1 monoclonal antibody blocking programmed death ligand 1, has shown promising antitumor activity and manageable safety. METHODS: To support the dosing strategy for bintrafusp alfa, we developed a population pharmacokinetics model using a full covariate modeling approach, based on pharmacokinetic and covariate data from 644 patients with various solid tumors who received bintrafusp alfa intravenously in two clinical studies. RESULTS: A two-compartmental linear model best described bintrafusp alfa concentrations, and no time-varying clearance was identified. Using this model, the estimated clearance was 0.0158 l/h (relative standard error, 4.1%), and the central and peripheral volume of distribution were 3.21 l (relative standard error, 3.2%) and 0.483 l (relative standard error, 9.8%), respectively. The estimated mean elimination half-life of bintrafusp alfa was 6.93 days (95% CI 4.69-9.65 days). Several intrinsic factors (bodyweight, albumin, sex, and tumor type) were found to influence bintrafusp alfa pharmacokinetics, but none of these covariate effects was considered clinically meaningful and no dosage adjustments are recommended. Notably, simulations from the model suggested less variability in exposure metrics with flat dosing versus weight-based dosing. CONCLUSIONS: Pharmacokinetic analysis of bintrafusp alfa supports the use of a flat dose regimen in further clinical trials (recommended phase 2 dose: 1200 mg every 2 weeks). TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT02517398 and NCT02699515. FUNDING: Merck Healthcare KGaA as part of an alliance between Merck Healthcare KGaA and GlaxoSmithKline.

Time-Varying Clearance and Impact of Disease State on the Pharmacokinetics of Avelumab in Merkel Cell Carcinoma and Urothelial Carcinoma.

Avelumab, a human anti-programmed death ligand 1 immunoglobulin G1 antibody, has shown efficacy and manageable safety in multiple tumors. A two-compartment population pharmacokinetic model for avelumab incorporating intrinsic and extrinsic covariates and time-varying clearance (CL) was identified based on data from 1,827 patients across three clinical studies. Of 14 tumor types, a decrease in CL over time was more notable in metastatic Merkel cell carcinoma and squamous cell carcinoma of the head and neck, which had maximum decreases of 32.1% and 24.7%, respectively. The magnitude of reduction in CL was higher in responders than in nonresponders. Significant covariate effects of baseline weight, baseline albumin, and sex were identified on both CL and central distribution volume. Significant covariate effects of black/African American race, C-reactive protein, and immunogenicity were found on CL. None of the covariate or time-dependent effects were clinically important or warranted dose adjustment.