Malidi Ahamadi

Systematic evaluation of pembrolizumab dosing in patients with advanced non-small-cell lung cancer

BACKGROUND In the phase I KEYNOTE-001 study, pembrolizumab demonstrated durable antitumor activity in patients with advanced non-small-cell lung cancer (NSCLC). We sought to characterize the relationship between pembrolizumab dose, exposure, and response to define an effective dose for these patients. PATIENTS AND METHODS Patients received pembrolizumab 2 mg/kg every 3 weeks (Q3W) (n = 55), 10 mg/kg Q3W (n = 238), or 10 mg/kg Q2W (n = 156). Response (RECIST v1.1) was assessed every 9 weeks. The relationship between the estimated pembrolizumab area under the concentration-time curve at steady state over 6 weeks (AUCss-6weeks) and the longitudinal change in tumor size (sum of longest diameters) was analyzed by regression and non-linear mixed effects modeling. This model was simultaneously fit to all tumor size data, then used to simulate response rates, normalizing the trial data across dose for prognostic covariates (tumor PD-L1 expression and EGFR mutation status). The exposure-safety relationship was assessed by logistic regression of pembrolizumab AUCss-6weeks versus occurrence of adverse events (AEs) of interest based on their immune etiology. RESULTS Overall response rates were 15% [95% confidence interval (CI) 7%-28%] at 2 mg/kg Q3W, 25% (18%-33%) at 10 mg/kg Q3W, and 21% (95% CI 14%-30%) at 10 mg/kg Q2W. Regression analyses of percentage change from baseline in tumor size versus AUCss-6weeks indicated a flat relationship (regression slope P > 0.05). Simulations showed the exposure-response relationship to be similarly flat, thus indicating that the lowest evaluated dose of 2 mg/kg Q3W to likely be at or near the efficacy plateau. Exposure-safety analysis showed the AE incidence to be similar among the clinically tested doses. CONCLUSIONS No significant exposure dependency on efficacy or safety was identified for pembrolizumab across doses of 2-10 mg/kg. These results support the use of a 2 mg/kg Q3W dosage in patients with previously treated, advanced NSCLC. CLINICALTRIALSGOV REGISTRY NCT01295827.

Model‐Based Characterization of the Pharmacokinetics of Pembrolizumab: A Humanized Anti–PD‐1 Monoclonal Antibody in Advanced Solid Tumors

Pembrolizumab, a potent antibody against programmed death 1 (PD‐1) receptor, has shown robust antitumor activity and manageable safety in patients with advanced solid tumors. Its pharmacokinetic (PK) properties were analyzed with population PK modeling using pooled data from the KEYNOTE‐001, −002, and −006 studies of patients with advanced melanoma, non‐small cell lung cancer (NSCLC), and other solid tumor types. Pembrolizumab clearance was low and the volume of distribution small, as is typical for therapeutic antibodies. Identified effects of sex, baseline Eastern Cooperative Oncology Group performance status, measures of renal and hepatic function, tumor type and burden, and prior ipilimumab treatment on pembrolizumab exposure were modest and lacked clinical significance. Furthermore, simulations demonstrated the model has robust power to detect clinically relevant covariate effects on clearance. These results support the use of the approved pembrolizumab dose of 2 mg/kg every 3 weeks without dose adjustment in a variety of patient subpopulations.

Pembrolizumab: Role of Modeling and Simulation in Bringing a Novel Immunotherapy to Patients With Melanoma

Recently, immunotherapy has yielded promising results in several cancer types. Contrary to the established classical chemotherapy‐dosing paradigm, a maximum tolerated dose approach does not always produce better clinical outcomes for novel targeted therapies, as their efficacy is frequently robust at pharmacologically active doses below the maximum tolerated dose. Integrated safety and efficacy assessments are needed to inform clinical dose and trial design, and to support an early identification of potentially safe and efficacious combination treatments.

Population Pharmacokinetic/Pharmacodynamic Modeling of Tumor Size Dynamics in Pembrolizumab-Treated Advanced Melanoma

Pembrolizumab is a potent immune‐modulating antibody active in advanced melanoma, as demonstrated in the KEYNOTE‐001, ‐002, and ‐006 studies. Longitudinal tumor size modeling was pursued to quantify exposure‐response relationships for efficacy. A mixture model was first developed based on an initial dataset from KEYNOTE‐001 to describe four patterns of tumor growth and shrinkage. For subsequent analyses, tumor size measurements were adequately described by a single consolidated model structure that captured continuous tumor size with a combination of growth and regression terms, as well as a fraction of tumor responsive to therapy. This revised model structure provided a framework to efficiently evaluate the impact of covariates and pembrolizumab exposure. Both models indicated that exposure to the drug was not a significant predictor of tumor size response, demonstrating that the dose range evaluated (2 and 10 mg/kg every 3 weeks) is likely near or at the plateau of maximal response.

Methods and strategies for assessing uncontrolled drug–drug interactions in population pharmacokinetic analyses: results from the International Society of Pharmacometrics (ISOP) Working Group

The purpose of this work was to present a consolidated set of guidelines for the analysis of uncontrolled concomitant medications (ConMed) as a covariate and potential perpetrator in population pharmacokinetic (PopPK) analyses. This white paper is the result of an industry-academia-regulatory collaboration. It is the recommendation of the working group that greater focus be given to the analysis of uncontrolled ConMeds as part of a PopPK analysis of Phase 2/3 data to ensure that the resulting outcome in the PopPK analysis can be viewed as reliable. Other recommendations include: (1) collection of start and stop date and clock time, as well as dose and frequency, in Case Report Forms regarding ConMed administration schedule; (2) prespecification of goals and the methods of analysis, (3) consideration of alternate models, other than the binary covariate model, that might more fully characterize the interaction between perpetrator and victim drug, (4) analysts should consider whether the sample size, not the percent of subjects taking a ConMed, is sufficient to detect a ConMed effect if one is present and to consider the correlation with other covariates when the analysis is conducted, (5) grouping of ConMeds should be based on mechanism (e.g., PGP-inhibitor) and not drug class (e.g., beta-blocker), and (6) when reporting the results in a publication, all details related to the ConMed analysis should be presented allowing the reader to understand the methods and be able to appropriately interpret the results.

Abstract CT112: Exposure-response analysis of pembrolizumab in patients with advanced melanoma and non-small cell lung cancer enrolled in KEYNOTE-001, -002, and -006

Background: The anti-PD-1 monoclonal antibody pembrolizumab has demonstrated durable antitumor activity against several advanced malignancies and is generally well tolerated. In the KEYNOTE-001, -002, and -006 trials, patients with advanced/metastatic melanoma and non-small cell lung cancer (NSCLC) were given pembrolizumab doses ranging from 2 mg/kg Q3W to 10 mg/kg Q2W. The objective of this current analysis was to explore the relationship between exposure to pembrolizumab and safety/efficacy in patients with advanced melanoma or NSCLC to help select an appropriate therapeutic dose. Methods: Exposure-response analyses (using graphical exploration and nonlinear mixed effects modeling) of tumor size data were used to characterize the relationship between pembrolizumab exposure and tumor size reduction. Data for these analyses were derived from 1366 patients with melanoma and 496 with NSCLC; exposure-response analyses were performed separately for each indication. Tumor size, defined as the sum of longest dimensions (SLD) of target lesions, was the response readout and individual steady-state area under the curve (AUC) estimates from a population PK model were used as an integrated exposure measure across all concentration data for each patient. Additionally, exposure-adverse event (AE) logistic regression was performed on the integrated dataset, focusing on AEs of special interest (AEOSIs), defined as a broad category of potentially immune-related AEs. Results: The graphical analysis for both melanoma (stratified by IPI pretreatment status) and NSCLC (stratified by PD-L1 expression status) identified an almost flat relationship between exposure and change in tumor size from baseline at 24 wk (melanoma) or 18 wk (NSCLC), with substantial overlap in confidence intervals. In agreement with the exploratory graphical analyses, individual pembrolizumab exposures showed a small and statistically insignificant influence on the final model estimated tumor decay parameter for both melanoma (slope = 0.131, P = 0.20 for IPI-naive; and slope = 0.1, P = 0.25 for IPI-experienced), and NSCLC (slope = 0.196, P = 0.54) patients. Clinical trial simulations, using the tumor size model to normalize for covariates, predicted little variation and considerable overlap in the confidence intervals for response across the dose regimens studied for both populations, confirming lack of clinically meaningful differences between 2 mg/kg and 10 mg/kg. The exposure-AEOSI analysis did not identify exposure to pembrolizumab as a significant predictor of the occurrence of AEOSIs. Conclusions: The exposure range associated with 2 mg/kg Q3W dose provides near maximal efficacy with acceptable tolerability, and thus there is no clear benefit to higher dosing. The findings of this analysis support a common regimen of 2 mg/kg Q3W for pembrolizumab in melanoma and NSCLC. Citation Format: Manash S. Chatterjee, David C. Turner, Malidi Ahamadi, Rik de Greef, Tomoko Freshwater, Kapil Mayawala, David Dong, Julie Stone, Dinesh de Alwis, Anna Kondic. Exposure-response analysis of pembrolizumab in patients with advanced melanoma and non-small cell lung cancer enrolled in KEYNOTE-001, -002, and -006. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr CT112.