Nivolumab is a fully human monoclonal antibody that inhibits programmed death‐1 activation. The clinical pharmacology profile of nivolumab was analyzed by a population pharmacokinetics model that assessed covariate effects on nivolumab concentrations in 1,895 patients who received 0.3–10.0 mg/kg nivolumab in 11 clinical trials. Nivolumab pharmacokinetics is linear with a time‐varying clearance. A full covariate model was developed to assess covariate effects on pharmacokinetic parameters. Nivolumab clearance and volume of distribution increase with body weight. The final model included the effects of baseline performance status (PS), baseline body weight, and baseline estimated glomerular filtration rate (eGFR), sex, and race on clearance, and effects of baseline body weight and sex on volume of distribution in the central compartment. Sex, PS, baseline eGFR, age, race, baseline lactate dehydrogenase, mild hepatic impairment, tumor type, tumor burden, and programmed death ligand‐1 expression had a significant but not clinically relevant (<20%) effect on nivolumab clearance.

Comprehensive uncertainty analyses of complex models of environmental and biological systems are essential but often not feasible due to the computational resources they require. "Traditional" methods, such as standard Monte Carlo and Latin Hypercube Sampling, for propagating uncertainty and developing probability densities of model outputs, may in fact require performing a prohibitive number of model simulations. An alternative is offered, for a wide range of problems, by the computationally efficient "Stochastic Response Surface Methods (SRSMs)" for uncertainty propagation. These methods extend the classical response surface methodology to systems with stochastic inputs and outputs. This is accomplished by approximating both inputs and outputs of the uncertain system through stochastic series of "well behaved" standard random variables; the series expansions of the outputs contain unknown coefficients which are calculated by a method that uses the results of a limited number of model simulations. Two case studies are presented here involving (a) a physiologically-based pharmacokinetic (PBPK) model for perchloroethylene (PERC) for humans, and (b) an atmospheric photochemical model, the Reactive Plume Model (RPM-IV). The results obtained agree closely with those of traditional Monte Carlo and Latin Hypercube Sampling methods, while significantly reducing the required number of model simulations.

Inadequate selection of the dose to bring forward in confirmatory trials has been identified as one of the key drivers of the decreasing success rates observed in drug development programs across the pharmaceutical industry. In recognition of this problem, the Pharmaceutical Research and Manufacturers of America (PhRMA), formed a working group to evaluate and develop alternative approaches to dose finding, including adaptive dose-ranging designs. This paper summarizes the work of the group, including the results and conclusions of a comprehensive simulation study, and puts forward recommendations on how to improve dose ranging in clinical development, including, but not limited to, the use of adaptive dose-ranging methods.

BackgroundNivolumab 3 mg/kg every 2 weeks (Q2W) has shown benefit versus the standard of care in melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). However, flat dosing is expected to shorten preparation time and improve ease of administration. With knowledge of nivolumab safety, efficacy, and pharmacokinetics across a wide dose range in body weight (BW) dosing, assessment of the benefit–risk profile of a 240-mg flat dose relative to the approved 3-mg/kg dose was approached by quantitative clinical pharmacology.Patients and methodsA flat dose of 240 mg was selected based on its equivalence to the 3-mg/kg dose at the median BW of ∼80 kg in patients in the nivolumab program. The benefit–risk profile of nivolumab 240 mg was evaluated by comparing exposures at 3 mg/kg Q2W and 240 mg Q2W across BW and tumor types; clinical safety at 3 mg/kg Q2W by BW and exposure quartiles in melanoma, NSCLC, and RCC; and safety and efficacy at 240 mg Q2W relative to 3 mg/kg Q2W in melanoma, NSCLC, and RCC.ResultsThe median nivolumab exposure and its distribution at 240 mg Q2W were similar to 3 mg/kg Q2W in the simulated population. Safety analyses did not demonstrate a clinically meaningful relationship between BW or nivolumab exposure quartiles and frequency or severity of adverse events. The predicted safety and efficacy were similar across nivolumab exposure ranges achieved with 3 mg/kg Q2W or 240 mg Q2W flat dose.ConclusionBased on population pharmacokinetic modeling, established flat exposure–response relationships for efficacy and safety, and clinical safety, the benefit–risk profile of nivolumab 240 mg Q2W was comparable to 3 mg/kg Q2W. The quantitative clinical pharmacology approach provided evidence for regulatory decision-making on dose modification, obviating the need for an independent clinical study.