A substantial part of critically ill patients suffer from sepsis-induced immunosuppression. Reversal of immunosuppression through PD-1 checkpoint inhibition has been proposed as a treatment strategy to overcome immunosuppression in these patients. The PD-1 inhibitor nivolumab, currently used in treatment of cancer, has been evaluated in phase I/II studies in patients with sepsis, demonstrating tolerability and signs of clinical efficacy. No proper dose finding was performed in these studies and, after a single high dose of 480 mg or 960 mg nivolumab, PD-1 inhibition persisted beyond 90 days in the majority of cases. As the duration of sepsis is ~7-10 days, prolonged PD-1 inhibition may unnecessarily induce longer-term immune-related side effects. Based on previously published pharmacokinetic and pharmacodynamic data of nivolumab, a thorough in silico dose finding study for nivolumab in critically ill patients was performed. We found that volume of distribution and clearance of nivolumab were not higher in patients with sepsis compared to the cancer population for which nivolumab is currently approved and showed profound variability. We found that with a single dose of 20 mg nivolumab, the PD-1 receptor occupancy is predicted to stay above the 90% threshold for a median of 23 days (90% prediction interval of 7-78 days). We propose to investigate this dose in critically ill patients as a potential safe and cost-effective pharmacotherapeutic intervention to treat sepsis-induced immunosuppression.

First-in-human dose predictions are primarily based on no-observed-adverse-effect levels in animal studies. Predictions from these animal models are only as effective as their ability to predict human results. To narrow the gap between human and animals, researchers have, among other things, focused on the replacement of animal cytochrome P450 (CYP) enzymes with their human counterparts (called humanization), especially in mice. Whereas research in humanized mice is extensive, the emphasis has been particularly on qualitative rather than quantitative predictions. Because the CYP3A4 enzyme is most involved in the metabolism of clinically used drugs, most benefit was expected from CYP3A4 models. There are several applications of these mouse models regarding in vivo CYP3A4 functionality, one of which might be their capacity to help improve first-in-human (FIH) dose predictions for CYP3A4-metabolized drugs. To evaluate whether human-CYP3A4-transgenic mouse models are better predictors of human exposure compared to the wild-type mouse model, we performed a meta-analysis comparing both mouse models in their ability to accurately predict human exposure of small-molecule drugs metabolized by CYP3A4. Results showed that, in general, the human-CYP3A4-transgenic mouse model had similar accuracy in the prediction of human exposure compared to the wild-type mouse model, suggesting that there is limited added value in humanization of the mouse Cyp3a enzymes if the primary aim is to acquire more accurate FIH dose predictions. Despite the results of this meta-analysis, corrections for interspecies differences through extension of human-CYP3A4-transgenic mouse models with pharmacokinetic modeling approaches seems a promising contribution to more accurate quantitative predictions of human pharmacokinetics.