Population pharmacokinetic modeling of oral brepocitinib in healthy volunteers and patients with immuno-inflammatory diseases.

The objective of this population pharmacokinetic (PK) analysis was to characterize the concentration-time profile of brepocitinib plasma concentration after single- and multiple-oral administration in healthy volunteers (HVs) and patients with immuno-inflammatory diseases. Blood samples from phase I HV and phase II clinical studies of patients with alopecia areata, psoriasis, psoriatic arthritis, ulcerative colitis (UC), vitiligo, and hidradenitis suppurativa were analyzed using a nonlinear mixed-effects modeling approach. Effects of patients' characteristics on brepocitinib exposure were investigated. Overall, 8552 brepocitinib plasma concentrations from 775 individuals were included in the analysis. The PKs of brepocitinib were adequately described by a two-compartment model with first-order absorption and a lag time for tablet formulation, dose-dependent bioavailability, and Box-Cox transformed interindividual variabilities on apparent clearance (CL/F) and apparent central volume of distribution (Vc/F). For a typical 70-kg non-Asian female patient with baseline aspartate aminotransferase of 22 unit/liter, CL/F and Vc/F estimates were 17.5 L/h and 88.5 L, respectively. Asians had a higher exposure (independent of body weight), caused by a 10% lower CL/F when compared to other individuals. Independent of baseline body weight, the male population showed 13% higher Vc/F compared to the female population. Patients with UC were predicted to have 46% slower absorption rate compared to other individuals. The PKs of brepocitinib were well-characterized by a two-compartment model with first-order absorption and dose-dependent bioavailability. Several covariates, such as race and sex, were identified to have statistically significant, but not clinically meaningful, effects on the estimated PK parameters.

How drug onset rate and duration of action affect drug forgiveness.

Medication nonadherence is one of the largest problems in healthcare today, particularly for patients undergoing long-term pharmacotherapy. To combat nonadherence, it is often recommended to prescribe so-called "forgiving" drugs, which maintain their effect despite lapses in patient adherence. Nevertheless, drug forgiveness is difficult to quantify and compare between different drugs. In this paper, we construct and analyze a stochastic pharmacokinetic/pharmacodynamic (PK/PD) model to quantify and understand drug forgiveness. The model parameterizes a medication merely by an effective rate of onset of effect when the medication is taken (on-rate) and an effective rate of loss of effect when a dose is missed (off-rate). Patient dosing is modeled by a stochastic process that allows for correlations in missed doses. We analyze this "on/off" model and derive explicit formulas that show how treatment efficacy depends on drug parameters and patient adherence. As a case study, we compare the effects of nonadherence on the efficacy of various antihypertensive medications. Our analysis shows how different drugs can have identical efficacies under perfect adherence, but vastly different efficacies for adherence patterns typical of actual patients. We further demonstrate that complex PK/PD models can indeed be parameterized in terms of effective on-rates and off-rates. Finally, we have created an online app to allow pharmacometricians to explore the implications of our model and analysis.

Should patients skip late doses of medication? A pharmacokinetic perspective.

Missed doses, late doses, and other dosing irregularities are major barriers to effective pharmacotherapy, especially for the treatment of chronic conditions. What should a patient do if they did not take their last dose at the prescribed time? Should they take it late or skip it? In this paper, we investigate the pharmacokinetic effects of taking a late dose. We consider a single compartment model with linear absorption and elimination for a patient instructed to take doses at regular time intervals. We suppose that the patient forgets to take a dose and then realizes some time later and must decide what remedial steps to take. Using mathematical analysis, we derive several metrics which quantify the effects of taking the dose late. The metrics involve the difference between the drug concentration time courses for the case that the dose is taken late and the case that the dose is taken on time. In particular, the metrics are the integral of the absolute difference over all time, the maximum of the difference, and the maximum of the integral of the difference over any single dosing interval. We apply these general mathematical formulas to levothyroxine, atorvastatin, and immediate release and extended release formulations of lamotrigine. We further show how population variability can be immediately incorporated into these results. Finally, we use this analysis to propose general principles and strategies for dealing with dosing irregularities.