Population Pharmacokinetics and Exposure-Response Modeling Analyses of Golimumab in Children and Young Adults with Recently Diagnosed Type 1 Diabetes (T1D)

Golimumab was recently evaluated in a Phase 2a, randomized, double-blind, placebo-controlled, multicenter study for safety and efficacy in children and young adults with newly diagnosed T1D (type 1 diabetes). Golimumab showed significant treatment effect where endogenous insulin production was preserved and clinical and metabolic parameters improved. The objective of this report was to evaluate pharmacokinetic (PK) and pharmacodynamic (PD) data from the T1GER study by developing a population pharmacokinetic (PopPK) model and performing exposure-response (ER) analyses. The PopPK model was developed using data from the T1D study and two other pediatric studies with golimumab in ulcerative colitis and in polyarticular juvenile idiopathic arthritis. A one-compartment model with first-order absorption and elimination was applied to describe the concentration-time profiles. Typical parameters normalized to the values in subjects with a standard weight of 70 kg were: apparent clearance (CL/F), 0.850 L/day; apparent volume of distribution (V/F), 16.0 L; absorption rate constant (k_a ), 1.01 day^-1 . From the ER analyses, no clear trends were observed for changes in both C-peptide AUC and HbA1c levels for the relatively narrow exposure ranges following the body surface area-based dosing regimen used in this study. In conclusion, the developed PopPK model was able to adequately describe the observed PK of golimumab in T1D patients. Although golimumab showed significant treatment effect, the ER analyses did not show clear trends within the active treatment group which may indicate that the exposure from this T1D-specific dosing regimen was at the plateau of the ER curve. This article is protected by copyright. All rights reserved.

Exposure-Response Modeling to Support Dosing Selection for Phase IIb Development of Kukoamine B in Sepsis Patients

Aim: Kukoamine B, a small molecule compound, is being developed for the treatment of sepsis in a Phase II clinical trial. The objective of this study was to optimize dosing selection for a Phase IIb clinical trial using an exposure-response model.

Methods: Data of 34 sepsis patients from a Phase IIa clinical trial were used in the model: 10 sepsis patients from the placebo group and a total of 24 sepsis patients from the 0.06 mg/kg, 0.12 mg/kg, and 0.24 mg/kg drug groups. Exposure-response relationship was constructed to model the impact of the standard care therapy and area under curve (AUC) of kukoamine B to the disease biomarker (SOFA score). The model was evaluated by goodness of fit and visual predictive check. The simulation was performed 1,000 times based on the built model.

Results: The data of the placebo and the drug groups were pooled and modeled by a nonlinear mixed-effect modeling approach in sepsis. A latent-variable approach in conjunction with an inhibitory indirect response model was used to link the standard care therapy effect and drug exposure to SOFA score. The maximum fraction of the standard care therapy was estimated to 0.792. The eliminate rate constant of the SOFA score was 0.263/day for the standard care therapy. The production rate of SOFA score (K_in) was estimated at 0.0569/day and the AUC at half the maximal drug effect (EAUC₅₀) was estimated at 1,320 h*ng/mL. Model evaluation showed that the built model could well describe the observed SOFA score. Model-based simulations showed that the SOFA score on day 7 decreased to a plateau when AUC increased to 1,500 h*ng/mL.

Conclusion: We built an exposure-response model characterizing the pharmacological effect of kukoamine B from the standard care therapy in sepsis patients. A dose regimen of 0.24 mg/kg was finally recommended for the Phase IIb clinical trial of kukoamine B based on modeling and simulation results.

Population Pharmacokinetics of Doravirine and Exposure-Response Analysis in Individuals with HIV-1

Doravirine is a novel nonnucleoside reverse transcriptase inhibitor for the treatment of human immunodeficiency virus 1 (HIV-1) infection. A population pharmacokinetic (PK) model was developed for doravirine using pooled data from densely sampled phase 1 trials and from sparsely sampled phase 2b and phase 3 trials evaluating doravirine administered orally as a single entity or as part of a fixed-dose combination of doravirine-lamivudine-tenofovir disoproxil fumarate. A one-compartment model with linear clearance from the central compartment adequately described the clinical PK of doravirine. While weight, age, and healthy versus HIV-1 status were identified as statistically significant covariates affecting doravirine PK, the magnitude of their effects was not clinically meaningful. Other intrinsic factors (gender, body mass index, race, ethnicity, and renal function) did not have statistically significant or clinically meaningful effects on doravirine PK. Individual exposure estimates for individuals in the phase 2b and 3 trials obtained from the final model were used for subsequent exposure-response analyses for virologic response (proportion of individuals achieving <50 copies/ml) and virologic failure. The exposure-response relationships between these efficacy endpoints and doravirine PK were generally flat over the range of exposures achieved for the 100 mg once-daily regimen in the phase 3 trials, with a minimal decrease in efficacy in individuals in the lowest 10th percentile of steady-state doravirine concentration at 24 h values. These findings support 100 mg once daily as the selected dose of doravirine, with no dose adjustment warranted for the studied intrinsic factors.

Individual-Specific QT Interval Correction for Drugs With Substantial Heart Rate Effect Using Holter ECGs Extracted Over a Wide Range of Heart Rates

Although fixed QT correction methods are typically used to adjust for the effect of heart rate on the QT interval in thorough QT/QTc studies, individual-specific QT correction (QTcI = QT/RR^I ) is advisable for drugs that increase the heart rate by >5 to 10 beats/minute (bpm). QTcI is traditionally derived using resting drug-free electrocardiograms (ECGs) collected at prespecified times. However, the resting heart rate range in healthy individuals is narrow, and extrapolation of inferences from these data to higher heart rates could be inappropriate. Accordingly, the QTcI derived from triplicate ECGs extracted at prespecified times (the traditional [T] method, yielding QTcIT) was compared with QTcIs obtained using ECGs with a wider heart rate range (alternative Holter [H] method, yielding QTcIH) from 24-hour Holter recordings from 40 healthy individuals selected from a central ECG laboratory database. For QTcIH, 10-second ECGs were extracted at stable heart rates in the ranges of 51-60, 61-70, 71-80, and 81-90 bpm (9 ECGs in each bin = 36 ECGs). An independent set of 40 ECGs with heart rates from 51 to 90 bpm was extracted from each individual to validate the accuracy of QTcI by the 2 methods. For the validation set, the QTcIH was a better QT correction method (slope of QTc vs heart rate closer to zero) than QTcIT. The mean difference between QTcIT and QTcIH increased from 3.1 milliseconds at 65 bpm to 10.0 milliseconds at 90 bpm (P < 0.01). The QTcIT exceeded QTcIH at heart rates > 60 bpm. Employment of the QTcIH may be more appropriate for studies involving drugs that increase heart rate.

Inhalation cancer risk assessment of hexavalent chromium based on updated mortality for Painesville chromate production workers

The exposure-response for hexavalent chromium (Cr(VI))-induced lung cancer among workers of the Painesville Ohio chromate production facility has been used internationally for quantitative risk assessment of environmental and occupational exposures to airborne Cr(VI). We updated the mortality of 714 Painesville workers (including 198 short-term workers) through December 2011, reconstructed exposures, and conducted exposure-response modeling using Poisson and Cox regressions to provide quantitative lung cancer risk estimates. The average length of follow-up was 34.4 years with 24,535 person-years at risk. Lung cancer was significantly increased for the cohort (standardized mortality ratio (SMR)=186; 95% confidence interval (CI) 145-228), for those hired before 1959, those with >30-year tenure, and those with cumulative exposure >1.41 mg/m(3)-years or highest monthly exposures >0.26 mg/m(3). Of the models assessed, the linear Cox model with unlagged cumulative exposure provided the best fit and was preferred. Smoking and age at hire were also significant predictors of lung cancer mortality. Adjusting for these variables, the occupational unit risk was 0.00166 (95% CI 0.000713-0.00349), and the environmental unit risk was 0.00832 (95% CI 0.00359-0.0174), which are 20% and 15% lower, respectively, than values developed in a previous study of this cohort.