Utilization of Physiologically Based Pharmacokinetic Modeling in Clinical Pharmacology and Therapeutics: an Overview.

The purpose of this review was to assess the advancement of applications for physiologically based pharmacokinetic (PBPK) modeling in various therapeutic areas. We conducted a PubMed search, and 166 articles published between 2012 and 2018 on FDA-approved drug products were selected for further review. Qualifying publications were summarized according to therapeutic area, medication(s) studied, pharmacokinetic model type utilized, simulator program used, and the applications of that modeling. The results showed a 13-fold increase in the number of papers published from 2012 to 2018, with the largest proportion of articles dedicated to the areas of infectious diseases, oncology, and neurology, and application extensions including prediction of drug-drug interactions due to metabolism and/or transporter-mediated effects and understanding drug kinetics in special populations. In addition, we profiled several high-impact studies whose results were used to guide package insert information and formulate dose recommendations. These results show that while utilization of PBPK modeling has drastically increased over the past several years, regulatory support, lack of easy-to-use systems for clinicians, and challenges with model validation remain major challenges for the widespread adoption of this practice in institutional and ambulatory settings. However, PBPK modeling will continue to be a useful tool in the future to assess therapeutic drug monitoring and the growing field of personalized medicine.

A Physiologically Based Pharmacokinetic Model for Optimally Profiling Lamotrigine Disposition and Drug-Drug Interactions.

BACKGROUND AND OBJECTIVES: Lamotrigine (Lamictal®) is a broad-spectrum antiepileptic drug available in both immediate-(IR) and extended-release (XR) formulations. Here, we present a new physiologically based pharmacokinetic (PBPK) model for IR and XR formulations of lamotrigine to predict disposition in adults and children, plus drug-drug interactions (DDIs). METHODS: Models for lamotrigine IR and XR formulations were constructed using a Simcyp® Simulator. Concentration-time profiles were simulated for lamotrigine IR single (SD) and steady-state (SS) doses ranging from 25 to 200 mg in adults, as well as 2 mg/kg (SD), and 7.7-9.4 mg/kg (SS) in children aged between 4 and 17 years. Lamotrigine XR profiles were simulated for SD and SS doses ranging from 250 to 400 mg. DDI prediction with lamotrigine was simulated in adults with enzyme-inducing drugs, rifampin (rifampicin) and ritonavir, as well as the enzyme inhibitor, valproic acid. RESULTS: The lamotrigine model predicted adult area-under-the-curve (AUC) and peak plasma concentration (Cmax) results for IR SD within 35% of observed data; lamotrigine IR SS dosing was within 10% and 30% of observed data, respectively. Pediatric lamotrigine IR SD AUC and Cmax values were within 10% and 15% of observed data, respectively. AUC and Cmax values for lamotrigine XR SD simulated in adults were within 20% of observed data; similarly lamotrigine XR SS parameters were within 10%. Concerning DDI simulation in adults, predicted-to-observed lamotrigine AUC ratios [AUCDDI/AUCalone] were within 15% for ritonavir and rifampin, and 20% for valproic acid. CONCLUSIONS: Our developed PBPK lamotrigine profile accurately predicts DDIs and lamotrigine IR/XR formulation disposition in adults and children. This PBPK model will be helpful in designing future DDI studies for co-administration of lamotrigine with other drugs and in designing individualized patient dosing regimens.

Physiologically based pharmacokinetic modeling of disposition and drug-drug interactions for valproic acid and divalproex.

Valproic acid (VPA) is an older first-line antiepileptic drug with a complex pharmacokinetic (PK) profile, currently under investigation for several novel neurologic and non-neurologic indications. Our study objective was to design and validate a mechanistic model of VPA disposition in adults and children; and evaluate its predictive performance of drug-drug interactions (DDIs). This study expands upon existing physiologically based pharmacokinetic (PBPK) models for VPA by incorporating UGT enzyme kinetics and an advanced dissolution, absorption, and metabolism (ADAM) model for extended-release (ER) formulation. PBPK models for VPA IR and ER formulations were constructed using Simcyp Simulator (Version 15). First-order absorption was used for the immediate-release (IR) formulation and the ADAM model, including a controlled-release profile, for ER. Data from twenty-one published clinical studies were used to assess model performance. The model accurately predicted the concentration-time profiles of IR formulation for single-dose and steady-state doses ranging from 200mg to 1000mg. Similarly profiles were also simulated for ER formulation after a single-dose and steady-state doses of 500mg and 1000mg, respectively. In addition, simulated PK profiles agreed well with the observed data from studies in which VPA ER formulation was given to pediatric patients and VPA IR formulation to adult patients with cirrhosis. The model was further validated with individual adult data from a Phase I clinical trial consisting of eight cohorts after IV infusion of VPA with doses ranging from 15 to 150mg/kg. Co-administrations of VPA as an enzyme-inhibitor with victim drug phenytoin or lorazepam, as well as a substrate with enzyme inducer carbamazepine or phenobarbital, were simulated with the model to evaluate drug-drug interaction. The simulated serum concentration-time profiles were within the 5th and 95th percentiles, and the majority of the predicted area-under-the-curve (AUC) and peak plasma concentration (Cmax) values were within 25% of the reported average values. The comprehensive VPA PBPK model defined by this study may be used to support dosage regimen optimization to improve the safety and efficacy profile of this agent under different scenarios.