Model-Based Bioequivalence Analysis to Assess and Predict the Relative Bioavailability of Valproic Acid Formulations.

BACKGROUND AND OBJECTIVE: Model-based bioequivalence (MBBE) encompasses the use of nonlinear mixed effect models supporting the estimation of pharmacokinetic endpoints to assess the relative bioavailability between multi-source drug products. This application emerges as a valuable alternative to the standard non-compartmental analysis (NCA) in bioequivalence (BE) studies in which dense sampling is not possible. In this work, we aimed to assess the application of MBBE compared to traditional methods in evaluating the relative bioavailability of two formulations with different drug release properties. Additionally, we sought to predict the performance of a modified-release formulation in a multiple-dose scenario, leveraging data from a single-dose study. METHODS: MBBE analysis was implemented to estimate the BE endpoints (90% CI for the Test/Reference geometric mean ratio, T/R GMR) in area under the concentration-time curve (AUC) and maximum concentration (Cmax) using data from a single-dose, 2-period, 2-sequence BE study performed in 14 healthy subjects between a locally developed valproic acid extended-release formulation (Test) and the brand-name delayed-release formulation (Reference). RESULTS: Results were compared with the standard approach, revealing that MBBE analysis achieved higher discrimination between formulations for Cmax, addressing limitations of the experimental sampling design and highlighting an advantage for this model-based analysis even when rich data are available. Additionally, the bioequivalence outcome under the multiple-dose scenario was predicted through a simulation-based study for both total and unbound valproic acid concentrations, considering the impact of valproic acid saturable binding on BE conclusions. CONCLUSIONS: The MBBE analysis was superior to the NCA approach in detecting product-related differences, overcoming limitations in the study experimental design. Predictions for the multiple-dose scenario preclude that the extended-release properties of the Test formulation would persist at steady state, resulting in lower peak-to-trough fluctuation and bioequivalent performance in terms of the extent of drug absorption. Overall, these results should discourage unnecessary experimentation in healthy subjects.

Quantitative systems pharmacology Model to characterize valproic acid-induced hyperammonemia and the effect of L-carnitine supplementation.

Valproic acid (VPA) is a short-chain fatty acid widely prescribed in the treatment of seizure disorders and epilepsy syndromes, although its therapeutic value may be undermined by its toxicity. VPA serious adverse effects are reported to have a significant and dose-dependent incidence, many associated with VPA-induced hyperammonemia. This effect has been linked with reduced levels of carnitine; an endogenous compound involved in fatty acid's mitochondrial ß-oxidation by facilitation of its entrance via the carnitine shuttle. High exposure to VPA can lead to carnitine depletion causing a misbalance between the intra-mitochondrial ß-oxidation and the microsomal ω-oxidation, a pathway that produces toxic metabolites such as 4-en-VPA which inhibits ammonia elimination. Moreover, a reduction in carnitine levels might be also related to VPA-induced obesity and lipids disorder. In turn, L-carnitine supplementation (CS) has been recommended and empirically used to reduce VPA's hepatotoxicity. The aim of this work was to develop a Quantitative Systems Pharmacology (QSP) model to characterize VPA-induced hyperammonemia and evaluate the benefits of CS in preventing hyperammonemia under both chronic treatment and after VPA overdosing. The QSP model included a VPA population pharmacokinetics model that allowed the prediction of total and unbound concentrations after single and multiple oral doses considering its saturable binding to plasma proteins. Predictions of time courses for 2-en-VPA, 4-en-DPA, VPA-glucuronide, carnitine, ammonia and urea levels, and for the relative change in fatty acids, Acetyl-CoA, and glutamate reflected the VPA induced changes and the efficacy of the treatment with L-carnitine. The QSP model was implemented to give a rational basis for the L-carnitine dose selection to optimize CS depending on VPA dosage regime and to assess the currently recommended L-carnitine rescue therapy after VPA overdosing. Results show that a L-carnitine dose equal to the double of the VPA dose using the same interdose interval would maintain the ammonia levels at baseline. The QSP model may be expanded in the future to describe other adverse events linked to VPA-induced changes in endogenous compounds.

Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products.

Bioequivalence implementation in developing countries where a high proportion of similar drug products are being marketed has found several obstacles, impeding regulatory agencies to move forward with this policy. Biopharmaceutical quality of these products, several of which are massively prescribed, remains unknown. In this context, an in vitro-in silico-in vivo approach is proposed as a mean to screen product performance and target specific formulations for bioequivalence assessment. By coupling in vitro biorelevant dissolution testing in USP-4 Apparatus (flow-through cell) with physiologically-based pharmacokinetic (PBPK) modeling in PK-Sim® software (Bayer, Germany), the performance of seven similar products of carvedilol tablets containing 25 mg available in the Uruguayan market were compared with the brand-name drug Dilatrend®. In silico simulations for Dilatrend® were compared with published results of bioequivalence studies performed in fasting conditions allowing model development through a learning and confirming process. Single-dose pharmacokinetic profiles were then simulated for the brand-name drug and two similar drug products selected according to in vitro observations, in a virtual Caucasian population of 1000 subjects (50% male, aged between 18 and 50 years with standard body-weights). Population bioequivalence ratios were estimated revealing that in vitro differences in drug release would have a major impact in carvedilol maximum plasma concentration, leading to a non-bioequivalence outcome. Predictions support the need to perform in vivo bioequivalence for these products of extensive use. Application of the in vitro-in silico-in vivo approach stands as an interesting alternative to tackle and reduce drug product variability in biopharmaceutical quality.