(M1030-02-11) Demonstration of Virtual Bioequivalence (VBE) Between Progesterone Vaginal Rings Using Mechanistic Vaginal Absorption and Metabolism Model (MechVAM) Within Simcyp Simulator

Purpose: Further innovation in women’s health is desperately needed and there is a critical demand for swifter progress in clinical development to address the disease burden. Utilization of mechanistic modeling-based approaches may accelerate the development of novel vaginally administered therapeutics or reformulation of existing ones to improve dosing convenience or tolerability. These models may be useful to understand the product application time required to achieve expected local or systemic exposure, clinical trial design, and evaluation of potential drug candidates. Due to lack of standardized in vitro release methodologies for vaginal products, the direct input of in vitro release profiles of vaginal rings does not mechanistically translate into the in vivo predictions, necessitating the development of an in vitro-in vivo relationship (IVIVR) which can be leveraged as a model input. The current objective was twofold: 1) Develop and validate an IVIVR for a progesterone vaginal ring to be used to predict the in vivo release from the measured in vitro release profiles 2) Virtually evaluate the bioequivalence (BE) of the progesterone vaginal ring using a previously validated PBPK model for progesterone vaginal absorption (MechVAM model) and systemic pharmacokinetic (PK) data from three different clinical trials.

Methods: The validated Mechanistic Vaginal Absorption & Metabolism (MechVAM) model of progesterone within Simcyp Simulator (V23) (Certara UK, Sheffield, UK) was used to deconvolute the progesterone plasma profiles of one clinical plasma profile data set by estimating the in vivo release profile using the parameter estimation (PE) tool. The IVIVR between cumulative % in vitro release and the estimated % in vivo release could be described and fitted using a Weibull function. The IVIVR was validated by comparing predicted plasma profiles with the results of two other clinical trials using derived % in vivo release from the IVIVR and in vitro release profiles. The in vitro release profiles were derived from different batches used in the respective clinical trials. BE testing was performed under various study designs using the VBE module available within the Simcyp Simulator. PK data from three different clinical trials was used, at each time assuming one as the reference and the other as the test formulation. The evaluation was based on comparison of the plasma progesterone PK parameters, including maximum plasma concentration (C_max) and area under the concentration versus time curve (AUC), for the test and reference formulations.

Results: Figure 1 shows the stepwise methodology for the development of the IVIVR using the observed data from clinical trial 1. The IVIVR equation was utilized to calculate the % in vivo release profiles of clinical trial 2 and 3 from the respective in vitro release profiles. Using the former profiles as input in the MechVAM model, the IVIVR was validated as demonstrated by the close matching of predicted progesterone plasma profiles and observed data of the respective trial (Figure 2). After simulating ten clinical BE trials for each test/reference pair, the geometric mean ratio of the primary PK parameters between the test and reference were well within the 80 to 125% BE limits (Figure 3).

Conclusion: The MechVAM model predictions of plasma progesterone concentration versus time profiles, using the developed and validated IVIVR as an input function, were in good agreement with the reported clinical data of three different batches of a vaginal ring formulation of progesterone. Furthermore, the Simcyp VBE module was successfully utilized to explore model capabilities in terms of simulating different BE study designs and assessing bioequivalence. PBPK modelling can guide the development of vaginal drug products and support alternative BE approaches. The results of these simulations and the influence on the BE outcomes will be used to determine clinically relevant dissolution specifications and to create an in vitro dissolution rate safe space for the studied progesterone vaginal ring.


Figure 1: Stepwise methodology for the development of an IVIVR using the Weibull function by inputting the in vitro release profile and the deconvoluted in vivo release profile of clinical trial 1.


Figure 2: Predicted versus observed progesterone plasma concentrations of clinical trial 2 (A) and clinical trial 3 (B). The MechVAM model was used for the prediction with the in vivo release profile generated by the developed IVIVR as an input function.
Yellow circles - observed mean data, solid green line - prediction mean, solid grey lines - 95th and 5th percentiles of the prediction.


Figure 3: Comparing BE of three clinical trials using parallel study designs. The different plots show Cmax and AUCinf geometric mean ratios of trial 1 versus trial 2 (A, B), trial 2 versus trial 3 (C, D), and trial 1 versus trial 3 (E, F).