In Vitro–In Vivo Correlation (IVIVC) Population Modeling for the In Silico Bioequivalence of a Long-Acting Release Formulation of Progesterone

Abstract

Health authorities carefully evaluate any change in the batch manufacturing process of a drug before and after regulatory approval. In the absence of an adequate in vitro–in vivo correlation (Level A IVIVC), an in vivo bioequivalence (BE) study is frequently required, increasing the cost and time of drug development. This study focused on developing a Level A IVIVC for progesterone vaginal rings (PVRs), a dosage form designed for the continuous delivery in vivo. The pharmacokinetics (PK) of four batches of rings charged with 125, 375, 750 and 1500 mg of progesterone and characterized by different in vitro release rates were evaluated in two clinical studies. In vivo serum concentrations and in vitro release profiles were used to develop a population IVIVC progesterone ring (P-ring) model through a direct differential-equation-based method and a nonlinear-mixed-effect approach. The in vivo release, was predicted from the in vitro profile through a nonlinear relationship. was used as the input of a compartmental PK model describing the in vivo serum concentration dynamics of progesterone. The proposed IVIVC P-ring model was able to correctly predict the in vivo concentration–time profiles of progesterone starting from the in vitro PVR release profiles. Its internal and external predictability was carefully evaluated considering the FDA acceptance criteria for IVIVC assessment of extended-release oral drugs. Obtained results justified the use of the in vitro release testing in lieu of clinical studies for the BE assessment of any new PVRs batches. Finally, the possible use of the developed population IVIVC model as a simulator of virtual BE trials was explored through a case study.

A Brief Review on Pharmaceutical Dissolution Interlinking the Aspects of Science and Regulation

“…There are five different levels of IVIVC -Level A, B, C, D, and multilevel C. Level A correlations are considered for biowaivers, where the product shows a point-to-point relationship of their invivo and in-vitro data for a minimum of three formulation batches. The correlation can be applied by using deconvolution and convolution techniques 33 .…”

In silico trial for the assessment of givinostat dose adjustment rules based on the management of key hematological parameters in polycythemia vera patients

“…Modeling and simulation has gained increasing relevance in anticancer drug development as it provides the opportunity to guide dose selection in early clinical phases, 1–3 inform clinical trial designs, 4 optimize administration protocols, anticipate clinical outcomes, 5,6 and support evidence of effectiveness and/or safety 7 . For these reasons, adopting in silico approaches to clinical trials meets pharmaceutical industry needs of a more efficient development of anticancer agents and is strongly encouraged by regulatory agencies 8–11 …”

Development and Validation of a Novel High-Performance Liquid Chromatography (HPLC)/Refractive Index Detector (RID) Method to Determine Residual Polyvinyl Alcohol (PVA) in Microspheres

“…Aripiprazole-loaded PLGA microspheres composed of PLGA, aripiprazole, mannitol, and PVA as active substances were selected as an example product. e microspheres are indicated for the treatment of schizophrenia, and its critical quality attributes include particle size, drug loading, initial burst, morphology, in vitro release features [20,21], residual organic solvent content [22,23], and residual PVA content. In this study, the residual PVA content in microspheres was successfully determined.…”