In Vitro/In Vivo Correlation (IVIVC): Definition, Approaches, and Levels

Definition

“A predictive mathematical treatment describing the relationship between an in vitro property of a dosage form (e.g., the rate or extent of drug release) and a relevant in vivo response (e.g., plasma concentration-time data)”

Reference: FDA Guidance for Industry Extended Release Solid Oral Dosage Forms: Development, Evaluation, and Application of In Vitro/In Vivo Correlations (1997).

In other words, IVIVC is used to correlate and predict key pharmacokinetic parameters like Cmax and AUC based on in vitro dissolution data.

Why to use IVIVC

Finding predictive dissolution tests and valid IVIVCs are essential activities in generic industry, three major uses can be highlighted: as a surrogate for human bioequivalence studies, to support and validate the use of dissolution methods and specifications, and to improve drug development efficiency. IVIVCs can be developed by two different strategies: a one-step approach or a two-step approach.

IVIVC approaches

The one-step approach allows predicted plasma profiles to be obtained directly from a combination of in vitro data and experimental in vivo plasma concentrations by mathematical modeling with differential equations. By its side, in the two-step approach, experimental plasma profiles must be, firstly, transformed to fractions absorbed by deconvolution, and the IVIVC is obtained by relating in vitro fractions dissolved with in vivo fractions absorbed; then, for being returned to plasma concentrations, predicted fractions absorbed are reconverted by convolution.

Conventional deconvolution methods

Conventional IVIVC relies on three deconvolution methods: Wagner-Nelson, Loo-Riegelman, and numerical methods. ?These methods use several important assumptions. The first two approaches deconvolute the systemic input rate which is a composite function: dissolution + gastrointestinal (GI) transit + GI permeation + first pass metabolism. These two methods are also restricted to being applied to drugs that undergo linear elimination. Also, the Wagner-Nelson method treats the body as a single compartment. Thus, this method is not appropriate for drugs that follow multi-ple compartment characteristics. Likewise, it does not assume that the ab-sorption follows zero- or first-order kinetics. Finally, it has the advantage of being able to calculate the fraction of drug absorbed over time without requiring IV plasma drug concentration-time data. By contrast, the Loo-Riegelman Method takes a compartmental modeling ap-proach. This method requires concentration-time data from both extravascular and intravenous administration of the drug to the same subject.

When to use mechanistic IVIVC

All of these conventional methods sometimes are not sufficient for IVIVC models where no complex ADME processes are involved. Sometimes, you may want to separately estimate the different processes that are involved in drug systemic absorption (dissolution, GI transit time, permeation, gut wall metabolism, and first pass metabolism). In this case, you’ll want to use a mechanistic IVIVC approach. This approach can separate?in vivo?dissolution from systemic input to be correlated against?in vitro?dissolution and provide a better IVIVC.

Levels of IVIVC

The categorization of IVIVC can be broadly classified into three levels - Level A, Level B, and Level C. In addition to these levels, there is a subcategory known as Multiple Level C correlation. Level A is the most commonly used category for demonstrating the correlation between in vitro dissolution and in vivo input rates. Level C correlation can be useful during the early stages of development and is the second most common. Level B and Multiple Level C correlations are relatively uncommon.

Level A correlation is generally linear and involves a point-to-point relationship between in vitro dissolution rate and in vivo input rate. Nonlinear correlations may also be considered if they are deemed appropriate. The FDA recommends the use of Level A for demonstrating IVIVC relationships for two or more formulations with different release rates. The use of multiple formulations is also suggested in order to predict the entire in vivo time course from the in vitro data.

Level B correlation uses the same data as Level A but is based on the principles of statistical moment analysis. The mean in vitro dissolution time of the drug is compared to either the mean in vivo residence time or the mean in vivo dissolution time. This category is less useful for regulatory purposes as it does not reflect the actual in vivo plasma level curves.

Level C correlation involves determining the relationship between in vivo pharmacokinetic (PK) parameters and in vitro dissolution data at a single point. This category is not sufficient for obtaining a bioequivalence waiver and cannot predict the complete shape of the plasma concentration time curve, which is a critical factor in determining the performance of extended release products. Level C can only predict Cmax and AUC, which can help establish bioavailability and bioequivalence.

When IVIVC is possible ?