An updated overview with simple and practical approach for developing in vitro–in vivo correlation

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Abstract
Preclinical Research & Development An in vitro–in vivo correlation (IVIVC) is as a predictive mathematical model that demonstrates a key role in the development, advancement, evaluation and optimization of extended release, modified release and immediate release pharmaceutical formulations. A validated IVIVC model can serve as a surrogate for bioequivalence studies and subsequently save time, effort and expenditure during pharmaceutical product development. This review discusses about different levels of correlations, general approaches to develop an IVIVC by mathematical modelling, validation, data analysis and various applications. In the current setting, the dearth of success associated with IVIVC is due to complexity of underlying scientific principles as well as the practice of fitting/matching in vivo plasma level‐time data with in vitro dissolution profile. Hence, a simple, straightforward practical means to predict plasma drug levels by convolution technique and percentage drug absorbed computed from in vitro dissolution profile based on deconvolution method are illustrated. The bioavailability/bioequivalence assessment and evaluation are frequently validated by the pharmacokinetic parameters such as maximum concentration, time to reach maximum concentration, and area under the curve. The implementation of a quality by design manufacturing based on in vivo bioavailability and clinically relevant dissolution specification are recommended because corresponding design safe space will guarantee that all batches from relevant products are met with sufficient quality and bioperformance. Recently, United States Food and Drug Administration and European Medicines Agency have proposed that in silico/physiologically based pharmacokinetic modelling can be used in decision making during preclinical experiments as well as to recognize the dissolution profiles that can forecast and ensure the desired clinical performance.

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