In vivo Relevant Drug Product Evaluation by Using the Biphasic Dissolution Assay (BiPHa+)

Abstract

An increasing number of new chemical entities struggled with a very poor solubility in aqueous media. Solubility or the ability to dissolve in intestinal media is obligatory for oral bioavailability. Dealing with this challenge, advanced formulation technologies (e.g. amorphous solid dispersion) were developed. Followed by this formulation approaches, new <em>in vitro</em> characterisation methods became obligatory to sufficiently characterize the potential <em>in vivo</em> performance (e.g. biorelevant dissolution assay) guiding formulation development. There are already numerous improved <em>in vitro</em> test systems, which either offer only limited predictive power with regard to the <em>in vivo</em> performance of drug formulations or are more complex and error-prone to perform.<br /> The aim of the present study was a development of an efficiently to perform biphasic dissolution assay (BiPHa+) having a high predictive power. The assay was intended to characterize bioavailability enhancing formulations with regard to their <em>in vivo</em> performance in a meaningful manner, and enable a deeper mechanistic understanding of drug dissolution. In combination with the modelling approaches developed in this work, the biphasic dissolution data were intended to improve the prediction of the <em>in vivo</em> performance of drug formulations.<br /> The BiPHa+ assay was successfully validated by human <em>in vivo</em> data, exhibited a remarkable power in terms of predicting the extent of passive drug absorption <em>in vivo</em> and was also applicable for dog <em>in vivo</em> trials. The presented prediction workflows represented a valuable tool in the formulation development process to assess the dissolution behaviour towards the probable <em>in vivo</em> pharmacokinetic. Furthermore, the study results demonstrated the BiPHa+ assay as a powerful screening tool for different types of enabling formulation approaches, which could guide formulation development, increase mechanistic understanding and is potentially able to decrease the number of animal experiment during early stages of drug product development.