Abstract
The selection of the best drug candidates is based on multiparametric choices combining the potential efficacy, ADME characteristics and the safety profile of the new chemical entities. In this sense, the early prediction of pharmacokinetic is essential to guide decision-making and provide a relevant course for projects. Because of its central role in drug disposition, metabolic clearance mediated primarily by the liver is one of the most important parameters. The objective of this project was to improve clearance prediction by focusing on low clearance compounds that are still difficult to study. This work allowed us to expand our knowledge on in vitro liver models and usual extrapolation methods but also to discover and develop new prediction strategies. We focused on metabolic clearance and all parameters that impact the predictions. Micropatterned co-cultures (MPCCs) of primary human hepatocytes (HepatopacTM), which stabilizes hepatocytes over several weeks, has been identified as a judicious alternative to routine models when the molecules cannot be studied in conventional monolayer culture. The study of plasma protein binding and the integration of new physiological hypothesis such as the "Albumin-Facilitated Uptake" also contributed to improve the predictions. Given the performance of the HepatopacTM model, we have developed an innovative approach using a digital dispensing system to spot collagen and produce all types of micropatterned co-cultures. Co-cultures manufactured by this technique demonstrate that the method is robust, accessible and easy to use. Our spotting method was used to evolve the MPCC model and explore new applications.