WP-1 In Vitro Phys-Chem Tools

WP leaders Rene Holm, H Lundbeck A/S and Anette Müllertz, Copenhagen University. 

The objectives of WP1 are to

  • Provide a range of in vitro physico-chemical tools and in silico models that can assess the API’s key molecular properties important for in vivo performance, including excipient interactions
  • Provide the information gained by use of tools, defined in objective 1, for a subset of the OrBiTo database to establish a drug development decision tool, expanding the DCS and facilitating drug formulation selection and optimise the dosage form design process
  • Cross-fertilize with “In vitro tools – understanding the formulation” (WP2) using the knowledge and results obtained from the physico-chemical studies and models (WP1).
  • Serve as physico-chemical parameter input for integrated modelling and predictive tools developed in WP4.

In order to significantly contribute to the understanding of molecular biopharmaceutics, WP1 has two cornerstones:

i) A structurally diverse set of APIs (n ≥ 50) with focus on poorly soluble compounds (BCS class II and IV), selected primarily among the EFPIA API to cover a representative chemical space. To this space, satellite structures of BCS class I and III are added.

ii) A set of simulated gastro-intestinal media (SGIM), reflecting compositions of the human GI fluids in the fasted and the fed state.

The sets of API and SGIM will form the basis for the standardized, validated physico-chemical tools that are developed in WP1. These models will improve the current physico-chemical profiling of APIs, by comparing and linking to in vivo data, and thereby securing relevance for API in vivo solubility and permeability. Novel methodologies for dissolution rate, supersaturating propensity including re-crystallization/precipitation, permeability including impact of mucus diffusion, and surface activity profiling, will be developed as described below. In addition, new in silico tools for predictions of biorelevant physico-chemical variables making use of the experimental data will be devised. All of these tools will be used to facilitate the interpretation of the biopharmaceutical performance at a molecular level, thereby enabling an extension of the DCS for guiding formulation selection.