Presentation: 4A03

At GSK efforts are underway to determine how best to leverage high throughput assay technologies to generate large, off target data sets to assist with rational compound design. With late stage attrition of otherwise promising compound candidates a common problem, there is a perception that access to early information relating to key ‘developability’ targets, even at the hit to lead stage could be used to flag, priorities or discount active series and ultimately circumvent problems later in the drug development pipeline.

To this end, we have embarked on collaborative efforts between preclinical development and early stage discovery functions to better understand structure activity relationships around the interactions of small molecule ligands with various transporter proteins. Transporter targets with key roles in drug disposition, drug-drug interactions and essential physiological processes are chosen based on the expertise and experience of DMPK and Safety Assessment scientists and high throughput compatible assays are then developed by discovery scientists. In certain instances novel assay methodologies have been required to enable the production of this data.

Once such data sets are available, it is possible to design computational models to predict liabilities, use tool compound data sets to assess the physiological relevance and significance of the in vitro data and specifically screen out liabilities eg therapeutic area-specific drug-drug interactions, toxicity, undesirable PK etc. A vital part of this overall process is the communication of findings from high throughput experiments with the necessary caveats. A highly integrated, multidisciplinary effort is therefore essential for success.

Close Window X