Target selection is key to creating success in drug discovery.
Selecting each target is a significant decision and the future success of any molecule will depend on that initial decision.
We combine genetic data and global literature in machine learning models to anticipate and confirm disease-target associations
Our experimental platform records responses in real patient samples allowing us to generate high-precision views of potential patient response.
Targets must also be small-molecule druggable, meaning they have sites complementary to the properties of effecacious, safe small molecules
Targets and Disease
Our AI-driven precision target systems are built to identify emerging hotspots of opportunity.
We combine global genetic data and literature with specific readouts from primary patient tissue, generated in our own laboratories.
By bringing together complementary layers of data, we are able to build precise views of disease-relevant target space.
This comprehensive strategy allows us to work on both first in class and validated targets, within a single unified framework.
Our discovery approaches extend beyond single molecular targets.
We can apply the same strategic approaches to diseases areas where individual target mechanisms are unclear yet.
In these situations, drug discovery can be conducted at a cell, tissue or whole organism level by measuring a changes in a high-content image or a phenotypic response.
In our own laboratories we can also use single cell phenotypic screening in primary patient tissue to identify novel target space for small molecule discovery.
We identify targets amenable to ‘gold standard’ small molecule discovery through advanced drugability and tractability assessment
These anticipate whether a binding site is predisposed to accomodate a well-balanced small molecule that is both potent and selective whilst other key pharmacology criteria such as absorption, solubility and CNS are also achieved.
Established proteins may have data that enable detailed assessment but for less researched targets with little supporting data, assessments focus on what seed data should be generated to qualify target potential.
Our Precision Experiment systems, especially biophysical fragment screening, are ideal for such work.