At the forefront of small molecule drug discovery
WE ARE THE FIRST COMPANY TO AUTOMATE DRUG DESIGN, SURPASSING CONVENTIONAL HUMAN ENDEAVOUR.
Our AI driven systems actively learn best practice from vast repositories of discovery data and are further enhanced with knowledge acquired from seasoned drug hunters
With better information to hand than any researcher could acquire individually, our knowledge-driven systems design millions of novel, project-specific compounds and pre-assess each for predicted potency, selectivity, ADME and other key criteria.
From this, a selection of the best, information-rich compounds are selected for synthesis and assay.
With new experimental data generated, the results are integrated and the next design cycle initiated.
Rapid design-make-test cycles ensure unparalleled progress towards desired project goals.
Exscientia has already delivered exceptional productivity, generating candidates in roughly one-quarter of the time of traditional approaches.
we address how quantum mechanics may be applied to the therapy of infectious diseases, immune disorders, neurological conditions and aging
Bispecific Small Molecules
SINGLE COMPOUNDS THAT INDEPENDENTLY BIND TWO DISTINCT TARGETS.
Most diseases are highly networked, so therapies often need to hit multiple nodes to have a sustainable effect.
Furthermore, many drugs have now been shown to hit more than one target, suggesting that this polypharmacologyis more frequent than previously anticipated.
Exscientia have harnessed this knowledge to develop a system to design molecules that explicitly hit more than one target.
Seeded by experimental data for individual targets, our design process can assess the chemical tractability of any biologically relevant pairing. Only those target pairs appearing amenable are taken forward.
Bispecific designs are rapidly synthesised and tested to confirm the overall opportunity for each prioritised pairing.
Those displaying the potential to encode key chemistry into a single integrated pharmacophore, are taken forward to become active drug discovery projects.
we apply inverse modelling, Electron Energy Loss Spectroscopy (EELS) and first-principles to detect new pharmaceutical polymorphs