We offer a wide array of solutions for therapeutics discovery from target identification to the development/repurposing of clinical stage drugs.
Specifically, we look into how advanced network analytics and Machine learning/AI approaches can help mine omics data to uncover therapeutically meaningful targets. Selected targets are subjected to biophysical characterization and in silico analysis to establish druggability. This is followed by in silico high throughput screening that is used to assist with in vitro assay pipeline building.
We also focus our efforts on compound re-purposing and therapeutic strategy establishment from inception to market analytics.
Services and solutions overview
In-house curated libraries and knowledge-bases allow to build highly reliable gene and protein regulatory networks.
By incorporating epigenome, metabolome and expressome data we can further refine interactome and discover new biological links.
Established networks can be used to model and predict therapeutic outcome.
State-of-the-art machine learning and AI platform for target characterisation allows to identify promising targets within the disease networks.
Selected targets are ranked based on their tractability and druggability potential.
Best therapeutic intervention options are evaluated for each new therapeutic target.
By using large proprietary compound/biologics libraries we can design custom biologics or compounds.