Reinventing Small Molecule Drug Discovery
We tackle some of the most challenging and previously undruggable targets, redefining the drug discovery landscape. Our AI-driven approach streamlines the identification of novel therapeutics, increasing the probability of success and providing drug developers with a more efficient and scalable discovery platform.
AI Models Powering Our Biomedical Research
Our AI models collectively work to bridge the gap between data and discovery, allowing us to deliver cutting-edge insights that propel biomedical research forward. With scalable, adaptive algorithms, our software enables rapid hypothesis generation, minimises experimental failures, and accelerates the translation of scientific breakthroughs into viable treatments.
DeepVariant AI
Accurately detects genetic variations from sequencing data, improving precision medicine applications by identifying rare mutations and genetic predispositions.
OmicsNet
Integrates multi-omics datasets, such as genomics, proteomics, and metabolomics, to uncover disease biomarkers and therapeutic targets, enabling deeper biological insights.
PharmaGen AI
Predicts drug-target interactions, accelerating small molecule discovery and drug repurposing by evaluating vast chemical libraries with enhanced accuracy.
OmicsNet
Models biological pathways to predict disease progression and therapeutic interventions, improving the understanding of disease mechanisms and potential treatment pathways.
ImmuneNet
Simulates immune response dynamics, optimising vaccine and immunotherapy design by predicting antigenic responses and immune cell interactions.
ClinAI Trial Optimiser
Enhances clinical trial design by identifying optimal patient cohorts and response predictors, ensuring more efficient and targeted clinical studies.
