Triangle BioTech transforms complex biological data into high-confidence therapeutic targets and prioritized drug candidates — reducing attrition and accelerating timelines.
Request a Scientific DemoDrug discovery remains expensive, slow, and high-risk. Despite unprecedented biological data, most programs fail before approval due to fragmented workflows and low-confidence target selection.
Average cost per approved drug
Failure rate in clinical development
Underutilized biological data points
Our AI-powered SaaS platform integrates multi-omics, literature, clinical data, and experimental results into a unified discovery environment.
Graph-based AI models uncover novel gene–disease relationships and prioritize high-confidence targets.
Identify predictive and prognostic biomarkers from transcriptomic and proteomic datasets.
Rank compounds using multimodal biological context and structure–activity modeling.
Unify genomics, proteomics, clinical outcomes, and literature within one system.
Triangle BioTech combines systems biology, graph neural networks, transformer-based biological models, and causal inference frameworks. Our models are benchmarked against historical development outcomes and continuously refined with new data.
Accelerate preclinical development and strengthen investor confidence.
Enhance pipeline productivity and systematically reduce attrition.
Move discovery programs toward therapeutic applications faster.
Our mission is to make drug discovery computationally predictable. We bring together expertise in computational biology, machine learning, translational medicine, and enterprise software engineering.
See how Triangle BioTech can accelerate your discovery program.