Our integrated AI + wet-lab workflow covers 95 % of known human drug targets and delivers a 10x higher hit rate than competing methods—validated across 40+ client projects.
DiscoveryEngine™ is PharmAI Discovery’s proprietary platform for designing and developing small-molecule therapeutics. We start with atomic-level target data and use interpretable AI combined with 3D molecular modeling and a virtual library of over 80 billion compounds. This approach accelerates early discovery, improves hit rates, and reduces risk—all within a fully integrated system.
Our capabilities go far beyond in-silico design. We validate selected compounds through in vitro and in vivo studies, advancing them toward IND submission. We continue development into Phase I and II clinical trials.
At PharmAI Discovery, we don’t just find molecules— We build and advance clinically meaningful drug candidates from the ground up.
Years Of Research
10x Higher Hit Rate
Our integrated AI + wet-lab workflow covers 95 % of known human drug targets and delivers a 10x higher hit rate than competing methods—validated across 40+ client projects.
Our discoveries don't just live in the lab—they move peer review and secure patent offices worldwide. Over the last five years we've (i) authored benchmark studies on AI-driven hit-finding, (ii) filed four patent families across oncology & neurology, and (iii) Converted in-silico insights into clinic-ready assets now in pre-clinical or in-vivo validation.
AI hit-finding validated in Eur J Med Chem & J Clin Invest
HSP27 neuro-protective inhibitors — 2 granted
2 filings on Tetramer disruptors (Oct 2024)
Proprietary 3-D fingerprinting & 300 M-compound dataset
DiscoveryEngine™ unites atomic-level AI screening with on-site chemistry, biology and radiolabeling. Your project stays in one secure pipeline—from virtual hit to in-vivo proof—eliminating hand-offs, data loss and delays.
300 M-compound virtual screens straight into wet-lab validation.
10x higher hit rate and integrated QC shave months off timelines.
Our deterministic AI platform converts raw target data into compounds that break protein–protein interactions — shutting down pathways long deemed “undruggable” — and into radiolabeled small molecules that double as precision diagnostics and therapies. The result: clinic-ready assets up to 18 months faster and with a 10× higher hit rate than conventional discovery.
versus standard high-throughput screens
Explainable AI pinpoints hot-spot residues and guides medicinal chemistry to destabilise multi-subunit protein complexes, delivering first-in-class small molecules that block function at its structural core.
Covalently modifiable scaffolds support stable α- or β-emitter attachment, enabling same-molecule PET imaging, dosimetry and targeted radiotherapy with deep-tissue penetration and minimal off-target burden.
300 M-compound virtual screen flows directly into on-site synthesis, potency assays and full GLP toxicology — eliminating hand-offs, data loss and the usual six-month lag.
Every intermediate model, assay trace and patent filing is shared in real time, giving partners full ownership for regulatory submissions, out-licensing or co-development.
Trusted by organizations, institutions, and researchers worldwide.
A single, integrated pipeline takes your biological target from raw data to lab-validated leads—compressing timelines by months and giving you full ownership of every result.
300 M-compound screen yields 200 ranked hits; clustering, ADME filters and in-vitro binding narrow these to 10-20 high-quality leads.
Medicinal chemistry boosts potency, selectivity and PK.
Optimised leads undergo GLP tox, PK/PD and rodent disease-model studies—pinpointing the 2-3 safest, most efficacious candidates.
CMC, tox and in-vivo data compiled into a regulatory dossier—ready for IND filing and Phase 1 entry.
