Bayesian Intelligence for Reliable Drug Candidate Screening
InferALL™ combines predictions from up to 6 independent ADMET tools using Bayesian probability — delivering ensemble predictions with quantified confidence levels that R&D teams can trust.
InferALL™ combines predictions from up to 6 independent ADMET tools using Bayesian probability — delivering ensemble predictions with quantified confidence levels that R&D teams can trust.
One engine. Six tools. Zero guesswork.
InferALL doesn't replace your existing ADMET tools — it makes them work together, producing predictions that are smarter than any single source.
Don't rely on a single model — InferALL™ synthesizes ADMET and BBB predictions from up to 6 industry-leading tools into one smart, unified score.
Move beyond guesswork with Bayesian uncertainty estimates that tell you exactly how much to trust every ADMET and BBB score.
Rank an entire compound library by composite ADMET, BBB penetration, FDA similarity, or any single PK property — sort and re-rank instantly to match your program priorities.
Bridge the gap between lab and clinic by automatically identifying Clinical Cousins — FDA-approved drugs with similar chemical signatures.
Brain-penetration consensus from multiple ADMET tools — critical for CNS programs and quietly disqualifying for therapies that should stay peripheral.
Other tools give you numbers. InferALL™ translates them into how a real human will metabolize, distribute, and tolerate your candidate — grounded in FDA-approved drug data.
From compounds to confidence in three steps
Submit a CSV of drug compounds with names and SMILES codes. From a handful to thousands — InferALL™ handles any scale.
InferALL sends each compound to up to 6 prediction tools, then combines their answers using Bayesian probability for smarter, weighted predictions.
Get a ranked list of your top candidates with ADMET scores, toxicity risk, BBB permeability, radar charts, and FDA Clinical Cousins — all in one view.
Recognized by industry leaders.
Top ADMET Prediction and PKPD Modeling Solution in Canada — 2026.
“Our platform does not attempt to replace existing ADMET or PKPD tools. Instead, it resolves the uncertainty by turning incomplete, fragmented predictions into actionable insight that better reflects human biology.”
Proholistic Discovery was recognized by Life Sciences Review Canada as a Top ADMET Prediction and PKPD Modeling Solution in Canada — 2026 for its commitment to turning uncertainty into practical, quantitative insights that drive smarter experiments. The platform has helped early-stage biotech firms screen compound libraries and supported later-stage organizations in refining dosage strategies for clinical trials. Backed by an advisory board led by Nobel Laureate Sir Michael Houghton.