Optimizing candidates, Eliminating Avoidable Failure
AxineScreen evaluates and ranks drug compounds against a specific disease target. It runs 100+ ADMET checks — toxicity, pharmacokinetics, bioavailability, and more — and uses our Drug Worthiness Score to surface candidates most likely to survive clinical development.
Platform Overview
AxineScreen scores each compound on toxicity, ADMET profile, molecular optimization, and in silico simulation results — all in the context of the target disease.
The result is a ranked list ordered by real probability of clinical success, not just structural novelty or binding affinity.
Key Features
Each feature below contributes to the Drug Worthiness Score — the single number that tells you how likely a compound is to make it through clinical development for your target disease.
Predicts hepatotoxicity, cardiotoxicity, neurotoxicity, genotoxicity, mitochondrial disruption, and hERG liabilities across candidate molecules.
Generative adversarial networks iteratively refine molecular structures to remove toxicity-prone functional groups, while cross-referencing large-scale toxicology datasets.
Models pharmacokinetic and pharmacodynamic properties including solubility, bioavailability, membrane permeability, blood–brain barrier penetration, and plasma protein binding.
Covers absorption (solubility, permeability, bioavailability), distribution (BBB penetration, plasma protein binding), metabolism (CYP450 interactions, metabolic stability), elimination (renal and hepatic clearance), and toxicity (LD50, mutagenicity, carcinogenicity). All predictions are powered by in silico models trained on FDA-approved and clinically validated compounds.
Uses multi-objective reinforcement learning to suggest structural changes that raise efficacy and selectivity without introducing new liabilities. It also flags potential drug–drug interactions and off-target binding, so ranked candidates are optimized across the full risk profile — not just one metric.
Use Cases
Generates and ranks compounds for cancer targets with chronic-use safety as a hard constraint — minimizing hepatotoxicity and cardiotoxicity while keeping target specificity high.
Ranks compounds for acute infections where short-term tolerability matters more than chronic-use safety. Good for fast-moving targets like malaria or viral diseases where speed to a viable candidate matters.
In silico screening reduces the experimental burden for rare diseases where full preclinical pipelines aren't economically viable. AxineScreen narrows the candidate space before any lab work begins.
Scores compounds that need to hit multiple proteins or pathways at once, while predicting off-target binding and drug–drug interactions. Useful for complex diseases like neurodegeneration or metabolic syndrome where single-target approaches consistently fail.
Talk to us about a demo, a partnership, or any questions about what we're building.
Talk to us about a demo, a partnership, or any questions about what we're building.