AlgoraeOS
AI-powered Drug Discovery
AlgoraeOS is our AI-powered drug discovery platform, built in partnership with UNSW AI Institute and CSIRO Data61, with independent validation from the Peter MacCallum Cancer Centre.
The platform generates high-confidence novel drug-combination candidates across complex disease areas for licensing and co-development.
AlgoraeOS drives our long-term therapeutic pipeline, creating value across both the AI platform itself and the novel drug candidates it generates.
Platform Overview
AlgoraeOS connects fragmented pre-clinical, clinical, chemical and biological data to generate novel drug-combination candidates for patients with significant unmet medical need.
AlgoraeOS operates as a closed-loop platform: each stage of discovery and pre-clinical development generates data that continuously strengthens the platform’s predictive capability, compounding its value over time. The platforms intellectual property is 100% owned by Algorae.
Platform Validation
- Trained on more than 5.5 million unique inhibition records (~11M with augmentation)
- 500,000 drug-cell line predictions across 3,000+ drugs and 170 cancer cell lines
- Models the full dose-response surface across Bliss, Loewe, HSA and ZIP
- In published benchmarks, AOS2 outperformed representative state-of-the-art models, including those from Google DeepMind, delivering lower error and stronger correlations across all major synergy formalisms
- 90 high-confidence drug-combination candidates available for validation and partnering
- Independent wet-lab validation at Peter MacCallum Cancer Centre: 21 drug-drug targets tested across 4 cancer cell lines, generating approximately 10,000 data points
- Research partners: UNSW AI Institute, CSIRO / Data61, Peter MacCallum Cancer Centre
- Publication pending: Uncertainty-Aware Deep Learning for Multi-Metric and Dose-Specific Prediction of Drug Synergy
From Discovery to Development
AlgoraeOS generates drug-combination candidates that are then validated with partners available for licensing and co-development with pharmaceutical and biotech partners.
Licensing
Validated candidates are available for out-licensing to pharmaceutical partners. AI-116 (PCT/AU2024/050791) and AI-168 (PCT/AU2024/051253) are priority licensing candidates.
Co-Development
AI-116 is in development with La Trobe University. AI-168 is in development with the Monash Biomedicine Discovery Institute / Victorian Heart Institute.
UNSW AI Institute
AlgoraeOS is developed in collaboration with the UNSW Data Science Hub (uDASH) — a dedicated hub that brings together data specialists to solve complex, real-world challenges in biomedicine.
uDASH provides advanced tools for data analysis and access to high-performance computing infrastructure. The team employs statistical modelling, machine learning, and data visualisation to transform complex biological data into actionable drug discovery insights.
Programs
The following three programs predate AlgoraeOS and were developed independently of the platforms AI capabilities.
AI-116
Dementia
Stage: Preclinical | PCT Filed
Fixed-dose combination of CBD and donepezil. Preclinical validation demonstrated 53% cell viability versus 17% with donepezil alone. PCT patent filed (PCT/AU2024/050791).
AI-168
Cardiovascular
Stage: Preclinical | PCT Filed
Fixed-dose cannabinoid combination candidate for cardiovascular disease. Preclinical data: 94% endothelial restoration, 80% smooth muscle normalisation and 68% reduction in cardiomyocyte damage.
NTCELL
Parkinson’s
Stage: Phase 2 data under review
Alginate-coated capsule containing neonatal porcine choroid plexus cells. Phase 2 clinical trial data under scientific review.
Principal Investigator
Prof. Fatemeh Vafaee
AlgoraeOS Principal Investigator — UNSW AI Institute
Professor Fatemeh Vafaee leads the AI Biomedical Laboratory at UNSW School of Biotechnology and Biomolecular Sciences and is Deputy Director of the UNSW Data Science Hub (uDASH) and Program Lead of the Med-Tech.AI Next-Generation Graduate Program. Her R&D activities focus on developing computational models and advanced AI methods to diagnose and treat complex diseases. She has published extensively in leading journals and has over a decade of translational research experience working closely with industry and leading institutes in Australia and internationally. She received the 2023 Asia-Pacific ‘AI in Health’ award and was runner-up for the ‘APAC Women in AI Innovator of the Year’ award. She holds a PhD in AI from the University of Illinois, Chicago.
AlgoraeOS: long-term discovery value built on commercial foundations.
Sign Up for Email Updates
"*" indicates required fields