Proven AI that guides drug discovery
AI-Guided Drug Discovery
Reducing the time and cost of your discovery cycles
Proactively highlight high-quality compounds by ‘filling in’ sparse data
Increase confidence in decision making, identify hidden opportunities, flag outliers and false negatives
Help you translate AI insights into the planning of experiments to focus on the most valuable measurements
Enable you to gain more value from your compound data, accurately predicting complex endpoints, intractable with conventional QSAR modeling
Add value at any scale, from individual project datasets to global compound data repositories
Cerella uses a unique, peer-reviewed deep learning method, with demonstrated successes in drug discovery.
Cerella™ is powered by Alchemite™, a deep learning method developed by Optibrium’s technology partner Intellegens Limited. In collaboration with pharmaceutical and biotechnology partners, Optibrium has rigorously demonstrated Alchemite’s unique benefits over conventional modelling methods in peer-reviewed studies, resulting in reductions in cost and time of discovery cycles.
Cerella™ has proven its benefits in several collaborations with pharma and biotech organisations, working with individual project-level datasets up to global compound data repository level investigations.
- Irwin et al. “Guiding Drug Optimisation Using Deep Learning Imputation and Compound Generation” International Pharmaceutical Industry (2020) 12(2), pp. 28-31.
- Irwin et al. “Deep Imputation on Large-Scale Drug Discovery Data” Applied AI Lett. (2021) DOI: 10.1002/ail2.31
- Whitehead et al., “Imputation of Assay Bioactivity Data Using Deep Learning,” J. Chem. Inf. Model. (2019) 59(3), pp. 1197-1204.
- B. Irwin, et al., “Practical Applications of Deep Learning to Impute Heterogeneous Drug Discovery Data,” J.Chem. Inf. Model. (2020) 60(6), pp. 2848-2857.
4 Case Studies in 10 minutes
Scalable & Secure
Cerella offers cloud-enabled deployment, scaling from individual projects to global pharma databases. Data in the cloud are anonymised and fully encrypted in transit and at rest, and a multi-level security model controls access.
Security Concept and Deployment Options in 3 minutes
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