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AI Drug Discovery Software

You already have the answers…
Rigorously verified AI software that reveals transformative insights from your data

Guide your projects

With Proven AI Drug Discovery

Cerella™ uses a unique deep learning approach to overcome limitations in drug discovery data, reducing costs and accelerating drug discovery cycles. Cerella highlights high-quality compounds with confidence, finding hidden opportunities caused by missing, uncertain or inaccurate data and prioritises the most valuable experiments. From working with early hits to nominating preclinical candidates, Cerella delivers industry-leading results, designed for enterprise deployment and integrating with experimentalist’s workflows.


AI-Guided Drug Discovery

Proactively highlight high-quality compounds by ‘filling in’ sparse data

Increase confidence in decision making, identify hidden opportunities, flag outliers and false negatives

Translate artificial intelligence insights into the planning of experiments to focus on the most valuable measurements

Gain more value from your compound data, accurately predicting complex endpoints, intractable with conventional QSAR modelling

Add value at any scale, from individual project datasets to global compound data repositories

AI Drug Discovery Case Studies

Showcasing Cerella


AI Without The Hype

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, and proven Cerella’s benefits in several case studies, from individual project-level datasets up to global compound data repository level investigations.

Cerella uses a unique, peer-reviewed deep learning method, with demonstrated successes in drug discovery

Guiding Drug Optimisation Using Deep Learning Imputation and Compound Generation

Irwin et al. International Pharmaceutical Industry (2020) 12(2), pp. 28-31.

Deep Imputation on Large-Scale Drug Discovery Data

Irwin et al. Applied AI Lett. (2021) DOI: 10.1002/ail2.31

Imputation of Assay Bioactivity Data Using Deep Learning

Whitehead et al., J. Chem. Inf. Model. (2019) 59(3), pp. 1197-1204.

Practical Applications of Deep Learning to Impute Heterogeneous Drug Discovery Data

B. Irwin, et al., J.Chem. Inf. Model. (2020) 60(6), pp. 2848-2857.


Cerella Security

Cerella is secure and scalable, offering cloud-enabled deployment, scaling from individual projects to global pharma databases.


Predicting PK From Limited ADME Data With Deep Learning

Watch our webinar introducing a real world case study where we applied Cerella’s deep learning methods to guide a drug discovery project. Our collaborators had identified potential compounds with good activity profiles but needed to improve their pharmacokinetic profiles to achieve better efficacy.


Get In Touch

To trial Cerella please complete the form and a member of the team will get in touch to understand your needs and get you set-up with a license that works best for you.