Accelerating the design
of safer chemicals
We provide the chemical producing industries with a comprehensive, AI enabled R&D platform to rapidly guide the design and selection of safer compounds.
Our approach combines standardized, high quality phenotypic screens, machine learning and cloud computing to predict potential toxicity risk earlier in R&D, without the use of animals. Earlier identification of toxicity risk supports industry initiatives to improve productivity, accelerate timelines and reduce costs of new chemical development.
Our screens are offered as a service and results are viewed on the cloud (SaaS).
Trusted by 18,000+ teams around the globe
Servicing the chemical producing industries
Supporting improved safety, productivity and sustainability
Pharmaceuticals
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Agricultural Chemicals
Industrial Chemicals
Cosmetics
Natural Products
Nutraceuticals
Selection, prioritization and progression of safer compounds
Our comprehensive, AI enabled R&D discovery platform helps provide chemists with a valuable cheminformatic tool to guide the design and selection of safer compounds
Centralised data storage, organisation and analysis
Reproducible high content, phenotypic screens
Biological fingerprints used
for similarity analysis
Proprietary Machine Learning approach predicts toxicity risk
Sophisticated, yet simple
data visualisation tools
Thousands of curated compounds for comparison
Our Step by Step Approach
We combine machine learning (ML), high content cellular screens and cloud computing to predict human and environmental safety risk, without the use of animals.
1. Screen
- High content phenotypic screens assess compound toxicity
- Standardized human cell and Zebrafish embryo models
- Multiparametric data generated for each new compound
- Proprietary algorithms transform data into biological fingerprint
2. Analyse
- ML algorithm compares new vs. historical compound fingerprints
- Fingerprint similarity predicts potential toxicity risk for new compounds
- Diverse ML training set: withdrawn, discontinued, on-market drugs
- Training set carefully curated, with known human safety profiles
3. Visualize
- Toxicity risk probability scores color coded for easy interpretation
- Results are elegantly visualized in our 3RnD® cloud platform (SaaS)
- State-of-the-art visualization accelerates data to decision transition
- Architecture (AWS) supports secure and private multi-user data sharing
4. Prioritize
- Fingerprint similarity to known toxins improves compound selection
- Select, prioritize and progress safer compounds earlier in R&D
- Excellent SAR tool to assess the impact of design modifications
- Identifying toxicity risk earlier prevents costly downstream attrition
Introducing 3RnD®
Elegant visualization for intuitive exploration
Informative translation of complex chemical and biological data
- Subscription-based, cloud-hosted (AWS) R&D database
- Next generation R&D platform with integrated safety prediction
- Store, organize, analyze and visualize compound associated data
- Visually interrogate new and historical compound similarities
- Compare chemical structures or their biological fingerprints
Progress rapidly from data to decision
Discard the spreadsheet. Analysis of large compound libraries and associated biological data using spreadsheets takes days, weeks and even months to figure out what it all means. With 3RnD, reduce that process to minutes.
- Transform complex chemical and biological data
- State-of-the-art, easy to use visualization approaches
- Simple, elegant visual tools for rapid decision making
Novel phenotypic screens predict chemical safety risk
Our high content, phenotypic screens measure multiple biological parameters that define acute toxicity risk for chemicals. Proprietary human cell and zebrafish embryo models use biological fingerprinting and ML to identify acute toxicity and teratogenesis risk. These New Approach Methodologies (NAM’s) represent the next generation of safety risk assessment tools.
- SYSTEMETRIC® Cell Health Screen
- ZBEScreen™ - teratogenesis and acute toxicity
- Data quality and reproducibility central to screen design
- Proprietary ML algorithms automate predictive analysis
- Industry leading approach to validation of performance