Nucleai
Nucleai has developed an AI-powered platform that utilizes military-grade geospatial analysis to interpret complex cellular interactions in biopsy samples, generating spatial biomarkers for precision medicine. This technology enhances drug development by providing actionable insights that improve patient selection for clinical trials and optimize treatment strategies.
- Artificial Intelligence
- Data & Analytics
- Biotechnology
- Digital Health
Funding
Raised to date
$60.5MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Drug development and clinical trials are hindered by the difficulty of interpreting complex cellular interactions within biopsy samples. Traditional methods lack the ability to translate these interactions into actionable insights for patient selection and treatment optimization.
Solution
Nucleai offers an AI-powered platform that analyzes biopsy samples using geospatial analysis to decipher intricate cellular relationships. The platform ingests multimodal images, including H&E, IHC, multiplex immunofluorescence, and spatial transcriptomics data. By applying advanced spatial analysis, the platform generates spatial biomarkers that can be used to improve patient stratification in clinical trials, determine biomarker prevalence, elucidate mechanisms of action (MoA), and predict therapy response. The technology provides actionable insights to accelerate drug development and improve precision medicine.
Target Audience
The primary audience includes biopharmaceutical companies and research institutions involved in drug development, translational research, and precision medicine.
Features
- AI-driven spatial biomarker analysis for comprehensive understanding of cellular interactions
- Multimodal image ingestion from H&E, IHC, multiplex immunofluorescence, and spatial transcriptomics
- Advanced spatial analysis to generate actionable insights
- Biomarker scoring to optimize patient selection
- Determination of biomarker prevalence and mechanism of action (MoA)
- Prediction of response to therapy