Provides a cloud-based platform that uses machine learning and AI-driven image analysis to convert microscopic images into quantifiable phenotypic data, enabling researchers and regulators to evaluate therapeutic candidates, bio-manufactured products, and personalized treatments. By automating cellular feature extraction and aggregating millions of morphological signatures, it improves decision-making in drug discovery, safety assessment, and climate-resilient agriculture.
Funding
$10K raised to dateRaised 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
Current methods for phenotypic modeling rely on a mix of open-source and commercial tools, often trained on outdated data and lacking the latest advances in imaging and AI. This results in inefficient drug discovery and safety assessment processes.
Solution
Quantiscope's PhenotypIQ platform uses AI-driven image analysis to transform microscopic images into quantifiable phenotypic data. The platform automates cellular feature extraction and aggregates morphological signatures, enabling researchers and regulators to evaluate therapeutic candidates, bio-manufactured products, and personalized treatments. By incorporating advances in imaging and NLP AI into plug-and-play dashboards, PhenotypIQ enhances decision-making in drug discovery, safety assessment, and climate-resilient agriculture. The cloud-based GPU architecture facilitates rapid production and aggregation of millions of signatures, which are then presented as hierarchical rankings to indicate the best and safest therapeutic candidates, viable batches of bio-manufactured products, or suitable oncology treatments for individual patients.
Target Audience
The primary users are researchers and regulators in drug discovery, drug safety, climate resilience, and personalized medicine.
Features
- AI-driven segmentation of cells and subcellular structures from brightfield or stained high-content images.
- Automated extraction of hundreds to thousands of nodes within the cellular analysis target to develop phenotypic signatures.
- Cloud-based GPU architecture for rapid production and aggregation of millions of morphological signatures.
- Hierarchical rankings of therapeutic candidates, bio-manufactured products, or oncology treatments based on predictive potential.
- Plug-and-play, team-oriented dashboards for enhanced drug discovery decision-making.