phenAID

AI-powered image-based virtual screening and phenotypic profiling platform

by Ardigen · Drug Discovery AI

Executive Summary

phenAID is Ardigen's AI-driven platform designed to transform high-content screening (HCS) and Cell Painting data into predictive biological insights. By combining computer vision, deep learning, and AI-cheminformatics, phenAID enables researchers to perform image-based virtual screening, predict mechanism of action (MoA), and optimize small molecule design. The platform integrates multimodal data streams—such as microscopic cell images and chemical structure representations—to profile morphological changes in cells induced by perturbagens. phenAID allows drug discovery teams to prioritize hits, dissect complex biological pathways, and explore extensive public and proprietary phenotypic libraries, including the JUMP-Cell Painting consortium datasets. Offered primarily via custom biotech and pharma collaborations and cloud-accessible modules (such as the JUMP-CP Data Explorer), phenAID bridges molecular biology and machine learning to de-risk and accelerate early-stage phenotypic drug discovery campaigns.

Use Cases

  • Mechanism of Action (MoA) deconvolution and bioactivity prediction
  • High-content screening (HCS) and Cell Painting phenotypic profiling
  • Image-based virtual screening and hit prioritization for small molecules
  • Biological pathway dissection and target identification in oncology and immunology

Features

Visibility

  • Interactive Profile Exploration: Visualize morphological similarity clusters and multidimensional phenotypic trajectories across treatment conditions.
  • Image-to-Compound Mapping: Directly cross-reference cellular phenotype micrographs with chemical structure representations and metadata.

Intelligence

  • Multimodal MoA Deconvolution: Predict drug mechanism of action through deep fusion of image-derived phenotypes and chemical structure fingerprints.
  • Image-Based Virtual Screening: Prioritize novel small molecule hits without needing exhaustive wet-lab screening runs for every candidate.

Support

  • Domain Expert Collaboration: Direct support and pipeline customization from Ardigen bioinformatics and computational biology specialists.

Technical Specifications

Architecture
Cloud-native, modular AI platform integrating microservices for image processing, deep feature extraction, cheminformatics, and data visualization
Deployment
SaaS
Authentication
SSO/SAML
API Available
Yes
MCP Server
No

Infrastructure

  • AWS

AI/ML Stack

  • PyTorch
  • TensorFlow
  • Vision Transformers
  • Convolutional Neural Networks
  • Cheminformatics Toolkits (RDKit)

Integrations

  • CellProfiler
  • AWS S3
  • JUMP-Cell Painting Consortium

Security & Compliance

Certifications: ISO 27001, GDPR

Encryption: AES-256 for data at rest and TLS 1.3 for data in transit

Pricing

Model
Enterprise licensing & CRO project-based pricing
Starting Price
Contact sales
Target Customer
Mid-Market,Enterprise
Contract Type
Annual / Project-based
Free Trial
No

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