Augmented Intelligence (AI) Platform

Accelerating Data-driven

Predictions for Biomarker & Drug Discovery

Contact us for Collaborations & Contract Research Partnerships

 

In Silico Biomarker & Drug Discovery

Workflow Schematic

Check out this beautiful visualization video of how deep learning looks like from the inside

Now imagine the novel insights & predictions you can generate from this multi-dimensional view of life science big data

In-house Programs & Collaborative Partnerships

 

    • Identification of novel biomarkers from healthy v disease patient (GC/MS) metabolomics datasets in bladder cancer and Crohn's disease
    • Identification non-toxic novel molecular targets for colorectal cancer from healthy versus disease multi-omics datasets.
    • Identification novel molecular targets from breast cancer phenotypic screening datasets.
    • Identification novel drug repurposing indications from transcriptomics datasets for cancer and rare disease.

Enquire about Programs or Collaboration

Contract Research Services

 

    • Repurposing drugs for novel indications using machine learning models
    • Prediction of compound combination therapies
    • Identification of novel biomarkers from multiomics data
    • Recognition & mapping of compound structures & structure activity relationships (SAR) from patents & experimental data
  • Identification of novel molecular targets using machine learning models
  • Drug pipeline & clinical data analysis tools for R&D trends
  • Electronic health record (EHR) conversion & analysis
  • Drug labeling information extraction & analysis
  • Wearable  sensor data analytics for digital biomarkers
  • Machine learning models of in vivo experimental data

 

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Structured Text & Data Resources

Enterprise-grade Virtual Biomarker & Drug Discovery Platform - Launch 2018

 

Features

 

    • Hypothesis generation with 3D landscape network visualization
    • Semantic search inside  1 billion structured life science data points
    • Personalized AI recommendations for literature, Images, research tools & experimental datasets
    • Experimental image matching & text extraction tool
    • Recommendations for test hypotheses validation assays

 

          Custom Integrations

 

  • Proprietary scientific corpi, discovery & clinical trials data & omics dataset
  • 50+ integrated ontologies with automated thesauri & menu filtering
  • 250+ selected life science data repositories
  • Secure private cloud for cross-team experimental data discussion & internal project collaboration

 

In Vitro & In Vivo Assay Hubs

AI-recommended Validation Experiment Assays & Tools from Literature, Images, & Data Repositories

Antibody Hub is a smart browser with Automated Thesauri & Semantic Search optimized for Antibodies. Browse the latest papers, figure images, methods, products & services, as well as experimental datasets & analysis tools.We have extracted Antibody protocol conditions Methods & Antibody Registry Data, as well as displaying figure images of Antibodies from experimental results. Our marketplace contains 2 million Antibodies ranked by literature citations.

Go to Hub

Cell Hub is a smart browser with Automated Thesauri & Semantic Search optimized for Cell Lines. Find which cell lines are available to purchase or obtain from a collaborator. Search cell lines & methods from matched full text research papers & figure images. Find tools to analyse your cell line, and contract research service providers.

Go to Hub

In Vivo Hub is a smart browser with an Automated Thesauri & Semantic Search optimized for Rodent, Fly, Worm & Fish. Browse the latest papers, figures, methods, products & services, as well as experimental datasets & analysis tools. Discover the best in vivo models for your next experiment. Analyse your current model, and find correlations within the published literature & databases.

Go to Hub

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Meet The Team

Mark

Pavel

Anna

Michael

Colum

Niranjan

CEO & Co-founder

CTO & Co-founder

COO & Co-founder

Metabolomics & Cheminformatics

Digital Marketing & Design

Genomics & Transcriptomics

Background in emerging biotechnology & bio-medical research with over a decade of commercial experience in the life science research market. Previously, associate director at Merck KgaA leading the emerging biotechnology initiative in Europe. Mark co-founded Curogenix, a European commercial agency for in vitro & in vivo contract research services, and prior to that worked at Sigma-Aldrich as a field  applications specialist for emerging technologies.

Pavel has a background in computer science, software engineering &  applied bioinformatics. He has particular expertise in biological patterns, data classification and recognition, machine learning approaches using GPGPU based predictive modeling, code conversion & optimization, general-purpose computations on graphical processors & java technologies as well as R, C/C++, java, verilog, python, bash (linux shell), visual basic, perl, and tcl.

Background in economics & finance from Kemmy business school at University of Limerick. Anna has worked in the Life Science, Food & Banking industries, & brings over 10 years expertise in  project management ,  operations & finance to the team.  She has previously founded a company in the food industry, after working in RBS global markets in the US. Anna has also won a management award while at Aramark.

Michael has a PhD in analytical chemistry & is a  lecturer in biostatistics. He has a background in cheminformatics and data science with 10 years of experience in developing machine learning, pattern recognition and biomarker discovery tools to interrogate metabolomics datasets leading to the non-invasive diagnosis of cancers and diseases.

Background in digital marketing with a proven track record in digital design, search engine optimisation, social media & automated marketing. Colum also has graphic design  & animation experience for generating online media content. He has several certifications in design, digital marketing & animation.

Niranjan has a background in molecular biology & applied bioinformatics. He has expertise in handling NGS HiSeq data, quality control and filtering of NGS data: de novo or reference based using assemblers,   reference based genome alignment, detection of genomic variation, RNA-seq  differential expression analysis, and identification of sequence binding motifs using ChIP-seq.

We are actively looking for interns with experience in data science or bioinformatics to join our team, click the button below to apply with your CV

Enquire about joining our team

In The News

Investment Support & Program Finalists

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