We discovered and designed composite biomarkers for more successful clinical trials
We explored genes and gene-signature interactions to identify and explain treatment responses with Checkmate Pharmaceuticals
There is a bottleneck in biomarker discovery
Collecting patient data from clinical trials is time-consuming and expensive.
Scientists and researchers are often left with small and disjointed datasets (few samples and disparate pieces of information) to explain drug responses. The result is that the FDA approves only 1 to 3 biomarkers for clinical use each year[1].
The customer: Checkmate Pharmaceuticals
We supported a single Computational Biologist with expertise in target discovery and target validation in oncology.
Why Abzu?
Because traditional machine learning techniques don’t deliver enough actionable insights for scientists and researchers.
Technology + services
Abzu’s flexible services include our explainable AI, the QLattice®, and data access, data processing, and regulatory compliance and approval.
The Abzoids
The Abzoids dedicated to this project were Lykke Pedersen, PhD in Biophysics, Valdemar Stentoft-Hansen, MSc in Economics, and Martin Mathiasen, Business + Customers.
Flexibility to suit your needs
Data access + data processing
We enhance your research with biobank access and prepare your raw data for analysis.
High-performing + interpretable results
Receive a set of composite biomarker signatures with clear and explainable model interpretations.
Regularly compliance + approval
Confidently nominate your signature with our comprehensive report and support.
What people are saying…
Working with Abzu and using the QLattice to analyze our clinical data has provided us with new insights and helped us generate new hypotheses for exploring the potential for a biomarker-based enrichment strategy across cancer.
Collaborating with Abzu has led to highly significant new knowledge. Using the QLattice in combination with biomarkers as well as medical and social register data is a very promising approach to personalised medicine.
Hypotheses generated by Abzu's explainable AI QLattice technology are brilliantly put into context with our knowledge graphs. I believe a combined setup like ours is a very realistic picture of the future of data science.
Collaborating with Abzu helped identify quantifiable key drivers that led to discovering the key biomarkers involved with SARS-CoV-2 infection. Abzu was able to enrich our understanding and produce novel analyses.
Looking for more?
publication
Elyse Sims
November 30, 2022
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Journal of Gastroenterology and Hepatology
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Intelligent Health AI
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Sam Demharter
September 8, 2022
