Abzu improved the hit-rate and reduced R&D risk for a top-10 pharmaceutical company
We yielded a 44 percentage point improvement in catching toxic drugs in the drug development pipeline, reducing R&D risk and time.
Abzu yielded a 44 percentage point improvement in catching toxic drugs
Understanding what drives drug properties in conjunction with accurate drug activity predictions are clear advantages to improving drug candidate hit rate.
The customer: A top-10 pharmaceutical company
We supported a single Bioinformatician from a small bioinformatics department and Biologists and Chemists operating in a wet lab at an undisclosed top-10 pharmaceutical company.
Why Abzu?
Because traditional machine learning techniques don’t deliver enough actionable insights for scientists and researchers.
Technology + services
Abzu’s flexible packages include our proprietary technology, the QLattice®, and iterative lead generation and optimization.
The Abzoids
The Abzoids dedicated to this project were Casper Wilstrup, CEO, and Jaan Kasak, MSc in Theoretical and Mathematical Physics.
Revealing the “why” behind disease mechanisms and drug activity drastically reduces risk and timelines in drug development
Flexibility to suit your needs
Enhanced library design
Custom library of digital molecules for lead generation and optimization.
Explainable predictions
Iterative lead optimization with our experts in AI and RNA therapeutics.
Digital report
Progress, recommendations, and actions to develop safe and efficacious therapeutics.
Hypotheses generated by Abzu's explainable AI, the QLattice, 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.
Umut Eser,
CIO
While we consider ourselves world-leading in the computational design of oligonucleotide-based therapies, our collaboration with Abzu has added new aspects when applying machine learning to drug discovery data.
Morten Lindow,
Therapeutic Modalities
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 perosnalized medicine.
Michael Christiansen
Chief Physician
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.
Afshin Beheshti,
President
