Better RNA therapeutics design with AI.
Our AI-powered technology suite designs better compounds for RNA therapeutics.
Proven team, technology, and results.
Abzu has deep experience in, but not limited to, designing and selecting successful siRNAs, anti-miRs and ASOs.
We apply an AI guided drug design process, ensuring higher quality designs that match exactly your needs.
How you benefit from AI.
Maximize your success by only testing the best compounds.
We provide an RNA drug design process that takes into account relevant factors, such as thermodynamics, genetic variation and various drug properties that traditional methods do not consider.
Maximize your likelihood of successfully developing a drug by only having to test the best compounds.
Faster turnaround for promising candidates.
Fewer cycles spent on designs destined to fail.
Smart models that incorporate existing learnings.
Data-driven drug design.
Predictive models that are trained and validated by our data scientists on curated data.
Abzu’s data-driven approach leverages a suite of predictive models that are trained and validated on data our data scientists have curated and used successfully in projects.
Using AI models that predict drug properties such as activity, cross-reactivity and off-target potential, we design compounds that are more likely to succeed.
Ready-to-use compound designs.
The outcome is a list of ready-to-use compound designs and a report that outlines the selection process, including how our models have weeded out compounds that are likely to fail on important metrics.
Should you already have usable data from previous experiments, we also offer to help you incorporate that into a model to give you the best possible results.
Abzu as a one-stop solution from design to in-vitro validation.
To supercharge the drug design process, we offer ourselves as a one-stop shop for design and in vitro screening for those who want the full benefits of data-driven drug design.
Reduced project management overhead.
Reduced design time.
Directly from target to in vitro validated candidates.
Scientific approach to data.
We design experiments to a high standard that ensures the necessary quality for AI and machine learning, which wouldn’t be obtained otherwise. This method maximises learning by grounding our models in real-world results and reduces the overall time-to-result in a reliable way.
We do our own data generation, research and modelling. This means you leverage not only your existing data, but also all of our data and models we’ve trained from the get go.
Case studies.
Dive into our case studies that showcase how AI can reshape the landscape of drug design.
Ready to take your first step?
Start your journey towards better RNA designs today.
Reach out to explore how you can start leveraging high-quality data and predictive models to improve your designs.
The latest news and events.
Here we use the QLattice® to generate siRNA activity models from publicly available data to create insights that can be used to design active siRNAs.
Artificial intelligence: Selective boom? We consider the benefits of explainable AI and its applications within the pharma industry.
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