TARGET IDENTIFICATION

Design and optimize multi-target medicines with Abzu’s explainable AI

You can rationally design more efficacious drugs with fewer side effects with Abzu’s explainable AI.

Target identificationOncologySmall moleculesGenomics
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LUNG ADENOCARCINOMA

Our highly-predictive and explainable models reduce the time required to discover and develop new medicines

Multi-target therapies offer new possibilities and advantages

Multi-target approaches have the potential to reduce treatment resistance and increase therapy efficacy and safety.

In a world of high-throughput technologies, we tell you where to focus

Our highly-predictive and explainable models outperformed other methods, improving target identification and saving time.

Looking for a needle in a haystack? Join us on the next scientific revolution

Our technology is helping Dogodan Therapeutics to develop better nucleic acid therapeutics and raise capital for additional R+D.

Modern genomic technologies paired with powerful computational tools are reshaping drug discovery

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Lung adenocarcinoma is the leading cause of cancer death globally. [1]

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LUAD is the most common cancer subtype to be diagnosed in non-smokers. [1]

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Despite new treatments, the 5-year survival rate is still less than 15%. [1]

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Acquired resistance often develops with single-target therapies. [2]

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The QLattice helps determine the precise genomic locations for controlling transcription factor binding and modulating gene expression of a given target. This is a major step forward.

Thomas Tibbitts, CEO @ Dogodan Therapeutics

Black-box predictions aren’t science

Genomic medicine, the next frontier in biotech, can’t advance without high-performing technology that explores and reveals all available relationships in data.

Cutting-edge discoveries require cutting-edge technology

Developing multi-pronged genomic medicines targeted at multiple nodes in the biological network relies on truly understanding biological mechanisms.

The Abzu difference is explainability

The QLattice identified combinations of elements that lead to looping and unlooping of DNA and targeted positions to modulate gene expression – not just blind predictions: explanations.

The data set

The data is a combination of public genomic data sets and proprietary and private data.

Abzu advancing genomic medicine

Abzu's data science and full packages include our explainable AI and flexible data science, data generation, and scientific support.

Data quantification
Data preparation
Abzu’s QLattice®
AI modelling

The team

We remotely support a team of 5 scientists with experience in Computational Biology, Structural Biology, and Data Science. Our Abzoids dedicated to this project are Sam Demarter, PhD in Systems Biology, and Marco Salvatore, PhD in Bioinformatics.

FOR SCIENCE

Abzu’s explainable AI optimizes drugs

We only understand a fraction of the human body. Let’s know more.
REFERENCES

[1] National Center for Biotechnology Information. Lung Adenocarcinoma. David J. Myers; Jason M. Wallen. 2021. https://www.ncbi.nlm.nih.gov/books/NBK519578/

[2] LUNGevity Foundation. Lung Adenocarcinoma. 2021. https://www.lungevity.org/for-patients-caregivers/lung-cancer-101/types-of-lung-cancer/lung-adenocarcinoma