Explora Biotech Srl

  • Michal Riha profile
    Michal Riha
    11 September 2020 - updated 8 months ago
Finalist
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Country: 
Italy

What is the innovation?

AI-driven automatic computation of DNA fragments for seamless DNA assembly

What problem does the innovation solve?

Synthetic biology holds the key to revolutionize the manufacturing paradigm by empowering the design and development of cell factories. However, the key step of designing DNA synthesis fragments to be assembled to engineer microorganism is still a time-consuming task manually performed by researchers. This severely limits the number and complexity of designs and prevents researchers worldwide to fully exploit the power of synthetic biology.

How does the innovation solve the problem?

Our AI-driven algorithm is designed to automatically compute the optimal DNA fragments to assemble a custom plasmid or vector. Our algorithm uses cutting-edge machine learning and proprietary experimental data to design DNA fragments that are both manufacturable and compliant with most common assembly techniques. Our algorithm is available through an web-based app: https://getstarted.doulix.com/scarless-wizard/

Is there any other existing cutting edge solution? If so, how does yours differ?

To the best of our knowledge there are no existing solution to tackle ab initio automated fragment design that use experimental data and machine learning. Similar solution provided by Benchling, Genious and Snapgene software are based on heuristic approaches. To this regard, our approach is stands out as it leverages experimental data and artificial intelligence to provide optimal solutions. Within the framework of the EU project TOPCAPI, our algorithm was successfully employed to compute and assemble complex metabolic pathway with extreme GC content that would have otherwise required genome amplification.

Tell us about your team?

Our team is a unique blend of computer scientists and experimental biologists who share the passion for tackling big challenge and delivery tangible solution. The team is diverse and includes 2 women and 4 men form 3 different countries.

How big is the market for this innovation?

The innovation is a key enabling technology (KET) that tackles a common problem faced by any researcher who wishes to assemble complex DNA constructs in both public and private institution. “Market and Trends” research report estimates the market for software-based KET in the range from $50 mln. by 2023 with a CAGR exceeding 20%.

What EU-funded research project was this innovation developed in?

Project TOPCAPI.