Stef van Grieken, CEO and co-founder:

We are excited to announce today that Cradle has partnered with Ginkgo Bioworks, the leading platform for cell programming and biosecurity, as part of the creation of the Ginkgo Technology Network. 

We’re delighted to be partnering with Ginkgo for two reasons. 

Firstly, to be recognised as a leader in AI for biology and protein engineering by one of the biggest names in biotech is a great motivator for our team and solid proof of our progress so far. One of the focus areas for the Ginkgo Technology Network is AI and Cradle was invited to be one of the initiative’s launch partners due to our industry-leading generative AI capabilities for protein engineering. 

Secondly, and most importantly, we see this collaboration as a fantastic way to bring our Machine Learning technology to more bio R&D teams, helping them to progress quicker, spend less and be more successful in protein design, whether it’s through the optimization of enzymes, vaccines, peptides, antibodies or diagnostic proteins. 

Accelerating R&D

One of our core principles at Cradle is that our technology should be easy to use for any team of scientists and that users should not need computational expertise to use our Machine Learning tools. This collaboration helps us advance this mission. 

Biology R&D teams that are already using Ginkgo’s technology will be able to easily access our platform to engineer better proteins, faster, using generative Machine Learning models that are uniquely capable of multi property optimization and have passed extensive benchmarking and in-house wet-lab validation. Results to date show that teams who use the Cradle platform are 3.5x more productive in meeting their protein engineering objectives. This means that progress that previously took 10 experimental rounds can now be achieved in 3 rounds or less.

Our best-in-class protein engineering tools will be seamlessly integrated with Ginkgo’s scaled closed-loop “design-build-test-learn” Foundry platform, enabling biologists to engineer proteins directly from their web browser without requiring their own wet lab or any support from a machine learning engineer. 

How does this work in practice? 

Cradle-generated sequences can be automatically tested and validated by Ginkgo, and Ginkgo-generated experimental data can be automatically uploaded to Cradle and used to fine tune Cradle’s customer-specific Machine Learning model.

Teams using Cradle through Ginkgo’s Technology Network can get started with just a sequence or set of sequences without prior data, or an existing dataset of sequences and assay values. With either starting point, the best results are usually achieved when testing a minimum of 96 sequences per round using a plate-based setup. Cradle and Ginkgo can help R&D teams meet these experimental criteria and deliver faster progress across a wide range of sectors, from pharma to food and specialty chemicals. 

The level of automation this collaboration unlocks is unprecedented and we're excited for Ginkgo customers to be the first to experience it and to see the ripple effects it will have inside those organisations.

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To find out more about our partnership with Ginkgo please get in touch or come speak to us at Ferment 2024 in Boston on April 11th.