Great models demand great data

Wherever you are in model development, excellence begins with right DNA and protein tools.

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WEBINAR

Powering AI-Based Protein Engineering With Scalable Data

"Twist enables us by allowing routine synthesis of tens or hundreds of thousands fully defined sequences."

A-Alpha Bio

Ryan Emerson, PhD

Senior Vice President, Data Science & Platform Solutions

Model Build Phase

With high-quality datasets, researchers can train and refine their AI models. Twist delivers the accuracy and consistency trusted by leading discovery teams, ensuring your training data, validation datasets, and experimental results all reflect the same quality standard.

 

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Model Test Phase

Model success in silico often fails to translate to the laboratory environment. This is why wet lab validation is necessary. Twist enables the validation of your AI outputs whether you are screening thousands of new genes for trait discovery or characterizing antibody candidates.

 

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CASE STUDY

A CRE.AI.TIVE application of AI: Engineering a more resilient global food supply

“Out of all the solutions we have tried, Twist’s oligos are the most faithful to our designs. We absolutely need this fidelity when we’re validating AI outputs.”

Colleen Drapek, PhD
Lead R&D Scientist, Trait Discovery

BLOG POST

AI’s Future Hinges On The Wet Lab

“The result was a much more efficient path to antibody optimization.”

Twist Biosciences

Colby Souders, PhD

Chief Scientific Officer,
Twist Bioscience 

Model Learn Phase

After AI/ML models downselects the design space and proposes an initial set of candidates, researchers must generate real-world wet-lab data to understand how those sequences actually perform. In silico screening can prioritize enzyme or antibody sequence variants, but only physical assays provide the ground-truth measurements needed to train, refine, or select AI-generated designs. 

 

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