Cradle

Cradle is an AI platform designed for biologists to accelerate the protein engineering process through generative design. The software utilizes machine learning to suggest protein designs optimized for specific biological properties such as stability, solubility, or binding affinity. Instead of relying on time-consuming trial-and-error laboratory methods, Cradle enables the pre-selection of promising candidates through in-silico experiments.

The interface integrates into existing laboratory workflows, helping scientists manage their data centrally and evaluate results in real-time. By continuously incorporating feedback loops from the laboratory, the AI learns from every experiment and significantly improves its predictions for future development cycles. This leads to a drastic reduction in the number of laboratory iterations required.

In addition to the software, the company provides technical interfaces that allow seamless data exchange between biological data sources and the AI platform. Users can choose from a variety of models specialized for specific protein engineering tasks. The goal is to make the development of new enzymes, therapeutics, and biological materials more efficient and cost-effective.

• Generative Protein Design — The platform uses state-of-the-art AI models to suggest sequences that meet specific biological requirements. This allows for targeted protein optimization as early as the design phase.
• Experimental Feedback — Scientists can feed their lab results directly back into the system. The AI processes this data to continuously increase the accuracy of its future predictions.
• Collaboration Platform — The software provides tools for teams to securely share research findings and plan experiments together. This encourages interdisciplinary knowledge exchange within the lab.

The tool is primarily aimed at molecular biologists, biochemists, and researchers in the pharmaceutical and industrial biotechnology sectors. It is ideal for teams conducting protein engineering who wish to optimize their lab workflows using modern AI methods.

A biotech company aims to develop an enzyme that remains stable in industrial detergents at low temperatures. The team uploads existing sequence and activity data to the Cradle platform, which then generates thousands of variant suggestions. By simulating thermostability, researchers can select the top 20 candidates for subsequent laboratory synthesis. This process reduces the number of required lab test series from hundreds to a minimum, saving both time and resources.

• The tool is primarily aimed at molecular biologists, biochemists, and researchers in the pharmaceutical and industrial biotechnology sectors. It is ideal for teams conducting protein engineering who wish to optimize their lab workflows using modern AI methods.
• A biotech company aims to develop an enzyme that remains stable in industrial detergents at low temperatures.
• Generative Protein Design: The platform uses state-of-the-art AI models to suggest sequences that meet specific biological requirements. This allows for targeted protein optimization as early as the design phase.
• Experimental Feedback: Scientists can feed their lab results directly back into the system. The AI processes this data to continuously increase the accuracy of its future predictions.
• Collaboration Platform: The software provides tools for teams to securely share research findings and plan experiments together. This encourages interdisciplinary knowledge exchange within the lab.

Cradle should not be used if no biological source data is available, as the AI relies on high-quality input data. Furthermore, the tool is not designed for clinical diagnostics or direct medical applications on humans.

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