Cradle

Description

Cradle offers a powerful AI-driven platform engineered to accelerate protein engineering processes, enabling scientists to discover and optimize proteins with greater speed and precision. The platform leverages advanced AI models to generate novel protein candidates and improve their existing properties, significantly reducing the time and resources required for research and development.

At its core, Cradle empowers users to engineer better proteins faster. By integrating experimental data directly into the AI models, the platform learns and refines protein designs iteratively. This approach leads to more breakthroughs with fewer experiments, guiding R&D teams toward desired objectives more efficiently. Users can track project progress from candidate generation to experimental result uploading, with comprehensive reporting tools to manage data and explore insights.

Trusted by leading Biopharma and Industrial Bio R&D teams, Cradle has demonstrated its ability to shorten development timelines and accelerate the market introduction of biosolutions. Case studies highlight its success in areas such as producing vaccine adjuvants, engineering therapeutic peptides with high success rates under multi-property constraints, improving vaccine thermostability, and rescuing stalled protein campaigns.

The platform facilitates co-optimization of multiple protein properties, including activity, binding affinity, specificity, stability, and expression. This capability allows teams to navigate complex trade-offs and achieve optimized solutions in fewer experimental rounds. Cradle is designed to work with any protein, supporting the entire journey from hit identification to lead optimization and beyond, making it suitable for therapeutics, agricultural solutions, and food ingredients.

Cradle prioritizes data privacy and security, ensuring that user sequences and data remain private, secure, and exclusively owned by the organization. The platform is protected by bank-grade security and is SOC 2 compliant. It offers a zero-maintenance, fully managed AI infrastructure with dedicated support from scientists and ML experts. Cradle also operates its own wet lab in Amsterdam to ensure its AI models are performant from day one, even before integrating proprietary data, mirroring best practices in AI development.

Cradle's Core Features

• AI-driven protein candidate generation

• Protein property optimization using experimental data

• Iterative model refinement based on wet lab results

• Co-optimization of multiple protein properties (activity, stability, etc.)

• Accelerated development timelines (2-12x faster reported)

• Exploration of multiple design strategies

• Secure and private data handling

• SOC 2 compliant infrastructure

• Single Sign-on (SSO) support for Google and Microsoft

• Integration of custom predictors (BETA)

• Fully managed AI infrastructure with scalable GPU

• Dedicated scientific and ML expert support

• Proprietary data remains private and is not used for external model training

How to use Cradle?

1. 1

   Configure: Define protein engineering goals and input experimental data.

2. 2

   Generate: Leverage AI to create novel protein candidates.

3. 3

   Track: Monitor project progress from candidate generation to results.

4. 4

   Explore: Analyze reports and explore optimized protein designs.

5. 5

   Optimize: Iterate on designs based on AI feedback and new experimental data.

6. 6

   Deploy: Bring improved proteins to market faster.

Cradle's Use Cases

• Therapeutic Peptide Engineering
• Vaccine Adjuvant Production
• Antibody Optimization
• Enzyme Development
• Vaccine Antigen Stabilization
• IgG Campaign Rescue
• Food Ingredient Innovation
• Agricultural Solution Development

FAQ from Cradle

• What is Cradle's primary function in protein engineering?

  Cradle's primary function is to use AI to generate protein candidates and improve their properties, accelerating the protein engineering process for scientists.

• How does Cradle leverage experimental data?

  Cradle integrates experimental data directly into its AI models, allowing the models to learn and refine protein designs iteratively for better performance.

• What are the reported benefits of using Cradle?

  Teams using Cradle report 2-12x faster development timelines, enabling more breakthroughs with fewer experiments and quicker market entry for biosolutions.

• Can Cradle optimize multiple protein properties simultaneously?

  Yes, Cradle allows for the co-optimization of multiple properties such as activity, binding affinity, stability, and expression, turning complex trade-offs into optimized solutions.

• Is my protein sequence and experimental data kept private with Cradle?

  Yes, Cradle ensures that your sequences and data remain private, secure, and entirely yours. Only authorized users can access your data, and it is never used to train models for others.

• What industries can benefit from Cradle?

  Cradle is suitable for Biopharma and Industrial Bio R&D teams, supporting the development of therapeutics, agricultural solutions, food ingredients, and more.

• Does Cradle offer any security certifications?

  Yes, Cradle is fully SOC 2 compliant with active monitoring and tight security protocols in place.

• What kind of support does Cradle provide?

  Cradle offers dedicated support from a team of scientists and ML experts ready to assist with any issues.

• How does Cradle ensure its AI models are performant?

  Cradle operates its own wet lab in Amsterdam to test and fine-tune its AI models in real-world scenarios, ensuring high performance even before integrating user data.

• What is the pricing model for Cradle?

  Cradle operates on a software subscription fee model, with no royalties required.

• Can I use my own custom predictors within Cradle?

  Yes, Cradle offers a BETA feature for using internally developed predictors directly within the platform.