Key features
Supports point-and-click design and optimization of candidate proteins, bringing machine learning capabilities directly into the hands of experimental scientists.
All web-based features are exposed via open APIs, enabling scriptable, large-scale integration into users’ existing technology stacks.
Use cases and audience
Research teams in biopharmaceuticals and industrial biotechnology, including pharmaceutical R&D departments and academic research groups.
- Designs and optimizes antibodies to be mature, highly developable, and low in immunogenicity, suitable for antibody-drug conjugates (ADCs) or multispecific antibodies.
- Optimizes enzyme catalytic activity, ensuring stability even under harsh conditions.
- Design vaccine antigens to ensure their structural stability even outside the laboratory.
Target protein information or proprietary amino acid sequences, along with experimentally measured performance data (such as potency, specificity, expression levels, thermal stability, etc.).
Protein candidate sequences designed and optimized by AI across multiple attributes, ready for downstream experimental validation.
Frequently asked questions
Does Cradle support all types of proteins?
Yes, Cradle is applicable across pharmaceuticals, crops, materials, and other fields, covering peptides, enzymes, vaccines, antibodies, and more—regardless of whether the protein already exists.
How is customer data secured?
Cradle platform is ISO 27001 and SOC 2 Type II certified, runs on Google Cloud infrastructure, and features robust technical controls, data isolation, and continuous monitoring; customer data is visible only to authorized personnel.
How to use
- 01
Starting from the target protein or a self-ordered sequence, Cradle generates optimized designs based on data and scientists’ domain expertise.
- 02
Simultaneously optimize various protein properties, including efficacy, developability, and manufacturability.
- 03
Feed experimental data back into the platform, allowing the second round of design to automatically inherit the learnings from the first round.
- 04
Integrate Cradle into existing workflows via API, enabling large-scale automation.
Benefits and limitations
Benefits
- Accelerating the timeline of protein engineering
- Improving protein properties through AI-driven design
- Simultaneously optimizing multiple properties
- Providing a secure and private data management platform
- Offering dedicated support from scientists and machine learning experts
Limitations
- Requires experimental data for model training
- May require expertise in both protein engineering and AI
- Pricing information is not explicitly listed on the website
Pricing and availability
Royalty-free with no milestone fees; purchased by license, and customers retain full ownership of their data.
- Pricing source
- https://www.cradle.bio/
- Pricing last updated
- 2026-10-28
Prices and limits may change. Check the official website for current terms.
Official website & sources
Updated on 2026-10-28
