Cradle

Cradle reports an external biotechnology customer's P450 enzyme optimization campaign nearly tripling substrate conversion in three AI-assisted laboratory rounds after ten prior rounds testing 1,200 variants.

Cradle describes three therapeutic peptide optimization programs for an unnamed top-20 pharmaceutical partner, generating 96 candidates per program in one round with at least 50% meeting simultaneous potency, specificity, expression and thermostability constraints.

Cradle applies generative protein-design models with biotechnology partners, while broad deployment remains narrower than general AI platforms.

Cradle documents CRADLE-1 adaptation using evolutionary-neighborhood evotuning, group direct preference optimization and assay-trained regression predictors, with diversity-aware candidate search and multi-property optimization.

Cradle develops generative models for protein engineering and biological sequence design.

Cradle develops generative models for protein engineering and biological sequence design.

Cradle announced US$73 million in Series B funding led by IVP in November 2024, with continued backing from Index Ventures and Kindred Capital, taking total funding above US$100 million. This completed financing is independent of the historical ML and biotechnology collaboration capability.

Cradle's November 2024 announcement reports more than 21 customers developing 31 proteins and names users including Novo Nordisk, Johnson & Johnson Innovative Medicine, Novonesis and Grifols. The disclosed commercial customer base is independent of financing and the general experimental collaboration observation.

Cradle combines ML engineering with biotechnology product and experimental collaboration capabilities.

Cradle documents round-by-round custom-model training on public data, proprietary wet-lab data and project experimental results, with API access and provenance tracking for experimental workflows.

Generative modeling skills transfer broadly, while protein engineering specialization limits cross-market portability.

Generative modeling skills transfer broadly, while protein engineering specialization limits cross-market portability.