Earendil Labs offers an AI‑driven platform that automates protein therapeutic design and optimization by predicting target binding, stability, and developability with deep‑learning and generative models. The system enables biotech and pharmaceutical R&D teams to screen millions of candidate sequences in silico, integrate assay data in real time, and reduce the number of required wet‑lab experiments.
Funding
Funding not disclosed
Founders
Product
Problem
Protein therapeutic discovery relies on extensive wet‑lab screening and iterative engineering cycles, leading to long timelines, high R&D costs, and low hit rates for viable drug candidates. These bottlenecks limit the ability of biotech and pharma companies to bring next‑generation biologics to market efficiently.
Solution
Earendil Labs offers an AI‑driven platform that automates key stages of protein therapeutic R&D. The system uses deep‑learning models and generative algorithms to predict target binding, stability, and developability, enabling rapid in silico identification of high‑quality candidates. Integrated workflows connect computational design with experimental validation, shortening the design‑build‑test loop. By continuously retraining on assay data, the platform improves prediction accuracy over time, reducing the number of required wet‑lab experiments and accelerating candidate progression toward preclinical studies.
Target Audience
Primary customers are biotech and pharmaceutical R&D organizations, contract research laboratories, and academic drug‑discovery groups that develop protein‑based therapeutics and seek to accelerate candidate identification and optimization.
Features
- Proprietary deep‑learning models for protein structure prediction, affinity estimation, and developability scoring
- Generative protein design engine that proposes novel sequences optimized for target binding and manufacturability
- High‑throughput in silico screening pipeline capable of evaluating millions of variants within hours
- Automated data integration layer that ingests assay results to refine model parameters in real time
- Cloud‑native platform with RESTful APIs for seamless connection to existing LIMS and ELN systems
- Secure, HIPAA‑compatible data storage with role‑based access controls and audit logging
- Visualization dashboard that presents predicted metrics, confidence intervals, and design rationale for each candidate
- Compatibility with downstream expression and purification workflows through export of codon‑optimized DNA constructs