JURA Bio
Developer of an integrated AI-native drug discovery stack that combines manufacturing-aware generative sequence models, large-scale DNA library synthesis, high-throughput human-cell functional screening, and machine learning training objectives designed to learn from these wet-lab datasets. The platform focuses on discovering immune-based therapeutics (TCRs, TCR-mimicking antibodies, CAR candidates) by co-designing experimental data generation and predictive/causal models.
Industries
Nr. of Employees
small (1-50)
Patents
Major histocompatibility complex-based chimeric receptors and uses thereof for treating autoimmune diseases
US-12421293-B2
View DetailsMajor histocompatibility complex-based chimeric receptors and uses thereof for treating autoimmune diseases
US-11826385-B2
View Details
Major histocompatibility complex-based chimeric receptors and uses thereof for treating autoimmune diseases
US-12421293-B2
View DetailsMajor histocompatibility complex-based chimeric receptors and uses thereof for treating autoimmune diseases
US-11826385-B2
View DetailsProducts
Synthesized human antibody and TCR candidate libraries
Large, in-distribution libraries of human-like antibody CDRs and TCR candidates generated by manufacturing-aware models and physically synthesized for screening.
Synthesized human antibody and TCR candidate libraries
Large, in-distribution libraries of human-like antibody CDRs and TCR candidates generated by manufacturing-aware models and physically synthesized for screening.
Services
Collaborative research that combines generative sequence design, scaled synthesis, and high-throughput human-cell screening to generate training datasets and discover receptor/antibody candidates.
Design and manufacture of massive synthetic sequence libraries from generative models and downstream screening in engineered human cells with single-cell readouts.
Collaborative research that combines generative sequence design, scaled synthesis, and high-throughput human-cell screening to generate training datasets and discover receptor/antibody candidates.
Design and manufacture of massive synthetic sequence libraries from generative models and downstream screening in engineered human cells with single-cell readouts.
Expertise Areas
- Generative protein and sequence design
- High-throughput DNA library synthesis and manufacture
- High-throughput functional screening in human cells
- Sequence-to-activity predictive modeling (CNNs, transformers)
Key Technologies
- Manufacturing-aware generative models
- High-throughput DNA synthesis
- Single-cell sequencing
- DNA-barcoded antigen assays
News & Updates
Research partnership to apply machine learning and synthetic libraries to discover antigen-specific TCRs for development of TCR-NK cell therapies; JURA to receive research funding, milestone and option payments.
Description of LeaVS, a library-aware training objective and experimental-design approach for learning sequence-to-activity maps from measurement-limited screens.
Overview of the VISTA system for creating large, in vitro datasets by steering synthesis and screening with AI models to train therapeutics-focused predictors and generative models.
Introduction of variational synthesis, a manufacturing-aware generative architecture for producing designs that can be synthesized at massive scale and for producing synthesis instructions.
Presentation of CAIRE, a causal estimation method that uses repertoire sequencing and clinical outcomes to infer effects of TCRs on patient outcomes and to prioritize therapeutic candidates.
Produced >1,000 diverse candidate scFv-CARs with specified binding against clinically relevant peptide–HLA targets and validated humanness and specificity metrics in human-cell assays.
Research partnership to apply machine learning and synthetic libraries to discover antigen-specific TCRs for development of TCR-NK cell therapies; JURA to receive research funding, milestone and option payments.
Description of LeaVS, a library-aware training objective and experimental-design approach for learning sequence-to-activity maps from measurement-limited screens.
Overview of the VISTA system for creating large, in vitro datasets by steering synthesis and screening with AI models to train therapeutics-focused predictors and generative models.
Introduction of variational synthesis, a manufacturing-aware generative architecture for producing designs that can be synthesized at massive scale and for producing synthesis instructions.
Presentation of CAIRE, a causal estimation method that uses repertoire sequencing and clinical outcomes to infer effects of TCRs on patient outcomes and to prioritize therapeutic candidates.
Produced >1,000 diverse candidate scFv-CARs with specified binding against clinically relevant peptide–HLA targets and validated humanness and specificity metrics in human-cell assays.