Rayca Precision
Generative Biology Powering Multimodal Drug Design
Rayca’s AI rapidly designs, screens and optimizes thousands of therapeutic candidates for hard-to-drug targets, leading our owned and partnered pipelines from concept to IND-Approval
Rayca Precision Drug Discovery Suite
Rayca’s platform is a closed-loop process where each data point—from screening, in vitro testing, or preclinical validation—feeds back into the AI models to continuously improve future drug designs
Rayca’s AI rapidly designs, screens and optimizes thousands of therapeutic candidates for hard-to-drug targets, leading our owned and partnered therapeutic pipelines from concept to IND-approval.
What We Do
From small molecules to RNA-based drugs, we specialize in designing and optimizing therapeutic candidates that tackle the hardest-to-drug targets. Our platform integrates multi-omics insights, virtual screening technologies, and predictive modeling to uncover hidden opportunities and accelerate breakthroughs. Every data point—whether from screening, testing, or validation—feeds back into our platform, refining and advancing the next generation of therapies.
Faster Failures, Smarter Designs, Increased Approvals
Generative Biology Powering Multimodal Drug Design
Rayca’s AI generates small molecules, antibodies, peptides, proteins, and CAR proteins and predicts the optimal drug properties, optimizes druggability early in the process.
Fixing the Broken Drug Development Workflow
Incorporates continuous feedback from lab results to optimize for Binding Affinity, Bioactivity, Selectivity, ADMET, PK/PD, and Stability from the start to reduce costly wet lab iterations which connects every phase of discovery into a unified workflow.
The data lakehouse forms the backbone of a living knowledge hub
Rayca Precision’s data lakehouse architecture merges the adaptability of a data lake with the stable, organized structures of a data warehouse. This design allows multi-omics datasets—such as genomic, proteomic, and transcriptomic profiles—to be ingested, catalogued, and analyzed in a single system without the need to shuttle data between multiple tools or storage layers. By unifying these sources, scientists can seamlessly work with next-generation sequencing outputs, high-content imaging results, and clinical datasets under one roof, eliminating many of the barriers that typically hinder interdisciplinary research.
Therapeutic Modalities
Partnership Models and Collaboration
Rayca Precision engages in highly focused collaborations with pharmaceutical and biotechnology organizations seeking novel therapeutic candidates across diverse disease areas. We do not license or sell our platform; instead, we deliver precisely crafted candidate libraries, meticulously optimized through our proprietary computational and experimental pipelines.
Target-Focused Alliances
We work with partners to define a specific therapeutic target or molecular pathway, then generate and refine customized libraries that exhibit high binding affinity, favorable ADMET profiles, and minimal off-target liabilities.
Therapeutic Area Collaboration
For companies aiming to expand or diversify a pipeline, we create comprehensive libraries tailored to key oncology, immunotherapy, or rare disease programs. This end-to-end approach compresses the timeline from concept to lead selection by leveraging extensive multi-omics insights.
Multi-Project Engagements
Longer-term alliances often involve multiple sequential or parallel projects, allowing our iterative discovery process—incorporating real-world data and emerging biomarkers—to refine and deliver successive candidate libraries with escalating precision.
Validation Studies
Throughout these collaborations, we provide continual scientific support, including data review, target validation insights, and guidance on subsequent validation studies, ensuring partners can swiftly progress high-potential leads into advanced preclinical and clinical development.
Regulatory Considerations and Acceleration of IND Filings
A critical yet sometimes overlooked part of drug development is securing regulatory approval to move promising candidates into clinical trials. Rayca Precision’s data-driven platform supports this process by generating a well-documented, easily auditable record that meets the requirements for Investigational New Drug (IND) submissions. Our approach integrates multi-omics profiles, high-throughput screening outcomes, and in vitro/in vivo study data to produce a thorough dossier that demonstrates both the scientific rationale and safety considerations for each candidate.
One of the platform’s strengths is its early detection of off-target toxicities and pharmacokinetic risks, thanks to predictive modeling that links cheminformatics, protein engineering, and ADMET assessments. Catching these issues before large-scale animal studies significantly lowers the probability of last-minute failures and reduces overall development costs. Additionally, each computational step is version-controlled and benchmarked against experimental results, creating an auditable trail of how lead molecules were discovered, refined, and de-risked over time.