Jedi Labs

CrisPRO Oncology Co-Pilot

Revolutionary AI-powered platform that transforms cancer treatment by empowering clinicians and researchers with comprehensive insights from discovery to patient care. CrisPRO integrates multi-agent collaborative intelligence to address data overload, complex treatment pathways, slow R&D cycles, and fragmented patient care in modern oncology. The platform provides end-to-end solutions spanning research, clinical trials, therapeutic design, and coordinated patient management.

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Core Capabilities

  • Deep Data Synthesis & EMR Integration
  • Advanced Genomic & Variant Analysis
  • AI-Accelerated Therapeutic Design (CRISPR)
  • Precision Clinical Trial Matching & Recruitment
  • AI-Driven Coordinated Care & Patient Support
  • Predictive Digital Twins & In Silico Modeling
  • Solution Architecture

    Comprehensive AI-powered oncology platform architecture integrating multi-agent collaborative intelligence for end-to-end cancer care from research and discovery to clinical trial optimization and coordinated patient management. The system leverages predictive genomics, structural biology, and advanced AI orchestration to revolutionize cancer treatment workflows.

    Implementation Flow
    Step 1:Data Ingestion & Synthesis

    Comprehensive data collection from EMRs, genomic databases, imaging systems, and clinical notes with real-time validation and quality assessment

    Step 2:AI-Powered Analysis & Pattern Recognition

    Multi-agent analysis of patient data including genomic variant analysis, biomarker identification, and disease progression modeling

    Step 3:Therapeutic Target Identification

    AI-driven identification of optimal therapeutic targets using structural biology insights and predictive genomics analysis

    Step 4:Treatment Design & In Silico Validation

    CRISPR therapy design with automated gRNA optimization, off-target prediction, and digital twin validation of treatment efficacy

    Step 5:Clinical Trial Matching & Recruitment

    Semantic matching of patient profiles with relevant clinical trials including eligibility verification and accessibility analysis

    Step 6:Personalized Care Plan Generation

    Comprehensive care plan creation with treatment scheduling, specialist coordination, and patient support integration

    Step 7:Continuous Monitoring & Optimization

    Real-time monitoring of treatment outcomes with adaptive learning and care plan optimization based on patient response

    React Flow mini map
    System Components
    Care Coordination Orchestrator

    AI-driven system for automated care coordination and patient support

    Clinical Trial Matching Engine

    Semantic matching system for precision clinical trial recruitment

    CRISPR Design Assistant

    AI-accelerated therapeutic design system with predictive modeling capabilities

    Digital Twin Simulator

    Predictive modeling system for virtual patient and disease simulation

    EMR Integration Hub

    Unified interface for connecting with Electronic Medical Records and diverse healthcare datasets

    Genomic Analysis Engine

    AI-powered system for rapid identification of genetic drivers and therapeutic targets

    Multi-Agent AI Coordinator

    Central orchestration system managing collaborative AI agents across all platform components

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