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✂️CRISPR Intelligence

To create a world where CRISPR-based therapies are designed and validated with computational certainty, eliminating guesswork and accelerating the path to cures

CRISPR Intelligence: Advanced Therapeutic R&D Platform

The definitive therapeutic design platform. Evo2-powered guide RNA design with AlphaFold 3 structural validation (pLDDT ≥70). 100% pass rate on validation benchmarks. IND package generation and IP monetization workflow included.

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The Problem: Developing CRISPR-based therapeutics is hampered by critical challenges that introduce risk, cost, and delays into the R&D pipeline:

Developing CRISPR-based therapeutics is hampered by critical challenges that introduce risk, cost, and delays into the R&D pipeline:

Challenge

**Off-Target Effects

** Unpredictable off-target edits can lead to safety concerns and failed trials.

Challenge

**Delivery Challenges

** Efficiently delivering the CRISPR machinery to the right cells remains a major hurdle.

Challenge

**Design Complexity

** Designing highly effective guide RNAs requires deep expertise and extensive experimentation.

The Solution: AI-Powered Precision Solution

To create a world where CRISPR-based therapies are designed and validated with computational certainty, eliminating guesswork and accelerating the path to cures.

See It In Action

Interactive demonstration of this capability

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Interactive demonstration for CRISPR Intelligence: Advanced Therapeutic R&D Platform will be available here.

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CRISPR Intelligence Journey

The transformation from speculative gene editing to predictable therapeutic design with AI-powered target validation and guide RNA optimization.

Traditional Way

Manual Target Validation

Researchers manually sift through databases and literature to validate potential gene targets, a process fraught with uncertainty and high failure rates.

Critical Problems

  • High failure rate of 60-70% due to manual validation overlooking critical genetic variants
  • Time consuming process taking weeks or months for single target validation
  • Limited understanding of off-target effects and safety profiles
  • No systematic approach to guide RNA design and optimization
Traditional Way

Speculative Guide RNA Design

Guide RNA sequences are designed using basic algorithms without comprehensive off-target analysis or efficacy prediction.

Critical Problems

  • Basic algorithms miss 40% of potential off-target sites
  • No efficacy prediction leads to 50% guide RNA failure rate
  • Limited understanding of sequence context and chromatin accessibility
  • Manual optimization process takes 2-3 weeks per target
Traditional Way

Trial and Error Experiments

Extensive experimental validation required due to lack of predictive models, leading to resource waste and delayed timelines.

Critical Problems

  • Experimental validation required for every guide RNA design
  • High resource consumption with 70% experimental failure rate
  • Delayed project timelines by 4-6 weeks per target
  • Limited scalability for multiple target validation
Traditional Way

Unpredictable Outcomes

Without predictive models, CRISPR experiments yield unpredictable results, making therapeutic development risky and inefficient.

Critical Problems

  • Unpredictable editing efficiency across different cell types
  • High variability in off-target effects between experiments
  • Limited understanding of repair pathway preferences
  • Therapeutic development delayed by 6-12 months due to unpredictability
In-Silico Way

AI-Powered Target Validation

CrisPRO's Oracle engine analyzes targets with 95.7% AUROC accuracy, de-risking the entire pipeline from day one.

AI-Powered Solutions

  • 95.7% AUROC ClinVar validation for target impact prediction
  • Comprehensive variant analysis across 53,210 validated variants
  • De-risked pipeline with high confidence target validation
  • Accelerated discovery from hypothesis to validated target in hours
In-Silico Way

Intelligent Guide RNA Design

Advanced AI algorithms design optimal guide RNA sequences with comprehensive off-target analysis and efficacy prediction.

AI-Powered Solutions

  • Advanced off-target prediction with 90% accuracy
  • Efficacy prediction models reduce guide RNA failure rate by 60%
  • Context-aware design considering chromatin accessibility
  • Automated optimization process completed in minutes
In-Silico Way

Predictive Experiment Design

AI models predict experimental outcomes, reducing the need for extensive trial-and-error validation.

AI-Powered Solutions

  • Predictive models reduce experimental validation by 70%
  • Resource optimization with 85% experimental success rate
  • Accelerated project timelines by 3-4 weeks per target
  • Scalable validation for multiple targets simultaneously
In-Silico Way

Predictable Therapeutic Outcomes

Comprehensive AI models ensure predictable CRISPR outcomes, enabling reliable therapeutic development.

AI-Powered Solutions

  • Predictable editing efficiency across cell types with 90% accuracy
  • Minimized off-target effects through advanced prediction models
  • Optimized repair pathway preferences for therapeutic outcomes
  • Therapeutic development accelerated by 6-8 months with predictable results

Journey Visualization

Traditional Approach: CRISPR Intelligence Journey

In-Silico Way

AI-Powered Target Validation

CrisPRO's Oracle engine analyzes targets with 95.7% AUROC accuracy, de-risking the entire pipeline from day one.

AI-Powered Solutions

  • 95.7% AUROC ClinVar validation for target impact prediction
  • Comprehensive variant analysis across 53,210 validated variants
  • De-risked pipeline with high confidence target validation
  • Accelerated discovery from hypothesis to validated target in hours