CrisPRO.ai: In-Silico Research Framework

Accelerating drug discovery through AI fusion

An in-silico research-use-only (RUO) framework designed to accelerate drug discovery by fusing the capabilities of discriminative and generative Artificial Intelligence. Our platform orchestrates a generalist genome foundation model with a suite of specialist predictors and structural oracles to achieve state-of-the-art performance across multiple benchmarks.

SAE Biological Mastery

Virus Hunter

Identifies viral sequences and prophage regions

3D Folding Master

Predicts protein structure from 1D sequences

Genetic Surgery

Precise CRISPR guide RNA design and optimization

Universal Knowledge

Cross-species biological understanding

Complete AI Platform Integration

Oracle
Forge
Boltz
Command Center

Fusion Workflow: End-to-End Therapeutic Pipeline

Complete RUO workflow combining discriminative and generative AI for therapeutic discovery, from problem framing to validated designs ready for wet-lab validation.

1

Problem Framing & Data Curation

Active

Assemble genomic loci, clinical variants, DMS datasets, and assay priors

Process Details

  • Genomic loci identification
  • Clinical variant collection
  • DMS dataset integration
  • Assay prior establishment

Expected Outputs

  • Curated dataset
  • Problem statement
  • Success criteria
2

Target Assessment (Discriminative)

Score disease-relevant variants with CrisPRO.ai ΔLL and specialist ensemble

Process Details

  • CrisPRO.ai zero-shot ΔLL scoring (8,192 bp context)
  • AlphaMissense/GPN-MSA ensemble
  • Noncoding and splice variant analysis
  • Confidence score generation

Expected Outputs

  • Variant scores
  • Confidence metrics
  • Evidence tiers
3

Mechanistic Triage & Hypothesis

Use CrisPRO.ai embeddings for exon/intron features and region ranking

Process Details

  • CrisPRO.ai embedding analysis
  • Exon/intron classification
  • Motif feature extraction
  • Perturbation region ranking

Expected Outputs

  • Mechanistic insights
  • Hypothesis ranking
  • Feature importance
4

Design (Generative)

CrisPRO.ai sequence proposals with epigenomic guidance and structural validation

Process Details

  • CrisPRO.ai sequence generation
  • Enformer+Borzoi epigenomic guidance
  • AlphaFold 3 structural validation
  • Sequence naturalness screening

Expected Outputs

  • Design candidates
  • Structural models
  • Epigenomic scores
5

In-Silico Validation

Aggregate scores and prioritize designs for wet-lab validation

Process Details

  • ΔLL score aggregation
  • Splice and regulatory AUROC
  • Structure metrics (pLDDT/PAE)
  • Pfam hit analysis

Expected Outputs

  • Validation scores
  • Priority ranking
  • Minipool candidates
6

Feedback & Calibration

Fit supervised heads and calibrate by cohort for continuous improvement

Process Details

  • Lightweight supervised head training
  • CrisPRO.ai embedding calibration
  • Cohort-specific adjustment
  • Platt/isotonic calibration

Expected Outputs

  • Calibrated models
  • Performance metrics
  • Updated thresholds
7

Reporting & Provenance

Generate evidence reports with traceable citations and audit trails

Process Details

  • Evidence report generation
  • Traceable citation linking
  • Audit trail documentation
  • RUO compliance verification

Expected Outputs

  • Final report
  • Provenance log
  • Compliance certificate

Business Value: From Research to Revenue

Our results demonstrate that this fusion approach achieves 95.7% AUROC ClinVar validation on 53,210 samples, resolves 73% of Variants of Uncertain Significance (VUS), and provides a comprehensive, transparent, and controllable system for in-silico drug discovery.

Key Points

Accelerate R&D from years to weeks

Reduce experimental costs by $2.1M per program

Transform 40% VUS rate to 15% with validated predictions

Enable precision therapeutic design with predictable quality scaling

Provide comprehensive, transparent, and controllable system

Business Impact

Reduce experimental costs by $2.1M per program