A Bio-IT SaaS Platform

The Computational Compiler for Personalized Medicine.

We don't build drugs in labs. We engineer the digital information to reprogram biology from the inside out, targeting the unique architecture of every individual tumor.

Platform Output Example

// ONCOPRINT BLUEPRINT V1.0
{
  "target": "LUNG_TUMOR_CX4",
  "cargo": "mRNA_SEQ_772A1...",
  "vehicle": {
    "type": "LNP_LIGAND",
    "docking_site": "EGFR_SURFACE_6",
    "binding_affinity": "0.982"
  },
  "pathway": "IMMUNE_FLANK_A"
}

Generating (Manufacturing-ready) genetic sequences using open-source foundation models.

The Necessity of Precision

Cancer is not one disease; it is millions of unique genetic architectures. Traditional "one-size-fits-all" drug development is failing 1 in 6 deaths worldwide.

Why Traditional Methods Fall Short

  • One-Size-Fits-All Inefficiency

    Generic treatments target broad cohorts, ignoring the extreme genetic heterogeneity of tumors.

  • Delivery Toxicity

    Current gene delivery lacks precise targeting, often damaging healthy organs like the liver.

  • CapEx Dependency

    Hundreds of millions wasted in physical wet-lab maintenance and real estate.

The Cellular Kill-Chain

Explore how OncoPrint AI reprogram's biology to destroy lung cancer. Unlike toxic chemotherapy, our computational approach uses precision infiltration and targeted destruction.

Ligand trajectory toward tumor receptor

Phase 1: Precision Infiltration

Our ESM-3 models design molecular "keys" (ligands) that exclusively fit the "locks" (receptors) overexpressed on lung tumor cells. The drug bypasses healthy tissue entirely, traveling as a digital blueprint translated into a physical vehicle.

Deployment Roadmap

The transition from raw patient data to manufacturing-ready blueprints in 12 months.

1

Secure Ingestion

Month 1-3

HIPAA compliant pipelines to ingest NGS genomic files (FASTQ/BAM).

2

Cargo Assembly

Month 4-6

Isolating driver mutations and optimizing mRNA sequences via Immunostruct.

3

Vehicle Engineering

Month 7-9

Structural ESM-3 models design custom AAV capsids or LNP ligands.

4

Go-To-Market

Month 10-12

Launching the compiler for partner labs to synthesize drugs on-site.

Disruptive Economics

By replacing physical labs with computational intelligence, we achieve Enterprise SaaS margins in a historically capital-heavy industry. We don't manufacture drugs; we manufacture the information to build them.

Zero CapEx

No physical wet-lab footprint or maintenance costs.

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Scale Margins

Usage-based token model matching software gross margins.

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Open Leverage

Built on billions in open-source research (ESM-3, OpenFold).

Longevity Ready

Agnostic architecture adaptable to longevity and rare disease.

CapEx Comparison (USD Million)

Estimated comparison: Traditional Gene Therapy Corp vs. OncoPrint AI Platform Model

Invest in the Future of Oncology

OncoPrint AI is currently seeking strategic partnerships and funding to accelerate the deployment of our computational compiler. We are looking for visionary partners who want to transform personalized medicine into an asset-light, highly scalable SaaS ecosystem.

Areas for Collaboration:

  • Integrating clinical multi-omic datasets to refine our ESM-3 and Immunostruct pipelines.
  • Partnerships with high-throughput CROs for rapid in vitro validation loops.
  • Strategic capital to expand cloud infrastructure capacity for global scaling.

Let's Build the Compiler.

Reach out directly to discuss technical integration, investment opportunities, or to schedule a live demonstration of the pipeline.

AS

Avinash Singh

Enterprise Architect & Founder

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Direct Contact

+91 9958600928