High-Throughput mRNA Discovery Strategy | BioTech360

BioTech360: Direct Alignment to Sanofi mRNA CoE Pillars

Strategy & Roadmap for High-Throughput mRNA Discovery & Development

Strategic Alignment Overview

1. Data

Foundations & Continuity: Biology-native master assets that persist beyond isolated experiments.

2. AI

Explainability & Readiness: Semantic knowledge graphs enabling reasoning on biology.

3. Governance

Trust & Ownership: Auditability embedded in the data foundation, not retrofitted.

4. Scale

Portfolio Impact: Modular adoption enabling reuse across sites and programmes.

1. Data: Moving Beyond Isolated Records

Sanofi mRNA CoE Need: Reliable, reusable biological data across discovery, development, and scale-up.

Establishes biology-native master assets (DNA/RNA, plasmids) with enforced uniqueness.

Preserves biological lineage across constructs, variants, and experiments.

Operates above existing systems, ensuring continuity without system replacement.

Critical Traceability: mRNA Construct Lineage

BioTech360 maps the genealogy from initial plasmid design to final LNP formulation, linking experimental results to the unique biological entity.

2. AI: From Exploration to Readiness

Sanofi mRNA CoE Need

AI that can reason on biology, not just consume disconnected datasets.

BioTech360 Contribution

Provides a semantic knowledge graph where entities and results are contextually connected.

Structures data to FAIR principles for traceable, explainable AI.

Ensures AI outputs are grounded in biological context, reducing black-box risk.

Impact: Acceleration Through Reuse

BioTech360 structural continuity dramatically reduces time spent on data harmonization.

3. Governance: Embedded Trust & Compliance

Ownership

Deployed in Sanofi-controlled environments ensuring full data sovereignty.

Harmonization

Ontology-based models replace ad-hoc conventions for true interoperability.

Auditability

Scientific traceability aligned with enterprise governance from day one.

System-Agnostic Architecture

BioTech360 acts as the connective tissue, integrating with existing LIMS, ELN, and Analytics tools versus replacing them.

4. Scale: From Research to Portfolio Impact

Avoid siloed point solutions that block portfolio-level insight.

Modular Adoption

Start with specific biology workflows, expand incrementally.

Knowledge Reuse

Enable reuse across projects, sites, and therapeutic areas.

FAIR Data Transformation

Current State: Fragmented

• Data locked in PDF/Excel

• Ambiguous naming conventions

• Lineage lost during external transfers

With BioTech360: Connected

• Machine-readable entities

• Standardized ontologies

• Complete genealogy (Gene->Protein->Assay)

The Bottom Line

BioTech360 does not compete with Sanofi’s digital R&D stack. It stabilizes and connects it.

Ensuring biological meaning, lineage, and context persist across systems — a prerequisite for scalable AI and confident decisions.