Built on science.
Engineered for outcomes.

Decode combines an automated R&D engine with deep multiomics and clinical data expertise so your program moves from question to validated findings ready for your commercial roadmap.

Decode’s structured program model combines repeatable platform methodology with deep scientific expertise, producing results that hold up under commercial and regulatory scrutiny. Self-service tools require you to supply the science. Traditional engagements don’t compound. Decode solves both.

How the Platform Works

Every program runs through three structured phases with a defined scope, a fixed deliverable, and a clear decision gate at each step.

Every program runs through three structured phases with a defined scope, a fixed deliverable, and a clear decision gate at each step. Decode combines three things most R&D programs have to build separately: access to real patient data, an automated analytical engine, and deep scientific expertise in multiomics, clinical data, and health economics.

Programs start with a defined scope so partners can evaluate on real results before expanding. As programs demonstrate value, commercial structures naturally broaden into licensing, milestone-based arrangements, or revenue-sharing models. Partners often find that the first program opens the door to the next.

The platform improves with each program. Every engagement adds to a more calibrated pipeline, a richer proprietary data estate, and a deeper body of validated methodology. These are compounding assets that software alone cannot replicate. Your second program runs faster than your first.

As individual components mature, more of the pipeline runs autonomously, freeing the scientific team to focus on study design, biological interpretation, and commercial strategy.

01 Discovery Sprint

Define the question, map your data, agree on what success looks like before any platform work begins.

Inside Phase 1

Structured kickoff with Decode’s scientific and clinical team
Review of available data sources: your data, Decode’s proprietary cohorts, or public datasets
Identification of 1-2 use cases with the clearest commercial and scientific rationale
Agreement on measurable success criteria before any pipeline work begins

02 Platform Development

Dozens of standardized analytical steps from ingestion through results, spanning automated processing and expert-configured analysis.

Inside Phase 2

Multi-modal data integration across genomic, clinical, claims, and real-world sources, harmonized into a unified analytical framework
Competitive ML modeling across multiple algorithm families, with generative AI accelerating hypothesis generation
Every significant finding mapped against published literature with mechanistic context and evidence grading
Quality control at every stage with auditable outputs across genomic, clinical, claims, and real-world data

03 Results For Your Next Stage

Validated findings structured for commercialization, regulatory review, investor diligence, or the next phase of your program.

Inside Phase 3

Ranked biomarker panels with standardized result packages structured for scientific and commercial review
Validated risk models with clinical and economic context for payer, partner, or licensing conversations
Evidence packages ready for regulatory, diligence, or commercialization use
Every program produces IP with commercial value, with terms structured to align incentives around outcomes

The Data Advantage

Proprietary Cohorts

IRB-approved, annotated patient cohorts across neurology and select disease areas, with established pathways to extend into new conditions. For the right programs, meaningful analysis can begin immediately.

Public & Licensed Data Acceleration

The platform is designed to work with publicly available multiomics datasets (DNA, RNA, protein) and licensed claims and EHR data, dramatically reducing the time and cost of de novo data collection.

Data Partnerships

When neither proprietary nor public data exists in sufficient depth, Decode’s established relationships with clinical networks, biorepositories, and sample collection partners provide a solution. The absence of data is a solvable problem, not a program blocker.