Model-First Design for Medical Research
Turn critical protocol choices into decisions you can defend
Even robust science fails when fragile design assumptions meet real-world variability, and that decision has to survive review, scrutiny, and hindsight
We turn implicit design choices into explicit decisions, supported by written, model-backed justification
that you can stand behind with reviewers, funders, and regulators
Written modelability assessment · ~1 business day · No sensitive IP
What we actually do for you
Most teams already have strong clinical and biological hypotheses. Where studies struggle is in the design logic
The chain that connects:
- who is included (inclusion / exclusion criteria)
- when and how often interventions happen (timing & scheduling)
- how much and through which route (dosing & delivery)
- what you measure and when (endpoints & assessments)
- and under which operational constraints (recruitment, logistics, CMC, budget)
Every one of these links hides a decision that will later be questioned
What we do is force those choices into the open
So one design path can be chosen, justified, and defended in writing.
At Method2Model, we don’t just “build a model” or generate more sensitivity plots
We co-author the logic of your protocol and make it:
Explicit
all major assumptions and constraints made visible
and reviewable.
Stress-tested
evaluated against recruitment drift, drop-out, missingness, and operational variability.
Defensible
backed by a transparent model that explains why one design path is preferred over others.
Instead of handing you scenarios, we deliver one recommended decision
and a Rational Design Justification that explains why it holds.
Where Method2Model fits in your work
Method2Model is most valuable when:
- You are 2–6 weeks away from a funding, ethics, or protocol submission deadline, and you know at least one design choice will be challenged.
You have competing design options (e.g., two dosing schedules, two delivery platforms, or two endpoint strategies) and no neutral way to compare them. - A previous or pilot study produced ambiguous or “null” results, and you want to prevent the same failure mode in the next iteration.
- Internal stakeholders (clinical, biostatistics, CMC, operations) do not fully agree, and you need a structured, documented way to converge on one design.
- You need to convince an external body (DSMB, regulator, partner, or investor) that your design is not only scientifically sound but also resilient under real-world constraints.
If any of these sound familiar, you are already making the decision, just without a defensible record
On the Solutions page
we map these situations into 12 concrete Method2Model use cases
Each illustrated with articles and case reports so you can see exactly how the method translates into practice
If you’re not sure which one applies, Stage-0 will route you to the right use case in one day
Shared accountability for high-stakes decisions
You own the clinical hypothesis. We own the logic integrity
Your team brings the indication knowledge, patient reality, and scientific rationale.
We bring the tooling and discipline to ensure the protocol logic is internally consistent and robust.
Our role is to:
- Formalize your assumptions into a transparent architecture (who, what, when, how often, under which constraints).
- Expose where hidden fragilities live (e.g., sensitivity to recruitment pace, adherence, assay variability, CMC batch drift).
- Provide a rigorous technical defense of the chosen design that can be inspected by reviewers and regulators.
You remain the owner of the clinical and biological story
We sign our name under the logic of the decision your protocol is built on
This principle sits at the center of how Method2Model works with every client.
How it fits into your workflow
We plug into your existing research and development workflow in clearly separated stages:
Feasibility Assessment (Free)
You send a short description of the decision you are stuck with.
We respond with a written note stating:
whether the decision is modelable,
what kind of model is required.
and which decision class it belongs to.
Architecture & Assumptions
We map your protocol into
an explicit architecture
and an Assumptions / Logic Risk Register.
Formula Pack & I/O Contract
We formalize the agreed architecture into equations plus a precise input–output schema, ready for implementation.
Code, Runs & Proof of Match
We deliver executable code, example runs, and verification materials if you want us to implement the model.
For a detailed view of each step, see the Process page.
What you receive in practice
Each deliverable exists to answer one question:
“Why was this design choice reasonable at the time it was made?”
Modelability Report (Stage-0)
a concise document on whether and how modeling can de-risk your decision.
Assumptions Map / Logic Risk Register
a structured, citable record of what must “go right” for your design to work.
Strategic Design Brief
(Decision Note)
a written recommendation of one preferred design path, including conditions and trade-offs.
Formula Pack & I/O Contract
the mathematical spine and data interface that make the model reproducible and auditable.
Executable Model & Example Runs (Stage-3)
code and configs ready to integrate into your internal workflow.
Reviewer-Ready Appendix (optional)
figures and explanations that can be adapted for protocols, grants, or regulatory submissions.
All documents are delivered in research-grade, citable formats (PDF/LaTeX, structured data, and version-controlled code)
Proof you can inspect
We maintain public, de-identified examples of our work so you can see what you are actually buying:
A full Stage-1/2/3 package for a dual-platform mRNA therapy in X-linked adrenoleukodystrophy (ALD) — including architecture, formula pack, executable code, and verification materials.
Accompanying code repositories with executable examples, configuration files, and documentation on platforms such as GitHub.
A growing library of case reports and articles that mirror the 12 Method2Model use cases on the Solutions page , from in-vitro screening systems to protocol redesign and power-drift risk analysis.
These deliverables are hosted on scientific platforms (e.g., Zenodo, GitHub) in formats that are transparent and citable. They are not marketing slides. They are real, inspectable artifacts that your peers, reviewers, and partners can read, run, and critique.
Selected modeling case studies
Here are a few public-facing examples showing how we turn study methods into transparent, reviewable computational models—and targeted in silico experiments that support real-world decisions.
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Dual-Platform ABCD1 mRNA Therapy for X-Linked ALD | Method2Model
Most ALD mRNA programs don’t fail on biology—they fail on decision ambiguity: unclear…
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In-Vitro Screening System — Complete Architecture + Formal Formula Pack for Deterministic QC and Selection (5HN & CD8)
This case study documents an end-to-end, stage-locked in-vitro screening system for sOMF exposure…
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Equilibrium Window of Health: Early-Drift Monitoring Core (Stage-Locked, Deterministic, Event-Aware)
Equilibrium Window of Health is a stage-locked, event-aware early-drift monitoring core designed for…
Who we stand next to in decisions
Clinician-researchers & PIs
Designing or adapting single high-stakes studies (rare and complex diseases, cell & gene, mRNA, targeted therapies) who must justify their choices to ethics boards and funders.
Academic & hospital groups
With multiple protocols and a need for a reusable, defensible modeling core that supports repeated decisions across projects.
Small pharma, biotech, medtech teams
For whom one fragile trial, CMC constraint or mis-timed endpoint can erase years of work, and who want decisions that can survive external review.
Articles & deep dives on decision-focused modeling
We write openly about the ideas behind Method2Model:
how assumptions break trials, how power erodes in the real world,
and how to treat modeling as a way to stabilise decisions, not just to generate plots.
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A Bridging mRNA Strategy for ALD: How “Model-First” Design Prevents Million-Euro Mistakes
Dual-platform mRNA programs multiply uncertainty—and teams often pay for that…
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Targeted Delivery of Chemotherapy and Immunotherapy: From Concept to Clinic
Targeted delivery systems for chemotherapy and immunotherapy aim to flip…
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mRNA Therapy as a Bridging Strategy in Adrenoleukodystrophy (ALD): Stabilizing Patients While Awaiting Curative Treatment
A time-limited “bridge” therapy with ABCD1 mRNA could help stabilize…
Privacy, ownership, and publication
Your methods, data, and models are treated as confidential project material. This is especially important in computational modeling for medical research, where sensitive clinical information and early-stage ideas are often involved.
NDAs are available on request. Models and code built for you can remain fully private; publication, reuse, or open-sourcing only happens with your written approval. Ownership of project-specific models can be clearly defined from the start.
When you choose to publish, we are happy to support you in integrating the model into manuscripts, internal reports, or regulatory submissions—for example by providing technical appendices, clear descriptions of the modeling workflow, and reproducible code snippets.
If you need NDA from day 1, we can start Stage-0 under NDA as well.
Not sure if your protocol is modelable and defensible?
Don’t commit to a six-figure study on an unstated assumption.
Turn it into a decision you can defend , in writing.
Stage-0 answers one question:
“Is this protocol modelable and where would it fail first?”
