Frequently Asked Questions (FAQ)

1. What does Method2Model.com actually do?

Method2Model turns real-world medical, pharma, and allied-health study methods into decision-focused, inspectable modeling assets. We are method-focused, not outcome-judging: we make decision logic explicit, testable, and defensible under review.

• A clear, reviewable model architecture (method + decision logic made explicit)
• A transparent mathematical model (formulas + inputs/outputs + assumptions)
• Reproducible code you can run, plus verification evidence
• Optional managed runs (we run the code for you under NDA/DPA on sensitive data, if needed)
• Concise decision notes explaining what the outputs imply for your next step

You bring the clinical context, protocols, and constraints. We translate them into explicit, testable decision logic and deliverables you can defend under scrutiny.

2. Who is this service for?

Typical clients include:

• Clinician–researchers facing high-stakes protocol, endpoint, dosing, measurement, or interpretation decisions
• Academic and hospital research groups needing reviewer-ready justification for design choices (IRB, grants, publications)
• Small pharma, biotech, and medtech teams needing defensible go/no-go, design, or amendment decisions
• Funds & Boards (Governance) de-risking portfolio milestones via protocol integrity audits and inspectable artifacts

You do not need to be a mathematician or programmer. Clinical and research expertise is enough.

3. What kinds of projects are “modelable”?

A project is usually modelable if:

• There is a clear method or protocol (or a draft we can refine)
• Key elements can be described as states, flows, events, and decisions over time
• There is a defined decision gate the model should support (e.g., before protocol lock, before submission, after results)

Examples include decision problems such as:

• Power/sample size under real-world heterogeneity and missingness
• Endpoint selection and measurement timing strategy
• Dosing, scheduling, PK/PD trade-offs, and adherence realism
• Disease progression or response trajectories
• Patient flow through diagnostic/treatment pathways and operational constraints

If you are not sure, Stage-0 Logic Check is designed to answer “is this decision modelable, and what is the lowest-effort defensible path?”.

4. What is Stage-0 Logic Check and why is it free?

Stage 0 – Stage-0 Logic Check (Free) is a short, honest, no-obligation review designed to route you to the right decision path.

You share a non-sensitive summary of your decision, question, and method (a short description is often enough). We reply with a brief written assessment covering:

• Whether it looks modelable (as defined above)
• If it could be modelable with changes (and what changes)
• The most realistic next step: a suggested decision use case (one of 12) and the minimum inputs for Stage 1
• For funds/boards (if applicable): a suggested governance tier

Stage 0 is free because it protects both sides from starting the wrong project. It is designed to be non-sensitive and does not require a contract or NDA.

5. What should I (not) send in Stage 0?

Stage 0 is intentionally non-sensitive. A short summary is enough. Please avoid sending identifiable patient data, full datasets, or proprietary partner documents.

• Good: a 5–10 line description; draft protocol outline; the decision gate you’re at; endpoint list; timing plan; constraints.
• Avoid: identifiable data; full raw datasets; confidential sponsor contracts; anything you would only share under NDA/DPA.

6. What happens after Stage 0?

If both sides want to continue, we propose a scoped plan for Stage 1 (deliverables + price bracket + timeline), anchored around the specific decision gate we agreed to support. Work then progresses stage by stage with review checkpoints and approvals:

1. Stage 1 – Logic Lock & Architecture (Assumptions Map + Architecture + Input Spec + Verification Plan)
2. Stage 2 – Formula Bridge (Formula Pack + I/O Contract + scenario configs)
3. Stage 3 – Code & Evidence (runnable code package + runbook + verification evidence)
4. Stage 4 – Managed Runs (optional) (we run the code for you under NDA/DPA on sensitive data, if you want)

You only commit to one paid stage at a time. Each stage has clear deliverables, a review pass, and an approval step before moving on.

7. Do I need to have data before starting?

Not necessarily.

• Stages 0–1 mainly need a method/protocol and a clear decision gate, not full datasets.
• Stage 2 benefits from any available data (even partial) to set realistic units, ranges, and variability assumptions.
• Stage 3 can be delivered with synthetic or de-identified example data so you can run and test the pipeline.
• Stage 4 (optional) can use your real data if you want us to run it under NDA/DPA.

If you have no data yet, we can still build a strong model foundation and specify what data would be most valuable to collect for future decisions.

8. How much mathematics or coding do I need to know?

Very little.

• You do not need to write equations or code.
• We explain the model in plain language, using diagrams and tables where helpful.
• You remain the expert on clinical meaning, plausibility, and constraints; we translate that into decision-focused model form.

9. Which medical fields do you work in?

Our focus is on:

• Medicine and clinical research
• Pharmacology / PK–PD / exposure–response questions
• Oncology, neurology, pediatrics, rare disease
• Allied health (rehab, physio, etc.) when there is a clear structured method
• Clinical pathways, diagnostics, workflows, and logistics

If your project falls clearly outside health and life sciences, we may decline or redirect you after Stage 0.

10. How do you communicate during a project?

We keep communication in one main place:

• A project dashboard where you can upload files, review drafts, approve deliverables, and respond to questions.

Email notifications mirror what happens in the dashboard, so you do not have to keep checking manually.

We ask that you:

• Respond to key questions and drafts within a reasonable time
• Tell us early if your method, constraints, or endpoints change, especially if it affects the target decision gate

If we cannot get answers after repeated reminders, we may pause the project until the missing inputs arrive.

11. When do you sign an NDA or data-processing agreement?

Stage 0 is non-sensitive and requires no NDA. NDAs and data-processing agreements (DPA) are available from Stage 1 onward when appropriate.

In most cases, we can do a lot with de-identified or synthetic data. Identifiable patient data is rarely needed, and if it is ever involved, it must be handled under proper approvals and agreements.

12. How do you handle my data, privacy, and publication?

• We do not publish your raw data, identifiable information, or confidential project specifics.
• We prefer de-identified or synthetic data whenever possible.
• Transparency stance: we may publish sanitized examples of code patterns, reusable components, and general model templates that show what type of decision gate a model supports—without any client-specific inputs, results, or sensitive context.
• If you need everything to remain fully private (including abstracted model patterns), tell us upfront. This may require additional scoping and can affect pricing.
• Governance mode (optional): audits can run in full privacy mode by default upon request.

More details are described on the Policies page.

13. Who owns the models and code?

In short:

• Your original methods and data remain your intellectual property.
• The project-specific code package delivered in Stage 3 is yours to use and run to support your own research and decision-making. (Any special commercial/IP terms should be agreed before Stage 2 or Stage 3 starts.)
• We may reuse our own pre-existing libraries, internal tooling, and generalized templates across projects. When we publish examples publicly, they are sanitized and non-client-specific (unless you request no-publication).

14. Can I run the code myself? Do you also run it for us?

Yes. Stage 3 delivers code you can run on your own system (with a runbook and configs). If you prefer, Stage 4 is optional: we can run the code for you under NDA/DPA on sensitive data and deliver results and a run certificate, plus short decision notes summarizing what the runs imply.

15. How is pricing structured?

• Stage 0 is free.
• Stages 1–3 are paid and scoped with clear deliverables and a price bracket.
• Stage 4 (managed runs) is optional and quoted based on run volume and constraints.

Price depends mainly on:

• Complexity of the method, target decision gate, and desired outputs
• Number of scenarios and outputs
• Verification/reproducibility requirements
• Whether the scope is a scenario add-on or an architecture change

An overview is available on the Services & Pricing page; exact scope and pricing are confirmed after Stage 0.

16. When do I receive the files?

For each paid stage:

1. We prepare a draft for your review.
2. You send comments and we make revisions within the agreed scope.
3. Once the stage is approved and payment is completed, we unlock the final deliverables in your dashboard and send an email confirmation.

Until payment is complete, drafts may be shared for review, but final downloadable files and full code may remain locked or watermarked.

17. What are the main limitations of your service?

Important boundaries:

• We provide research and decision-support modeling, not direct medical advice.
• We do not make clinical decisions for individual patients.
• We do not provide regulatory approvals and we do not guarantee trial outcomes or commercial success.

Models are always approximations. Their usefulness depends on the quality of the method, data, and assumptions. You remain responsible for how you interpret and use the outputs in your own decisions.

18. How do I get started?

Starting is simple:

1. Go to the Stage-0 Logic Check page.
2. Fill in the short form and share a non-sensitive summary of your method/protocol and the decision gate you want support for.
3. We review it and send you a short written answer: whether it is modelable, what the lowest-effort defensible next step looks like, which decision use case fits best, and what minimum inputs we need for Stage 1.

If you have a question that is not covered here, please contact us through the Contact page or mention it in your Stage 0 submission.