About Method2Model
from medical idea to defensible decision models
Bridging the gap between medical decisions and computational models
Method2Model is a small, focused medical computational modeling studio built for real-world medical and pharmaceutical research. We sit between two worlds: clinicians and researchers with strong protocols and hypotheses, and heavy modeling consultancies or in-silico platforms designed mainly for big-pharma workflows.
Our role is to bridge that gap. We help you move from an “interesting method on paper” to clear, testable decision logic and a small decision-focused model you can actually use in study design, review, or interpretation.
What we do
We translate your study method, protocol, or care pathway into explicit, reviewable model logic, then into formalized equations and reproducible code. The goal is simple: anchor the work around a specific high-stakes decision, and make that decision more defensible before execution, defensible under review, and interpretable after results.
Who we work with
Clinician
researchers
who see patterns in daily practice and want to test “what-if” scenarios in silico before committing to real-world decisions
Academic labs
that need models and simulations
they can reuse across projects
to support
design, power, and interpretation decisions.
Small biotech and MedTech teams
exploring therapies, delivery systems, diagnostics, or devices and needing defensible design and go/no-go decisions without building a heavy, opaque platform.
Typical questions we help answer
- “Can we stress-test this protocol before we commit time, budget, animals, or patients?”
- “Is our endpoint and timing sensitive enough to detect the effect we claim?”
- “Is our sample size powered for real-world variability—not a clean textbook assumption?”
- “What changed mid-study, and which adjustment is the lowest-risk?”
- “If results diverged, where did the logic break—and what should be our next defensible step?”
How we are different
Several things make Method2Model a bit unusual as a medical computational modeling studio:
Method first, modeling second
We don’t jump straight into equations. We start by making the method explicit: endpoints, assumptions, variables, constraints, and decision logic. If a method cannot be made model-ready around a clear decision, we will say so honestly—even if that means not building a model yet.
Designed for individual researchers and small teams
Most large modeling services are tuned for long enterprise contracts. We focus on the “long tail”: clinician-researchers, academic labs, PhD students, early-stage teams that need serious modeling—delivered in a format that fits real-world budgets and timelines and answers specific protocol and pathway decisions, not just “exploration.
Deliverables you can understand and reuse
We care as much about clarity as complexity. Our deliverables are reviewable: assumption logs, architecture diagrams, formal I/O contracts, and versioned code. You can re-run scenarios, change parameters, and explain what the model is doing—and how each result connects back to the decision it supports—without guessing.
Traceability and defensibility
down to the code
Every project is built so you can trace a decision: from protocol text → assumptions map → model architecture → formulas → code → outputs. That chain makes it much easier to defend your reasoning in manuscripts, reviews, and internal discussions.
Honest Go/No-Go culture
Sometimes the best research move is to not build a model yet: because the method is under-specified, the endpoint logic is mismatched, or the required inputs aren’t realistically obtainable. We tell you that early, so you can make a clear go/no-go decision instead of investing in an opaque black box.
Transparency, privacy, and IP
- Stage 0 is anonymous and requires no NDA.
- From Stage 1 onward, NDAs and data-processing agreements are available when appropriate.
- Client data is never published. We prefer de-identified or synthetic data whenever possible; identifiable data is rarely needed.
- Our transparency stance: we may publish sanitized, public-facing examples of code patterns, reusable components, and general model templates (showing what type of decision or question a model answers) without any client-specific inputs, results, or sensitive context.
- If you need everything to remain fully private—including any abstracted model pattern—tell us upfront. That request may require additional scoping and can affect pricing.
The person behind Method2Model
Method2Model is led by Dr. Ramyar Azar, a medical doctor with a strongly interdisciplinary background spanning clinical work and computational modeling. This “bridge” profile—clinic ↔ modeling ↔ product—shapes how the studio operates: we understand how a method reads in a protocol, how a model behaves in code, and what reviewers and stakeholders will ask when they challenge the decisions your study is built on.
How to start
You don’t need to be a programmer. You do need a real question, a method or protocol on paper, and a willingness to refine it.
The simplest way to begin is a free feasibility check (Stage 0). Share a short non-sensitive summary of your project and the decision you need to make (what you want the model to support). We’ll respond with an honest feasibility note, a suggested decision use case, and the minimum inputs needed to start Stage 1.