Solutions & Evidence

A unified library of decision-focused modeling for medical research: use cases, case studies, and articles showing how high-stakes protocol and pathway decisions become explicit, reviewable models and simulations.

Method-focused, not outcome-judging — we make decision logic inspectable and testable.

You don’t need more services. You need to make the next high-stakes decision without betting months of work on hidden assumptions.

Why this exists

Most studies don’t fail because the science is wrong. They fail because one or two implicit assumptions quietly break in the real world — and the design decisions built on them only get questioned after time, budget, animals, or patients are already committed.

Illustration of the method to model process turning clinicians’ ideas and approved protocols into working computational models on screen.

What this prevents :

(the expensive version of “learning”)

Protocol rewrites and approval delays after “final” lock

“Null” results driven by variability, timing, or adherence instead of biology

Budget burn on measurements that never change the decision

We surface fragility early — before it becomes sunk cost.

What you receive (inspectable artifacts)

1

Assumptions & Fragility Register (MRR)

Ranked “what must go right” assumptions and failure modes tied to your decision.

2

Scenario Pack (Stress Tests)

Focused what-ifs (variance, missingness, drift, heterogeneity) that show which choices are robust vs fragile.

3

Decision Memo (review-ready)

A forwardable rationale: minimum fix set, trade-offs, and “what changes conviction” thresholds.

Artifacts are inspectable (LaTeX/PDF), versioned, and reviewable — not marketing decks.

Same library — different packaging

The modules below are shared. The framing differs by context: research delivery, product development, operational rollout, or governance triage.

What decision are you facing right now?

Pick the decision gate you’re at today:
  • About to lock (design risk / feasibility)
  • Finalizing sample size & budget (power / detectability)
  • Preparing external review (defensibility)
  • Mid-study drift / amendment (least-risk adjustment)
  • Results diverged (interpretation / next step)
  • Planning a redesign / next study (learning / v2)
  • Building a reusable asset (reuse / continuity)

If you’re evaluating a portfolio or governance milestone, use the same decision gates via → Governance.

Decision modules (library)

Protocol Blind-Spot Scan
Find protocol weaknesses before time, budget, animals, or patients are committed.
Real-World Power Check
Test study power under real-world heterogeneity, missingness, and behavior.
Measurement Decision Design
Choose what to measure and when—minimal burden, maximum decision value.
Regimen Robustness & Dose Decision
Stress-test dose and schedule against adherence, variability, and safety.
Transferability & Scaling Check
See what holds and what breaks when you move across populations or settings.
Care Pathway Reliability Check
Simulate bottlenecks and drop-offs before changing or scaling a pathway.
Reviewer-Ready Logic Pack
Make your protocol logic defensible for IRB, grants, and sponsor review.
Mid-Study Amendment Decision
Compare amendment options and choose the one that won’t invalidate the study.
Null-Result Next-Step Map
Turn “null” or weak results into a clear, defensible next-step decision.
Result Robustness & Reproduction Check
Check whether your result holds under re-runs and realistic uncertainty.
Hidden-Variable Discovery Pack
Use model–reality gaps to surface candidate confounders and missing links.
Reusable Decision Model Asset
Deliver a documented, reusable model your team can rerun, adapt, and extend.
See all use cases →

Not sure which block fits your situation? Stage-0 helps you identify which decision risks actually matter before you invest further. You get a short written verdict — modelable as-is, modelable with changes, or not a fit right now — plus the lowest-effort next step.

Enter Stage-0 (Logic Intake)

Evidence

Selected examples

A selection of computational modeling case studies where we turned medical and pharmaceutical methods into working models, simulations, and tools that support specific protocol and pathway decisions. Client-identifying details are removed; technical documentation and code are available on request for most projects.

If you’d like to see what a similar model could look like for your own project, you can start your own computational modeling case from our Stage 0 form.

Stylized Python logo made of neural mesh on a dark background, symbolizing code, simulations, and computational modeling articles.
Example Deliverables (Zenodo)


Public, versioned proof-of-work (Stage-0 → Stage-3).
Shows the exact artifact format we deliver: assumptions map, logic contract, formula pack, and tests.

Featured examples

(methods + medical)

These are examples of how we document and verify logic under publication and review constraints.
They are not claims about your specific study, they illustrate the architecture, rigor, and documentation standard we apply.

All Modeling Case-Studies

Browse the full library of computational modeling case studies, including dynamic health models, trial simulations, device models, and more.

Science & Articles

Brief articles and reflections at the intersection of computational modeling, medicine, and study design—many of which are also shared on LinkedIn and Medium. … together with the case studies above, they show how computational modeling can support real medical and pharma decision-making — from design and power to interpretation and reuse.

3D DNA helix over a dark background of digital code, representing medical and pharma computational modeling case studies.

Featured Articles

All Articles

All articles related to computational modeling, targeted therapies, and the future of human-relevant preclinical science.

Code & Reproducible Work (GitHub)

Each computational modeling case study here is backed by real code. For most projects, we keep a dedicated GitHub repository linked from the case page. If you want to explore the broader codebase and reusable modeling components, you can browse our GitHub profile.

Visit Github Profile

The repositories are organised by project, matching the case studies on this page (mRNA modeling, trial simulation, device models, etc.).