Live platform · Sponsors · Biotech · CRO operations

Closed‑loop clinical supply planning for complex IMP trials

Import the planning file your team already trusts. Prove parity against your baseline with round‑trip validation. Then run every cycle — plan, approve, export, load actuals, measure, re‑plan — with an audit trail behind each step.

Plan your trial supply Book a demo

No implementation project. Parity is verified before your team relies on a single number.

  • Deterministic logic. Same inputs, same plan, every run.
  • File‑based migration. Round‑trip validation against your source.
  • Closed‑loop workflow. Baseline to re‑plan, on the record.
  • Audit‑ready. Append‑only planning history.
  • Global visibility. Coverage per depot and per country.

01 — Why ClinSupplyCompass

The middle ground clinical supply teams were missing

Most supply teams live at one of two extremes. On one side sits file‑based planning: logic your planners trust and have refined over years — but no baseline control, no actuals feedback, and nothing an auditor can follow. On the other side sit heavyweight enterprise suites: operational discipline bought at the price of a multi‑quarter process replacement and planning logic your team no longer recognizes.

ClinSupplyCompass is built for the ground between. It imports your existing planning file as a complete, runnable study and proves parity against your trusted source before your team relies on it. Then it adds what a static file cannot: approved baselines, actuals ingestion, forecast‑accuracy KPIs, and disciplined re‑planning — with every cycle preserved as evidence.

You keep the planning logic you trust. You gain the operational loop you were missing.

02 — Capabilities

What the platform does today

Everything below is live in the production application — not a roadmap, not a preview.

  • Deterministic planning engine. Same inputs, same plan — every number explainable.
  • Depot‑ and country‑aware coverage. Months of supply and forward coverage, risk‑signaled.
  • Parity‑proven migration. Your planning file imported, then validated round‑trip.
  • Closed‑loop discipline. Baseline, actuals, KPIs, re‑plan — on the record.
A

Multi‑drug, multi‑country, multi‑depot planning

Model complex IMP studies as they actually run: several drugs, dozens of countries, multiple depots, and explicit country‑to‑depot routing. The plan reflects your real network, not a simplified one.

B

A deterministic planning engine

The same inputs always produce the same plan. Every quantity traces back to inputs and stated assumptions — no black‑box decisions between your planners and the numbers they sign off on.

C

Depot‑ and country‑aware coverage

Months of supply and months of forward coverage, computed per depot and per country, with risk signaling that separates healthy coverage from tight from critical — so attention lands where it should.

D

Demand outputs for downstream processes

Each planning cycle produces a demand output your enterprise planning and procurement processes can consume — the bridge from study‑level planning to organization‑level execution.

Arrive without a leap of faith

Migration is where planning platforms usually lose a team’s trust. Here it is where trust is established.

  • Study import from your planning file. A complete, runnable study — populations, countries, depots, timing — created directly from the file you plan with today.
  • Parity, proven — not promised. Imported files are validated by round‑trip verification against your trusted source. You confirm fidelity before you rely on the platform, not after.
  • Guided study setup. Study‑design‑aware forms in business language — including multi‑country regulatory approval timing, crossover, double‑blind, and titration designs — with a preview of outputs before anything is saved.
  • Drafts with autosave. Study setup pauses and resumes without loss, so a setup that spans days and interruptions never starts over.

Discipline inside the loop

Forecast Accuracy KPIs with honest status
Accuracy is always measured against the approved baseline. When data is missing, the metric reports as unavailable with the reason stated — never a fabricated number, and missing actuals are never read as zero.
Explainable Data Quality scoring
Weighted, named components with business‑language bands and reasons. A score you can defend, because you can see how it was built.
Append‑only planning history
Every plan‑versus‑actual comparison is preserved as traceable evidence across cycles. Nothing is overwritten; nothing quietly disappears.
Retention‑ and discontinuation‑aware re‑planning
Expected retention curves, dropout assumptions, and actual discontinuation counts inform every re‑plan — and assumptions and observed facts are never double‑counted, so plans reflect reality without compounding it.
Supply recommendations each cycle
Every planning cycle closes with concrete supply recommendations, generated from the same deterministic logic as the plan itself.

Visibility for the people accountable

Portfolio readiness check‑in
Cross‑study readiness states for operational leadership — concise, current, and readable on a phone between meetings.
Organization‑level dashboard
Study health and momentum across the portfolio, for the owners answerable when a study runs short.
Planner‑first, business‑language experience
Every planner‑facing term and metric is defined in the built‑in plain‑language Concepts reference. No internal jargon reaches your team.

03 — The closed loop

One loop. Six steps. Every cycle on the record.

This is the discipline a static planning file cannot give you — and the reason a plan here is evidence, not just a forecast.

  1. Plan. The deterministic engine turns study design, enrollment assumptions, and your supply network into a complete, explainable plan.
  2. Approve baseline. The team commits to a plan. From this moment, accuracy has a fixed reference — the baseline your KPIs answer to.
  3. Export demand output. The approved plan becomes a demand output for enterprise planning and procurement processes downstream.
  4. Load actuals. Enrollment and shipment actuals enter the study. They stay distinct from assumptions — observed facts, labeled as such.
  5. KPI snapshot. Forecast accuracy is measured against the approved baseline. Missing data reports as unavailable, with the reason — never as zero.
  6. Re‑plan. A new cycle begins from reality: retention curves, dropout assumptions, and actual discontinuations — never double‑counted.

Three rules the platform never breaks

Parity is proven, not promised.

Imported planning files are validated round‑trip against your trusted source before your team depends on them.

Metrics are honest.

When data is missing, the platform says “unavailable” and tells you why. It never invents a number, and missing actuals are never read as zero.

Assumptions and facts never double‑count.

Planning assumptions and observed actuals are kept distinct, so re‑planning reflects reality without compounding it.

04 — Where it sits

Chosen against real alternatives

Against static file‑based planning

Your planning file holds real intelligence — that is exactly why it is imported and verified rather than discarded. What a file cannot hold is a loop: an approved baseline, actuals flowing in, accuracy measured against commitments, and a history nobody can quietly edit. ClinSupplyCompass keeps the logic and adds the loop.

Against generic planning platforms

General‑purpose demand tools do not know what a titration arm is, why country‑level regulatory approval timing gates enrollment, or how blinding constrains supply. ClinSupplyCompass is built on those realities — crossover, double‑blind, titration, multi‑country approval timing — not retrofitted with study‑shaped fields.

Against heavyweight enterprise suites

A full suite asks you to replace how your team plans before it proves it deserves to. ClinSupplyCompass is not a CTMS and does not attempt to absorb your operation: it takes on supply planning, executes it with auditable discipline, and starts from the file you already trust — days of adoption, not quarters of implementation.

05 — Who it’s for

Four seats at the same table

Sponsors

Portfolio‑level readiness states and an organization dashboard give accountable owners a defensible answer to “are we covered?” — per study, per country, per depot.

Biotech

A lean team heading into a pivotal study gains closed‑loop planning discipline without adding headcount — starting from the planning file it already maintains, operational in days.

CROs

Run many studies for many clients with each client’s studies kept strictly separate, access scoped to responsibility, and every action on the record — plus parity validation to show each client their planning logic survived the move.

Planners & supply operations

The professionals who run the loop day to day work with deterministic numbers they can explain and defend, business‑language forms, drafts that autosave, and a plain‑language Concepts reference for every term on screen.

06 — Trust

Built like the regulated industry it serves

Clinical supply data is competitive, confidential, and consequential. The platform treats it that way.

  • Your studies are yours alone. Every organization’s data is kept fully separate, end to end — separation is built into the platform, not left to policy.
  • Access follows responsibility. Planners, approvers, and viewers each see and do exactly what their role requires — nothing more.
  • Actions are on the record. Consequential steps — including every baseline approval — are recorded: who, what, when.
  • History cannot be rewritten. Every plan‑versus‑actual comparison is preserved as evidence across planning cycles.
  • Metrics stay honest. “Unavailable, and here is why” is enforced by the platform itself — a missing number is never invented.

07 — Coming next

Where the platform is heading

Everything in this section is future work — in development or planned, and clearly not part of the platform today. It ships when it meets the same standard as everything above.

In development

Deeper inventory realism

Lot‑ and batch‑level expiry, first‑expiry‑first‑out logic, and stability pull‑points — so coverage accounts for when supply expires, not only where it sits.

In development

Finer‑grained demand truth

Dispensing‑level demand actuals and the accuracy metrics they make possible, extending the honest‑KPI discipline to a finer resolution.

Planned

Sharper clinical assumptions

Per‑drug and per‑arm retention curves, and treatment‑age‑aware discontinuation attribution — richer clinical shape in every re‑plan.

Planned

Sharper supply logic

Dynamic safety buffers and required‑by‑date lead‑time logic, tightening the connection between coverage risk and reorder timing.

Planned

Wider planning reach

Site‑level distribution and patient‑level dosing, extending today’s depot‑ and country‑level planning downward.

Planned

Optimization & scenarios

Cost and comparator optimization, and assistive AI scenario planning — held to the same rule as today’s assistant: grounded in your data, never the planning engine.

Start now

Bring the file you already trust

Adoption here is not a leap — it is a verification. Create your organization, import your current planning file, run the round‑trip parity check against your baseline, and see your own study running in a closed loop. If the numbers don’t match your trusted source, you will know before you commit to anything.

  1. Create your organization — self‑service, no implementation project
  2. Import your planning file into a complete, runnable study
  3. Validate parity round‑trip against your trusted baseline
  4. Approve your baseline and start the loop
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