The signals sit in different teams
Site operations, clinical operations and clinical supply each hold part of the picture. The handover between them is where planning problems are usually discovered too late to act on cheaply.
Solution FamilyLife Sciences & Clinical Operations
Clinical Trial Supply Chain Intelligence
Four independent experiences, one connected clinical-supply decision journey
Clinical-supply decisions are rarely undone by a single bad number. They are undone by a signal that never travelled — a site quietly under-recruiting, an enrollment curve bending away from plan, and a depot that finds out too late to matter.
This family follows that chain deliberately. Four independent synthetic-data experiences each own one specialist decision domain, and together they show how site execution becomes an enrollment outlook, how an enrollment outlook becomes clinical-supply requirement, and how that requirement resolves into a resupply response a person still has to approve.
Clinical OperationsEnrollment OutlookClinical SupplyConnected Decision JourneySynthetic Data
Synthetic clinical-trial data onlyNo patient dataOperational planning, not clinical decisionsHuman review required
Why This Family Exists
Clinical supply is a chain of derived signals
Site execution shapes enrollment. Enrollment shapes patient demand. Patient demand becomes kit demand, which then has to be reconciled against depot and site inventory, expiry exposure, shortage risk, shipment conditions and resupply timing. Each link is a specialist decision — and each one inherits the quality of the link before it.
Supply demand is derived, not observed
Nobody measures kit demand directly. It is inferred from how many patients are expected, which is inferred from how sites are actually recruiting — so an error early in the chain arrives late and amplified.
Specialist depth still matters
Collapsing site performance, enrollment forecasting and supply planning into one view loses the depth each decision needs. The answer is connected experiences, not a merged one.
The last step belongs to a person
Every path in this family ends at a qualified reviewer. Nothing here approves, releases or executes a clinical-supply action.
How to read this family
The four experiences are independent — none contains another, none is a parent of another, and each can evolve on its own. They are also connected: the business signals genuinely flow across them in one direction, from process foundation through site execution and enrollment outlook into clinical supply planning. Independent experiences, one connected decision journey. Everything shown across the family is built on synthetic data.
Decision Framework
Family decision journey
One sequence across the whole family, with the owning experience named at every stage. This is the contract that keeps the four experiences from telling the same story twice.
- Stage 01Process foundationEstablishes the SAP-aligned process and object context the family assumes — study setup, planning, manufacturing and packaging, distribution and traceability.SAP Clinical Supply Foundation
- Stage 02Site readiness & current executionWhich sites are executing well right now — ranking and selection support, site profiles, and where dropout, protocol-deviation or data-quality exposure is accumulating.Site Performance Intelligence
- Stage 03Observed recruitment signalWhat sites have actually screened and randomised so far. Measured behaviour, and the evidence any forward view has to be built on.Site Performance Intelligence
- Stage 04Forward enrollment outlookWhere enrollment is heading over the forecast horizon, held against a naive baseline and evaluated across successive historical origins before either becomes operational.Enrollment Forecasting & Site Risk Intelligence
- Stage 05Forecast-risk qualificationHow far to trust that outlook, and which sites contribute most to the risk of missing plan.Enrollment Forecasting & Site Risk Intelligence
- Stage 06Patient-demand signal becomes kit requirementThe enrollment outlook is consumed as an input and translated into kit demand across trials, arms, visits and kit types.Clinical Supply Planning & Resupply Intelligence
- Stage 07Inventory, stockout, expiry & shipment exposureWhere depot and site coverage is thin, which batches are close to expiry, and which shipments carry delay or cold-chain risk.Clinical Supply Planning & Resupply Intelligence
- Stage 08Resupply, exception & scenario responseCandidate resupply with quantity, urgency and transport mode, an ordered exception queue, and scenario replanning against a retained baseline.Clinical Supply Planning & Resupply Intelligence
- Stage 09Human clinical-supply decisionEvery output is a proposal. No experience in this family approves, releases, ships or executes anything.Qualified reviewers
The Four Experiences
What each experience uniquely owns
Each card states the decision domain that experience owns — and, where the boundary matters, what it deliberately leaves to a sibling.
Process Foundation
SAP Clinical Supply Foundation
The process and object context the rest of the family assumes.
An architecture and positioning page rather than a prototype application — no runtime, no dataset, no screenshots. It describes the clinical-supply process backbone across study and supply setup, planning, manufacturing and packaging, distribution and traceability, plus the SAP-aligned object and action vocabulary the three experiences borrow rather than invent.
Process contextObject modelAction vocabularyLifecycle & traceability
Boundary
Not an application. Site analytics, enrollment forecasting and supply planning all belong to the three active experiences.
Active Experience
Clinical Trial Site Performance Intelligence
How sites are executing now.
Site ranking and selection support, site profiles, observed recruitment performance, and site-level operational-risk indication across dropout, protocol deviation and data quality — with country and region comparison, operational scenarios and reason-carrying recommendations on synthetic data.
Site ranking & selectionSite profilesObserved recruitmentDropout & deviation riskData quality & monitoringCountry & region view
Boundary
Forward enrollment forecasting belongs to the next experience. Risk here is site-level operational indication, never patient-level prediction.
Coming soon
Active Experience
Clinical Enrollment Forecasting & Site Risk Intelligence
Where enrollment is heading, and how much to trust it.
Forward enrollment trajectory with the forecast method kept on screen — a naive baseline, an ML model, and one-step-ahead rolling-origin evaluation deciding which one becomes operational. On this synthetic dataset the baseline won, and the page says so rather than promoting the model.
Forward trajectoryForecast riskForecast methodologyRolling-origin evaluationSite contribution to riskIntervention review
Boundary
Site operations depth belongs to Site Performance Intelligence. Error figures are synthetic-data evaluation only, not validated accuracy.
Coming soon
Active Experience
Clinical Supply Planning & Resupply Intelligence
How forecasted patient demand becomes a supply response.
Enrollment-to-kit-demand translation, depot, country and site inventory position, stockout and expiry exposure, shipment and cold-chain risk, exception prioritization, scenario review and SAP-oriented action proposals — all on synthetic data, all ending at a planner.
Kit-demand translationDepot & site inventoryStockout riskExpiry & wasteShipment & cold-chain riskResupply proposals
Boundary
Enrollment is a consumed input here, not a forecasting capability this experience owns. Resupply is threshold and rule-based candidate logic, not mathematical optimization.
Coming soon
Connective Tissue
How the four experiences connect
The handovers, stated plainly. Each experience keeps its own depth; what travels between them is a signal, not a duplicated capability.
Foundation → all three
The foundation supplies the shared process and object language. The three prototypes reference it rather than redefining it.
Site Performance → Enrollment Forecasting
Observed site execution is the evidence the forward trajectory is built on. One measures what happened; the other projects what follows.
Enrollment Forecasting → Supply Planning
The enrollment outlook is the input that becomes kit demand. Supply planning consumes the forecast; it does not produce a competing one.
All three → a person
Each experience ends at a proposal with its evidence attached, and a qualified reviewer decides what happens next.
Connected, but not wired together
These handovers are a portfolio decision flow, not a technical integration. The prototypes are separate applications on separate synthetic datasets; no signal moves between them at runtime.
Family Scope & Governance
What this family is, and what it is not
This is a clinical-operations and clinical-supply planning family. It supports operational decisions about sites, enrollment outlook and supply position. It does not touch clinical, medical or regulatory decision-making, and these boundaries apply to every experience within it.
- Synthetic clinical-trial data only
- No real patient data
- No real clinical-trial, sponsor or site data
- Independent professional prototypes
- Operational planning support only
- No medical, treatment or patient-care decisions
- No protocol decisions
- No efficacy claims
- No patient-safety determination
- No product release or GMP disposition
- Not validated GxP or regulatory software
- No automated clinical-supply release
- No autonomous resupply execution
- No live SAP connection
- No live clinical-system integration
- No runtime integration between the experiences
- Modelled and simulated planning actions only
- Qualified human review required for every output
Possible Future Direction
Concepts under consideration for the family. These are directions of interest, not completed work and not part of the current family.
Investigational product riskTrial operations decision intelligenceCross-trial portfolio intelligence
Continue through the lab
This family sits alongside the flagship experiences and the Applied Supply Chain Intelligence prototypes in the Applied AI Supply Chain Lab.