The published work
TrialTelemetry.com presents Kevin’s clinical-trial signal framework and a May 2026 white paper. The paper develops the March Operational Telemetry concept into a broader model for trial information, including endpoint, safety, patient, device, vendor, data-quality, and operational signals.
The website and paper are public work products grounded in his earlier operating history. They demonstrate a developed architecture and point of view. They are not presented as evidence of an undisclosed sponsor deployment or a regulator-endorsed product.
A signal needs an operating definition
The May paper treats a useful signal as more than a metric. It must have an identifiable origin, definition, timing expectation, context of use, and route to an accountable party. The model asks whether the underlying information is sufficiently complete, current, and trustworthy for its intended decision.
That distinction changes the architecture. Data may be suitable for exploratory analysis but not for a workflow with clinical consequences. An apparent change may reflect delayed entry, an altered definition, or a vendor bottleneck rather than a change in the underlying clinical or operational condition.
Systems of record remain important
The framework considers information from EHRs, EDC, CTMS, eTMF, IRT, eCOA, digital health technologies, safety systems, laboratories, imaging vendors, sites, and patient-generated sources. These are proposed source environments for the model. The framework coordinates signals across them while retaining their roles as systems of record.
Governance includes identity, authorized originators, timing, definitions, provenance, auditability, privacy, validation, change control, and traceability. The objective is to preserve enough context to know what moved through the system and why it was used.
C4I + Trust in practical terms
Kevin describes four interacting functions: ingestion, governance, analysis, and execution. Ingestion receives information with source context. Governance assesses whether and how it may be used. Analysis identifies meaningful patterns or exceptions. Execution connects the result to review, escalation, clarification, or an appropriately controlled automated task.
Trust is the condition for moving between those functions. The model also needs a record of what happened after a signal was generated: who reviewed it, what action occurred, and whether the action was documented.
Proposed use cases
The paper develops bounded use cases around recruitment and screening efficiency, query aging, site burden, vendor/infrastructure performance, digital endpoint readiness, safety-review support, and portfolio awareness. It also considers continuous inspection readiness and carefully defined regulator-facing signal exchange.
These are proposed applications of the framework. Each would require its own intended use, data assessment, evaluation, operational ownership, and appropriate specialist review. The paper is most useful as a way to make those dependencies explicit before a team commits to a technology implementation.
AI within a governed workflow
The design allows for rules-based, statistical, AI-assisted, and human analysis. Kevin places model context of use, input lineage, performance expectations, drift monitoring, human review, and accountability around any AI-derived signal. The model does not assume that an output becomes trustworthy merely because it can be generated quickly.
This connects the framework to his recent AI governance work and to the earlier clinical informatics experience. It also distinguishes current AI methods from the rules-based systems used in his historical remote-care programs.
Relationship to clinical operations and product leadership
The framework translates Kevin’s experience with patient-facing data capture, clinical systems, biosensors, vendor dependencies, quality, and distributed delivery into a lifecycle design method. Its pre-FPI review considers whether the trial can reliably generate and use the information on which its decisions depend.
The contribution is both strategic and practical: define a bounded need, map the data and human workflow, establish ownership and trust conditions, then evaluate the pathway before scaling it. The independent framework remains separate from the proprietary detail of his former employer’s systems.
Sources and record basis
- Published work productTrialTelemetry.com · Published framework
Kevin’s public framework and advisory perspective for governed clinical-trial signals. A published framework is distinct from a completed client deployment.
- White paperTrial Telemetry · May 2026 white-paper page
Public introduction to the May 2026 paper. The separate site requests contact details for its PDF; this archive provides an openly readable account of the framework.
Trial Telemetry and pre-FPI review are authored frameworks. Their records do not establish completed client engagements or measured deployment outcomes.