FDA's 2025 TPLC draft guidance and final PCCP guidance establish a lifecycle
accountability framework for clinical AI, but leave implementation mechanics to
each organization. This schema fills that gap: 40 controls across five SRF layers,
each with a named accountable persona, a measurable threshold, and an HL7 FHIR
AuditEvent evidence pointer.
Experimental schema. This vertical is a proposed
extension of the CoSAI Shared Responsibility Framework, developed independently to
demonstrate the approach. It is not part of CoSAI SRF v1.0 and has not been endorsed
by CoSAI, the FDA, or any regulator. Verify regulatory section references against the
source documents before use.
40
Controls
5
SRF layers
4
Clinical lifecycle stages
7
Regulatory crosswalks
The FDA TPLC gap. The FDA's January 2025 draft guidance on
lifecycle management for AI-enabled device software functions and the August 2025
final PCCP guidance establish what clinical AI systems must do across their
lifecycle. They do not resolve how a hospital system, a medtech manufacturer,
or a health IT developer implements those accountabilities under HIPAA, ONC
certification requirements, and EU AI Act obligations simultaneously.
FDA AI/ML SaMD resources ↗
What the schema provides. Each control maps an SRF layer to a
specific clinical lifecycle stage (design and development, verification and validation,
post-market surveillance, human oversight and review), names the accountable
persona, and specifies the HL7 FHIR resource and attribute that proves the control
is functioning. FHIR AuditEvent, MeasureReport, Provenance, and Device resources
replace annual attestations with continuous, machine-readable evidence.
Agentic clinical AI coverage. All 40 controls apply to Agent-Clinical
deployments, which carry the largest surface area under FDA TPLC and HIPAA minimum-necessary
obligations. L3 and L4 controls address human-in-the-loop gates, SMART on FHIR scope
enforcement, prompt injection defense, and agentic task boundary monitoring.
In this section
Schema design
Accountability plane
SRF layers and clinical personas
Each control names one accountable persona. Five layers map to the clinical AI
lifecycle: governance, data, application, platform, and model. One accountable
party per control, regardless of operating model.
Control plane
Safety thresholds and FDA tier parameters
Controls define the metric, operator, and parameter name. Organizations set
values per SaMD risk tier (Class I, II, III). Zero-tolerance and verification
controls carry fixed values by design.
Evidence plane
HL7 FHIR R4 resource pointers
Each threshold names the FHIR resource type and attribute that proves the control
is operating: AuditEvent, MeasureReport, Provenance, Device, DeviceMetric.
Continuous, machine-readable evidence; not annual attestations.
Regulatory crosswalks
FDA TPLC GuidanceTotal product lifecycle management for AI/ML SaMD (January 2025 draft)
FDA PCCPPredetermined Change Control Plan final guidance (August 2025); crosswalk follows the 2023 FDA, Health Canada, and MHRA guiding principles
ONC HTI-1Algorithmic transparency for certified health IT (effective January 2025)