ClaraWell Inc. (Dr. Emanuel Tkach, Eric Blum)

ClaraWell Inc. respectfully submits the attached Response Framework for GenAI-Enabled Medical Devices, prepared by Dr. Emanuel Tkach and Eric Blum, in response to FDA’s Considerations for the Regulation of Generative AI-Enabled Medical Devices: Discussion Paper and Request for Feedback.

The attached response consolidates the 26 discussion questions into four underlying regulatory areas and considers each through patient, clinical / institutional, and technological perspectives.

We appreciate the opportunity to provide stakeholder feedback for FDA’s consideration.

Response Framework for GenAI-Enabled Medical Devices

Considerations for the Regulation of Generative AI-Enabled Medical Devices
Discussion Paper and Request for Feedback

October 2026

ClaraWell Inc.

Prepared By:

Dr. Emanuel Tkach

Eric Blum

FDA’s Considerations for the Regulation of Generative AI-Enabled Medical Devices:

Discussion Paper and Request for Feedback presents 26 discussion questions.

ClaraWell organizes these questions into four underlying regulatory areas: risk, premarket evidence,
postmarket control, and autonomy or external model dependency.

1. What makes a GenAI-enabled medical device function risky?

2. How should safety and effectiveness be demonstrated before deployment?

3. How should safety be maintained through deployment and change?

4. How should responsibility and control be assigned when intelligence is external or
autonomous?

Each question is considered through three perspectives:

Patient | Clinical / Institutional | Technological

The three perspectives reflect where risk is experienced and managed:

• Patient: understanding, reliance, consequence, escalation, and recourse.

• Clinical / Institutional: clinical judgment, standard of care, supervision, governance, and
accountability.

• Technological: variability, reproducibility, provenance, monitoring, change control, and autonomy.

Together, these perspectives provide a consistent structure for examining the four regulatory questions.

The central challenge is to distinguish acceptable variability from safety-critical behavior that must
remain controlled across the total product lifecycle.

ClaraWell Inc. | Boston, Massachusetts | www.clarawell.com
1. What makes a GenAI-enabled medical device function risky?
Primary FDA discussion questions: 1-6

Patient Risk rises when a patient cannot reasonably evaluate an output or when an incorrect
output leads to harmful or delayed action. Patient-facing use should not by itself
determine risk.

The key factors are reliance, consequence, reversibility, and access to escalation or
recourse. Effective escalation depends not only on patient-facing instructions, but
also on reliable integration with a clinical workflow that preserves context and routes
the patient to appropriate follow-up.

Clinical / Clinical and institutional risk depends on the device’s autonomy, the consequence of
Institutional error, the deployment context, and the safeguards available. Assessment should
consider the deployed model and product configuration, intended user, and clinical
setting.

Workflow integration can increase risk when it encourages automation bias, loses
clinical context during handoffs, or fails to route outputs and escalations to the
appropriate care pathway. Clinician oversight is meaningful only when the reviewer
has the expertise, time, and authority to question or override the output.
Retrospective review supports learning but does not protect the individual patient in
real time.

Before deployment, institutions should assess clinical and workflow fit and establish
standard operating procedures (SOPs) that incorporate the technology into existing
care processes. Training should be tailored to the intended user and setting, address
the device’s limitations and escalation pathways, and explicitly address automation
bias and inappropriate overreliance.

Technological Risk should be characterized by consequence, autonomy, directiveness, variability,
observability, reversibility, and control. Ordinary generative variation may be
acceptable. Safety-critical behaviors such as escalation, refusal, or diagnostic
conclusions require tighter bounds and reproducible testing.

ClaraWell Inc. | Boston, Massachusetts | www.clarawell.com
2. How should the safety and effectiveness of a GenAI-enabled medical device function be
demonstrated before deployment?
Primary FDA discussion questions: 7-17

Patient Premarket evaluation should reflect how patients will actually use and understand the
device. Testing should account for realistic variation in literacy, phrasing, incomplete
information, and repeated interaction, with emphasis on whether users can
understand the output and its limitations.

FDA specifically raises communication quality, user comprehension, subgroup
performance, and clinically representative use. Testing should also assess whether
the user interface helps patients understand the device’s output, limitations, and
appropriate next steps, including when to seek further care.

Clinical / Premarket evidence should combine structured benchmarking with clinical
Institutional confirmation appropriate to the device’s intended use and risk profile.
Benchmarking can demonstrate defined capabilities and known failure modes, but it
cannot fully predict performance in clinical practice. When feasible, sponsors should
confirm performance in real-world or clinically representative settings that reflect the
intended users and workflows.

Shadow deployment can be a useful pre-deployment stress test: the device
processes real clinical inputs in a live workflow, but its outputs do not affect patient
care. When this is not feasible, an alternative clinically representative evaluation
should be used.

Technological Safety and effectiveness should be demonstrated on the deployed device
configuration, not the foundation model alone. Evaluation should be prespecified,
reproducible, risk-proportionate, and broad enough to test safety behavior, clinical
task performance, robustness, and generalizability before clinical confirmation. FDA’s
proposed framework explicitly combines benchmarking with clinical confirmation and
expects methods, scoring, and acceptance criteria to be defined in advance.

ClaraWell Inc. | Boston, Massachusetts | www.clarawell.com
3. How should the safety of a GenAI-enabled medical device function be maintained through
deployment and change?
Primary FDA discussion questions: 18-24

Patient Postmarket safety should account for whether changes in the device alter what
patients experience or how they may act on its outputs. Material changes in
behavior, escalation, or reliability should be detectable before they create avoidable
harm, and patients should retain clear paths to escalation or recourse when
performance degrades.

Clinical / The manufacturer remains responsible for device-level postmarket monitoring,
Institutional investigation, corrective action, and re-evaluation of changes.

Clinical and institutional safety should be supported through a risk-proportionate
quality process that tracks clinically meaningful events, performance concerns, and
workflow effects; identifies recurring or safety-relevant signals; investigates and
addresses them through established quality-system processes when warranted; and
evaluates whether resulting actions are effective.

Clinicians and healthcare institutions should share relevant real-world feedback when
available and applicable through existing reporting and quality processes. Planned,
evolving, or externally initiated changes should be assessed for their potential effect
on clinical use, workflow, and the applicable standard of care, with the scope of reevaluation proportionate to the change and the device’s risk profile.

Technological Postmarket control should maintain a traceable baseline for the deployed
configuration and require re-evaluation after changes that could affect safety or
effectiveness.

Monitoring should address drift, model or system updates, third-party dependencies,
and other material modifications through versioning, re-benchmarking, auditability,
and rollback where appropriate.

ClaraWell Inc. | Boston, Massachusetts | www.clarawell.com
4. How should responsibility and control be assigned when a GenAI-enabled medical device
function relies on external or autonomous intelligence?
Primary FDA discussion questions: 25-26

Patient When a GenAI-enabled medical device function depends on external or autonomous
intelligence, patients should still have a clear understanding of who is responsible for
the device’s actions and how concerns can be escalated. Increased autonomy
should not reduce transparency, recourse, or the ability to identify accountable
parties when harm occurs.

Clinical / Responsibility for a GenAI-enabled medical device function should remain
Institutional identifiable and aligned with the ability to control the relevant clinical and technical
risks. The manufacturer should remain accountable for the safety and effectiveness
of the deployed device function, including its use of external models, tools, and
updates.

Clinicians retain responsibility for clinical judgment and decisions within their
professional role; use of an AI-enabled device does not transfer that responsibility to
the device or its manufacturer.

Healthcare institutions remain responsible for implementation of governance,
workflow design, user training, and local oversight appropriate to the function’s risk
and degree of autonomy.
As autonomy increases, the system should operate within a clearly defined clinical
scope, with explicit authority limits, appropriate human-oversight points, and
escalation pathways for situations that exceed its intended use or safety boundaries.
Institutions should be able to identify the device’s intended role in the workflow, the
actions it may take, the circumstances requiring clinician review, and the process to
disable or suspend the device locally if safety concerns arise. External-model
dependencies should not create ambiguity about accountability or reduce the ability
of clinicians, institutions, patients, or regulators to identify and escalate concerns.

Technological Responsibility should remain tied to control of the deployed device function, including
its models, tools, permissions, updates, and safety boundaries.

External foundation-model dependencies require sufficient visibility into model
versioning and change control. While autonomous systems should operate within
defined permissions, human oversight points, auditable action histories, and safe
failure states.
FDA specifically raises Foundation Model MAFs and additional oversight for agentic
systems with autonomous multi-step action and reduced opportunity for human
review.

ClaraWell Inc. | Boston, Massachusetts | www.clarawell.com
Concluding Position

ClaraWell views the regulation of GenAI-enabled medical devices as a lifecycle problem rather than a
model-specific problem.

A device may use probabilistic or generative components while still operating within defined clinical,
institutional and technical boundaries. The regulatory objective should therefore be to identify which
behaviors may vary, which must remain reliably constrained, and what evidence is required to
demonstrate that distinction.

Across the patient, clinical / institutional, and technological perspectives, four principles remain
consistent:

1. Risk should reflect the consequence and controllability of the device function, not the use of
GenAI alone.

2. Premarket evidence should be proportionate to the function’s intended use, autonomy, and
potential harm.

3. Safety-critical behavior should remain observable, testable, traceable, and subject to appropriate
re-evaluation after material change.

4. Accountability should remain identifiable even when a device depends on third-party models or
increasingly autonomous systems.

The central question is therefore not whether GenAI-enabled medical devices can vary. It is whether that
variability can be understood, bounded, evaluated, and managed throughout the total product lifecycle.

ClaraWell believes a regulatory framework built around those principles can preserve meaningful
innovation while maintaining clear expectations for safety, evidence, and accountability.

ClaraWell Inc. | Boston, Massachusetts | www.clarawell.com