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Example output · Healthcare Compliance Officer AI

What the PCCP Scope Audit actually produces

This tool analyzes a proposed AI medical device modification against an existing Predetermined Change Control Plan (per the FDA's December 2024 final guidance) and determines whether the change fits the current PCCP, requires a PCCP amendment, or triggers a new regulatory submission (510(k), De Novo, or PMA). It structures the analysis across the three PCCP sections: Description of Modifications, Modification Protocol, and Impact Assessment.

Real output from this tool's promptPediatric population PCCP scope audit
The input
Device Context:
ClearView Retinal AI v2.1 — Class II 510(k)-cleared diabetic retinopathy screening device. Cleared with a PCCP in August 2023. Intended use: automated detection and severity grading of DR in adults.
Proposed Change:
Expand the model's training dataset to include pediatric fundus images (ages 10–17) and update confidence thresholds to improve sensitivity in this population.
Existing Pccp Summary:
PCCP covers retraining on adult fundus image datasets from new clinical sites, minor threshold adjustments within ±5% of cleared performance specs, and software version updates that do not alter intended use or patient population.
Modification Driver:
Post-market pediatric endocrinology clinic partnership; clinical need identified for DR screening in adolescent Type 1 diabetics.
Section-by-Section PCCP Fit Assessment

PCCP SECTION 1 (Description of Modifications) — Current scope: retraining on adult fundus datasets from new clinical sites, minor threshold adjustments (±5% of cleared performance), software version updates not altering intended use or patient population. Proposed change: expand training dataset to include pediatric fundus images (ages 10-17) and update thresholds for pediatric population. ASSESSMENT: The proposed change materially EXCEEDS the existing PCCP scope. The current PCCP explicitly states modifications do not alter 'patient population,' and expanding from adults to pediatric (ages 10-17) is a clear patient-population change. This does not fit Section 1 as written. PCCP SECTION 2 (Modification Protocol) — Current scope: specifies verification/validation procedures for retraining on new adult datasets within ±5% performance adjustment. Proposed change verification needs: (a) pediatric dataset representativeness validation, (b) pediatric-specific threshold optimization, (c) clinical study in pediatric population (if claimed efficacy in pediatric cohort). ASSESSMENT: The existing modification protocol assumes adult-dataset retraining and adult-centered performance metrics (sensitivity/specificity on adult fundus images). Pediatric images may differ in quality, anatomic landmarks, and disease presentation. The protocol does not address pediatric-specific verification (e.g., handling of variable pupil dilation, media opacity common in pediatric exams). DOES NOT FIT existing protocol. PCCP SECTION 3 (Impact Assessment) — Current scope: analysis of risk for adult-population retraining. Proposed change impact: pediatric population introduces new failure modes (e.g., poorer performance on non-dilated pediatric exams, sensitivity to anatomic variants in younger patients) not contemplated in adult-focused risk assessment. ASSESSMENT: The existing impact assessment does not cover pediatric patient subgroup. DOES NOT FIT. CONCLUSION: Proposed change does NOT fit existing PCCP across all three sections. Requires amendment or new submission.

Amendment Gap Analysis (What to Add to Each PCCP Section)

IF PCCP AMENDMENT IS PURSUED: (1) SECTION 1 (Description of Modifications) — AMENDMENT REQUIRED. Current language: 'Modifications do not alter intended use or patient population.' Proposed amendment: 'Modifications include retraining on pediatric fundus image datasets (ages 10-17) to optimize performance in pediatric Type 1 diabetes screening context. Intended use expands to include pediatric patients ages 10-17. Threshold adjustments up to ±10% of cleared adult-population performance baseline permitted to optimize pediatric sensitivity.' Rationale: Making patient-population expansion explicit and setting pediatric-specific performance threshold range. (2) SECTION 2 (Modification Protocol) — AMENDMENT REQUIRED. Current protocol does not specify pediatric verification. Proposed addition: 'For pediatric datasets: (a) Clinical validation on minimum 500 pediatric fundus images from ≥2 independent clinical sites; (b) demographic stratification by age group (10-13, 14-17), gender, ethnicity; (c) sensitivity/specificity targets for pediatric cohort [specify target, e.g., ≥95% sensitivity matching adult predicate]; (d) image-quality assessment (dilated vs non-dilated, media opacity grading) across pediatric cohort; (e) threshold optimization via pediatric validation cohort, with results reported separately from adult performance.' (3) SECTION 3 (Impact Assessment) — AMENDMENT REQUIRED. Current assessment does not address pediatric-specific risks. Proposed addition: 'Pediatric patient subgroup failure modes: (a) Reduced image quality in pediatric exams may increase false-negative rate; mitigation: image-quality flagging alerts clinician to manual review; (b) anatomic/physiologic differences (pupil size, lens density) may affect algorithm performance; mitigation: age-stratified validation and threshold adjustment per Section 2; (c) low population incidence of advanced DR in pediatric Type 1 diabetes (most are early stages) may bias model toward sensitivity at cost of specificity; mitigation: performance targets emphasize sensitivity >95% to minimize missed cases. New risk: use of adult-trained thresholds on pediatric images may yield higher false-positive rate, potentially driving unnecessary referrals; mitigation: pediatric threshold optimization and clinical audit of false-positive rate in real-world deployment.' Expected regulatory timeline for amendment: 4-6 weeks for regulatory affairs + engineering collaboration to assemble evidence; submission to FDA for pre-submission meeting (Type C) recommended before formal amendment.

Preliminary Recommendation & Escalation Triggers

RECOMMENDATION: The proposed change REQUIRES A PCCP AMENDMENT (not a full 510(k)). However, a PCCP amendment is appropriate only if (a) the pediatric validation data are robust (≥500 images from ≥2 sites, independent of adult training), and (b) the performance targets for pediatric cohort are clearly defined and met. If either condition is not met, a NEW 510(k) submission (substantial equivalence to adult predicate) is necessary. CRITICAL CAVEAT: If the proposed change is driven by post-market signal (e.g., pediatric patients presenting with symptoms of advanced DR being missed by the adult model), this may trigger MDR-adjacent obligations under 21 CFR 803 even if the modification mechanically fits a PCCP amendment. QUESTIONS FOR REGULATORY AFFAIRS LEAD: (1) Do we have existing pediatric fundus-image data (500+ images, ≥2 clinical sites)? If yes, what is the data-maturity status (raw, labeled, validated)? Timeline to finalize validation? (2) What performance targets are we claiming for the pediatric cohort, and how do they compare to the adult predicate (IDx-DR)? If pediatric sensitivity is lower, what is the clinical/regulatory rationale? (3) Is there a post-market signal (complaints, failed detections) driving this change, or is it a proactive opportunity expansion? If signal-driven, what is the incident frequency and severity? (4) Have we engaged the FDA in a Type C pre-submission meeting for the PCCP amendment, or should we do so before investing in validation? QUESTIONS FOR CLINICAL LEAD: (1) What is the clinical justification for expanding to ages 10-17? Is there documented unmet need (e.g., rising Type 1 diabetes incidence in this age group, screening gaps in pediatric endocrinology clinics)? (2) Are the pediatric fundus images representative of intended real-world use (e.g., mix of dilated and non-dilated images, typical image quality from pediatric clinics)? (3) What is the expected sensitivity/specificity in pediatric cohort, and is it clinically acceptable for screening (e.g., ≥95% sensitivity to avoid missed cases of moderate-to-severe DR)? QUESTIONS FOR EXTERNAL REGULATORY COUNSEL: (1) Does FDA guidance on pediatric AI/ML modifications favor PCCP amendment (if data-robust) or new submission? Has FDA issued specific PCCP amendment precedents for patient-population expansion? (2) If this is signal-driven (post-market issue in pediatric cohort), does 21 CFR 803 MDR reporting apply, and should we prepare adverse-event documentation alongside the amendment submission? (3) What is the anticipated FDA review timeline for a PCCP amendment vs. a full 510(k) for this modification?

What to edit for your situation

Replace the device context, existing PCCP summary, and proposed change with your actual cleared device, your PCCP's specific language, and the modification your team is evaluating. The more precisely you quote your PCCP's scope language, the tighter and more accurate the gap analysis will be.

Human review: This output is preparatory analysis only — a qualified regulatory affairs professional or FDA counsel must review all findings before any submission pathway decision is made or any PCCP amendment is drafted for submission.

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