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PMD-200

Medasense Biometrics Ltd. • Anesthesiology • 02/17/2023

De NovoIEC 62304 Class C
FDA Summary PDF

Device Purpose

The PMD-200 (Nociception Level™ Index) aims to objectively monitor intraoperative nociception in anesthetized adult patients receiving opioids, thereby enabling optimized analgesic administration. It achieves this using an AI-driven algorithm that synthesizes data from multiple physiological parameters like photoplethysmogram and skin conductance into a single, actionable index (0-100).

Summary

The PMD-200, also known as the Nociception Level™ (NOL) Index, is a medical device designed to monitor the level of pain or nociception in adult patients who are under general anesthesia and receiving opioid analgesics. Its core methodology relies on an artificial intelligence-based algorithm that integrates data from multiple physiological signals, including photoplethysmogram, skin conductance, pulse amplitude, and perfusion. This combination produces a single numerical score, the NOL Index, ranging from 0 to 100, providing anesthesiologists with a continuous, objective measure of the patient's nociceptive state to guide analgesic administration, particularly when the index suggests an increase in nociception during surgery. Clinical validation of the PMD-200, conducted through both surgical patient studies and volunteer trials, has demonstrated its superior capability in detecting noxious events compared to monitoring systems that depend on only a single physiological parameter. By offering a composite and objective metric for pain, the PMD-200 facilitates more precise optimization of analgesia. This enhanced precision aims to mitigate the risks associated with both excessive and insufficient opioid dosing during surgical procedures, thereby improving patient management under anesthesia.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

Keywords

PMD-200Nociception Level IndexAnesthesiaOpioidsAI-based algorithmPhysiological signalsPhotoplethysmogramSkin conductanceNoxious eventsAnalgesia

Device Metadata

Submission Number
DEN210022
Company
Medasense Biometrics Ltd.
Panel
Anesthesiology
Product Code
N/A
Data Type
Signals
Clinical Function
Intervention
AI Function
Analysis
AI Subclass
quantification/feature localization

Relevant Clinical Questions

  • Q1. How does the AI algorithm specifically weigh each physiological signal (photoplethysmogram, skin conductance, pulse amplitude, perfusion) in calculating the NOL Index, and is this weighting dynamic or fixed?; What were the specific characteristics of the surgical and volunteer studies that validated the PMD-200, particularly concerning patient demographics, types of surgeries, and the nature of noxious stimuli applied?; Are there any known confounders or patient populations (e.g., those with autonomic dysfunction, specific medication regimens, or certain co-morbidities) where the NOL Index accuracy might be affected?; Beyond adjusting analgesic medication, what is the evidence for the PMD-200's impact on longer-term patient outcomes, such as post-operative pain, opioid consumption, or recovery times?; How does the PMD-200 differentiate between physiological responses to nociception versus other intraoperative stimuli or changes in patient state that might affect the measured parameters?

Risk Classification

ESL Analysis
FDA Device ClassII

FDA Class II via De Novo pathway; IEC 62304 Class C (software safety classification); Authorized before §524B enforcement

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Cybersecurity Evidence

Powered by SBOMator™

Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.

Cyber Score20/100
SBOM Evidence⚠ Not mentioned in summary
Cyber Risk Assessment⚠ Not mentioned in summary
Postmarket Plan✓ Detected in Summary
§524B ApplicableNo

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials
- Not detected
ML-BOMMachine Learning Bill of Materials(algorithm)
✓ Detected
SaaSBOMSoftware-as-a-Service Bill of Materials
- Not detected
HBOMHardware Bill of Materials
- Not detected
CBOMCryptography Bill of Materials
- Not detected
VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange
- Not detected
OBOMOperations Bill of Materials
- Not detected

Analysis:

• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.

• Evidence of ML-BOM detected in AI-generated device summary.

• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.

• Not detected in AI-generated device summary: SBOM, SaaSBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.

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PMD-200 - Medasense Biometrics Ltd. | ESL FDA AI Device Intelligence