(82 days)
The Otsuka Digital Feedback Device consists of a miniaturized, wearable sensor for ambulatory recording of physiological and behavioral metrics such as heart rate, activity, body angle relative to gravity (body position), and time-stamped patient-logged events, including events signaled by co-incidence with, or co ingestion with, the ingestible sensor accessory. When the ingestible sensor is ingested, the Otsuka Digital Feedback Device is intended to log, track, and trend intake times. When co-ingested with medication, the tracking and trending of intake times may be used as an aid to measure medication adherence. The Otsuka Digital Feedback Device may be used in any instance where quantifiable analysis of event-associated physiological and behavioral metrics is desirable and enables unattended data collection for clinical and research applications.
The Otsuka Digital Feedback Device consists of 3 components: a wearable sensor, an ingestible sensor accessory, and software that aggregates, processes, and enables display of data collected by the sensors.
The wearable sensor in the Otsuka Digital Feedback Device is a body-worn sensor that consists of a single-use patch known as the D-Tect wearable sensor or D-Tect Patch. The D-Tect Patch collects physiological and behavioral metrics such as heart rate, activity, body angle, and time stamped patient-logged events, including events signaled by the co-incidence with, or co-ingestion with, the ingestible sensor accessory. Note: While the device includes automated heart rate (HR) measurement, it does not provide an ECG waveform recording for display or analysis. The device is not intended to diagnose heart-related conditions and does not include alarms. HR measurement is not intended to be used in alarm system. HR data may not be accurate for patients with pacemakers.
The ingestible sensor is embedded inside an inactive tablet (the pill or sensor-enabled pill) for ease of handling and swallowing. After the ingestible sensor reaches the stomach, it activates and communicates its presence with a unique identifier to the wearable sensor. When the ingestible sensor is co-ingested with medication, the Otsuka Digital Feedback Device is intended to log, track, and trend medicine intake times to measure medication adherence.
The software on the general computing device receives the data from the wearable sensor for further processing and analysis of metrics. The processed data is then sent to the user interface for display, as well as being saved in a local record database for storage. The software component includes firmware running on the wearable sensor that collects and records the data from the sensors and a software that receives data from the wearable sensor for further analysis, processing, storage, and display to the user.
For purposes of this 510(k), the changes from the predicate device (Otsuka Digital Feedback Device-RW, K223463) to the Otsuka Digital Feedback Device with D-Tect Patch (the device subject of this 510[k]) are the wearable sensor and the software for the user interface. The ingestible sensor remains the same as the predicate device.
Here's a breakdown of the acceptance criteria and the study that proves the Otsuka Digital Feedback Device meets them, based on the provided FDA 510(k) clearance letter.
1. Table of Acceptance Criteria and Reported Device Performance
The document implicitly defines acceptance criteria through its performance testing sections. For the purpose of this analysis, I will focus on the most explicitly quantified performance metrics from the provided text.
| Performance Characteristic | Acceptance Criteria (from text) | Reported Device Performance (from text) |
|---|---|---|
| Wear Duration (Adherence) | ≥ 5 days in ≥ 50% of subjects | Minimum of 79.0% adherence for a minimum of 5 days (95% CI) |
| Wear Duration (Extended Adherence) | Not explicitly stated as a pass/fail criterion, but reported as an improvement. | Minimum of 61.5% adherence for a minimum of 7 days (95% CI) |
| Comfort | > 3.5 (on a scale of 1-5 where 5 = very comfortable) | Average comfort rating of 4.7 (very comfortable) |
| Skin Irritation (Safety) | Similar safety profile to predicate device, no new safety concerns identified. | 7/55 (12.7%) subjects experienced Grade 1 or 2 AE; 6/55 (10.9%) Grade 1; 2/55 (3.6%) Grade 2. All other subjects Grade 0. Similar to predicate. |
| Pill Detection Capability | Not explicitly quantified, but stated as an "Improvement" over predicate. | Enhanced low-noise analog front end improves sensitivity of IEM detection by >50%. |
| Step Counting | Not explicitly quantified, but stated as an "Improvement" over predicate. | Improved step metric based on passive fully continuous step counting. |
| Heart Rate Measurements | Not explicitly quantified, but stated as an "Improvement" over predicate. | Verified against real ECG signals and 100% measurement accuracy for simulated ECG signal. |
| Biocompatibility | Compliant with ISO 10993 standards (Irritation, Cytotoxicity, Sensitization) | Deemed compliant with ISO 10993-23-2021, ISO 10993-5-2009, and ISO 10993-10-2021. |
| Shelf Life | Verified shelf life | 3-years from the date of manufacturing. |
| Mechanical & Electrical | Meets all requirements and specifications. | Formal verification testing with passing results for LED, button, integrity, dimensions, water ingress, vibration, impact, push, drop, markings, static, functional, environmental. |
| Patient Electrical Safety (IEC 60601-1) | Compliant with IEC 60601-1, -1-2, -1-11, -1-6. | Compliant with all applicable requirements of IEC 60601-1: 2005 + A1:2012 + A2:2020, IEC 60601-1-2: 2014 + A1:2020, IEC 60601-1-11: 2015 + A1:2020, IEC 60601-1-6: 2010 + A1:2013 + A2:2020. |
| EMC (IEC 60601-1-2) | Meets IEC 60601-1-2 EMC standard (third and fourth edition). RF Emissions CISPR 11 Group 1, Class B; RF Immunity IEC 61000-4-3 Level 3; ESD Immunity IEC 61000-4-2 Level 4. | Meets requirements. Patch, mobile device, and software underwent evaluation. |
| Device Software (Firmware & Mobile App) | Meets requirements, no anomalies impacting performance/safety/effectiveness. | All identified requirements tested and successfully passed. No unresolved issues. |
| Cybersecurity | Compliant with FDA guidance, FD&C Act, AAMI/UL 2900-1, AAMI TIR-57, NIST SP 800-30, ISO 14971. No critical vulnerabilities in third-party testing. | Verified compliance, applicable security tests conducted. No critical vulnerabilities found. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size (Clinical Performance Data): A total of 55 subjects were tested for the clinical performance evaluation.
- Data Provenance: The study was conducted at 1 site in the United States. It was a prospective noninterventional validation study in healthy subjects.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The document does not specify the number or qualifications of experts used to establish a "ground truth" for the test set in the conventional sense (e.g., radiologists reviewing images). The clinical performance study focused on objective measurements like wear duration, comfort ratings self-reported by subjects, and skin irritation scores, which are typically assessed by trained clinical staff rather than expert consensus on a diagnostic outcome. Skin irritation scores are based on established clinical grading scales.
4. Adjudication Method for the Test Set
The document does not describe an explicit adjudication method (like 2+1 or 3+1 consensus) for the test set. For the wear duration, comfort, and skin irritation metrics, the data collection methods (instrumental recording for wear duration, self-reporting for comfort, and clinical scoring for irritation) are inherently less reliant on such adjudication compared to subjective diagnostic tasks.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
No MRMC comparative effectiveness study was mentioned in this document. The device, an "Ingestible Event Marker with wearable patch," is primarily focused on automated data collection for physiological and behavioral metrics and medication adherence, not on aiding human readers in interpreting complex diagnostic images or data where "AI assistance" would directly improve a reader's performance in a diagnostic task.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done
Yes, the testing described appears to largely cover standalone algorithm and device performance, particularly for:
- Pill Detection Capability: "Enhanced low-noise analog front end improves sensitivity of the IEM detection by >50%, increasing the likelihood of detection." This is an intrinsic algorithmic/hardware capability.
- Step Counting: "Improved step metric based on passive fully continuous step counting." This is an algorithmic function.
- Heart Rate Measurements: "Verified against real ECG signals and 100% measurement accuracy for simulated ECG signal." This tests the algorithm's performance.
- Wear Duration: This is objectively measured by the device's logging capability.
The clinical performance study focuses on the overall system's ability to log data correctly and be comfortable and safe, which inherently relies on the standalone performance of its components.
7. The Type of Ground Truth Used
- Wear Duration: Objective logging by the device itself, validated against study protocols of subjects wearing patches for specified periods.
- Comfort: Subject self-reporting on a defined scale.
- Skin Irritation: Clinical assessment based on established grading scales (Grade 0, 1, 2).
- Pill Detection, Step Counting, Heart Rate: Verified against reference methods/signals (e.g., real ECG signals, simulated ECG signals).
- Mechanical, Electrical, Software, Cybersecurity, Biocompatibility, Shelf Life: Ground truth is defined by compliance with applicable standards, specifications, and successful completion of pre-defined test protocols.
8. The Sample Size for the Training Set
The document does not provide details on the sample size used for the training set of any algorithms within the device. It focuses on the validation of the finalized device.
9. How the Ground Truth for the Training Set Was Established
Since the document does not mention the training set size, it also does not elaborate on how the ground truth for any potential training data was established. The improvements noted (e.g., improved pill detection, step counting, HR measurements) suggest iterative development and potentially machine learning, but the specifics of their training data and ground truth are not detailed in this regulatory summary.
§ 880.6305 Ingestible event marker.
(a)
Identification. An ingestible event marker is a prescription device used to record time-stamped, patient-logged events. The ingestible component links wirelessly through intrabody communication to an external recorder which records the date and time of ingestion as well as the unique serial number of the ingestible device.(b)
Classification. Class II (special controls). The special controls for this device are:(1) The device must be demonstrated to be biocompatible and non-toxic;
(2) Nonclinical, animal, and clinical testing must provide a reasonable assurance of safety and effectiveness, including device performance, durability, compatibility, usability (human factors testing), event recording, and proper excretion of the device;
(3) Appropriate analysis and nonclinical testing must validate electromagnetic compatibility performance, wireless performance, and electrical safety; and
(4) Labeling must include a detailed summary of the nonclinical and clinical testing pertinent to use of the device and the maximum number of daily device ingestions.