(272 days)
Sleepio is a digital therapeutic intended for the treatment of chronic insomnia disorder as an adjunct to usual care in patients aged 18 and older. Sleepio is a prescription device delivering Cognitive Behavioral Therapy for Insomnia (CBT-I) and can be made available on the order of a licensed healthcare provider.
Sleepio is a digital therapeutic for the treatment of chronic insomnia / insomnia disorder. Sleepio treats chronic insomnia disorder by delivering evidence-based techniques targeting the cognitive and behavioral factors that maintain insomnia and chronic sleep problems. Patient experience is tailored based on symptoms and daily sleep tracking. In addition to core therapeutic components, there is in-the-moment therapeutic content for help falling asleep. Content is delivered via smartphone and tablet applications (iOS and Android), as well as via web. Sleepio is intended as an adjunct to usual care treatment for chronic insomnia / insomnia disorder by a healthcare provider. Healthcare providers have access to a dashboard to track patient engagement with Sleepio.
Based on the provided text, the device in question is Sleepio, a digital therapeutic for the treatment of chronic insomnia disorder. Here's a breakdown of the acceptance criteria and the study proving the device meets them:
Disclaimer: The provided document is an FDA 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than setting explicit acceptance criteria for this specific device's performance in a new, de novo fashion. The clinical data presented serves to support the substantial equivalence claim by showing similar or superior performance to standard care (Sleep Hygiene Education, SHE) and implicitly, to the predicate. Therefore, the "acceptance criteria" table below is inferred from the goals of the clinical study and the claims made about the device's efficacy in the context of demonstrating substantial equivalence for an FDA 510(k) submission.
1. Table of inferred acceptance criteria and the reported device performance
| Acceptance Criteria Category (Inferred) | Specific Criterion (Inferred from study outcomes) | Reported Device Performance and Comparison (Sleepio vs. SHE) |
|---|---|---|
| Primary Endpoints (Co-Primary) | ||
| Insomnia Severity Index (ISI) Improvement | Significant reduction in ISI score compared to control (SHE). | Week 10: Sleepio ISI was 12.11 (SD 6.10) vs SHE ISI 14.74 (SD 5.00). Adjusted difference: -2.37 (SE 0.56) (99% CI: -3.81, -0.92), p<0.001. Cohen's d = 0.606.Week 16: Adjusted difference: -2.55 (SE 0.57) (99% CI: -4.01, -1.09), p<0.001.Week 24: Adjusted difference: -3.05 (SE 0.59) (99% CI: -4.56, -1.54). Cohen's d = 0.77. |
| Sleep Onset Latency (SOL) Reduction | Significant reduction in SOL compared to control (SHE). | Week 10: Sleepio SOL was 36.75 (SD 32.00) vs SHE SOL 45.54 (SD 48.82). Adjusted difference: -9.14 (3.63) (99% CI: -18.49, 0.20), p=0.012. Cohen's d = 0.23.Week 16: Adjusted difference: -6.68 (3.69) (99% CI: -16.18, 2.83), p=0.070.Week 24: Adjusted difference: -4.37 (3.99) (99% CI: -14.64, 5.90). Cohen's d = 0.11. |
| Wake After Sleep Onset (WASO) Reduction | Significant reduction in WASO compared to control (SHE). | Week 10: Sleepio WASO was 24.54 (SD 21.40) vs SHE WASO 33.82 (SD 30.06). Adjusted difference: -8.86 (2.94) (99% CI: -16.42, -1.29), p=0.003. Cohen's d = 0.21.Week 16: Adjusted difference: -11.69 (2.97) (99% CI: -19.35, -4.03), p<0.001.Week 24: Adjusted difference: -12.02 (3.19) (99% CI: -20.24, -3.80). Cohen's d = 0.29. |
| Secondary Outcomes | ||
| Remission Rate (ISI < 8) | Higher odds of remission compared to control. | Week 10: Sleepio participants had 5.8 odds of remission (OR=5.78; p<0.001, 99% CI: (2.11, 15.84)) compared with SHE. |
| Response Rate (ISI change of ≥6 points from baseline) | Higher odds of response compared to control. | Week 10: Sleepio participants had 2.52 odds of response (OR=2.52; p<0.001, 99% CI: (1.33, 4.75)) compared with SHE. |
| Response Rate (Post-hoc, ISI change of ≥8 points from baseline) | Higher odds of response compared to control. | Post-hoc analysis showed Sleepio participants had 3.30 odds ratio of response (OR=3.30; 95% CI: (1.92, 5.69)) compared to SHE. |
| Safety and Adverse Events | No adverse or serious adverse events reported. | No adverse or serious adverse events were reported by participants. |
| Nonclinical Performance (Software Verification & Validation) | Completed as recommended by FDA guidance for a "Moderate level of concern device." | Documentation provided as recommended by Guidance for Industry and FDA Staff: Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (2005), for a Moderate level of concern device. |
2. Sample size used for the test set and the data provenance
- Test set sample size: The clinical effectiveness was evaluated in the CrEDIT trial, a two-arm, parallel group, randomized controlled trial (RCT) with 336 adults.
- Sleepio group (n=168)
- Online sleep hygiene education (SHE) group (n=168)
- Data provenance: Participants were recruited from across the United States via social media. The study was prospective (Randomized Controlled Trial).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document does not specify the use of human experts to establish ground truth for the test set in the conventional sense of image or diagnostic adjudication. The ground truth for insomnia was established clinically based on self-reported patient assessments using standardized questionnaires (Insomnia Severity Index, ISI) and sleep diaries (SOL, WASO), and a DSM-5 diagnosis of insomnia disorder as criteria for study inclusion. The study evaluated the effectiveness of a therapeutic intervention, not the diagnostic accuracy of an AI model against expert consensus.
4. Adjudication method for the test set
Not applicable. As noted above, this study measures the therapeutic effectiveness of Sleepio based on patient-reported outcomes, not the performance of a diagnostic or classification algorithm that would require an adjudication method for ground truth.
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, an MRMC comparative effectiveness study was not done. This was a clinical trial evaluating a digital therapeutic directly delivered to patients for treatment, not an AI-assisted diagnostic tool for human readers. Therefore, the concept of "human readers improve with AI vs without AI assistance" does not apply.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Yes, in a way. Sleepio is a digital therapeutic that delivers Cognitive Behavioral Therapy for Insomnia (CBT-I) directly to patients via smartphone/tablet apps and web. While it's a "prescription device" and "can be made available on the order of a licensed healthcare provider" who "have access to a dashboard to track patient engagement," the core therapeutic delivery and patient interaction are directly from the algorithm/software. The study design directly assesses the effect of this standalone digital intervention compared to sleep hygiene education.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The ground truth or clinical endpoints were based on patient-reported outcomes data derived from:
- Insomnia Severity Index (ISI) scores: A standardized, self-reported questionnaire.
- Sleep diary data: Self-reported sleep onset latency (SOL) and wake after sleep onset (WASO).
- DSM-5 diagnosis of insomnia disorder: Used as an inclusion criterion for participants.
- Sleep Condition Indicator (SCI-8): A secondary outcome measure.
8. The sample size for the training set
The document does not specify a training set sample size in the context of an AI/ML model for this device. Sleepio delivers Cognitive Behavioral Therapy for Insomnia (CBT-I), which is an evidence-based therapeutic approach. The "training" for such a device would typically relate to the development of the CBT-I content and algorithms based on established clinical guidelines and research in psychology and sleep medicine, rather than a machine learning training dataset in the typical sense for image recognition or diagnostic AI. The software verification and validation are noted, but this refers to engineering and quality assurance processes, not a machine learning training curriculum.
9. How the ground truth for the training set was established
Not applicable directly, as this is not described as a device that uses a trained AI model in the sense of predictive or diagnostic capabilities. Sleepio is a digital delivery mechanism for an established therapy (CBT-I). The "ground truth" for its therapeutic approach is the established principles and efficacy of CBT-I as validated in clinical literature and practice over many years. The clinical study (CrEDIT trial) served as a validation study to demonstrate that Sleepio's digital implementation of CBT-I is effective, rather than a study to establish ground truth for a novel AI algorithm's training.
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August 5, 2024
Big Health, Inc. Reuben Lawson Vice President, Regulatory Affairs & Quality Systems 461 Bush St. Suite 200 San Francisco, California 94108
Re: K233577
Trade/Device Name: Sleepio® Regulation Number: 21 CFR 882.5801 Regulation Name: Computerized Behavioral Therapy Device For Psychiatric Disorders Regulatory Class: Class II Product Code: QVO Dated: June 24, 2024 Received: June 24, 2024
Dear Reuben Lawson:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
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Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Robert Kang -S
for Pamela Scott Assistant Director DHT5B: Division of Neuromodulation and Rehabilitation Devices OHT5: Office of Neurological and Physical Medicine Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K233577
Device Name Sleepio
Indications for Use (Describe)
Sleepio is a digital therapeutic intended for the treatment of chronic insomnia disorder as an adjunct to usual care in patients aged 18 and older. Sleepio is a prescription device delivering Cognitive Behavioral Therapy for Insomnia (CBT-I) and can be made available on the order of a licensed healthcare provider.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| ☑ Prescription Use (Part 21 CFR 801 Subpart D) | ☐ Over-The-Counter Use (21 CFR 801 Subpart C) |
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510(k) Summary - K233577
Submitter 1.
| Submitted by: | Big Health Inc. |
|---|---|
| Contact Name: | Reuben Lawson,Vice President, Quality Systems & Regulatory Affairs |
| Contact Phone: | (949) 439 3629 |
| Additional Contact: | Dr. Alasdair L. Henry, Senior Manager, ClinicalResearch |
-
- Device
| Device name: | Sleepio |
|---|---|
| Classification name: | Computerized Behavioral Therapy forPsychiatry Disorders (21 CFR 882.5801) |
| Regulatory class: | Class II (Special Controls) |
| Product code: | QVO |
3. Predicate device
| Device name: | Somryst | Category | Sleepio (this submission) | Somryst (predicate) |
|---|---|---|---|---|
| Manufacturer: | Pear Therapeutics | 510(k) number | K233577 | K191716 |
| Classification name: | Computerized Behavioral Therapy forPsychiatry Disorders (21 CFR 882.5801) | Classification regulation | 21 CFR 882.5801Computerized behavioraltherapy device for psychiatricdisorders | 21 CFR 882.5801Computerized behavioraltherapy device for psychiatricdisorders |
| Regulatory class: | Class II (Special Controls) | Intended use | SaMD intended to becomputerized behavioraltherapy device to treatpatients with chronicinsomnia / insomnia disorder | SaMD intended to becomputerized behavioraltherapy device to treatpatients with chronicinsomnia |
| 510(k) Number: | K191716 | Indications for use | Sleepio is a digitaltherapeutic intended for thetreatment of chronicinsomnia / insomnia disorderas an adjunct to usual care inpatients aged 18 years andolder. Sleepio is aprescription device deliveringCognitive BehavioralTherapy for Insomnia (CBT-I)and can be made availableon the order of a licensedhealthcare provider. | Somryst is a prescription-onlydigital therapeutic intended toprovide a neurobehavioralintervention (CognitiveBehavioral Therapy forInsomnia - CBT-I) in patients22 years of age and olderwith chronic insomnia.Somryst treats chronicinsomnia by improving apatient's insomnia symptoms |
| Product code: | QVO | Mechanism of action | Consolidation andregularization of sleep-wakecycle, restructuringdysfunctional beliefs andattitudes about sleep,cognitive-behavioralreconditioning, reducingsleep-related anxiety andarousal | Consolidation andregularization of sleep-wakecycle, restructuringdysfunctional beliefs andattitudes about sleep,cognitive-behavioralreconditioning, reducingsleep-related anxiety andarousal |
| Medical Device Type | Software as a MedicalDevice (SaMD) | Software as a Medical Device(SaMD) |
Device Description 4.
Sleepio is a digital therapeutic for the treatment of chronic insomnia / insomnia disorder. Sleepio treats chronic insomnia disorder by delivering evidence-based techniques targeting the cognitive and behavioral factors that maintain insomnia and chronic sleep problems. Patient experience is tailored based on symptoms and daily sleep tracking. In addition to core therapeutic components, there is in-the-moment therapeutic content for help falling asleep. Content is delivered via smartphone and tablet applications (iOS and Android), as well as via web. Sleepio is intended as an adjunct to usual care treatment for chronic insomnia / insomnia disorder by a healthcare provider. Healthcare providers have access to a dashboard to track patient engagement with Sleepio.
5. Intended use / Indications for use
Sleepio is a digital therapeutic intended for the treatment of chronic insomnia / insomnia disorder as an adjunct to usual care in patients aged 18 and older. Sleepio is a prescription device delivering Cognitive Behavioral Therapy for Insomnia (CBT-I) and can be made available on the order of a licensed healthcare provider.
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6. Substantial equivalence
Sleepio has an identical intended use and nearly identical technological characteristics compared to the predicate device, Somryst. Like Somryst, Sleepio delivers cognitive behavioral therapy for insomnia (CBT-I) by way of an app provided as an adjunct to usual care by the patient's healthcare provider. However, Sleepio is available for use in patients aged 18 and older, whereas Somryst is available for use in patients aged 22 and older. Patients can only access the product on the order of a licensed healthcare provider, who will themselves have access to patient progress through an online portal where salient patient information is provided.
Table 1: Substantial Equivalence of Technological Characteristics
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| Access | Prescription only | Prescription only |
|---|---|---|
| Adjunct use | Adjunct to supervisedoutpatient treatment | Adjunct to supervisedoutpatient treatment |
| Mobile platform | Mobile application(Smartphones, tablets [iOSand Android]), and webapplication | Mobile application(Smartphones, tablets [iOSand Android]) |
| Software architecture | Patient facing mobileapplication or website,clinician facing dashboard,backend services | Patient facing mobileapplication, clinician facingdashboard, backend services |
7. Performance data
7.1. Summary of nonclinical performance data
Software verification and validation testing was completed and documentation was provided as recommended by Guidance for Industry and FDA Staff: Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (2005), for a Moderate level of concern device.
7.2. Summary of clinical performance data
Sleepio was evaluated in the Clinical Effectiveness of Digital Insomnia Therapy (CrEDIT) trial which was a two-arm, parallel group, randomized controlled trial (RCT) comparing digital CBT (Sleepio) with online sleep hygiene education in 336 adults aged 22+ with insomnia disorder, as diagnosed in the DSM-5. Participants were recruited from across the United States via social media. Participants were allocated to receive Sleepio (n=168) or online sleep hyqiene education (SHE; n=168) in addition to their usual care.
The co-primary endpoints were insomnia severity, assessed using the insomnia severity index (ISI), sleep diary sleep onset latency (SOL) and wake after sleep onset (WASO) at 10 weeks post-randomization. Analyses were performed to evaluate the odds of insomnia response (reduction in IS) score of ≥8) and remission (ISI<8) at 10 weeks. Follow-up assessments occurred at 16 and 24 weeks post- randomization. Secondary outcomes included insomnia symptoms assessed by the Sleep Condition Indicator (SCI-8).
The average age of the sample was 46.4 (SD=9.9) years. The study sample closely mapped onto the US population on racial and socioeconomic characteristics. See Table 2 for a summary of the study demographics and comparison with the US population.
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| Demographic characteristics | Sleepio pivotal trial(CrEDIT) | Comparison to USpopulation |
|---|---|---|
| Gender, Female, % | 56% | 50.2%1 |
| Race, White, % | 71% | 59%5 |
| Education, College degree orhigher, % | 56% | 54%3 |
| Income | 61% with income<$74.999 | Median = $74,5804 |
| Employment, Full time, % | 48% | 52%5 |
Table 2: Summary of the CrEDIT trial study demographics and comparison with the US population.
Study Results
A summary of the ITT sample results of the CrEDIT trial for Sleepio vs SHE is provided in Tables 3 and 4 below. A subsequent post-hoc analysis was conducted in participants who had ≤6.5 hours sleep duration at baseline and results for this subgroup are presented in Table 5. Note the data in table 4 was calculated post-hoc because LS Mean difference was not the statistical analysis method originally pre-specified in the statistical analysis plan.
Table 3: ISI, SOL and WASO summary statistics by group and time, and estimated treatment effects at week 10 (primary outcome), and week 16 (follow-up) and week 24 (longterm follow-up). Effects are between-group mean differences.
| Assessment | Unadjusted mean (SD); n | Adjusteddifference(SE) | 99% CI | p -value | Cohen's d | |
|---|---|---|---|---|---|---|
| SHE | Sleepio | |||||
| ISI | ||||||
| Baseline | 18.33(4.19); 168 | 18.12 (3.72);168 | ||||
| Week 10 | 14.74(5.00); 156 | 12.11 (6.10);138 | -2.37 (0.56) | -3.81, -0.92 | <0.001 | 0.606 |
| Week 16 | 14.60(5.19); 153 | 11.37 (5.67);129 | -2.55 (0.57) | -4.01, -1.09 | <0.001 | 0.65 |
| Week 24 | 14.80(5.49); 147 | 11.00 (5.93);125 | -3.05 (0.59) | -4.56, -1.54 | 0.77 | |
| SOL | ||||||
| Baseline | 53.92(41.83);168 | 54.30(38.41); 168 | ||||
| Week 10 | 45.54(48.82);157 | 36.75(32.00); 132 | -9.14 (3.63) | -18.49, 0.20 | 0.012 | 0.23 |
| Week 16 | 38.82(38.23);153 | 32.56(29.70); 124 | -6.68 (3.69) | -16.18, 2.83 | 0.070 | 0.17 |
| Week 24 | 36.49(40.73);147 | 32.80(43.59); 122 | -4.37 (3.99) | -14.64, 5.90 | 0.11 | |
| WASO | ||||||
| Baseline | 46.06(31.45);168 | 48.71(50.71); 168 | ||||
| Week 10 | 33.82(30.06);157 | 24.54(21.40); 132 | -8.86 (2.94) | -16.42, -1.29 | 0.003 | 0.21 |
| Week 16 | 35.27(32.75);153 | 23.97(23.32); 124 | -11.69(2.97) | -19.35, -4.03 | <0.001 | 0.28 |
| Week 24 | 35.64(35.10);147 | 24.11(27.03); 122 | -12.02(3.19) | -20.24, -3.80 | 0.29 |
1 US Census Bureau (2023). https://www.census.gov/content/dam/Census/newsroom/presskits/2023/paa/2023-paa-paper-financial-insecurity-hardship-pulse-gender-identity-sex.pdf
2 US Census Bureau (2020). https://www.census.gov/quickfacts/fact/table/US/PST045222
3 Lumina Foundation. (2023). https://www.luminafoundation.org/stronger-nation/report/#/progress
4 US Census Bureau (2022). Income in the United States: 2022.
https://www.census.gov/library/publications/2023/demo/p60-279.html
5 Bureau of Labor Statistics (2022). Work Experience of the Population.
https://www.bls.gov/news.release/pdf/work.pdf
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6 Effect size when calculated using the standard deviation of ISI change at week 10, the effect size is d=0.47
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| Sleepio pivotal trial (CrEDIT) ITT analysis | ||||
|---|---|---|---|---|
| Assessment | Timepoint | Sleepio LS Mean | SHE LS Mean | Sleepio LS Mean difference (95% CI) |
| ISI | Post-treatment | -6.03 | -3.66 | -2.37 (-3.53, -1.21) |
| 24-week follow-up | -6.82 | -3.86 | -2.97 (-4.30, -1.63) | |
| SOL | Post-treatment | -17.50 | -8.05 | -9.45 (-17.90, -1.01) |
| 24-week follow-up | -22.49 | -16.68 | -5.81 (-15.96, 4.34) | |
| WASO | Post-treatment | -21.70 | -11.43 | -10.26 (-19.02, -1.49) |
| 24-week follow-up | -20.45 | -10.13 | -10.32 (-20.10, -0.56) |
Table 4: LS mean differences for Sleepio and SHE at post-intervention and 24 week followup in the ITT sample
Table 4 note: The reported 95% Cls for week 24 follow-up are not from pre-specified hypothesis tests and are without multiplicity adjustment.
Table 5: LS mean differences for Sleepio and SHE at post-intervention and 24 week followup in participants with ≤6.5 hours sleep duration at baseline
| Sleepio pivotal trial (CrEDIT) with ≤6.5 hours sleep duration | ||||
|---|---|---|---|---|
| Assessment | Timepoint | Sleepio LS Mean | SHE LS Mean | Sleepio LS Mean difference (95% CI) |
| ISI | Post-treatment | -6.44 | -3.98 | -2.46 (-4.42,-0.50) |
| 24 week follow-up | -7.43 | -3.65 | -3.77 (-6.06, -1.48) | |
| SOL | Post-treatment | -18.25 | -2.39 | -15.85 (-32.39, 0.69) |
| 24 week follow-up | -29.24 | -16.87 | -12.37 (-26.93, 2.18) | |
| WASO | Post-treatment | -33.79 | -10.69 | -23.10 (-42.37, -3.84) |
| 24 week follow-up | -33.67 | -7.76 | -25.91 (-46.70, -5.11) |
Table 5 note: The reported 95% Cls are not from pre-specified hypothesis tests and are without multiplicity adjustment.
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Remission and Responder Analyses
Treatment response and remission were assessed using the ISI. In pre-specified analyses, response was defined as a change of ≥6 points from baseline, and remission defined as a score of <8. At 10 weeks, Sleepio participants had 2.52 odds of response (OR=2.52; p<0.001, 99% Cl: (1.33, 4.75)), and 5.8 odds of remission (OR=5.78; p<0.001, 99% Cl: (2.11, 15.84)) compared with SHE. A post-hoc response analysis using a definition of a change of ≥8 points from baseline on the ISI showed that Sleepio participants had 3.30 odds ratio of response compared to SHE participants (OR=3.30; 95% CI: (1.92, 5.69)).
Note: Odds ratio >1 for ISI means the odds of being in remission/response are higher in Sleepio than Control Group.
No adverse or serious adverse events were reported by participants.
8. Conclusion
Sleepio and the predicate Somryst have the same Intended Use as computerized behavioral therapy devices for psychiatric disorders. There are slight differences in indications for use in that Sleepio is considered appropriate for transitional adolescents (18-21) as well as adults (22+) but this does not constitute a new intended use. Sleepio has similar technological characteristics to Somryst, including software architecture, delivery of digital behavioral therapy through a mobile application, and therapeutic content. Software testing and pivotal clinical study results validate Sleepio towards its proposed Indications for Use. This validation reasonably assures that Sleepio is substantially equivalent to the predicate device. Further, Sleepio met all of the Special Controls per the requirements of the regulation (21 CFR 882.5801). Thus, Sleepio is substantially equivalent to Somryst.
§ 882.5801 Computerized behavioral therapy device for psychiatric disorders.
(a)
Identification. A computerized behavioral therapy device for psychiatric disorders is a prescription only device intended to provide a computerized version of condition-specific behavioral therapy as an adjunct to clinician supervised outpatient treatment to patients with psychiatric conditions. The digital therapy is intended to provide patients access to therapy tools used during treatment sessions to improve recognized treatment outcomes.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Clinical data must be provided to fulfill the following:
(i) Describe a validated model of behavioral therapy for the psychiatric disorder; and
(ii) Validate the model of behavioral therapy as implemented by the device.
(2) Software must be described in detail in the software requirements specification (SRS) and software design specification (SDS). Software verification, validation, and hazard analysis must be performed. Software documentation must demonstrate that the device effectively implements the behavioral therapy model.
(3) The following labeling must be provided:
(i) Patient and physician labeling must include instructions for use, including images that demonstrate how to interact with the device.
(ii) Patient and physician labeling must list compatible devices.
(iii) Patient and physician labeling must include a warning that the device is not intended for use as a standalone therapy.
(iv) Patient and physician labeling must include a warning that the device does not represent a substitution for the patient's medication.
(v) Physician labeling must include a summary of the clinical testing with the device.