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FDA Submission

Use of Digital Health Technologies in Clinical Investigations to Support Drug and Biological Product Development (U01) Clinical Trials Optional

Background & Context

 

The FDA are exploring innovative ways to produce scientific evidence in support of regulatory submissions, including the development of new data sources, study designs, methodologies, and technologies. The FDA encourages the use of innovative approaches while ensuring that the scientific evidence supporting marketing approvals meets its high evidentiary standards.

the FDA recently posted a funding opportunity to obtain proposal that address topics related to the use of digital health technologies (DHTs) for remote data acquisition in clinical investigations to support drug development.

Text about pilot content -

Link to Executive summary of the results

In 2022, industry partners (i.e. EFPIA) has worked with EMA to identify optimisations to the regulatory procedures for qualification of novel methodologies as part of an EMA Focus Group. As an outcome of this EMA Focus Group, it was agreed to run a pilot for optimisation of the EU procedure qualification of novel methodologies (QoNM) using the DEEP ecosystem to test these optimisations.

Suggested content: Text about previous DiMe work and how this pilot was continuation etc. Potential references to DiME website.

Condition: Atopic dermatitis

  • Quantity/Quality of Sleep

    Scratching has been demonstrated to be increased at night due to several factors, including a disinhibited unconscious scratch response, increased trans-epidermal water losses, reduced corticosteroid and anti-inflammatory levels, and higher circadian distal skin temperatures. Several of these factors are also noted and intertwined in leading to sleep disruptions.

    References:

    - Laughter, M. R., et al. "The global burden of atopic dermatitis: lessons from the Global Burden of Disease Study 1990–2017." British Journal of Dermatology 184.2 (2021): 304-309. - Howell, Michael D., Fiona I. Kuo, and Paul A. Smith. "Targeting the Janus kinase family in autoimmune skin diseases." Frontiers in immunology 10 (2019): 490313. - Yarbrough, Kevin B., Kristin J. Neuhaus, and Eric L. Simpson. "The effects of treatment on itch in atopic dermatitis." Dermatologic therapy 26.2 (2013): 110-119. - Murota, Hiroyuki, and Ichiro Katayama. "Exacerbating factors of itch in atopic dermatitis." Allergology International 66.1 (2017): 8-13. - Lyons, Jonathan J., Joshua D. Milner, and Kelly D. Stone. "Atopic dermatitis in children: clinical features, pathophysiology, and treatment." Immunology and Allergy Clinics 35.1 (2015): 161-183. - Cesnakova, Lucia, et al. "A patient‐centred conceptual model of nocturnal scratch and its impact in atopic dermatitis: A mixed‐methods study supporting the development of novel digital measurements." Skin Health and Disease 3.5 (2023): e262. - Ke Wang, Will, et al. "Defining the Digital Measurement of Scratching During Sleep or Nocturnal Scratching: Review of the Literature." Journal of Medical Internet Research 25 (2023): e43617. - Kong, Tae Seok, et al. "Correlation between severity of atopic dermatitis and sleep quality in children and adults." Annals of dermatology 28.3 (2016): 321. - Besedovsky, Luciana, Tanja Lange, and Monika Haack. "The sleep-immune crosstalk in health and disease." Physiological reviews (2019). - DiMe Nocturnal Scratch Patient Research Quantitative Data (https://datacc.dimesociety.org/digital-measures-nocturnal-scratch/) - Weidinger S, Novak N. Atopic dermatitis. Lancet. 2016 Mar 12;387(10023):1109-1122. doi: 10.1016/S0140-6736(15)00149-X. Epub 2015 Sep 13. PMID: 26377142 - Kiebert, Gwendoline, et al. "Atopic dermatitis is associated with a decrement in health‐related quality of life." International journal of dermatology 41.3 (2002): 151-158. - Chang, Yung-Sen, and Bor-Luen Chiang. "Mechanism of sleep disturbance in children with atopic dermatitis and the role of the circadian rhythm and melatonin." International journal of molecular sciences 17.4 (2016): 462. - Krueger, James M., et al. "The role of cytokines in physiological sleep regulation." Annals of the New York Academy of Sciences 933.1 (2001): 211-221. - Opp, Mark R. "Cytokines and sleep." Sleep medicine reviews 9.5 (2005): 355-364. - Cevikbas, Ferda, and Ethan A. Lerner. "Physiology and pathophysiology of itch." Physiological reviews 100.3 (2020): 945-982.

  • Nocturnal Scratch

    An action/behaviour, of rhythmic and repetitive skin contact movement performed during a delimited time of intended sleep; not restricted to any specific time of the day or night.

    Measurement Variables

    • Total Scratch Time: amount of time scratching in TSO (e.g., 45 minutes).

    • Frequency of scratch: number of scratch bouts per unit time (e.g., 6 bouts/hr).

    • Total Scratch Bouts: sum of all scratch bouts in TSO (e.g., 37 bouts).

    • Scratch Percentage: per cent of TSO spent scratching (e.g., 6%).

    References

    - Laughter, M. R., et al. "The global burden of atopic dermatitis: lessons from the Global Burden of Disease Study 1990–2017." British Journal of Dermatology 184.2 (2021): 304-309. - Yarbrough, Kevin B., Kristin J. Neuhaus, and Eric L. Simpson. "The effects of treatment on itch in atopic dermatitis." Dermatologic therapy 26.2 (2013): 110-119. - Murota, Hiroyuki, and Ichiro Katayama. "Exacerbating factors of itch in atopic dermatitis." Allergology International 66.1 (2017): 8-13. - Lyons, Jonathan J., Joshua D. Milner, and Kelly D. Stone. "Atopic dermatitis in children: clinical features, pathophysiology, and treatment." Immunology and Allergy Clinics 35.1 (2015): 161-183. -Lavery, Michael Joseph, et al. "Pruritus: an overview. What drives people to scratch an itch?." The Ulster medical journal 85.3 (2016): 164. - Patel, Tejesh, Yozo Ishiuji, and Gil Yosipovitch. "Nocturnal itch: why do we itch at night?." Acta dermato-venereologica 87.4 (2007): 295-298. - Rinaldi, Giulia. "The itch-scratch cycle: a review of the mechanisms." Dermatology practical & conceptual 9.2 (2019): 90. - Cesnakova, Lucia, et al. "A patient‐centred conceptual model of nocturnal scratch and its impact in atopic dermatitis: A mixed‐methods study supporting the development of novel digital measurements." Skin Health and Disease 3.5 (2023): e262. - Ke Wang, Will, et al. "Defining the Digital Measurement of Scratching During Sleep or Nocturnal Scratching: Review of the Literature." Journal of Medical Internet Research 25 (2023): e43617. - Mahadevan, Nikhil, et al. "Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices." NPJ Digital Medicine 4.1 (2021): 42. - Oetjen, Landon K., et al. "Sensory neurons co-opt classical immune signaling pathways to mediate chronic itch." Cell 171.1 (2017): 217-228. - Bordon, Yvonne. "JAK in the itch." Nature Reviews Immunology 17.10 (2017): 591-591. - Usoskin, Dmitry, et al. "Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing." Nature neuroscience 18.1 (2015): 145-153. - Digital Measure Development: Nocturnal Scratch. A Report prepared for the Digital Medicine Society (DiMe), April 2022 - DiMe Nocturnal Scratch Patient Research Quantitative Data Set (https://datacc.dimesociety.org/digital-measures-nocturnal-scratch/) - Cornelissen, Christian, et al. "IL-31 regulates differentiation and filaggrin expression in human organotypic skin models." Journal of allergy and clinical immunology 129.2 (2012): 426-433. - Cevikbas, Ferda, and Ethan A. Lerner. "Physiology and pathophysiology of itch." Physiological reviews 100.3 (2020): 945-982. - Weidinger S, Novak N. Atopic dermatitis. Lancet. 2016 Mar 12;387(10023):1109-1122. doi: 10.1016/S0140-6736(15)00149-X. Epub 2015 Sep 13. PMID: 26377142. - Kiebert, Gwendoline, et al. "Atopic dermatitis is associated with a decrement in health‐related quality of life." International journal of dermatology 41.3 (2002): 151-158. - Ebata, Toshiya, et al. "The characteristics of nocturnal scratching in adults with atopic dermatitis." British Journal of Dermatology 141.1 (1999): 82-86. - We Are Social & Meltwater (2023), “Digital 2023 Global Overview Report, “ Retrieved from https://datareportal.com/reports/digital-2023-global-overview-report on 09 Jan 2023. - Cook, Karon F., et al. "Idio Scale Judgment: evaluation of a new method for estimating responder thresholds." Quality of Life Research 26 (2017): 2961-2971. - Kiritchenko, Svetlana, and Saif M. Mohammad. "Best-worst scaling more reliable than rating scales: A case study on sentiment intensity annotation." arXiv preprint arXiv:1712.01765 (2017). - Northcott, C.A., et al. MOSAIC: Monitoring of Scratch via Accelerometry in Children with Atopic Dermatitis. #463. Revolutionizing Atopic Dermatitis, 13 June 2021. British Journal of Dermatology. 185(3); 473-686, 2021. - Beck L.A., et al. Scratch and Sleep Quantification in Atopic Dermatitis (SQUAD) Study. ISAD, 2021. - Cheung, Kei Long, et al. "Using best–worst scaling to investigate preferences in health care." Pharmacoeconomics 34 (2016): 1195-1209. - Masoumian Hosseini, Mohsen, et al. "Smartwatches in healthcare medicine: assistance and monitoring; a scoping review." BMC Medical Informatics and Decision Making 23.1 (2023): 248. - McCleary K. More than Skin Deep "Voice of the Patient" Report. 2019. - International Agency for Research on Cancer. "Night shift work, IARC monographs on the identification of carcinogenic hazards to humans." Lyon, France: IARC (2019).

  • Accelerometry-based measurement of Nocturnal Scratch

    A set of features and requirements that define the standard for the wrist-worn-accelerometry-based measurement of Nocturnal Scratch, classified into essential and desirable based on their importance.

    Measurement Definition

    Condition - Atopic dermatitis Meaningful Aspect of Health (MAH) - Quantity/Quality of Sleep (Atopic Dermatitis) COI - Nocturnal Scratch (Atopic Dermatitis)

    Performance Requirements

    Name

    Wear location [Essential]

    Sensor Type [Essential]

    Two devices [Essential]

    Sampling Frequency

    Compatibility [Desirable]

    Total Sleep Opportunity

    Determination [Essential]

    Scratch Classification

    [Essential]

    Sleep/Wake Classification

    [Desirable]

    Wear Classification [Desirable]

    Arm Angle

    Calculation [Desitable]

    Reference Measure for Scratch

    [Essential]

    Reference Measure for

    Sleep [Desirable]

    Reference Measure for Total

    Sleep Opportunity [Essential]

    Description

    Wrist

    These solutions include an accelerometer but also may include a

    gyroscope and/or temperature sensors to enable the determination of

    Total Sleep Opportunity and/or classification of scratch and/or sleep.

    One on each wrist, worn contemporaneously

    These solutions typically down-sample sensor data to 20 Hz. Down-

    sampling however is not required.

    These solutions are able to determine the Total Sleep Opportunity.

    Performance must be validated against a reference measure.

    The algorithm must be able to classify scratch periods of accelerometer

    data to provide measures of total scratch duration and scratch

    frequency during the Total Sleep Opportunity. Performance must be

    validated against a reference measure.

    A reference measure for validation of sleep classification is required, e.g., Polysomnography.

    A reference measure for sleep is not mandatory as long as a reference measure is available to validate the Total Sleep Opportunity. Reference measures used include Polysomnography.

    Some of these solutions are able to classify sleep/wake periods.

    Determine wear periods if the total sleep opportunity is algorithmically

    derived.

    Calculate arm angle if the total sleep opportunity is algorithmically

    derived via the method described in Mahadevan et al.

    A reference measure for validation of scratch classification is required.

    Reference measures used include observer annotated Infrared video.

    Component Type

    Measurement Method

    Measurement Method

    Measurement Method

    Algorithm

    Algorithm

    Algorithm

    Algorithm

    Algorithm

    Algorithm

    Technical Verification/

    Analytical Validation

    Technical Verification/

    Analytical Validation

    Technical Verification/

    Analytical Validation

    References

    - Ji, Ju, et al. "Assessing nocturnal scratch with actigraphy in atopic dermatitis patients." NPJ Digital Medicine 6.1 (2023): 72. - Mahadevan, Nikhil, et al. "Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices." NPJ Digital Medicine 4.1 (2021): 42. - Moreau, Arnaud, et al. "Detection of nocturnal scratching movements in patients with atopic dermatitis using accelerometers and recurrent neural networks." IEEE journal of biomedical and health informatics 22.4 (2017): 1011-1018.

  • Measurement of nocturnal scratch and sleep using accelerometry (GeneActiv) and heuristic and machine learning algorithms in a hierarchical paradigm

    This solution uses a method that sequentially processes epochs of sample-level accelerometer data from a wrist-worn device to provide continuous digital measures of night-time scratching and sleep quantity. This approach uses heuristic and machine learning algorithms in a hierarchical paradigm by first determining when the patient intends to sleep, then detecting sleep–wake states along with scratching episodes, and lastly deriving objective measures of both sleep and scratch. Results are validated using polysomnography and video.

    Name

    FLIR A35; Flir Systems, Wilsonville, OR, USA

    GeneActiv Original; Activinsights, Kimbolton, UK

    Sleep module providing measures of sleep quality

    Atopic dermatitis patients - Accelerometry, Polysomnography, Video

    Scratch module for predictions of nigh-time scratch

    Polysomnography as a reference measure for sleep assessment

    Infrared video as a reference measure for scratch assessment

    Evaluating the performance of aggregate night time scratch endpoints

    Performance of aggregate night-time scratch endpoints

    Component Type

    Measurement Method

    Measurement Method

    Algorithm

    Algorithm

    Raw Data

    Technical Verification/Analytical Validation

    Technical Verification/Analytical Validation

    Clinical Validation

    Clinical Validation

    References:

    Mahadevan, Nikhil, et al. "Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices." NPJ Digital Medicine 4.1 (2021): 42.

  • Measurement of nocturnal scratch using accelerometry (GeneActiv) and recurrent neural networks

    This solution presents an algorithm to detect nocturnal scratching events based on accelerometry data. The twofold process consists of segmenting the data into “no motion,” “single handed motion,” and “both handed motion” followed by discriminating motion segments into scratching and other motion using a bidirectional recurrent neural network classifier. Results are validated using data gathered by infrared video.

    Name

    GeneActiv Original; Activinsights, Kimbolton, UK

    Recurrent Neural Network for scratch detection

    Atopic dermatitis patients - Accelerometry, Polysomnography, Video

    Infrared video as a reference measure for scratch assessment

    Evaluating the performance of the algorithm to score scratching events

    based on high-resolution actigraphy data

    Performance of algorithm to score scratching events based on

    high-resolution actigraphy data

    Component Type

    Measurement Method

    Algorithm

    Raw Data

    Technical Verification/Analytical Validation

    Clinical Validation

    Clinical Validation

    References:

    Moreau, Arnaud, et al. "Detection of nocturnal scratching movements in patients with atopic dermatitis using accelerometers and recurrent neural networks." IEEE journal of biomedical and health informatics 22.4 (2017): 1011-1018.

  • Measurement of nocturnal scratch using accelerometry and gyroscope (AX6) and a binary classifier trained to detect scratch events

    This solution presents the use of actigraphy (an accelerometer and gyroscope), highly predictive topological features, and a model-ensembling approach to develop an assessment of nocturnal scratch events by measuring scratch duration and intensity. The results are tested in a clinical setting against the ground truth obtained from video recordings, bed sensors and patient reported outcomes.

    Name

    AX6: 6-Axis Logging Accelerometer

    Emfit Bed Sensor

    Binary classifier trained to detect scratch events

    Atopic Dermatitis – Actigraphy, gyroscopic, video, patient-reported outcomes

    Infrared video as a reference measure for scratch assessment

    Patient Reported Outcome - Severity Scoring of Atopic Dermatitis Index

    Patient Reported Outcome - Atopic Dermatitis Sleep Scale

    Evaluating the assessment of nocturnal scratch with actigraphy

    Performance of the assessment of nocturnal scratch with actigraphy

    Component Type

    Measurement Method

    Measurement Method

    Algorithm

    Raw Data

    Technical Verification/Analytical Validation

    Technical Verification/Analytical Validation

    Technical Verification/Analytical Validation

    Clinical Validation

    Clinical Validation

    References:

    Ji, Ju, et al. "Assessing nocturnal scratch with actigraphy in atopic dermatitis patients." NPJ Digital Medicine 6.1 (2023): 72.

Condition: Psoriasis

  • Quality/Quantity of SLeep

    References

    - Armstrong AW. Psoriasis. JAMA Dermatol. 2017;153(9):956.
    - Helmick, Charles G., et al. "Prevalence of psoriasis among adults in the US: 2003–2006 and 2009–2010 National Health and Nutrition Examination Surveys." American journal of preventive medicine 47.1 (2014): 37-45.

  • Nocturnal Scratch

    References

    - Furue, Kazuhisa, et al. "Pathogenic implication of epidermal scratch injury in psoriasis and atopic dermatitis." The Journal of Dermatology 47.9 (2020): 979-988.
    - Szepietowski, Jacek C., Adam Reich, and Beata Wiśnicka. "Itching in patients suffering from psoriasis." Acta dermatovenerologica Croatica: ADC 10.4 (2002): 221-226.
    - Komiya, Eriko, et al. "Molecular and cellular mechanisms of itch in psoriasis." International Journal of Molecular Sciences 21.21 (2020): 8406.
    - Zhang, Xiaolin, et al. "Characteristics and pathogenesis of Koebner phenomenon." Experimental dermatology 32.4 (2023): 310-323.

Consortium Partners:

Condition: Atopic Dermatitis

  • Quantity/Quality of Sleep

    Scratching has been demonstrated to be increased at night due to several factors, including a disinhibited unconscious scratch response, increased trans-epidermal water losses, reduced corticosteroid and anti-inflammatory levels, and higher circadian distal skin temperatures. Several of these factors are also noted and intertwined in leading to sleep disruptions.

    References:

    - Laughter, M. R., et al. "The global burden of atopic dermatitis: lessons from the Global Burden of Disease Study 1990–2017." British Journal of Dermatology 184.2 (2021): 304-309. - Howell, Michael D., Fiona I. Kuo, and Paul A. Smith. "Targeting the Janus kinase family in autoimmune skin diseases." Frontiers in immunology 10 (2019): 490313. - Yarbrough, Kevin B., Kristin J. Neuhaus, and Eric L. Simpson. "The effects of treatment on itch in atopic dermatitis." Dermatologic therapy 26.2 (2013): 110-119. - Murota, Hiroyuki, and Ichiro Katayama. "Exacerbating factors of itch in atopic dermatitis." Allergology International 66.1 (2017): 8-13. - Lyons, Jonathan J., Joshua D. Milner, and Kelly D. Stone. "Atopic dermatitis in children: clinical features, pathophysiology, and treatment." Immunology and Allergy Clinics 35.1 (2015): 161-183. - Cesnakova, Lucia, et al. "A patient‐centred conceptual model of nocturnal scratch and its impact in atopic dermatitis: A mixed‐methods study supporting the development of novel digital measurements." Skin Health and Disease 3.5 (2023): e262. - Ke Wang, Will, et al. "Defining the Digital Measurement of Scratching During Sleep or Nocturnal Scratching: Review of the Literature." Journal of Medical Internet Research 25 (2023): e43617. - Kong, Tae Seok, et al. "Correlation between severity of atopic dermatitis and sleep quality in children and adults." Annals of dermatology 28.3 (2016): 321. - Besedovsky, Luciana, Tanja Lange, and Monika Haack. "The sleep-immune crosstalk in health and disease." Physiological reviews (2019). - DiMe Nocturnal Scratch Patient Research Quantitative Data (https://datacc.dimesociety.org/digital-measures-nocturnal-scratch/) - Weidinger S, Novak N. Atopic dermatitis. Lancet. 2016 Mar 12;387(10023):1109-1122. doi: 10.1016/S0140-6736(15)00149-X. Epub 2015 Sep 13. PMID: 26377142 - Kiebert, Gwendoline, et al. "Atopic dermatitis is associated with a decrement in health‐related quality of life." International journal of dermatology 41.3 (2002): 151-158. - Chang, Yung-Sen, and Bor-Luen Chiang. "Mechanism of sleep disturbance in children with atopic dermatitis and the role of the circadian rhythm and melatonin." International journal of molecular sciences 17.4 (2016): 462. - Krueger, James M., et al. "The role of cytokines in physiological sleep regulation." Annals of the New York Academy of Sciences 933.1 (2001): 211-221. - Opp, Mark R. "Cytokines and sleep." Sleep medicine reviews 9.5 (2005): 355-364. - Cevikbas, Ferda, and Ethan A. Lerner. "Physiology and pathophysiology of itch." Physiological reviews 100.3 (2020): 945-982.

  • Nocturnal Scratch

    An action/behaviour, of rhythmic and repetitive skin contact movement performed during a delimited time of intended sleep; not restricted to any specific time of the day or night.

    Measurement Variables

    • Total Scratch Time: amount of time scratching in TSO (e.g., 45 minutes).

    • Frequency of scratch: number of scratch bouts per unit time (e.g., 6 bouts/hr).

    • Total Scratch Bouts: sum of all scratch bouts in TSO (e.g., 37 bouts).

    • Scratch Percentage: per cent of TSO spent scratching (e.g., 6%).

    References

    - Laughter, M. R., et al. "The global burden of atopic dermatitis: lessons from the Global Burden of Disease Study 1990–2017." British Journal of Dermatology 184.2 (2021): 304-309. - Yarbrough, Kevin B., Kristin J. Neuhaus, and Eric L. Simpson. "The effects of treatment on itch in atopic dermatitis." Dermatologic therapy 26.2 (2013): 110-119. - Murota, Hiroyuki, and Ichiro Katayama. "Exacerbating factors of itch in atopic dermatitis." Allergology International 66.1 (2017): 8-13. - Lyons, Jonathan J., Joshua D. Milner, and Kelly D. Stone. "Atopic dermatitis in children: clinical features, pathophysiology, and treatment." Immunology and Allergy Clinics 35.1 (2015): 161-183. -Lavery, Michael Joseph, et al. "Pruritus: an overview. What drives people to scratch an itch?." The Ulster medical journal 85.3 (2016): 164. - Patel, Tejesh, Yozo Ishiuji, and Gil Yosipovitch. "Nocturnal itch: why do we itch at night?." Acta dermato-venereologica 87.4 (2007): 295-298. - Rinaldi, Giulia. "The itch-scratch cycle: a review of the mechanisms." Dermatology practical & conceptual 9.2 (2019): 90. - Cesnakova, Lucia, et al. "A patient‐centred conceptual model of nocturnal scratch and its impact in atopic dermatitis: A mixed‐methods study supporting the development of novel digital measurements." Skin Health and Disease 3.5 (2023): e262. - Ke Wang, Will, et al. "Defining the Digital Measurement of Scratching During Sleep or Nocturnal Scratching: Review of the Literature." Journal of Medical Internet Research 25 (2023): e43617. - Mahadevan, Nikhil, et al. "Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices." NPJ Digital Medicine 4.1 (2021): 42. - Oetjen, Landon K., et al. "Sensory neurons co-opt classical immune signaling pathways to mediate chronic itch." Cell 171.1 (2017): 217-228. - Bordon, Yvonne. "JAK in the itch." Nature Reviews Immunology 17.10 (2017): 591-591. - Usoskin, Dmitry, et al. "Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing." Nature neuroscience 18.1 (2015): 145-153. - Digital Measure Development: Nocturnal Scratch. A Report prepared for the Digital Medicine Society (DiMe), April 2022 - DiMe Nocturnal Scratch Patient Research Quantitative Data Set (https://datacc.dimesociety.org/digital-measures-nocturnal-scratch/) - Cornelissen, Christian, et al. "IL-31 regulates differentiation and filaggrin expression in human organotypic skin models." Journal of allergy and clinical immunology 129.2 (2012): 426-433. - Cevikbas, Ferda, and Ethan A. Lerner. "Physiology and pathophysiology of itch." Physiological reviews 100.3 (2020): 945-982. - Weidinger S, Novak N. Atopic dermatitis. Lancet. 2016 Mar 12;387(10023):1109-1122. doi: 10.1016/S0140-6736(15)00149-X. Epub 2015 Sep 13. PMID: 26377142. - Kiebert, Gwendoline, et al. "Atopic dermatitis is associated with a decrement in health‐related quality of life." International journal of dermatology 41.3 (2002): 151-158. - Ebata, Toshiya, et al. "The characteristics of nocturnal scratching in adults with atopic dermatitis." British Journal of Dermatology 141.1 (1999): 82-86. - We Are Social & Meltwater (2023), “Digital 2023 Global Overview Report, “ Retrieved from https://datareportal.com/reports/digital-2023-global-overview-report on 09 Jan 2023. - Cook, Karon F., et al. "Idio Scale Judgment: evaluation of a new method for estimating responder thresholds." Quality of Life Research 26 (2017): 2961-2971. - Kiritchenko, Svetlana, and Saif M. Mohammad. "Best-worst scaling more reliable than rating scales: A case study on sentiment intensity annotation." arXiv preprint arXiv:1712.01765 (2017). - Northcott, C.A., et al. MOSAIC: Monitoring of Scratch via Accelerometry in Children with Atopic Dermatitis. #463. Revolutionizing Atopic Dermatitis, 13 June 2021. British Journal of Dermatology. 185(3); 473-686, 2021. - Beck L.A., et al. Scratch and Sleep Quantification in Atopic Dermatitis (SQUAD) Study. ISAD, 2021. - Cheung, Kei Long, et al. "Using best–worst scaling to investigate preferences in health care." Pharmacoeconomics 34 (2016): 1195-1209. - Masoumian Hosseini, Mohsen, et al. "Smartwatches in healthcare medicine: assistance and monitoring; a scoping review." BMC Medical Informatics and Decision Making 23.1 (2023): 248. - McCleary K. More than Skin Deep "Voice of the Patient" Report. 2019. - International Agency for Research on Cancer. "Night shift work, IARC monographs on the identification of carcinogenic hazards to humans." Lyon, France: IARC (2019).

  • Accelerometry-based measurement of Nocturnal Scratch

    Condition - Atopic dermatitis
    Meaningful Aspect of Health (MAH) - Quantity/Quality of Sleep (Atopic Dermatitis)
    Concept of Interest (COI) - Nocturnal Scratch (Atopic Dermatitis)

    A set of features and requirements that define the standard for the wrist-worn-accelerometry-based measurement of Nocturnal Scratch, classified into essential and desirable based on their importance.

    Measurement Definition

    Name

    Wear location [Essential]

    Sensor Type [Essential]

    Two devices [Essential]

    Sampling Frequency

    Compatibility [Desirable]

    Total Sleep Opportunity

    Determination [Essential]

    Scratch Classification

    [Essential]

    Sleep/Wake Classification

    [Desirable]

    Wear Classification [Desirable]

    Arm Angle

    Calculation [Desitable]

    Reference Measure for Scratch

    [Essential]

    Reference Measure for

    Sleep [Desirable]

    Reference Measure for Total

    Sleep Opportunity [Essential]

    Description

    Wrist

    These solutions include an accelerometer but also may include a

    gyroscope and/or temperature sensors to enable the determination of

    Total Sleep Opportunity and/or classification of scratch and/or sleep.

    One on each wrist, worn contemporaneously

    These solutions typically down-sample sensor data to 20 Hz. Down-

    sampling however is not required.

    These solutions are able to determine the Total Sleep Opportunity.

    Performance must be validated against a reference measure.

    The algorithm must be able to classify scratch periods of accelerometer

    data to provide measures of total scratch duration and scratch

    frequency during the Total Sleep Opportunity. Performance must be

    validated against a reference measure.

    A reference measure for validation of sleep classification is required, e.g., Polysomnography.

    A reference measure for sleep is not mandatory as long as a reference measure is available to validate the Total Sleep Opportunity. Reference measures used include Polysomnography.

    Some of these solutions are able to classify sleep/wake periods.

    Determine wear periods if the total sleep opportunity is algorithmically

    derived.

    Calculate arm angle if the total sleep opportunity is algorithmically

    derived via the method described in Mahadevan et al.

    A reference measure for validation of scratch classification is required.

    Reference measures used include observer annotated Infrared video.

    Component Type

    Measurement Method

    Measurement Method

    Measurement Method

    Algorithm

    Algorithm

    Algorithm

    Algorithm

    Algorithm

    Algorithm

    Technical Verification/

    Analytical Validation

    Technical Verification/

    Analytical Validation

    Technical Verification/

    Analytical Validation

    References

    - Ji, Ju, et al. "Assessing nocturnal scratch with actigraphy in atopic dermatitis patients." NPJ Digital Medicine 6.1 (2023): 72. - Mahadevan, Nikhil, et al. "Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices." NPJ Digital Medicine 4.1 (2021): 42. - Moreau, Arnaud, et al. "Detection of nocturnal scratching movements in patients with atopic dermatitis using accelerometers and recurrent neural networks." IEEE journal of biomedical and health informatics 22.4 (2017): 1011-1018.

    Name
    Description
    Component Type
    Reference Measure for Total Sleep Opportunity [Essential]
    A reference measure for validation of sleep classification is required, e.g., Polysomnography.
    Technical Verification/ Analytical Validation
    Reference Measure for Sleep [Desirable]
    ​A  reference measure for sleep is not mandatory as long as a reference  measure is available to validate the Total Sleep Opportunity. Reference  measures used include Polysomnography.
    Technical Verification/ Analytical Validation
    Reference Measure for Scratch [Essential]
    A reference measure for validation of scratch classification is required. Reference measures used include observer annotated Infrared video.
    Technical Verification/ Analytical Validation
    Arm Angle Calculation [Desitable]
    Calculate arm angle if the total sleep opportunity is algorithmically derived via the method described in Mahadevan et al.
    Algorithm
    Wear Classification [Desirable]
    Determine wear periods if the total sleep opportunity is algorithmically derived.
    Algorithm
    Sleep/Wake Classification [Desirable]
    ​Some of these solutions are able to classify sleep/wake periods.
    Algorithm
    Scratch Classification [Essential]
    The algorithm must be able to classify scratch periods of accelerometer data to provide measures of total scratch duration and scratch frequency during the Total Sleep Opportunity. Performance must be validated against a reference measure.
    Algorithm
    Total Sleep Opportunity Determination [Essential]
    These solutions are able to determine the Total Sleep Opportunity. Performance must be validated against a reference measure.
    Algorithm
    Sampling Frequency Compatibility [Desirable]
    These solutions typically down-sample sensor data to 20 Hz. Down- sampling however is not required.
    Algorithm
    Two devices [Essential]
    One on each wrist, worn contemporaneously
    Measurement Method
    Sensor Type [Essential]
    These solutions include an accelerometer but also may include a gyroscope and/or temperature sensors to enable the determination of Total Sleep Opportunity and/or classification of scratch and/or sleep.
    Measurement Method
    Wear location [Essential]
    Wrist
    Measurement Method

    Performance Requirements

  • Measurement of nocturnal scratch and sleep using accelerometry (GeneActiv) and heuristic and machine learning algorithms in a hierarchical paradigm

    This solution uses a method that sequentially processes epochs of sample-level accelerometer data from a wrist-worn device to provide continuous digital measures of night-time scratching and sleep quantity. This approach uses heuristic and machine learning algorithms in a hierarchical paradigm by first determining when the patient intends to sleep, then detecting sleep–wake states along with scratching episodes, and lastly deriving objective measures of both sleep and scratch. Results are validated using polysomnography and video.

    Name

    FLIR A35; Flir Systems, Wilsonville, OR, USA

    GeneActiv Original; Activinsights, Kimbolton, UK

    Sleep module providing measures of sleep quality

    Atopic dermatitis patients - Accelerometry, Polysomnography, Video

    Scratch module for predictions of nigh-time scratch

    Polysomnography as a reference measure for sleep assessment

    Infrared video as a reference measure for scratch assessment

    Evaluating the performance of aggregate night time scratch endpoints

    Performance of aggregate night-time scratch endpoints

    Component Type

    Measurement Method

    Measurement Method

    Algorithm

    Algorithm

    Raw Data

    Technical Verification/Analytical Validation

    Technical Verification/Analytical Validation

    Clinical Validation

    Clinical Validation

    References:

    Mahadevan, Nikhil, et al. "Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices." NPJ Digital Medicine 4.1 (2021): 42.

    Component Name*
    Component Type
    FLIR A35; Flir Systems, Wilsonville, OR, USA
    Measurement Method
    GeneActiv Original; Activinsights, Kimbolton, UK
    Measurement Method
    Performance of aggregate night-time scratch endpoints
    Clinical Validation
    Evaluating the performance of aggregate night time scratch endpoints
    Technical Verification/Analytical Validation
    Infrared video as a reference measure for scratch assessment
    Technical Verification/Analytical Validation
    Polysomnography as a reference measure for sleep assessment
    Raw Data
    Atopic dermatitis patients - Accelerometry, Polysomnography, Video
    Algorithm
    Scratch module for predictions of nigh-time scratch
    Algorithm
    Sleep module providing measures of sleep quality
    Algorithm
  • Measurement of nocturnal scratch using accelerometry (GeneActiv) and recurrent neural networks

    This solution presents an algorithm to detect nocturnal scratching events based on accelerometry data. The twofold process consists of segmenting the data into “no motion,” “single handed motion,” and “both handed motion” followed by discriminating motion segments into scratching and other motion using a bidirectional recurrent neural network classifier. Results are validated using data gathered by infrared video.

    Name

    GeneActiv Original; Activinsights, Kimbolton, UK

    Recurrent Neural Network for scratch detection

    Atopic dermatitis patients - Accelerometry, Polysomnography, Video

    Infrared video as a reference measure for scratch assessment

    Evaluating the performance of the algorithm to score scratching events

    based on high-resolution actigraphy data

    Performance of algorithm to score scratching events based on

    high-resolution actigraphy data

    Component Type

    Measurement Method

    Algorithm

    Raw Data

    Technical Verification/Analytical Validation

    Clinical Validation

    Clinical Validation

    References:

    Moreau, Arnaud, et al. "Detection of nocturnal scratching movements in patients with atopic dermatitis using accelerometers and recurrent neural networks." IEEE journal of biomedical and health informatics 22.4 (2017): 1011-1018.

    Component Name*
    Component Type
    Performance of algorithm to score scratching events based on high-resolution actigraphy data
    Clinical Validation
    Evaluating the performance of the algorithm to score scratching events based on high-resolution actigraphy data
    Clinical Validation
    Infrared video as a reference measure for scratch assessment
    Technical Verification/Analytical Validation
    Atopic dermatitis patients - Accelerometry, Polysomnography, Video
    Raw Data
    Recurrent Neural Network for scratch detection
    Algorithm
    GeneActiv Original; Activinsights, Kimbolton, UK
    Measurement Method
  • Measurement of nocturnal scratch using accelerometry and gyroscope (AX6) and a binary classifier trained to detect scratch events

    Component Name*
    Component Type
    Performance of the assessment of nocturnal scratch with actigraphy
    Clinical Validation
    Evaluating the assessment of nocturnal scratch with actigraphy
    Clinical Validation
    Patient Reported Outcome - Atopic Dermatitis Sleep Scale
    Technical Verification/Analytical Validation
    Patient Reported Outcome - Severity Scoring of Atopic Dermatitis Index
    Technical Verification/Analytical Validation
    Infrared video as a reference measure for scratch assessment
    Technical Verification/Analytical Validation
    Atopic Dermatitis – Actigraphy, gyroscopic, video, patient-reported outcomes
    Raw Data
    Binary classifier trained to detect scratch events
    Algorithm
    Emfit Bed Sensor
    Measurement Method
    AX6: 6-Axis Logging Accelerometer
    Measurement Method

    This solution presents the use of actigraphy (an accelerometer and gyroscope), highly predictive topological features, and a model-ensembling approach to develop an assessment of nocturnal scratch events by measuring scratch duration and intensity. The results are tested in a clinical setting against the ground truth obtained from video recordings, bed sensors and patient reported outcomes.

    Name

    AX6: 6-Axis Logging Accelerometer

    Emfit Bed Sensor

    Binary classifier trained to detect scratch events

    Atopic Dermatitis – Actigraphy, gyroscopic, video, patient-reported outcomes

    Infrared video as a reference measure for scratch assessment

    Patient Reported Outcome - Severity Scoring of Atopic Dermatitis Index

    Patient Reported Outcome - Atopic Dermatitis Sleep Scale

    Evaluating the assessment of nocturnal scratch with actigraphy

    Performance of the assessment of nocturnal scratch with actigraphy

    Component Type

    Measurement Method

    Measurement Method

    Algorithm

    Raw Data

    Technical Verification/Analytical Validation

    Technical Verification/Analytical Validation

    Technical Verification/Analytical Validation

    Clinical Validation

    Clinical Validation

    References:

    Ji, Ju, et al. "Assessing nocturnal scratch with actigraphy in atopic dermatitis patients." NPJ Digital Medicine 6.1 (2023): 72.

Condition: Atopic Dermatitis

  • Quality/Quantity of Sleep

    References

    - Armstrong AW. Psoriasis. JAMA Dermatol. 2017;153(9):956.
    - Helmick, Charles G., et al. "Prevalence of psoriasis among adults in the US: 2003–2006 and 2009–2010 National Health and Nutrition Examination Surveys." American journal of preventive medicine 47.1 (2014): 37-45.

  • Nocturnal Scratch

    References

    - Furue, Kazuhisa, et al. "Pathogenic implication of epidermal scratch injury in psoriasis and atopic dermatitis." The Journal of Dermatology 47.9 (2020): 979-988.
    - Szepietowski, Jacek C., Adam Reich, and Beata Wiśnicka. "Itching in patients suffering from psoriasis." Acta dermatovenerologica Croatica: ADC 10.4 (2002): 221-226.
    - Komiya, Eriko, et al. "Molecular and cellular mechanisms of itch in psoriasis." International Journal of Molecular Sciences 21.21 (2020): 8406.
    - Zhang, Xiaolin, et al. "Characteristics and pathogenesis of Koebner phenomenon." Experimental dermatology 32.4 (2023): 310-323.

Consortium Partners:

Collaborating Partners

DEEP responded to this opportunity as follows:

Aim 1:  Introduce the DEEP model and demonstrate how the FDA can benefit from a) A structured review to support the measures for nocturnal scratch in Psoriasis b) Consistent evidence generation across a range of digital health tools

Aim 2:  Demonstrate how DEEP supports both the collaborative development of common definitions and performance requirements as well as the private early conversations about applicability in specific drug programs with specific solutions.

Aim 3: Present DEEP as a method for developing emerging standards and the collaboration with CDISC consensus methods to formalize them.

Aim 4: Fully develop and qualify the Nocturnal Scratch use case

Introductory Video

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