Considerations for development of an evidence dossier to support the use of mobile sensor technology for clinical outcome assessments in clinical trials

Walton, Marc K.; Cappelleri, Joseph C.; Byrom, Bill; Goldsack, Jennifer C.; Eremenco, Sonya; Harris, Denzil A.; Potero, Ed; Patel, Nikunj; Flood, Emuella; Däumer, Martin

doi:10.1016/j.cct.2020.105962

Cited by 38 publications

(31 citation statements)

References 15 publications

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“…The FDA, EMA and National Institute for Health and Care Excellence have issued guidances 38 – 42 which acknowledge the fast-moving nature of this field. We believe that enough data and experience exist in the DHTT community to converge on a consensus on digital outcome measure development that respects the principles of established methods for outcome development 43 .…”

Section: Discussionmentioning

confidence: 98%

Outcome measures based on digital health technology sensor data: data- and patient-centric approaches

et al. 2020

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Digital health technology tools (DHTT) are technologies such as apps, smartphones, and wearables that remotely acquire healthrelated information from individuals. They have the potential advantages of objectivity and sensitivity of measurement, richness of high-frequency sensor data, and opportunity for passive collection of health-related data. Thus, DHTTs promise to provide patient phenotyping at an order of granularity several times greater than is possible with traditional clinical research tools. While the conceptual development of novel DHTTs is keeping pace with technological and analytical advancements, an as yet unaddressed gap is how to develop robust and meaningful outcome measures based on sensor data. Here, we describe two roadmaps which were developed to generate outcome measures based on DHTT data: one using a data-centric approach and the second a patientcentric approach. The data-centric approach to develop digital outcome measures summarizes those sensor features maximally sensitive to the concept of interest, exemplified with the quantification of disease progression. The patient-centric approach summarizes those sensor features that are optimally relevant to patients' functioning in everyday life. Both roadmaps are exemplified for use in tracking disease progression in observational and clinical interventional studies, and with a DHTT designed to evaluate motor symptom severity and symptom experience in Parkinson's disease. Use cases other than disease progression (e.g., case-finding) are considered summarily. DHTT research requires methods to summarize sensor data into meaningful outcome measures. It is hoped that the concepts outlined here will encourage a scientific discourse and eventual consensus on the creation of novel digital outcome measures for both basic clinical research and clinical drug development.

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Section: Discussionmentioning

confidence: 98%

Outcome measures based on digital health technology sensor data: data- and patient-centric approaches

et al. 2020

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“…The list below illustrates examples of barriers to be addressed or overcome at the present time, some which have been reviewed by others (e.g., [14,15] The issues outlined above are difficult to address by any single individual entity. Precompetitive collaborations and public-private partnerships have been proposed as efficient means to address gaps in the development of DHT and their optimal use in drug development [16]. The opportunity to achieve a consensus among multidisciplinary stakeholders is one of the many reasons why public-private partnerships have grown in number.…”

Section: Challenges and Barriers To Advancing Dht For Use In Pd Trialsmentioning

confidence: 99%

“…A broad range of new precompetitive collaborations that have been launched over the past several years is now serving to engage and convene diverse stakeholders with expertise in DHT with clinical, academic, and industry researchers (e.g., [14,16,[21][22][23][24]). Many of these efforts represent true case examples illustrating how precompetitive collaborative activities are being employed efficiently to address challenges in the field.…”

Section: Examples Of How Collaborations Can Address Gapsmentioning

confidence: 99%

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science

et al. 2020

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Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease. This poses a major challenge for the development of new therapies and is compounded by the considerable heterogeneity in clinical manifestations across patients and the fluctuating nature of many signs and symptoms of PD. Digital health technologies (DHT), such as smartphone applications, wearable sensors, and digital diaries, have the potential to address many of these gaps by enabling the objective, remote, and frequent measurement of PD signs and symptoms in natural living environments. The current climate of the COVID-19 pandemic creates a heightened sense of urgency for effective implementation of such strategies. In order for these technologies to be adopted in drug development studies, a regulatory-aligned consensus on best practices in implementing appropriate technologies, including the collection, processing, and interpretation of digital sensor data, is required. A growing number of collaborative initiatives are being launched to identify effective ways to advance the use of DHT in PD clinical trials. The Critical Path for Parkinson’s Consortium of the Critical Path Institute is highlighted as a case example where stakeholders collectively engaged regulatory agencies on the effective use of DHT in PD clinical trials. Global regulatory agencies, including the US Food and Drug Administration and the European Medicines Agency, are encouraging the efficiencies of data-driven engagements through multistakeholder consortia. To this end, we review how the advancement of DHT can be most effectively achieved by aligning knowledge, expertise, and data sharing in ways that maximize efficiencies.

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“…Important contributions have been made to bring stakeholders onto the same page, e.g. harmonisation of terms for biomarkers and end points [7], guidelines for development of novel digital end points [8,9], frameworks for validation and primers [10][11][12], and guidelines for interactions with regulators [13][14][15]. However, the challenge for anyone aiming to deliver digital tools approved for use in research and ultimately clinical practice is to bring these recommendations together in one seamless roadmap from inception to adoption.…”

Section: Challenges To Adoption Of Dmosmentioning

confidence: 99%

A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach

et al. 2020

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Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely. Loss of mobility is also an important feature of many health conditions, providing a read-out of health as well as a target for intervention. Real-world, continuous digital measures of mobility (digital mobility outcomes or DMOs) provide an opportunity for novel insights into health care conditions complementing existing mobility measures. Accepted and approved DMOs are not yet widely available. The need for large collaborative efforts to tackle the critical steps to adoption is widely recognised. Mobilise-D is an example. It is a multidisciplinary consortium of 34 institutions from academia and industry funded through the European Innovative Medicines Initiative 2 Joint Undertaking. Members of Mobilise-D are collaborating to address the critical steps for DMOs to be adopted in clinical trials and ultimately health care. To achieve this, the consortium has developed a roadmap to inform the development, validation and approval of DMOs in Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease and recovery from proximal femoral fracture. Here we aim to describe the proposed approach and provide a high-level view of the ongoing and planned work of the Mobilise-D consortium. Ultimately, Mobilise-D aims to stimulate widespread adoption of DMOs through the provision of device agnostic software, standards and robust validation in order to bring digital outcomes from concept to use in clinical trials and health care.

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Considerations for development of an evidence dossier to support the use of mobile sensor technology for clinical outcome assessments in clinical trials

Cited by 38 publications

References 15 publications

Outcome measures based on digital health technology sensor data: data- and patient-centric approaches

Outcome measures based on digital health technology sensor data: data- and patient-centric approaches

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science

A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach

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