ACCESS enables individuals to contribute to critical research, via an iOS and Android smartphone mobile application. ACCESS combines patient reported outcomes, data from wearable devices and real-world data (such as claims, EHRs, etc), with an opt-in to participate in current and future studies for diagnostics, treatments and vaccines. The data that people share can be quickly and anonymously matched to research studies, providing researchers with a foundational framework for dynamic research at scale and participants a way to be personally matched and prescreened for future research.
In the urgency of the COVID-19 outbreak, Medable will enable an observational study protocol under which clinical trials can rapidly be conducted. The observational study protocol will include the conduct of smartphone based research to capture an essential dataset to improve our understanding of disease evolution, risk factors, and outcomes as well as enable population-based monitoring to reduce the spread of disease. Under this protocol, sub-studies and clinical trials can be conducted for interventions, including vaccine trials. The work may include new tools such as surface environmental or personal swabs to test for presence or absence of disease. Data collection efforts on behalf of rapidly evolving multiple study designs and participant opt-in data sharing, will enable the compilation of critical epidemiological and other data across the United States to accelerate the understanding for effective mitigation and treatment of COVID-19. ACCESS (American COVID-19 Collaborative Enabling Seamless Science), a novel COVID-19 digital research infrastructure, provides a mobile app tool for participants to report specific data and facilitate remote access to accelerate critical research and clinical treatment development. ACCESS leverages leading digital health technologies to facilitate at-home research, clinical trials, and population-based long-term outcome studies and data de-identification measures (data coding/tokenization). The infrastructure combines opt-in wearable sensors, patient reported data and outcomes, opt-in data aggregation and additional opportunities for users to participate in clinical trials and share their de-identified data based upon reported information. Prior to COVID-19, the FDA expressed an interest in expediting drug development through developing trial designs that test multiple drugs and/or multiple subpopulations in parallel under a single protocol, without a need to develop new protocols for every trial. This has become even more important during the COVID-19 pandemic. This type of work will also be enabled under the ACCESS system.
Study Type
OBSERVATIONAL
Enrollment
260
Medable Inc.
Palo Alto, California, United States
Development of population-based models of disease risk
To use multifaceted participant data consisting of participant reported outcomes, environmental surface and presence or absence of COVID-19 based on testing results, prescription medications (including off-label use), claims, lab, and medical record data to develop population-based models of disease risk, short and long-term outcomes, and efficacy of interventions and prevention measures.
Time frame: Up to 10 years
Relation between disease burden and geolocation
To leverage geolocation and lab results to provide population-level real-time data regarding disease burden at the community, state and national levels.
Time frame: Up to 10 years
Effect of medications on symptoms of COVID19
To specifically identify medications and regimens that address disease symptoms
Time frame: Up to 10 years
Effect of medications on disease severity of COVID19
To specifically identify medications and regimens that treat and reduce disease severity.
Time frame: Up to 10 years
Rate of COVID19 infection and disease outcomes
To identify regional variations in disease incidence and outcomes.
Time frame: Up to 10 years
Effect of COVID19 on health outcomes
To understand long-term outcomes such as risk of pulmonary and cardiovascular disease complications.
Time frame: Up to 10 years
Long-term follow up and recontact
To conduct long-term follow up of individuals who tested positive for COVID-19 compared to demographically matched individuals that did not.
Time frame: Up to 10 years
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