Medidata launches cloud platform to gather clinical trial data from sensors
Medidata has launched Sensor Cloud, a platform to manage a range of sensor and digital health technology data during clinical trials.
The New York-based company, which is a wholly-owned subsidiary of French software firm Dassault Systemes, said the Sensor Cloud integrates Medidata’s existing clinical cloud technology while supporting data collection from the company’s own sources and third-party medical grade sensors.
In October last year, Medidata bought the digital biomarker firm MC10, adding more clinical analytics and biosensor technology to its cloud offering.
The technology could allow for remote monitoring in clinical trials of data including vital signs, movement and sleep patterns.
Using Sensor Cloud, researchers can access sensor data through a single Application Programming Interface (API), a software intermediary that allows two applications to talk to each other) and integrate new sensor technologies in weeks rather than months.
According to the company benefits include greater operational efficacy, making it easier for patients to share data and stay enrolled on trials.
Data uptake can be standardised through a common model, reducing the burden on patients and research sites by cutting down on-site visits.
It can also cut time and travel expenses through a more flexible engagement model.
Anthony Costello, president of Patient Cloud at Medidata, said: “As sensor usage in clinical trials is projected to surge up to 70% by 20251, it is imperative that we create the platform needed to rapidly standardize and integrate sensor data in order to harness the full power of these technologies for the benefit of patients.”
Costello added that while COVID-19 has forced many pharma companies to use remote technology during trials, the industry will continue to use it once the pandemic has receded.
“These advancements will continue to grow in popularity, outlasting the pandemic and, as trials continue to improve and become more patient-centric, communication and engagement become increasingly important. Patient involvement and the quality of the data generated by sensors will be integral to the overall evolution of this innovative research model.”
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