Intel Corporation’s Pharma Analytics Platform is an artificial intelligence (AI) solution, which enables remote patient monitoring and continuous clinical data capture via sensors and wearable devices. The platform also applies machine learning to measure symptoms and quantify the effects of therapies, according to the company.
The contract research organizing (CRO) Icon has been working in the wearable space for several years, having conducted multiple small proof-of-concept and proof-of-value projects, explained Tom O’Leary, chief information officer, Icon.
However, with new regulations and larger studies – with an increasing amount of sensors – O’Leary told us the company needed a robust solution.
“With the experience that we gained working with Intel during another project for a large pharma client, we felt that Intel was the right partner to work with,” he said.
Through the partnership, Icon will be able to aggregate and analyze data from mHealth and wearable technologies using advanced analytics and machine-learning.
O’Leary added that the partnership also provides the opportunity to develop new digital biomarkers.
“The platform can ingest unlimited data volumes form any type of device, and provide near-real analysis and Insight to sponsors,” he said. For perspective, O’Leary explained that a typical phase II trial running for six months with 100 patients could generate more than 200bn data points.
“The platform replaces traditional paper-based patient diaries as the devices allow real-world data and evidence to be captured in real time, allowing for vastly improved quality and consistency of data,” he added.
For patients
The platform will reduce patient burden in a number of ways, O’Leary said. Notably, remote data capture allows patients to participate in clinical trials without traveling to study sites.
“It will also help improve patient compliance by providing automatic feedback mechanisms,” O’Leary explained.
“This collaboration will allow for enhanced patient engagement with advanced real-time analytics identifying those patients who are having difficulties adhering to the protocol and a patient engagement strategy that supports them when necessary.”