Researchers are working with digital therapeutics specialist Biofourmis, using machine learning technology and the Apple Watch to analyze dozens of physiology biomarkers.

Yale, Mayo Clinic to use biometric data from wearables to improve drug development for heart failure

By Nathan Eddy
10:54 AM

The Yale University-Mayo Clinic Center of Excellence in Regulatory Science and Innovation has teamed up with digital therapeutics specialist Biofourmis to study the effectiveness of patient-centric endpoints in determining future drug development of heart failure patients.

WHY IT MATTERS
The 60-day multicenter study is set to begin in August and will capture and analyze patient-centric endpoints through Biofourmis' mobile health platform BiovitalsHF.

The platform is able to capture raw biosensor data, using machine learning technology to analyze dozens of physiology biomarkers, from which it can then detect the heart's inability to maintain adequate circulation – weeks before the decompensation occurs.

The 60-day trial will employ two biosensors, a medical-grade device called Everion and the Apple Watch Series 4 smartwatch with ECG, to continuously collect physiology biomarkers and physical activity.

"If we can infer additional endpoints or biomarkers from the clinical-grade sensors that are similar to the consumer-grade sensors when leveraging our analytics platform, this study will be foundational in using the Apple Watch or similar consumer-grade wearables in future trials," Kuldeep Singh Rajput, CEO of Biofourmis, told HealthcareITNews.

The study also incorporates a patient-facing app to capture electronic patient-reported outcomes, or ePROs, such as adherence to medication.

Researchers feel the results could provide insights to the U.S. Food and Drug Administration on how patient-centric data could be used as alternative trial endpoints to traditional hard outcomes like mortality and hospitalization rates.

THE LARGER TREND
A recent guidance report from the FDA on drug development for treatment of heart failure has already indicated patient-centric endpoint data could be a basis for approving drugs to treat heart failure, which afflicts approximately 6.5 million people in the United States.

"Since precision medicine is all about getting the right dosage of the right therapy to the right patient at the right time, being able to capture continuous biometric data 24/7 and patient-generated data will play a key role in the future of how drug trials are conducted," Rajput explained. "This approach will also help ensure that therapies are very individualized to specific patients."

ON THE RECORD
"When it comes to clinical trials, any steps you can take to shorten the process can in turn shorten drug approval times, which ultimately decreases R&D costs and drug costs," Rajput said. "In standard clinical trials, remote monitoring and digital therapeutics can shorten clinical trial times by decreasing the amount of time patients need to spend traveling to a clinic so clinical investigators can gather data."

He also noted the recruitment of patients for a clinical trial is one of the most time-consuming aspects of the drug approval process.

"By making the process easier for patients by being monitored from the comfort of their own homes, patient recruitment also goes much more quickly, which also can help shorten the duration of clinical trials during the drug approval process," he said.

Focus on: The Future of Pharma

In the month of July, we'll take a closer look at the many answers to this question, as well as exploring what the changing face of pharma means for other healthcare stakeholders.

Nathan Eddy is a healthcare and technology freelancer based in Berlin.
Email the writer: nathaneddy@gmail.com
Twitter: @dropdeaded209