While there is much excitement about how technology can be used to change the management of clinical trials, some sponsors have yet to take the leap into the tech sphere. On the other hand, many trial planners and managers are using social media to recruit patients and others are looking at using technology to run virtual trials.

And when it comes to more consumer-led technology such as wearables and voice assistants, the healthcare and clinical research market alike are taking notice.

The State of the Markets

Consider that the market for smart wearables in healthcare is predicted to grow at 13.6 percent annually over the next 15 years.

Or that the wearables of today will become — in about five years — implantables or ingestibles, according to a report by telecommunications giant Ericsson. Sixty percent of those surveyed believe these sensors will be pills to swallow or chips under the skin and will be able to track vital health data.

Equally, voice assistants, led by Amazon Alexa and Google Assistant are also making inroads into clinical research. Lenovo is using Alexa to link patients and care teams, while HealthTap’s “Dr. A.I.” allows patients to ask about their conditions and ailments, Jim Walker at Cadient writes. Boston Children’s Hospital is embracing voice technology so parents can ask Alexa about their children’s medical concerns.

This post will examine both of these technologies and assess the roles they will play in clinical research. As we’ve noted before, trial sponsors and managers that embrace technology will set themselves apart from competitors.

Let’s start with voice technology.

Major Uses of Voice Assistants in Clinical Trials

There are many uses for voice technology in clinical trials. Ken Fabianovicz at Applied Clinical Trials lists the four most important.

• Reminds patients of appointments and helps them confirm or reschedule should it be necessary.
• Records patient diaries. The voice assistant will ask patients relevant questions and record their responses, making it easier for patients to complete and submit, and for trial managers to process and store them.
• Fosters collaboration between site investigators and sponsors. This works when site staff ask questions of the sponsors via the voice assistant, which then either finds the answers in the site’s database or requests that the sponsor respond directly.
• Increases physicians’ awareness of open clinical trials. When the voice assistant responds to questions about condition or diagnosis codes, it accesses clinical trial databases in order to obtain the necessary information.

Voice Assistants Could Broaden Patient Populations

One of the areas in which voice assistants could improve clinical trial management is recruitment and reducing attrition, Karin Beckstrom, senior product manager at eResearch Technology’s Innovation Lab, explains.

Working in partnership with Orbita, Beckstrom says their voice assistance data capture solution will answer patients’ questions and remind them when to arrive for a trial visit or when to take their treatment. It will also allow patients to submit data by answering surveys and reporting measurements. This will result in more efficient and regular data collection which in turn should make the data more accurate.

The voice assistant does what a mobile app can’t. It assists patients with limited movement or dexterity problems from Parkinson’s or arthritis, for example. Eliminating the need for handheld devices broadens the patient population to include those with physical disabilities or hindrances.

Voice Assistants Provide Better Data

It’s thanks to improved speech recognition technology, that we’re seeing a “boom of voice-assistant devices,” Nathan Treloar, president of voice management solution provider Orbita, says.

Treloar’s company has created HIPAA-compliant voice and chatbot applications for healthcare. The aim is to be able to reach and engage patients in trials or who are seeking healthcare remotely.

When patients can access their daily assessments and record information about their conditions, they are more likely to engage with the trial throughout its duration, Treloar explains. The result is better data gathered far more cheaply than traditional or site-based trials.

Voice Assistants for Recruitment, Compliance, Support and Treatment

“Alexa, I want to take the survey for that clinical trial.” While this is not current practice in clinical trial recruitment, Alessandro Renzi at Praxis suggests that it could well be.

Patients could ask their voice assistant, which is able to connect to databases of open trials, what trials and treatment options are available for their condition. The result could be a pre-screener survey conducted by talking to Alexa, Renzi writes.  

Compliance with trial protocol includes patients’ adherence to taking medications, as well as completing surveys and data entries. But what makes voice assistants better than simple reminders on mobile phones is that they prompt behavior from patients and also accurately retrieve data “while also learning a patient’s needs and preferences,” Renzi explains.

Voice assistants can support patients by acting as a trial companion. They will be able to answer patients’ questions about the trial and treatment. This level of at-home support is unprecedented and presents a significant advantage to improve patient satisfaction and engagement.

A voice assistant could even provide treatment for conditions such as depression. By talking to the voice assistant, patients could seek companionship and guidance. As this technology matures and AI is more able to recognize human emotions, the level of care would be significant.

Five Steps to Successful Implementation of Wearables

Another boon for the collection of health data is wearables, but with so much data to collect, researchers need to ensure these devices are used in the best possible manner, Nelia Padilla and Michael Phinney at QuintilesIMS write.

Their five steps to success are:

• Win fast, fail fast. Use proof of concepts (POC) to test new technologies, taking note of user interface/user experience concerns. This eliminates spending time and money on choosing one telehealth vendor and then implementing a trial.
• Determine who owns the POC. Testing technology in a clinical trial can affect how the protocol is determined, and can lead to inflated costs and regulatory issues. It’s best to select an “independent team to drive innovation in R&D, with the ability to test technologies quickly and cascade the learning through the broader organization,” Padilla and Phinney advise.
• Outline a foundational data strategy. Wearables produce a lot of data and without a coherent strategy, it will be overwhelming. Consider how data will be displayed, who will see and triage it and what they do with it.
• Involve key stakeholders. Engage patients and see them as contributors not consumers. This will help to determine how they will use wearables, which in turn will affect how data is collected.
• Incorporate KPIs and learning goals. Know your endpoints and how they will be analyzed and used.

Study Watches

The Apple Watch has taken on a healthcare focus, health and technology reporter Christina Farr writes. The next generation will feature an electrocardiogram (ECG or EKG) sensor to monitor heart activity and identify potential health issues.

While the Apple Watch always monitored heart rate (through an optical sensor), the measurement was in beats per minute. An EKG measures the electrical activity for a more thorough analysis.

The watch has been cleared — not approved — by the FDA, which means regulators have defined it as similar to another legally marketed device. This is different from regulatory approval.

Verily Life Sciences, a subsidiary of Google’s parent company Alphabet, has launched a clinical trial-specific watch, Juliet Van Wagenen at HealthTech writes. The Study Watch collects patients’ health data for clinical and observational studies. It uses physiological sensors to measure cardiovascular disorders and movement issues.

The watch has already been used in a study by Duke University and Stanford Medicine, which examined the transitions between health and disease, and in another called the Personalized Parkinson’s Project, where patterns of progression in that disease were identified.

Quality of Data From Wearables Needs to be Validated

While the true value of wearables has not yet been determined, researchers at Clinical Pharmacology & Therapeutics argue that the robustness and frequency of data gathered is reason enough to include in clinical study protocols.

However, the collected data needs to be validated through rigorous examination. When it comes to study endpoints, for example, data from wearables should be reliable and reflect trial objectives and demonstrate the “interpretability of endpoint measures derived from these data.”

Still, much optimism remains about data quality from wearables. Greg Reh, vice chairman and life sciences leader at Deloitte, says data from wearables will help biopharmaceutical companies not only get better data, but get it faster. This will lead to more efficient cycle times for products and increased patient satisfaction.

Adoption of these technologies — wearables, AI, VR, blockchain, social media — remains slow in clinical trials. “Surprisingly, many clinical trials still rely on paper,” Reh writes. But the companies that embrace technology will see better drug adherence by patients and patient-centered endpoints through wearable-sensor-captured data.

Better, faster and more efficient gathering and processing of data remains the key driving force behind adoption of technology. Of course, enhancing the patient experience and extending the reach of trials to previously underrepresented populations is also a fundamental goal of technology in clinical trials.

By employing the right technology, trial sponsors and managers will be well on their way to achieving all of these goals.

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