wearable technology

Piloting wearable sensor technologies for clinical trials

Vandenbruaene Nathalie — Mon, 30 May 2022 11:17:28 +0000

Piloting wearable sensor technologies for clinical trials

Isabela Niculae, Global Clinical Sciences and Operations Innovation

Vandenbruaene … Mon 30/05/2022 - 13:17

Measuring vital signs is a critical part of any clinical trial; it helps us to characterize diseases and the effect of our therapies. Wearable sensors have the potential to help us capture vital signs data more efficiently and with much more detail. Automating the remote collection of vital signs data in clinical studies promises to bring a wealth of benefits for patients, sites, study teams and project teams.

Before I explore these benefits, let’s take a look at how ��ֳ�’s Global Clinical Sciences and Operations (GCSO) Innovation has been working in this area as part of the Technology Transformation Implementation program.

Wearable sensor technologies: Walking in participants’ shoes
The development of wearable sensors has reached a stage where non-intrusive products can measure clinical dimensions continuously and in the real world with sufficient robustness. And GCSO Innovation has been piloting two wearable sensor solutions to explore how they can help us measure vital signs more effectively in our clinical trials.

The pilot engaged our colleagues across the organization in the innovation process, asking them to ‘walk a mile’ in patients’ shoes. An amazing eighty volunteered to take part, of which 24 were selected to wear each of the two devices for seven days.

Putting themselves in the place of a clinical trial participant, our colleagues reported on the comfort and usability of the devices.

New opportunities for medicines development
The COVID pandemic meant GCSO Innovation had to conduct the pilot virtually, which ultimately helped it learn about the potential for these devices in Decentralised Clinical Trials. With its final analysis complete and findings reported, GCSO Innovation concluded that “Devices capable of continuous data capture provide new opportunities for medicines development, and we were able to see a greater magnitude of granularity for physiological data”.

The report also revealed some important insights that ��ֳ� gleaned into operating clinical trials virtually and collecting continuous clinical trial data. Firstly, during the pilot, we learned that operating remotely presents new challenges to working with clinical trial participants. We are now considering how best to fully support participants in a virtual environment as we journey towards truly patient-centric clinical trials.

We also learned of some additional factors that we need to consider when we capture continuous data. These include device recharging times, loss of connectivity between the device and phone, how participants use or are challenged by these devices over time and their general comfort with these solutions.

Human beings are complex
But one of the most important things that we learned was that measuring physiological data continuously in a real-world setting presents a large degree of variability in measurements. That variability isn’t down to the underlying state of the participant but could instead be due to their extrinsic environment and activities of daily living.

In other words, human beings are complex creatures. The data that we continuously collect as participants go about their daily lives looks completely different from the data we capture in the controlled environment of hospitals during our clinical trials. We, therefore, need to understand what this complexity looks like and when measurement variations may naturally occur before we can maximize our use of these new tools.

Armed with this information, ��ֳ� study teams are now exploring how best to use wearable sensors in studies to benefit patients.

Rapidly advancing knowledge for the benefit of all
This pilot sandboxed GCSO Innovation’s investigation into our use of their innovative solutions. Sandboxing allows the team to gain timely, cost-effective feedback to rapidly advance their knowledge on how we can use wearable sensors effectively. Moreover, it also de-risks those innovations before we introduce them into our clinical trials.

Ultimately, I hope to see more pilots like this in the not too distant future. Trialing innovations in this way is a win-win for everybody. It benefits our patients and healthcare professionals by accelerating innovations. It benefits study teams and project teams by allowing them to capture continuous data in real-world settings. And it benefits ��ֳ� and our small and medium-sized enterprise (SME) partners by making us a better partner in the innovation ecosystems.

Moreover, ��ֳ� is looking to establish true partnerships at every step of the pharma value chain. Our new patient-centered framework, for instance, provides our colleagues in all business functions with a tangible roadmap on how to create a mutually beneficial, truly inclusive pharma. Find out more in the interview of our Chief Medical Officer Iris Loew Friedrich in a pharmaphorum article on "Engagement to partnership: The changing face of patient involvement".

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Differentiating symptoms of Parkinson’s and PSP: Is wearable technology the answer?

eCMSadmin — Fri, 24 Jul 2020 13:00:00 +0000

Differentiating symptoms of Parkinson’s and PSP: Is wearable technology the answer?

Tim Buchanan, Patient Value Neurology & Europe/International Solutions

eCMSadmin Fri 24/07/2020 - 15:00

One of the problems in trying to correctly diagnose and treat movement disorders such as Parkinson’s Disease (PD) and Progressive Supranuclear Palsy (PSP), as well as conduct clinical trials of new treatments, is that at present there is a lack of sensitive, objective and quantitative diagnostic measures of relevant functional ability.

Objective numerical measures of disease are needed for accurate diagnosis and staging of disease, monitoring of progression rate, stratification of patients for entry into clinical trials and detection of an early signal to guide critical go/no go decisions.

With the aim of addressing these challenges in 2016 ��ֳ� provided a grant to Oxford University for a highly innovative and pioneering project known as the Oxford QUantification In Parkinsonism (OxQUIP) study. The main objective of the study, led by Professor Chrystalina Antoniades, was to develop ways of accurately measuring neurological disorders such as PD and PSP, two progressive neurodegenerative brain disorders affecting movement and cognition.

This study was designed to precisely measure subtle abnormalities in the timing, speed and coordination of a range of movements in people with PD and PSP at various stages of progression over a three-year period, along with an age- and sex-matched healthy control group.

Within this study participants perform a range of tasks while wearing sensors that accurately quantify their performance. Measurements recorded included eye movements with infra-red cameras and body movements using accelerometers and cognitive function using a tablet. Participants also perform cognitive tasks on a tablet computer, testing for example their ability to deduce the rules governing the movement of shapes on the screen.

Early data from the OxQUIP study suggest wearable technology, combined with artificial intelligence and machine learning, could offer the potential to accurately distinguish symptoms of PD from PSP.

The research published in the journal Gait and Posture identified 17 features which allowed researchers to discriminate PSP with a high degree of sensitivity and specificity (86% and 90% respectively) using an array of six motion sensors.

The study also suggests that optimal separation between the two patient populations is achieved via application of motion sensors to three distinct body sites, however, a single lumbar motion sensor could deliver comparable classification, offsetting a modest loss of accuracy with increased convenience and simplicity.

“Although in the early stages the symptoms of PSP and PD can appear quite similar, from a modality perspective the two conditions have different underlying pathophysiology”, explained ��ֳ�’s Tim Buchanan, co-author of the paper and the clinical development lead on the anti-tau programme at ��ֳ�. “Being able to accurately differentiate the two diseases by harnessing wearable technology, combined with machine learning, could support movement disorder specialists in earlier diagnosis and tailored management approaches, avoiding misdiagnosis and supporting better and more targeted treatment strategies.

To maximise the benefit from any potentially disease-modifying treatment for PSP an early and accurate diagnosis will be required so that treatment may be initiated as early as possible in the course of the disease. To this end and based on the exciting initial findings from the OxQUIP study, ��ֳ� has extended its funding for an additional two years.

“We are delighted to continue our collaboration with ��ֳ� on the OxQUIP study which has the potential to be a game-changer when it comes to the early diagnosis of PSP” explained Professor Chrystalina Antoniades, lead study investigator for the programme.

The aim of the next phase of the collaboration is to increase the number of PSP patients as well as extend the acquisition of quantitative data to the real-world setting of the patient’s home. It is anticipated that this research will lead to further publications aimed to support the movement disorder community in improving the diagnosis and management of people living with this debilitating condition.

Learn more about PSP here.

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Progressive Supranuclear Palsy wearable technology PSP PD Parkinson’s disease Parkinson’s OxQUIP Oxford University machine learning

Comment:

Posted by Sandra Campbell, 18 August 2020

Wonderful developments supporting earlier diagnosis of PSP. Wishing the team continued success .

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wearable technology

Piloting wearable sensor technologies for clinical trials

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Differentiating symptoms of Parkinson’s and PSP: Is wearable technology the answer?

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