New movement biomarker tech can speed up drug development and free up hospital beds

As an innovation analyst for the NHS, Sigourney Waibel has witnessed first-hand the impact of rising chronic diseases and an ageing population on healthcare systems, realising it cannot be sustained for much longer. “There is no way we are going to be able to afford current levels of care with how population demographics are moving,” she says.

One of the most exciting areas she saw emerge focused on using AI and sensors to relieve pressure on clinicians. “With wards being completely overrun and clinicians having to make huge amounts of decisions during extremely long shifts, there’s not enough patient monitoring,” Waibel says. “If you can condense some information or support some aspects of the care clinicians are delivering, they can perform a better job.”

Now in the final months of a PhD within the Brain and Behaviour Lab at Imperial College London, Waibel and her team are redefining how we measure movement by developing a new generation of markers for higher precision prediction of complications and drug efficacy.

“Patient movement is a well-known marker for multiple diseases, ranging from dementia, Parkinson’s Disease, stroke, and also complications such as sepsis and organ failure,” Waibel says. “However, currently in hospitals and in clinical trials we assess patient movement intermittently by eye. This results in delayed detection of complications and delayed discharge of patients because they often don’t have a support system in place at home to monitor their behaviour. We also know that more than 57% of clinical trials for new drugs fail due to inadequate markers to determine drug efficacy.”

Waibel’s startup Ethomix, launched as part of Conception X Cohort V, has developed AI-powered software that could be integrated with any wearable device to capture relevant digital biomarkers in patients. This sensor data is translated into unique fingerprints of the patient’s movement and function, and sent back to clinical trial leads and hospital staff via a dashboard.

This approach can reduce the length of clinical trials by 43% and lower the cost by up to 44%. It can also reduce the cost of hospital stays by enabling remote monitoring of patients, freeing up staff capacity and hospital beds.

Ethomix has already tested its product with end users through pilots with acute stroke patients and children affected by rare genetic conditions at Charing Cross Hospital and the Great Ormond Street Hospital, where it was able to show improved predictions of which patients were going to deteriorate, increased sensitivity to pick up disease change compared to existing solutions, and high compliance of patients and clinical staff with the technology.

As a project set up and funded to solve a real-world problem experienced by clinicians, Waibel’s PhD trajectory had a clear focus from the start, with the goal of eventually producing a technology capable of improving healthcare practice. She joined Conception X in her final year, as the only venture programme tailored to PhD students working on deeptech research, to speed up the process.

“There are a lot of unique problems we face coming out of research organisations, such as having tech transfer offices involved and navigating the complexities of communicating deeptech solutions to investors,” Waibel says. “You can have a wonderful idea, great science and a great team, but then you may not be able to communicate the benefits and differentials you should be highlighting, especially if you’ve been working on something for five years and you’re very close to it. My business coach has been incredible in helping me to refine and communicate my idea, and understand the point of view of funders and customers.”

“Having access to a support network of like-minded people has also been great, as you’re going through the same hurdles,” she adds.

To date, the research behind Ethomix has been funded with £3 million in grants from the National Institute for Health Research, UK Research and Innovation, and the Duchenne Research Fund. The startup is now spinning out of Imperial College London, plans to launch a funding round in 2023 and has several clients lined up.

First, it plans to help pharmaceutical companies to bring down the prohibitive cost of clinical trials and speed up the discovery of life-saving drugs by detecting disease change early, reducing attrition rates through remote monitoring and ultimately shortening the duration of trials.

“For instance, Duchenne muscular dystrophy patients are children, they have to go to school,” Waibel says. “If you’re able to automatically and remotely record changes using sensors and conduct tests while they’re going about their everyday life, trials are more likely to be successful. This also has the potential to move trials outside of a controlled, artificial environment, assessing motor function and symptom improvements out in the real world.”

The team also plans to incubate its remote monitoring technology within the NHS to support its goal of building more than 20,000 virtual ward beds by the end of 2023, and eventually expand to the German and US markets.