Stress is an underlying cause of behavioural and disease states and yet it is poorly characterized, leading to badly controlled clinical trials with average drop-out rates at 30%[1]. For proof of concept, Cambridge Consultants designed a system to measure and monitor a participant’s stress levels during trials. Developed in consultation with clinical psychiatrists and neuroscientists, Verum harnesses the power of biometric data, primarily voice and electromyography (EMG), and machine learning to better understand outcomes and increase the likelihood of clinical success. This machine learning-driven system can provide deeper insight on participants during trials through real-time triggers and alerts, enabling clinicians, nurses and trial co-ordinators to mitigate the effect of stress on compliance, investigate stress as a confounding factor and inform better adaptive trial design through continuous data streams. With the average cost of a Phase 2 clinical trial ranging from $7 million to $19.6 million[2] and 80% of all clinical trials failing to reach completion[3] it’s clear that increased efficiency has the potential to deliver very significant savings.

Verum comprises sensors integrated into a wearable, a data collection app and a widget for healthcare dashboards that augments existing data with patient-specific predictions and alerts, for unprecedented clinical insight. Verum’s ability to provide rich, contextualized biometric information at both population and patient level has the potential to revolutionize precision medicine, post-market surveillance and drug development.

Verum works by enabling clinicians, nurses and trial co-ordinators to access biometric and behavioural data from continuously monitored patients, gaining valuable context around a specific condition. This is achieved by applying a machine learning algorithm to measure patient data, producing a single numerical estimator of a patient’s stress levels at any stage of the trial.

Commenting on Verum, Jaquie Finn, Head of Digital Health at Cambridge Consultants, said: “The rising cost of clinical trials, combined with the commercial risks of failure, mean it’s vital we’re able to harness the power of AI and continuous patient monitoring to mitigate the impact of stress on clinical trial outcomes. Verum informs better adaptive trial design through bigger, real-time contextualized data sets and will mark a step-change in the efficiency of clinical trials.”

Potential future applications of Verum include the diagnosis of neurological conditions, the post market surveillance of drugs, the development of closed loop therapeutics, rehabilitation and remote patient monitoring. Within the consumer space, Verum can enable consumer brands to gain measured, quantitative insights into the use of products during trials. This could accelerate the product development process and provide new insights to spark innovation.

Notes to editors