There is a high rate of failure among pain drugs development clinical trials compared to other areas. It is well established that pain is a very difficult outcome to measure due to its multifaceted and subjective nature. The factors impacting this failure rate reflects the complexity of this therapeutic area and for new drugs it can be difficult to prove effectiveness superior to placebo . The FDA Guidance for Industry went so far as to state that “There are known instances of failed clinical trials of analgesic drugs later found to be effective”.

Within drug development trials the most commonly used primary outcome assessments are self-reported daily pain diaries, collected daily in real world settings. However there are a significant number of issues surrounding the collection of robust subjective data in non-clinical settings. These include the robust and compliant completion of PRO - although the adoption of ePRO has improved compliance significantly but to 94% is some cases. What is less easy to control are environment factors and patient behaviours.

A subjects sleep and physical activity have been shown to have a significant inter-relationship with their pain scores- both in terms of causation and effect. A considerable body of work has been carried investigating complex co-relationship (13,395 pain and sleep articles and 43,482 Pain and Physical Activity articles listed in PubMed). While the exact relationship is not clearly understood for all indications, what is clear is that changes in physical activity and sleep can impact pain response and similarly pain response can impact physical activity and sleep.

In a pain study reducing non-therapeutic impacts on pain is clearly desirable and ICON Innovation has conducted a number of POC’s to develop tools to help improve patients adherence to protocol stipulations regarding physical behaviours which are particularly relevant for osteoarthritis, neuropathic pain and other similar chronic pain indications.

To develop a smartwatch mobile app combination that can be used to alert patients, and physicians and drug development teams to physical behaviours that may exacerbate patients’ pain. Combining data from smartwatches with subjective pain scores and analysing this data in real-time facilitates patients to better manage their pain through physical behaviour modification.

Healthy volunteers were provided with a smartwatch which they wore for a 3 day period to capture baseline data. Actigraphy data collected via sensors of the smartwatch were transmitted via bluetooth to a mobile app on a smartphone (Figure 1). Subject diary data was collected via the mobile app. An algorithm was devised based on increases in physical activity (>1SD), deceases in sleep linked to increases or no changes in the patients pain.

Physical activity and sleep data generated by a smartwatch is combined with pain diary data (planned and spontaneous numerical rating scale measurements) and analysed in a decision tree based algorithm which takes into account increased physical activity levels (greater than 1SD), decreases in sleep and combined with increases or no improvement in a patients pain score (Diagram 2). Changes in a patient’s pain score and pre-defined messages sent to the patient to better inform them of physical behaviours that may impact the therapeutic efficacy of the drug.

This data is visualised in a study dashboard (see diagram 3) where the study team have global visibility on changes in physical activity levels, sleep patterns and pain scores.

Monitoring physical behaviour and providing feedback in real-time has the potential to facilitate patients quantifying and controlling physical activities and better manage their pain. This data can also provide primary care teams with contextual insights on extrinsic factors that may be responsible for breakthrough pain and impact drug efficacy. The data can also be used in a clinical trial to reduce extrinsic behavioural elements that may impact therapeutic response. Further research is needed to assess the value, burden and compliance of the smartwatch on patients but this approach could provide real world insights for both patients and care teams.