Personalising neurostimulation in chronic pain management: tapping into the patient experience when we can’t measure pain

Nerve stimulation therapies for chronic pain can be very successful. But patients and clinicians face day-to-day challenges in the delivery of therapy that call for greater personalisation. Adaptive stimulation paradigms based on neural sensing data could help to achieve this – and give us additional insights.

Chronic pain can be difficult to treat, often evading the efforts of patients and clinicians to manage and understand the condition. Therapy is tailored to patients using verbal, qualitative feedback. Sensing data could add value to this process by allowing for better personalisation of therapy and bringing objective insight into the neural basis of pain through around-the-clock monitoring.

Around one in five adults are affected by chronic pain, with a smaller but meaningful number whose experience is particularly debilitating [1]. This is particularly true for neuropathic pain, where the pain is not necessarily caused by damage to tissue, but rather from damage to nerves themselves.  

One way to treat chronic pain is with opioid-based medication, but systemic administration can lead to undesirable side effects. Opioid prescription has also been linked to widespread problems of dependency and is increasingly seen as a less attractive solution by professionals [2].

Another form of pain relief is to apply electrical pulses to the nerves between the source of the pain and the brain, disrupting the pain signals to alleviate symptoms. Spinal cord stimulation (SCS) can help patients who would have historically been prescribed opioid drugs, and unlike opioids, SCS does not lead to problems with dependency or addiction.

SCS therapy is delivered via small electrodes, together with their wires, known as leads, that are implanted in the epidural space of the spinal column. Small electrical currents interfere with the transmission of nociceptive pain signals, preventing the pain experienced in the legs or lower back from reaching the brain.

Listening to the experience of patients that rely on SCS makes clear that many find effective relief from pain, but over time some experience a loss of therapeutic efficacy due to movement of the stimulation leads within the epidural space [3]. 

As patients change body positions, varying levels of current may be shunted by surrounding cerebrospinal fluid, such that not all stimulation successfully interacts with the relevant neural structures. If the electrode moves too far away from the nerve then the pain may start to return, and if the electrode moves too close, excessive stimulation can cause discomfort through a “pins and needles” sensation. Sometimes these changes are temporary as patients move around and go about their daily life, but the leads can also gradually migrate further away from the site of implantation in the longer term, leading to a loss of pain relief. 

It is usually possible to compensate for these small movements. Each lead comprises of multiple electrodes which can be individually turned on or off, and the level of stimulation can also be adjusted. From the perspective of these patients and their clinicians, the challenge is to monitor the changing lead positions and to adjust the stimulation settings to compensate for these movements. Often this involves hands-on time with the clinician reprogramming the device, which can be a lengthy process. It also relies on patients verbally describing their perceived pain, which can be a noisy process influenced by a multitude of factors. 

How might we go about compensating for these changing conditions to ensure patients receive maximum pain relief 100% of the time?

Today’s SCS implants allow for multiple treatment modes to be pre-programmed for stimulation, for example a different stimulation pattern may be needed during exercise compared to time spent lying down. The patient can switch between these manually via an app, or in some cases the implant can detect the body position automatically through a built-in accelerometer, so that there is less need for manual intervention from patients as they go about their daily lives. 

Addressing the issue of long-term lead migration is more complex, as the optimum parameters for a given posture may also change over time. One way of achieving truly adaptive therapies in the future could be closed-loop stimulation, where devices sense neural signals as well as deliver stimulation. 

Measuring pain directly is notoriously difficult, but adaptive stimulation based on nerve sensing data would bring us a large step closer to continuously controlling for the true target of therapy. This raises the exciting prospect that it will be possible to adapt stimulation parameters moment-to-moment to keep the stimulation within the therapeutic window, as the patient goes about their daily life – obviating the regular adjustments sometimes necessary with current systems and moving SCS closer to a fit-and-forget solution.

Extracting objective data from SCS devices could have wider value beyond enabling adaptive stimulation. Neural data could act as a valuable biomarker for the quantitative tracking of treatment efficacy, complimenting subjective data from patient diaries, which could accelerate clinical trials of novel therapeutics that impact the nervous system. And the value may not be limited to neuromodulation therapies; perhaps neural data could give insight into the action of pharmaceuticals as well.

The Covid-19 pandemic has highlighted the value of remote data tracking and connectivity in many areas of life as restrictions limit face-to-face interactions. Providing clinicians with the ability to remotely monitor changes in therapy response would offer insights that a video-call check-up alone could not provide and could even enable the convenience of informed remote programming of SCS devices. 

Finally, fundamental research will undoubtedly also benefit from this data, providing new insights into the underlying physiology that drives chronic pain. Readily available data could allow researchers to quickly gain confidence in the efficacy of newly proposed therapies, turning data into actionable information.

Pain is a multifaceted and highly individual experience, and patients benefit from truly personalised therapies. Adaptive SCS promises a future where pain is managed automatically by a small medical implant, meshing into the daily life of the patient to create a seamless patient experience. Data from implants also offer deep insights into the individual neural basis of pain, and we are on the cusp of bringing together the pieces of this puzzle to create fully closed-loop therapeutics for chronic pain.

TTP designs and develops next-generation neuromodulation devices. We run development programmes from technical feasibility through to setting up supply chains and transfer to manufacturing. Please reach out if you would like to discuss anything in this blog, or neurotechnology more generally.

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