Pain often leads to secondary problems such as disturbed sleep, anxiety, depression, and decreased cognitive and physical functioning. Chronic low-back pain alone is the leading cause of years lived with disabilities and loss of productive work (WHO burden of disease study). There is a high need for improving the management of patients suffering both acute and chronic pain, as pharmacotherapy of these conditions is often inadequate. In part, this is due to poor translation of results from preclinical models into clinical trials, and in part to a lack of sophistication in outcome reporting and of stratification in clinical trials.
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Therefore, it is very important to understand patient reported outcome measures to improve management of acute and chronic pain. This aspect will be addressed in the subproject PROMPT. Individual pain experiences can be described only by the affected person, but the quality of spontaneous reporting is very variable. This can be improved by using standardised patient reported outcome measures (PROMs) which are indicative of treatment success and predict chronicity or recovery. These will help health care professionals to follow the success of treatments of individual patients and provide opportunities for benchmarking quality of care across different hospitals or institutions. Pain management incurs net societal costs far higher than treatments of heart disease, diabetes or cancer. Identifying such predictive PROMs and implementing their standard use in randomized controlled trials (RCTs) and care of pain patients in clinical practice are the main objectives of subproject PROMPT.
Within the BioPain subproject biomarkers for pain are pharmacologically validated in healthy subjects and in animals. Currently available pharmacological therapies provide inadequate relief for many patients with chronic pain. It is known that novel drugs which are efficacious analgesics in preclinical models often have little or no clinical efficacy, but it is often not known whether the drug engaged the human target sufficiently to have a meaningful pharmacodynamic effect. Hence, early deselection of unpromising candidates would greatly reduce attrition rates in clinical development. This was encouraged by a new EMA/CHMP Guideline, but a novel research paradigm is needed which uses improved objective measures of nociceptive signal processing, functional biomarkers of pain which translate between animals and humans, and pharmacokinetic-pharmacodynamic (PK-PD) modelling. Subproject BioPain will develop, test and validate the tools necessary for this paradigm shift in analgesic and anti-hyperalgesic drug development.
Chronic pelvic pain is the focus of the subproject TRiPP and aims at improving the translation of laboratory and clinically findings into treatment. Although chronic pelvic pain is as common as asthma, migraine and back pain, and has very negative impacts on life quality, it remains a neglected field of research. The most common chronic pelvic pain is endometriosis associated pain (EAP); current treatments are limited to repeated surgeries or hormone suppression therapies which are often ineffective. Another recognised type of chronic pelvic pain, bladder pain syndrome (BPS), has a far lower prevalence (ca. 0.06%), but is also associated with strongly reduced life quality and significant psychological distress.
Current treatments target the bladder, but are as unsuccessful as those for EAP. As there are currently no non-invasive functional or biochemical biomarkers, unambiguous diagnosis of both conditions requires surgery. Co-morbidities such as autoimmune, endocrine and other pain conditions are common amongst EAP and BPS sufferers, and may confuse clinical evaluations and studies of the underlying causes of either condition.
Development of novel effective therapies has been hindered by the lack of preclinical models which reflect the full range of clinical symptoms. Subproject TRiPP will advance the field by adopting new approaches to stratify patients by underlying mechanistic pathways, which leverage cross-disciplinary knowledge of pain mechanisms with state-of-the-art biomarker discovery, and then to develop and optimise preclinical disease models.