Review or Commentary, Resource

Large variability in the individual response to even the most-efficacious pain treatments is observed clinically, which has led to calls for a more personalized, tailored approach to treating patients with pain (i.e., "precision pain medicine"). Precision pain medicine, currently an aspirational goal, would consist of empirically-based algorithms that determine the optimal treatments, or treatment combinations, for specific patients (i.e., targeting the right treatment, in the right dose, to the right patient, at the right time). Answering this question of "what works for whom" will certainly improve the clinical care of patients with pain. It may also support the success of novel drug development in pain, making it easier to identify novel treatments that work for certain patients and more accurately identify the magnitude of the treatment effect for those subgroups. Significant preliminary work has been done in this area, and analgesic trials are beginning to utilize precision pain medicine approaches such as stratified allocation on the basis of pre-specified patient phenotypes using assessment methodologies such as quantitative sensory testing. Current major challenges within the field include: (1) identifying optimal measurement approaches to assessing patient characteristics that are most robustly and consistently predictive of inter-patient variation in specific analgesic treatment outcomes, (2) designing clinical trials that can identify treatment-by-phenotype interactions, and (3) selecting the most promising therapeutics to be tested in this way. This review surveys the current state of precision pain medicine, with a focus on drug treatments (which have been most-studied in a precision pain medicine context). It further presents a set of evidence-based recommendations for accelerating the application of precision pain methods in chronic pain research. PERSPECTIVE: : Given the considerable variability in treatment outcomes for chronic pain, progress in precision pain treatment is critical for the field. An array of phenotypes and mechanisms contribute to chronic pain; this review summarizes current knowledge regarding which treatments are most effective for patients with specific biopsychosocial characteristics.

Recurrent abdominal pain is a common reason for repeated visits to outpatient clinics and emergency departments, reflecting a substantial unmet need for timely and accurate diagnosis. A lack of awareness of some of the rarer causes of recurrent abdominal pain may impede diagnosis and delay effective management. This article identifies some of the key rare but diagnosable causes that are frequently missed by gastroenterologists, and provides expert recommendations to support recognition, diagnosis, and management with the ultimate aim of improving patient outcomes.

Neuropathic pain is amongst the most common non-communicable disorders and the poor effectiveness of current treatment is an unmet need. Although pain is a universal experience, there are significant inter-individual phenotypic differences. Developing models that can accurately recapitulate the clinical pain features is crucial to better understand underlying pathophysiological mechanisms and find innovative treatments. Current data from heterologous expression systems that investigate properties of specific molecules involved in pain signaling, and from animal models, show limited success with their translation into the development of novel treatments for pain. This is in part because they do not recapitulate the native environment in which a particular molecule functions, and due to species-specific differences in the properties of several key molecules that are involved in pain signaling. The limited availability of post-mortem tissue, in particular dorsal root ganglia (DRG), has hampered research using human cells in pre-clinical studies. Human induced-pluripotent stem cells (iPSCs) have emerged as an exciting alternative platform to study patient-specific diseases. Sensory neurons that are derived from iPSCs (iPSC-SNs) have provided new avenues towards elucidating peripheral pathophysiological mechanisms, the potential for development of personalized treatments, and as a cell-based system for high-throughput screening for discovering novel analgesics. Nevertheless, reprogramming and differentiation protocols to obtain nociceptors have mostly yielded immature homogenous cell populations that do not recapitulate the heterogeneity of native sensory neurons. To close the gap between native human tissue and iPSCs, alternative strategies have been developed. We will review here recent developments in differentiating iPSC-SNs and their use in pre-clinical translational studies. Direct conversion of stem cells into the cells of interest has provided a more cost- and time-saving method to improve reproducibility and diversity of sensory cell types. Furthermore, multi-cellular strategies that mimic in vivo microenvironments for cell maturation, by improving cell contact and communication (co-cultures), reproducing the organ complexity and architecture (three-dimensional organoid), and providing iPSCs with the full spatiotemporal context and nutrients needed for acquiring a mature phenotype (xenotransplantation), have led to functional sensory neuron-like systems. Finally, this review touches on novel prospective strategies, including fluorescent-tracking to select the differentiated neurons of relevance, and dynamic clamp, an electrophysiological method that allows direct manipulation of ionic conductances that are missing in iPSC-SNs.

Despite the high prevalence of a myofascial pain component in chronic pelvic pain (CPP) syndromes, awareness and management of this component are lacking among health care providers.

The majority of people who have nonspecific chronic spinal pain (nCSP) report comorbid insomnia. However, in current treatment strategies for nCSP, insomnia is usually not addressed. Considering the bidirectional interaction between pain and sleep and its underlying psychophysiological mechanisms, insomnia may increase the risk of developing adverse physical and psychological health outcomes and should thus no longer be left untreated. As suggested by previous pilot studies, adding cognitive behavioral therapy for insomnia (CBT-I) to the contemporary evidence-based biopsychosocial physical therapy approach may also improve pain outcomes in nCSP. This manuscript aims to provide practical guidelines on hybrid physical therapy, including the combination of following components: (1) pain neuroscience education (eg, to reconceptualize pain) and cognition-targeted exercise therapy (eg, graded exposure to functional daily life movements), and (2) CBT-I (sleep psychoeducation, behavioral and cognitive therapy, correction of sleep hygiene, and relaxation therapy) can be deployed for the management of patients who have chronic spinal pain.

The upcoming 11th revision of the International Classification of Diseases (ICD-11) will include a comprehensive classification of chronic pain for the first time, which is based on the biopsychosocial definition of chronic pain. This presents a great opportunity for pain research and clinical practice. The new classification consists of seven main diagnostic categories of chronic pain, which are further divided into increasingly specific levels of diagnoses. Each diagnosis is characterized by clearly defined operationalized criteria. Future users will need to familiarize themselves with the new system and its application. The aim of the present publication is to provide users of the ICD-11 chronic pain classification with answers to frequently asked questions regarding the ICD-11 as a whole, the ICD-11 chronic pain classification, and its application to common pain syndromes. The questions compiled here reached the International Association for the Study of Pain Task Force via different routes (e.g., at conferences, by letter, or during field testing). Furthermore, the authors collected questions posted to the ICD-11 browser and contacted early users of the classification to enquire about their most frequent difficulties when applying the new diagnoses. The authors of the present publication prepared answers to these frequently asked questions. This publication intends to act as a guide for the future users of the new ICD-11 chronic pain classification, hence facilitating its implementation.

Opioid-related death and overdose have now reached epidemic proportions. In response to this public health crisis, the National Institutes of Health (NIH) launched the Helping to End Addiction Long-term Initiative, or NIH HEAL Initiative, an aggressive, trans-agency effort to speed scientific solutions to stem the national opioid public health crisis. Herein, we describe two NIH HEAL Initiative programs to accelerate development of non-opioid, non-addictive pain treatments: The Preclinical Screening Platform for Pain (PSPP) and Early Phase Pain Investigation Clinical Network (EPPIC-Net). These resources are provided at no cost to investigators, whether in academia or industry and whether within the USA or internationally. Both programs consider small molecules, biologics, devices, and natural products for acute and chronic pain, including repurposed and combination drugs. Importantly, confidentiality and intellectual property are protected. The PSPP provides a rigorous platform to identify and profile non-opioid, non-addictive therapeutics for pain. Accepted assets are evaluated in in vitro functional assays to rule out opioid receptor activity and to assess abuse liability. In vivo pharmacokinetic studies measure plasma and brain exposure to guide the dose range and pretreatment times for the side effect profile, efficacy, and abuse liability. Studies are conducted in accordance with published rigor criteria. EPPIC-Net provides academic and industry investigators with expert infrastructure for phase II testing of pain therapeutics across populations and the lifespan. For assets accepted after a rigorous, objective scientific review process, EPPIC-Net provides clinical trial design, management, implementation, and analysis.