Systematic review and meta-analysis of studies in which burrowing behaviour was assessed in rodent models of disease-associated persistent pain

Improving neuropathic pain treatment - by rigorous stratification from bench to bedside

Chronic pain is a constantly recurring and persistent illness, presenting a formidable healthcare challenge for patients and physicians alike. Current first-line analgesics offer only low-modest efficacy when averaged across populations, further contributing to this debilitating disease burden. Moreover, many recent trials for novel analgesics have not met primary efficacy endpoints, which is particularly striking considering the pharmacological advances have provided a range of highly relevant new drug targets. Heterogeneity within chronic pain cohorts is increasingly understood to play a critical role in these failures of treatment and drug discovery, with some patients deriving substantial benefits from a given intervention while it has little-to-no effect on others. As such, current treatment failures may not result from a true lack of efficacy, but rather a failure to target individuals whose pain is driven by mechanisms which it therapeutically modulates. This necessitates a move towards phenotypical stratification of patients to delineate responders and non-responders in a mechanistically driven manner. In this article, we outline a bench-to-bedside roadmap for this transition to mechanistically informed personalised pain medicine. We emphasise how the successful identification of novel analgesics is dependent on rigorous experimental design as well as the validity of models and translatability of outcome measures between the animal model and patients. Subsequently, we discuss general and specific aspects of human trial design to address heterogeneity in patient populations to increase the chance of identifying effective analgesics. Finally, we show how stratification approaches can be brought into clinical routine to the benefit of patients.

The role of neutrophils in pain: systematic review and meta-analysis of animal studies

ABSTRACT

The peripheral inflammatory response is an attractive therapeutic target for pain treatment. Neutrophils are the first circulating inflammatory cells recruited to sites of injury, but their contribution to pain outcomes is unclear. We performed a systematic review and meta-analysis of original preclinical studies, which evaluated the effect of preemptive neutrophil depletion on pain outcomes (PROSPERO registration number: CRD42022364004). Literature search (PubMed, January 19, 2023) identified 49 articles, which were meta-analyzed using a random-effects model. The risk of bias was evaluated using SYRCLE's tool. The pooled effect considering all studies showed that neutrophil depletion induced a consistent pain reduction. Inflammatory, joint, neuropathic, and visceral pain showed significant pain alleviation by neutrophil depletion with medium-large effect sizes. However, muscle and postoperative pain were not significantly alleviated by neutrophil depletion. Further analysis showed a differential contribution of neutrophils to pain outcomes. Neutrophils had a higher impact on mechanical hyperalgesia, followed by nociceptive behaviors and mechanical allodynia, with a smaller contribution to thermal hyperalgesia. Interspecies (mice or rats) differences were not appreciated. Analyses regarding intervention unveiled a lower pain reduction for some commonly used methods for neutrophil depletion, such as injection of antineutrophil serum or an anti-Gr-1 antibody, than for other agents such as administration of an anti-Ly6G antibody, fucoidan, vinblastine, CXCR1/2 inhibitors, and etanercept. In conclusion, the contribution of neutrophils to pain depends on pain etiology (experimental model), pain outcome, and the neutrophil depletion strategy. Further research is needed to improve our understanding on the mechanisms of these differences.

Finding new analgesics: Computational pharmacology faces drug discovery challenges

Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.

Practical approaches to improving translatability and reproducibility in preclinical pain research

Pain research continues to face the challenge of poor translatability of pre-clinical studies. In this short primer, we are summarizing the possible causes, with an emphasis on practical and constructive solutions. In particular, we stress the importance of increased heterogeneity in animal studies; formal or informal pre-registration to combat publication bias; and increased statistical training in order to help pre-clinical scientists appreciate the usefulness of available experimental design and reporting guidelines.

A systematic review and meta-analysis of thigmotactic behaviour in the open field test in rodent models associated with persistent pain

Thigmotaxis is an innate predator avoidance behaviour of rodents. To gain insight into how injury and disease models, and analgesic drug treatments affect thigmotaxis, we performed a systematic review and meta-analysis of studies that assessed thigmotaxis in the open field test. Systematic searches were conducted of 3 databases in October 2020, March and August 2022. Study design characteristics and experimental data were extracted and analysed using a random-effects meta-analysis. We also assessed the correlation between thigmotaxis and stimulus-evoked limb withdrawal. This review included the meta-analysis of 165 studies We report thigmotaxis was increased in injury and disease models associated with persistent pain and this increase was attenuated by analgesic drug treatments in both rat and mouse experiments. Its usefulness, however, may be limited in certain injury and disease models because our analysis suggested that thigmotaxis may be associated with the locomotor function. We also conducted subgroup analyses and meta-regression, but our findings on sources of heterogeneity are inconclusive because analyses were limited by insufficient available data. It was difficult to assess internal validity because reporting of methodological quality measures was poor, therefore, the studies have an unclear risk of bias. The correlation between time in the centre (type of a thigmotactic metric) and types of stimulus-evoked limb withdrawal was inconsistent. Therefore, stimulus-evoked and ethologically relevant behavioural paradigms should be viewed as two separate entities as they are conceptually and methodologically different from each other.