Human models of pain for the prediction of clinical analgesia

Epidural methadone and morphine pharmacokinetics and clinical effects in healthy volunteers: A randomized, crossover-design trial

AIMS

Epidural opioids can provide effective analgesia for acute postoperative pain. Due to its unique physicochemical properties and long systemic elimination half-life, epidural methadone may provide lasting analgesia with minimal adverse effects; however, human studies are lacking. The aim of the study was to test the hypothesis that epidural methadone would exhibit greater segmental analgesia (analgesia at the dermatome of injection vs. distant dermatomes) than epidural morphine.

METHODS

In a prospective, randomized, double-blinded, crossover study, thirteen healthy volunteers received a 4-mg epidural bolus of methadone or morphine at L3-L4 and underwent repeated assessment of dermatomal heat pain tolerance and pressure pain threshold at lumbar (L3) and trigeminal (V2) dermatomes, pupil diameter, respiratory parameters and venous opioid concentration for 24 h. The primary outcome was selective (lumbar vs. trigeminal) segmental analgesia for heat pain, as a marker of a spinal analgesic mechanism.

RESULTS

The degree of segmental analgesia to heat pain tolerance was not different between morphine and methadone (P = .09), although morphine (P = .0009) but not methadone (P = .81) produced significant analgesia to heat pain at the lumbar vs. trigeminal dermatome over 0-12 h. Morphine overall provided longer lasting analgesia to heat pain vs. methadone (24 vs. 2 h, respectively). Morphine elicited greater systemic effects, including miosis (P = .009) and opioid-related adverse effects (P = .002).

CONCLUSIONS

These results suggest that, with equal epidural doses, both methadone and morphine produced analgesia and methadone did not produce greater segmental effects than morphine. Epidural methadone provided a more favourable adverse effect profile.

Tonic pain alters functional connectivity of the descending pain modulatory network involving amygdala, periaqueductal gray, parabrachial nucleus and anterior cingulate cortex

INTRODUCTION

Resting state functional connectivity (FC) is widely used to assess functional brain alterations in patients with chronic pain. However, reports of FC accompanying tonic pain in pain-free persons are rare. A network we term the Descending Pain Modulatory Network (DPMN) is implicated in healthy and pathologic pain modulation. Here, we evaluate the effect of tonic pain on FC of specific nodes of this network: anterior cingulate cortex (ACC), amygdala (AMYG), periaqueductal gray (PAG), and parabrachial nuclei (PBN).

METHODS

In 50 pain-free participants (30F), we induced tonic pain using a capsaicin-heat pain model. functional MRI measured resting BOLD signal during pain-free rest with a 32°C thermode and then tonic pain where participants experienced a previously warm temperature combined with capsaicin. We evaluated FC from ACC, AMYG, PAG, and PBN with correlation of self-report pain intensity during both states. We hypothesized tonic pain would diminish FC dyads within the DPMN.

RESULTS

Of all hypothesized FC dyads, only PAG and subgenual ACC was weakly altered during pain (F=3.34; p=0.074; pain-free>pain d=0.25). After pain induction sACC-PAG FC became positively correlated with pain intensity (R=0.38; t=2.81; p=0.007). Right PBN-PAG FC during pain-free rest positively correlated with subsequently experienced pain (R=0.44; t=3.43; p=0.001). During pain, this connection's FC was diminished (paired t=-3.17; p=0.0026). In whole-brain analyses, during pain-free rest, FC between left AMYG and right superior parietal lobule and caudate nucleus were positively correlated with subsequent pain. During pain, FC between left AMYG and right inferior temporal gyrus negatively correlated with pain. Subsequent pain positively correlated with right AMYG FC with right claustrum; right primary visual cortex and right temporo-occipitoparietal junction Conclusion: We demonstrate sACC-PAG tonic pain FC positively correlates with experienced pain and resting right PBN-PAG FC correlates with subsequent pain and is diminished during tonic pain. Finally, we reveal PAG- and right AMYG-anchored networks which correlate with subsequently experienced pain intensity. Our findings suggest specific connectivity patterns within the DPMN at rest are associated with subsequently experienced pain and modulated by tonic pain. These nodes and their functional modulation may reveal new therapeutic targets for neuromodulation or biomarkers to guide interventions.

Machine-Learning Analysis of Serum Proteomics in Neuropathic Pain after Nerve Injury in Breast Cancer Surgery Points at Chemokine Signaling via SIRT2 Regulation

BACKGROUND

Persistent postsurgical neuropathic pain (PPSNP) can occur after intraoperative damage to somatosensory nerves, with a prevalence of 29-57% in breast cancer surgery. Proteomics is an active research field in neuropathic pain and the first results support its utility for establishing diagnoses or finding therapy strategies.

METHODS

57 women (30 non-PPSNP/27 PPSNP) who had experienced a surgeon-verified intercostobrachial nerve injury during breast cancer surgery, were examined for patterns in 74 serum proteomic markers that allowed discrimination between subgroups with or without PPSNP. Serum samples were obtained both before and after surgery.

RESULTS

Unsupervised data analyses, including principal component analysis and self-organizing maps of artificial neurons, revealed patterns that supported a data structure consistent with pain-related subgroup (non-PPSPN vs. PPSNP) separation. Subsequent supervised machine learning-based analyses revealed 19 proteins (CD244, SIRT2, CCL28, CXCL9, CCL20, CCL3, IL.10RA, MCP.1, TRAIL, CCL25, IL10, uPA, CCL4, DNER, STAMPB, CCL23, CST5, CCL11, FGF.23) that were informative for subgroup separation. In cross-validated training and testing of six different machine-learned algorithms, subgroup assignment was significantly better than chance, whereas this was not possible when training the algorithms with randomly permuted data or with the protein markers not selected. In particular, sirtuin 2 emerged as a key protein, presenting both before and after breast cancer treatments in the PPSNP compared with the non-PPSNP subgroup.

CONCLUSIONS

The identified proteins play important roles in immune processes such as cell migration, chemotaxis, and cytokine-signaling. They also have considerable overlap with currently known targets of approved or investigational drugs. Taken together, several lines of unsupervised and supervised analyses pointed to structures in serum proteomics data, obtained before and after breast cancer surgery, that relate to neuroinflammatory processes associated with the development of neuropathic pain after an intraoperative nerve lesion.

Determination of equi-analgesic doses of inhaled methoxyflurane versus intravenous fentanyl using the cold pressor test in volunteers: a randomised, double-blinded, placebo-controlled crossover study

Background

Inhaled methoxyflurane for acute pain relief has demonstrated an analgesic effect superior to placebo. Data comparing methoxyflurane to an opioid are needed. The aim of this study was to determine the equi-analgesic doses of inhaled methoxyflurane vs i.v. fentanyl. Both drugs have an onset within minutes and an analgesic effect of 20–30 min.

Methods

Twelve subjects were included in a randomised, double-blinded, placebo-controlled crossover study with four treatments: placebo (NaCl 0.9%), fentanyl 25 μg i.v., fentanyl 50 μg i.v., or inhaled methoxyflurane 3 ml. The subjects reported pain intensity using the verbal numeric rating scale (VNRS) from 0 to 10 during the cold pressor test (CPT). The CPT was performed before (CPT 1), 5 min (CPT 2), and 20 min (CPT 3) after drug administration.

Results

Inhaled methoxyflurane and fentanyl 25 μg reduced VNRS scores significantly compared with placebo at CPT 2 (–1.14 [estimated difference in VNRS between treatment groups with 95% confidence interval {CI}: –1.50 to –0.78]; –1.15 [95% CI: –1.51 to –0.79]; both P<0.001) and CPT 3 (–0.60 [95% CI: –0.96 to –0.24]; –0.84 [95% CI: –1.20 to –0.47]; both P<0.001). There were no significant differences between the two drugs. Methoxyflurane had significantly higher VNRS scores than fentanyl 50 μg at CPT 2 (0.90 [95% CI: 0.54–1.26]; P<0.001) and CPT 3 (0.57 [95% CI: 0.21–0.94]; P<0.001).

Conclusions

Inhaled methoxyflurane 3 ml was equi-analgesic to fentanyl 25 μg i.v. at CPT 2. Both resulted in significantly less pain than placebo. Fentanyl 50 μg i.v. demonstrated analgesia superior to methoxyflurane.

Clinical trial registration

NCT03894800

Central encoding of the strength of intranasal chemosensory trigeminal stimuli in a human experimental pain setting

An important measure in pain research is the intensity of nociceptive stimuli and their cortical representation. However, there is evidence of different cerebral representations of nociceptive stimuli, including the fact that cortical areas recruited during processing of intranasal nociceptive chemical stimuli included those outside the traditional trigeminal areas. Therefore, the aim of this study was to investigate the major cerebral representations of stimulus intensity associated with intranasal chemical trigeminal stimulation. Trigeminal stimulation was achieved with carbon dioxide presented to the nasal mucosa. Using a single-blinded, randomized crossover design, 24 subjects received nociceptive stimuli with two different stimulation paradigms, depending on the just noticeable differences in the stimulus strengths applied. Stimulus-related brain activations were recorded using functional magnetic resonance imaging with event-related design. Brain activations increased significantly with increasing stimulus intensity, with the largest cluster at the right Rolandic operculum and a global maximum in a smaller cluster at the left lower frontal orbital lobe. Region of interest analyses additionally supported an activation pattern correlated with the stimulus intensity at the piriform cortex as an area of special interest with the trigeminal input. The results support the piriform cortex, in addition to the secondary somatosensory cortex, as a major area of interest for stimulus strength-related brain activation in pain models using trigeminal stimuli. This makes both areas a primary objective to be observed in human experimental pain settings where trigeminal input is used to study effects of analgesics.

Druggable Targets in Endocannabinoid Signaling

Cannabis and cannabinoid-based extracts have long been utilized for their perceived therapeutic value, and support for the legalization of cannabis for medicinal purposes continues to increase worldwide. Since the discovery of Δ⁹-tetrahydrocannabinol (THC) as the primary psychoactive component of cannabis over 50 years ago, substantial effort has been directed toward detection of endogenous mediators of cannabinoid activity. The discovery of anandamide and 2-arachidonoylglycerol as two endogenous lipid mediators of cannabinoid-like effects (endocannabinoids) has inspired exponential growth in our understanding of this essential pathway, as well as the pathological conditions that result from dysregulated endocannabinoid signaling. This review examines current knowledge of the endocannabinoid system including metabolic enzymes involved in biosynthesis and degradation and their receptors, and evaluates potential druggable targets for therapeutic intervention.

Machine-Learned Association of Next-Generation Sequencing-Derived Variants in Thermosensitive Ion Channels Genes with Human Thermal Pain Sensitivity Phenotypes

Genetic association studies have shown their usefulness in assessing the role of ion channels in human thermal pain perception. We used machine learning to construct a complex phenotype from pain thresholds to thermal stimuli and associate it with the genetic information derived from the next-generation sequencing (NGS) of 15 ion channel genes which are involved in thermal perception, including ASIC1, ASIC2, ASIC3, ASIC4, TRPA1, TRPC1, TRPM2, TRPM3, TRPM4, TRPM5, TRPM8, TRPV1, TRPV2, TRPV3, and TRPV4. Phenotypic information was complete in 82 subjects and NGS genotypes were available in 67 subjects. A network of artificial neurons, implemented as emergent self-organizing maps, discovered two clusters characterized by high or low pain thresholds for heat and cold pain. A total of 1071 variants were discovered in the 15 ion channel genes. After feature selection, 80 genetic variants were retained for an association analysis based on machine learning. The measured performance of machine learning-mediated phenotype assignment based on this genetic information resulted in an area under the receiver operating characteristic curve of 77.2%, justifying a phenotype classification based on the genetic information. A further item categorization finally resulted in 38 genetic variants that contributed most to the phenotype assignment. Most of them (10) belonged to the TRPV3 gene, followed by TRPM3 (6). Therefore, the analysis successfully identified the particular importance of TRPV3 and TRPM3 for an average pain phenotype defined by the sensitivity to moderate thermal stimuli.

Delta-9-tetrahydrocannabinol reduces the performance in sensory delayed discrimination tasks. A pharmacological-fMRI study in healthy volunteers

BACKGROUND

Cannabis proofed to be effective in pain relief, but one major side effect is its influence on memory in humans. Therefore, the role of memory on central processing of nociceptive information was investigated in healthy volunteers.

METHODS

In a placebo-controlled cross-over study including 22 healthy subjects, the effect of 20 mg oral Δ9-tetrahydrocannabinol (THC) on memory involving nociceptive sensations was studied, using a delayed stimulus discrimination task (DSDT). To control for nociceptive specificity, a similar DSDT-based study was performed in a subgroup of thirteen subjects, using visual stimuli.

RESULTS

For each nociceptive stimulus pair, the second stimulus was associated with stronger and more extended brain activations than the first stimulus. These differences disappeared after THC administration. The THC effects were mainly located in two clusters comprising the insula and inferior frontal cortex in the right hemisphere, and the caudate nucleus and putamen bilaterally. These cerebral effects were accompanied in the DSDT by a significant reduction of correct ratings from 41.61% to 37.05% after THC administration (rm-ANOVA interaction "drug" by "measurement": F (1,21) = 4.685, p = 0.042). Rating performance was also reduced for the visual DSDT (69.87% to 54.35%; rm-ANOVA interaction of "drug" by "measurement": F (1,12) = 13.478, p = 0.003) and reflected in a reduction of stimulus-related brain deactivations in the bilateral angular gyrus.

CONCLUSIONS

Results suggest that part of the effect of THC on pain may be related to memory effects. THC reduced the performance in DSDT of nociceptive and visual stimuli, which was accompanied by significant effects on brain activations. However, a pain specificity of these effects cannot be deduced from the data presented.

A data science approach to the selection of most informative readouts of the human intradermal capsaicin pain model to assess pregabalin effects

Persistent and, in particular, neuropathic pain is a major healthcare problem with still insufficient pharmacological treatment options. This triggered research activities aimed at finding analgesics with a novel mechanism of action. Results of these efforts will need to pass through the phases of drug development, in which experimental human pain models are established components e.g. implemented as chemical hyperalgesia induced by capsaicin. We aimed at ranking the various readouts of a human capsaicin-based pain model with respect to the most relevant information about the effects of a potential reference analgesic. In a placebo-controlled, randomized cross-over study, seven different pain-related readouts were acquired in 16 healthy individuals before and after oral administration of 300 mg pregabalin. The sizes of the effect on pain induced by intradermal injection of capsaicin were quantified by calculating Cohen's d. While in four of the seven pain-related parameters, pregabalin provided a small effect judged by values of Cohen's d exceeding 0.2, an item categorization technique implemented as computed ABC analysis identified the pain intensities in the area of secondary hyperalgesia and of allodynia as the most suitable parameters to quantify the analgesic effects of pregabalin. Results of this study provide further support for the ability of the intradermal capsaicin pain model to show analgesic effects of pregabalin. Results can serve as a basis for the designs of studies where the inclusion of this particular pain model and pregabalin is planned.

[Generating knowledge from complex data sets in human experimental pain research]

Pain has a complex pathophysiology that is expressed in multifaceted and heterogeneous clinical phenotypes. This makes research on pain and its treatment a potentially data-rich field as large amounts of complex data are generated. Typical sources of such data are investigations with functional magnetic resonance imaging, complex quantitative sensory testing, next-generation DNA sequencing and functional genomic research approaches, such as those aimed at analgesic drug discovery or repositioning of drugs known from other indications as new analgesics. Extracting information from these big data requires complex data scientific-based methods belonging more to computer science than to statistics. A particular interest is currently focused on machine learning, the methods of which are used for the detection of interesting and biologically meaningful structures in high-dimensional data. Subsequently, classifiers can be created that predict clinical phenotypes from, e.g. clinical or genetic features acquired from subjects. In addition, knowledge discovery in big data accessible in electronic knowledge bases, can be used to generate hypotheses and to exploit the accumulated knowledge about pain for the discovery of new analgesic drugs. This enables so-called data-information-knowledge-wisdom (DIKW) approaches to be followed in pain research. This article highlights current examples from pain research to provide an overview about contemporary data scientific methods used in this field of research.

Effects of continuous theta-burst stimulation of the primary motor and secondary somatosensory areas on the central processing and the perception of trigeminal nociceptive input in healthy volunteers

Supplemental Digital Content is Available in the Text.

Inactivating paired continuous theta-burst stimulation of the primary motor cortex but not on the secondary somatosensory area flattened the relationship between brain activation and stimulus strength while not impacting on the subjective perceptions.

Noninvasive modulation of the activity of pain-related brain regions by means of transcranial magnetic stimulation promises an innovative approach at analgesic treatments. However, heterogeneous successes in pain modulation by setting reversible “virtual lesions” at different brain areas point at unresolved problems including the optimum stimulation site. The secondary somatosensory cortex (S2) has been previously identified to be involved in the perception of pain-intensity differences. Therefore, impeding its activity should impede the coding of the sensory component of pain intensity, resulting in a flattening of the relationship between pain intensity and physical stimulus strength. This was assessed using inactivating spaced continuous theta-burst stimulation (cTBS) in 18 healthy volunteers. In addition, cTBS was applied on the primary motor cortex (M1) shown previously to yield moderate and variable analgesic effects, whereas sham stimulation at both sites served as placebo condition. Continuous theta-burst stimulation flattened the relationship between brain activation and stimulus strength, mainly at S2, the insular cortex, and the postcentral gyrus (16 subjects analyzed). However, these effects were observed after inactivation of M1 while this effect was not observed after inactivation of S2. Nevertheless, both the M1 and the S2-spaced cTBS treatment were not reflected in the ratings of the nociceptive stimuli of different strengths (17 subjects analyzed), contrasting with the clear coding of stimulus strength by these data. Hence, while modulating the central processing of nociceptive input, cTBS failed to produce subjectively relevant changes in pain perception, indicating that the method in the present implementation is still unsuitable for clinical application.

Non-invasive Motor Cortex Neuromodulation Reduces Secondary Hyperalgesia and Enhances Activation of the Descending Pain Modulatory Network

Central sensitization is a driving mechanism in many chronic pain patients, and manifests as hyperalgesia and allodynia beyond any apparent injury. Recent studies have demonstrated analgesic effects of motor cortex (M1) stimulation in several chronic pain disorders, yet its neural mechanisms remain uncertain. We evaluated whether anodal M1 transcranial direct current stimulation (tDCS) would mitigate central sensitization as measured by indices of secondary hyperalgesia. We used a capsaicin-heat pain model to elicit secondary mechanical hyperalgesia in 27 healthy subjects. In an assessor and subject-blind randomized, sham-controlled, crossover trial, anodal M1 tDCS decreased the intensity of pinprick hyperalgesia more than cathodal or sham tDCS. To elucidate the mechanism driving analgesia, subjects underwent fMRI of painful mechanical stimuli prior to and following induction of the pain model, after receiving M1 tDCS. We hypothesized that anodal M1 tDCS would enhance engagement of a descending pain modulatory (DPM) network in response to mechanical stimuli. Anodal tDCS normalized the effects of central sensitization on neurophysiological responses to mechanical pain in the medial prefrontal cortex, pregenual anterior cingulate cortex, and periaqueductal gray, important regions in the DPM network. Taken together, these results provide support for the hypothesis that anodal M1-tDCS reduces central sensitization-induced hyperalgesia through the DPM network in humans.

Multicenter assessment of quantitative sensory testing (QST) for the detection of neuropathic-like pain responses using the topical capsaicin model

Background

The use of quantitative sensory testing (QST) in multicenter studies has been quite limited, due in part to lack of standardized procedures among centers.

Aim

The aim of this study was to assess the application of the capsaicin pain model as a surrogate experimental human model of neuropathic pain in different centers and verify the variation in reports of QST measures across centers.

Methods

A multicenter study conducted by the Quebec Pain Research Network in six laboratories allowed the evaluation of nine QST parameters in 60 healthy subjects treated with topical capsaicin to model unilateral pain and allodynia. The same measurements (without capsaicin) were taken in 20 patients with chronic neuropathic pain recruited from an independent pain clinic.

Results

Results revealed that six parameters detected a significant difference between the capsaicin-treated and the control skin areas: (1) cold detection threshold (CDT) and (2) cold pain threshold (CPT) are lower on the capsaicin-treated side, indicating a decreased in cold sensitivity; (3) heat pain threshold (HPT) was lower on the capsaicin-treated side in healthy subjects, suggesting an increased heat pain sensitivity; (4) dynamic mechanical allodynia (DMA); (5) mechanical pain after two stimulations (MPS2); and (6) mechanical pain summation after ten stimulations (MPS10), are increased on the capsaicin-treated side, suggesting an increased in mechanical pain (P < 0.002). CDT, CPT and HPT showed comparable effects across all six centers, with CPT and HPT demonstrating the best sensitivity. Data from the patients showed significant difference between affected and unaffected body side but only with CDT.

Conclusion

These results provide further support for the application of QST in multicenter studies examining normal and pathological pain responses.

Impact of suggestion on the human experimental model of cold hyperalgesia after topical application of high-concentration menthol [40%]

BACKGROUND

Human experimental pain models in healthy subjects offer unique possibilities to study mechanisms of pain within a defined setting of expected pain symptoms, signs and mechanisms. Previous trials in healthy subjects demonstrated that topical application of 40% menthol is suitable to induce cold hyperalgesia. The objective of this study was to evaluate the impact of suggestion on this experimental human pain model.

METHODS

The study was performed within a single-centre, randomized, placebo-controlled, double-blind, two-period crossover trial in a cohort of 16 healthy subjects. Subjects were tested twice after topical menthol application (40% dissolved in ethanol) and twice after ethanol (as placebo) application. In the style of a balanced placebo trial design, the subjects received during half of the testing the correct information about the applied substance (topical menthol or ethanol) and during half of the testing the incorrect information, leading to four tested conditions (treatment conditions: menthol-told-menthol and menthol-told-ethanol; placebo conditions: ethanol-told-menthol and ethanol-told-ethanol).

RESULTS

Cold but not mechanical hyperalgesia was reliably induced by the model. The cold pain threshold decreased in both treatment conditions regardless whether true or false information was given. Minor suggestion effects were found in subjects with prior ethanol application.

CONCLUSIONS

The menthol model is a reliable, nonsuggestible model to induce cold hyperalgesia. Mechanical hyperalgesia is not as reliable to induce.

SIGNIFICANCE

Cold hyperalgesia may be investigated under unbiased and suggestion-free conditions using the menthol model of pain.

Stratifying patients with peripheral neuropathic pain based on sensory profiles: algorithm and sample size recommendations

Supplemental Digital Content is Available in the Text.

Phenotype stratification of patients with peripheral neuropathic pain can be conducted with a novel algorithm based on sensory profiles.

In a recent cluster analysis, it has been shown that patients with peripheral neuropathic pain can be grouped into 3 sensory phenotypes based on quantitative sensory testing profiles, which are mainly characterized by either sensory loss, intact sensory function and mild thermal hyperalgesia and/or allodynia, or loss of thermal detection and mild mechanical hyperalgesia and/or allodynia. Here, we present an algorithm for allocation of individual patients to these subgroups. The algorithm is nondeterministic—ie, a patient can be sorted to more than one phenotype—and can separate patients with neuropathic pain from healthy subjects (sensitivity: 78%, specificity: 94%). We evaluated the frequency of each phenotype in a population of patients with painful diabetic polyneuropathy (n = 151), painful peripheral nerve injury (n = 335), and postherpetic neuralgia (n = 97) and propose sample sizes of study populations that need to be screened to reach a subpopulation large enough to conduct a phenotype-stratified study. The most common phenotype in diabetic polyneuropathy was sensory loss (83%), followed by mechanical hyperalgesia (75%) and thermal hyperalgesia (34%, note that percentages are overlapping and not additive). In peripheral nerve injury, frequencies were 37%, 59%, and 50%, and in postherpetic neuralgia, frequencies were 31%, 63%, and 46%. For parallel study design, either the estimated effect size of the treatment needs to be high (>0.7) or only phenotypes that are frequent in the clinical entity under study can realistically be performed. For crossover design, populations under 200 patients screened are sufficient for all phenotypes and clinical entities with a minimum estimated treatment effect size of 0.5.

Effect profile of paracetamol, Δ9-THC and promethazine using an evoked pain test battery in healthy subjects

BACKGROUND

A battery of evoked pain tasks (PainCart) was developed to investigate the pharmacodynamic properties of novel analgesics in early-phase clinical research. As part of its clinical validation, compounds with different pharmacological mechanisms of actions are investigated. The aim was to investigate the analgesic effects of classic and nonclassic analgesics compared to a sedating negative control in a randomized placebo-controlled crossover study in 24 healthy volunteers using the PainCart.

METHODS

The PainCart consisted of pain tasks eliciting electrical, pressure, heat, cold and inflammatory pain. Subjective scales for cognitive functioning and psychotomimetic effects were included. Subjects were administered each of the following oral treatments: paracetamol (1000 mg), Δ9-THC (10 mg), promethazine (50 mg) or matching placebo. Pharmacodynamic measurements were performed at baseline and repeated up to 10 h postdose.

RESULTS

Paracetamol did not show a significant reduction in pain sensation or subjective cognitive functioning compared to placebo. Promethazine induced a statistically significant reduction in PTT for cold pressor and pressure stimulation. Furthermore, reduced subjective alertness was observed. Δ9-THC showed a statistically significant decrease in PTT for electrical and pressure stimulation. Δ9-THC also demonstrated subjective effects, including changes in alertness and calmness, as well as feeling high and psychotomimetic effects.

CONCLUSIONS

This study found a decreased pain tolerance due to Δ9-THC and promethazine, or lack thereof, using an evoked pain task battery. Pain thresholds following paracetamol administration remained unchanged, which may be due to insufficient statistical power. We showed that pain thresholds determined using this pain test battery are not driven by sedation.

SIGNIFICANCE

The multimodal battery of evoked pain tasks utilized in this study may play an important role in early-phase clinical drug development. This battery of pain tasks is not sensitive to the effects of sedation alone, and thus suitable to investigate the analgesic potential of novel analgesic compounds.

Modulation of sodium channels as pharmacological tool for pain therapy-highlights and gaps

Voltage-gated sodium channels are crucially involved in the transduction and transmission of nociceptive signals and pathological pain states. In the past decades, a lot of effort has been spent examining and characterizing biophysical properties of the different sodium channels and their role in signaling pathways. Several gains of function mutations of the sodium channels Nav1.7, Nav1.8, and Nav1.9 are associated with pain disorders. Due to their critical role in nociceptive pathways voltage-gated sodium channels are regarded interesting targets for pharmacological pain treatment. However we still need to fill the gap that exists in the translation of efficacy in preclinical in vitro experiments and in models of pain into the clinic. This review summarizes biological and electrophysiological properties of voltage-gated sodium channels and aims to discuss limitations and promising pharmacological strategies in sodium channel research in the context of pain therapy.

Current evidence of cannabinoid-based analgesia obtained in preclinical and human experimental settings

Cannabinoids have a long record of recreational and medical use and become increasingly approved for pain therapy. This development is based on preclinical and human experimental research summarized in this review. Cannabinoid CB₁ receptors are widely expressed throughout the nociceptive system. Their activation by endogenous or exogenous cannabinoids modulates the release of neurotransmitters. This is reflected in antinociceptive effects of cannabinoids in preclinical models of inflammatory, cancer and neuropathic pain, and by nociceptive hypersensitivity of cannabinoid receptor-deficient mice. Cannabis-based medications available for humans mainly comprise Δ⁹ -tetrahydrocannabinol (THC), cannabidiol (CBD) and nabilone. During the last 10 years, six controlled studies assessing analgesic effects of cannabinoid-based drugs in human experimental settings were reported. An effect on nociceptive processing could be translated to the human setting in functional magnetic resonance imaging studies that pointed at a reduced connectivity within the pain matrix of the brain. However, cannabinoid-based drugs heterogeneously influenced the perception of experimentally induced pain including a reduction in only the affective but not the sensory perception of pain, only moderate analgesic effects, or occasional hyperalgesic effects. This extends to the clinical setting. While controlled studies showed a lack of robust analgesic effects, cannabis was nearly always associated with analgesia in open-label or retrospective reports, possibly indicating an effect on well-being or mood, rather than on sensory pain. Thus, while preclinical evidence supports cannabinoid-based analgesics, human evidence presently provides only reluctant support for a broad clinical use of cannabinoid-based medications in pain therapy.

SIGNIFICANCE

Cannabinoids consistently produced antinociceptive effects in preclinical models, whereas they heterogeneously influenced the perception of experimentally induced pain in humans and did not provide robust clinical analgesia, which jeopardizes the translation of preclinical research on cannabinoid-mediated antinociception into the human setting.

Challenges in translational drug research in neuropathic and inflammatory pain: the prerequisites for a new paradigm

AIM

Despite an improved understanding of the molecular mechanisms of nociception, existing analgesic drugs remain limited in terms of efficacy in chronic conditions, such as neuropathic pain. Here, we explore the underlying pathophysiological mechanisms of neuropathic and inflammatory pain and discuss the prerequisites and opportunities to reduce attrition and high-failure rate in the development of analgesic drugs.

METHODS

A literature search was performed on preclinical and clinical publications aimed at the evaluation of analgesic compounds using MESH terms in PubMed. Publications were selected, which focused on (1) disease mechanisms leading to chronic/neuropathic pain and (2) druggable targets which are currently under evaluation in drug development. Attention was also given to the role of biomarkers and pharmacokinetic-pharmacodynamic modelling.

RESULTS

Multiple mechanisms act concurrently to produce pain, which is a non-specific manifestation of underlying nociceptive pathways. Whereas these manifestations can be divided into neuropathic and inflammatory pain, it is now clear that inflammatory mechanisms are a common trigger for both types of pain. This has implications for drug development, as the assessment of drug effects in experimental models of neuropathic and chronic pain is driven by overt behavioural measures. By contrast, the use of mechanistic biomarkers in inflammatory pain has provided the pharmacological basis for dose selection and evaluation of non-steroidal anti-inflammatory drugs (NSAIDs).

CONCLUSION

A different paradigm is required for the identification of relevant targets and candidate molecules whereby pain is coupled to the cause of sensorial signal processing dysfunction rather than clinical symptoms. Biomarkers which enable the characterisation of drug binding and target activity are needed for a more robust dose rationale in early clinical development. Such an approach may be facilitated by quantitative clinical pharmacology and evolving technologies in brain imaging, allowing accurate assessment of target engagement, and prediction of treatment effects before embarking on large clinical trials.

The use of a battery of pain models to detect analgesic properties of compounds: a two-part four-way crossover study

AIM

The aim was to investigate the ability of a battery of pain models to detect analgesic properties of commonly used analgesics in healthy subjects.

METHODS

The battery consisted of tests eliciting electrical, mechanical and thermal (contact heat and cold pressor)-pain and included a UVB model, the thermal grill illusion and a paradigm of conditioned pain modulation. Subjects were administered fentanyl 3 μg kg^-1 , phenytoin 300 mg, (S)-ketamine 10 mg and placebo (part I), or imipramine 100 mg, pregabalin 300 mg, ibuprofen 600 mg and placebo (part II). Pain measurements were performed at baseline and up to 10 h post-dose. Endpoints were analysed using a mixed model analysis of variance.

RESULTS

Sixteen subjects (8 female) completed each part. The pain tolerance threshold (PTT) for electrical stimulation was increased (all P < 0.05) compared to placebo for (S)-ketamine (+10.1%), phenytoin (+8.5%) and pregabalin (+10.8%). The PTT for mechanical pain was increased by pregabalin (+14.1%). The cold pressor PTT was increased by fentanyl (+17.1%) and pregabalin (+46.4%). Normal skin heat pain detection threshold was increased by (S)-ketamine (+3.3%), fentanyl (+2.8%) and pregabalin (+4.1%). UVB treated skin pain detection threshold was increased by fentanyl (+2.6%) and ibuprofen (+4.0%). No differences in conditioned pain modulation were observed.

CONCLUSION

This study shows that these pain models are able to detect changes in pain thresholds after administration of different classes of analgesics in healthy subjects. The analgesic compounds all showed a unique profile in their effects on the pain tasks administered.

No evidence of potentiation of buprenorphine by milnacipran in healthy subjects using a nociceptive test battery

BACKGROUND

Serotonin-norepinephrine reuptake inhibitors inhibit the reuptake of serotonin and noradrenalin and are used in the treatment of neuropathic pain. Animal studies suggest that milnacipran co-administered with opioids may potentiate the analgesic effect of μ-opioid receptor agonists. This study hypothesized that co-administration of milnacipran and buprenorphine would have a synergistic effect in evoked pain models in healthy subjects.

METHODS

This was a randomized double-blinded, placebo-controlled, four-way cross-over, multiple dose clinical trial to investigate the analgesic effects of buprenorphine (placebo, 0.5, 1 and 3 μg/kg) in combination with milnacipran (placebo, 25 and 50 mg) in healthy subjects.

RESULTS

11 healthy men were enrolled in the study. Buprenorphine alone showed a dose-response relationship indicative of anti-nociception in the pain tests. Following milnacipran administration, no changes were seen in the pharmacodynamic measurements for pain, psychomotor function, body stability or eye movements. For the electrical tests, cold pressor test and pressure pain test, buprenorphine alone was superior when compared with buprenorphine plus milnacipran. No differences in pharmacodynamic variables, besides an increase in pupil/iris ratio, were observed after repeated administration of milnacipran 50 mg. Single and multiple doses of 25 or 50 mg milnacipran did not further potentiate the anti-nociceptive effects of buprenorphine.

CONCLUSIONS

Buprenorphine showed dose-dependent effects consistent with its pharmacological profile. Milnacipran alone did not affect any of the pain variables. The combination of both buprenorphine and milnacipran did not potentiate or show a synergistic effect on the pain models used in this study.

SIGNIFICANCE

Buprenorphine is known to be a potent opioid agonist. Animal studies suggest that milnacipran co-administered with opioids may potentiate the analgesic effect of μ-opioid receptor agonists. Here, we found that buprenorphine showed a dose-dependent analgesic effect, but that no potentiation or synergy on a battery of evoked pain tasks could be observed after co-administration of both milnacipran and buprenorphine.

Who Benefits from Chronic Opioid Therapy? Rethinking the Question of Opioid Misuse Risk

Beginning in the late 1990s, a movement began within the pain management field focused upon the underutilization of opioids, thought to be a potentially safe and effective class of pain medication. Concern for addiction and misuse were present at the start of this shift within pain medicine, and an emphasis was placed on developing reliable and valid methods and measures of identifying those at risk for opioid misuse. Since that time, the evidence for the safety and effectiveness of chronic opioid therapy (COT) has not been established. Rather, the harmful, dose-dependent deleterious effects have become clearer, including addiction, increased risk of injuries, respiratory depression, opioid induced hyperalgesia, and death. Still, many individuals on low doses of opioids for long periods of time appear to have good pain control and retain social and occupational functioning. Therefore, we propose that the question, “Who is at risk of opioid misuse?” should evolve to, “Who may benefit from COT?” in light of the current evidence.

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery

Human pain models are useful in the assessing the analgesic effect of drugs, providing information about a drug's pharmacology and identify potentially suitable therapeutic populations. The need to use a comprehensive battery of pain models is highlighted by studies whereby only a single pain model, thought to relate to the clinical situation, demonstrates lack of efficacy. No single experimental model can mimic the complex nature of clinical pain. The integrated, multi-modal pain task battery presented here encompasses the electrical stimulation task, pressure stimulation task, cold pressor task, the UVB inflammatory model which includes a thermal task and a paradigm for inhibitory conditioned pain modulation. These human pain models have been tested for predicative validity and reliability both in their own right and in combination, and can be used repeatedly, quickly, in short succession, with minimum burden for the subject and with a modest quantity of equipment. This allows a drug to be fully characterized and profiled for analgesic effect which is especially useful for drugs with a novel or untested mechanism of action.

Perspectives and Trends in Pharmacological Approaches to the Modulation of Pain

Pharmacological approaches to our understanding and treatment of pain have had a long history and have traditionally relied on very few drugs that either have significant side effects and abuse liability, such as the nonsteroidal anti-inflammatory drugs or the opioids, respectively, or those that have been developed for other conditions such as the tricyclic antidepressants. The pathophysiology of pain is undoubtedly complex, complicated in part by the fact that it is not a singular condition, and has a variety of etiologies and a number of associated comorbidities that make treatment interventions challenging. Moreover, there are changes in the central nervous system during the course of the development of chronic pain that, in a manner parallel to neurodegenerative disorders, likely require different pharmacological approaches in the early stages of acute pain compared to those that would be effective when pain has become chronic. This chapter reviews the current status of the field of pain research focusing on some relatively underdeveloped areas, such as pain and its associated comorbidities, and the use of transgenic animals and drug self-administration procedures in the context of analgesic assessment. This chapter also incorporates more recent developments and emerging trends in the area of epigenetics, biomarkers, and the use of induced pluripotent stem cells for pharmacological evaluation, target identification, and validation. Recent progress in the study of "organs-on-a-chip" will also be included in this overview, setting expectations for future progress that integrates these advances for deeper insights into mechanisms, novel treatments, and facilitated efforts in drug discovery.

Pattern of neuropathic pain induced by topical capsaicin application in healthy subjects

Human experimental pain models are widely used to study drug effects under controlled conditions, but they require further optimization to better reflect clinical pain conditions. To this end, we measured experimentally induced pain in 110 (46 men) healthy volunteers. The quantitative sensory testing (QST) battery (German Research Network on Neuropathic Pain) was applied on untreated ("control") and topical capsaicin-hypersensitized ("test") skin. Z-transformed QST-parameter values obtained at the test site were compared with corresponding values published from 1236 patients with neuropathic pain using Bayesian statistics. Subjects were clustered for the resemblance of their QST pattern to neuropathic pain. Although QST parameter values from the untreated site agreed with reference values, several QST parameters acquired at the test site treated with topical capsaicin deviated from normal. These deviations resembled in 0 to 7 parameters of the QST pattern observed in patients with neuropathic pain. Higher degrees (50%-60%) of resemblance to neuropathic QST pattern were obtained in 18% of the subjects. Inclusion in the respective clusters was predictable at a cross-validated accuracy of 86.9% by a classification and regression tree comprising 3 QST parameters (mechanical pain sensitivity, wind-up ratio, and z-transformed thermal sensory limen) from the control sites. Thus, we found that topical capsaicin partly induced the desired clinical pattern of neuropathic pain in a preselectable subgroup of healthy subjects to a degree that fuels expectations that experimental pain models can be optimized toward mimicking clinical pain. The subjects, therefore, qualify for enrollment in analgesic drug studies that use highly selected cohorts to enhance predictivity for clinical analgesia.

A small yet comprehensive subset of human experimental pain models emerging from correlation analysis with a clinical quantitative sensory testing protocol in healthy subjects

BACKGROUND

Picturing the complexity of pain in human experimental settings has increased the predictivity for clinical pain but requires increasingly complex test batteries. This raises problems in studies in which time is objectively limited, for example by the course of action of an analgesic drug. We addressed the selection of a small yet comprehensive set of pain tests for the use in such a situation.

METHOD

Nineteen different pain measures from 'classical' pain models (n = 9) and a clinically established QST-pain test battery (n = 10), were obtained from 72 healthy volunteers (34 men). The nonparametric correlation structure among the various pain measures was analysed using Ward clustering.

RESULTS

Four clusters emerged, each consisting of highly correlated pain measures. The pain model groups emerged comprised (I) pain thresholds and tolerances to blunt pressure or electrical pain; (II) pain thresholds to thermal stimuli; (III) pain measures obtained following application of punctate mechanical, intranasal CO2 chemical or cutaneous laser heat stimuli; and (IV) detection thresholds to thermal stimuli. The first three clusters agreed with an immediate mechanistic interpretation as reflecting C-fibre mediated pain, thermal pain and Aδ-fibre mediated pain, respectively, whereas the last cluster contained non-painful measures and was disregarded.

CONCLUSIONS

When basing a selection of a small comprehensive set of pain models on the assumption that highly correlated pain measures account for redundant results and therefore, one member of each group suffices an economic yet comprehensive pain study, results suggest inclusion of established C-fibre, Aδ-fibre mediated and thermal pain measures.

A more pessimistic life orientation is associated with experimental inducibility of a neuropathy-like pain pattern in healthy individuals

The clinical pattern of neuropathic pain, diagnosed using the quantitative sensory testing (QST) battery (German Research Network on Neuropathic Pain), could be partly mimicked in healthy volunteers after topical capsaicin application. However, similar to clinical neuropathic pain that develops in only a subgroup of patients who have a neurologic lesion, this attempt to mimick a neuropathic pain pattern succeeded only in a small fraction (18%) of healthy individuals. In the present assessment, we pursued the hypothesis that the inducible subgroup differed from the other healthy participants with respect to their psychological phenotype. Therefore, in an observational study, participants were assessed using a comprehensive set of psychological variables comprising general psychological and pain-related cognitive-emotional mechanisms. The sum scores of the questionnaires were significantly linearly correlated with each other. Principal component analysis indicated that a major source of variance (46%) could be attributed to dispositional optimism examined via the Life Orientation Test (LOT). The LOT score significantly differed between the groups of participants, either those in whom a neuropathy-like pattern of pain assessed via QST could be partly (50-60% of the 11 QST parameters) induced (n = 20) or not (n = 90; P = .0375). It emerged again as the main selection criterion in a classification and regression tree predicting a participant's group assignment (inducible neuropathy-like QST pattern versus noninducible neuropathy-like QST pattern) at a cross-validated accuracy of 95.5 ± 2.1%. Thus, the few participants in a random sample of healthy volunteers who, after topical capsaicin application, partly resemble (to a degree of about 60%) the clinical pattern of neuropathic pain in the QST test battery, are preselectable on the basis of psychological factors, with a particular emphasis on pessimistic life attitudes.

PERSPECTIVE

In a small fraction of 18% of healthy volunteers, topical capsaicin application resulted in a neuropathy-like pattern in 50 to 60% of the components of a clinical test battery. These individuals displayed a more pessimistic life attitude as assessed by means of the LOT.

Individualized pharmacological treatment of neuropathic pain

Patients with the same disease may suffer from completely different pain symptoms yet receive the same drug treatment. Several studies elucidate neuropathic pain and treatment response in human surrogate pain models. They show promising results toward a patient stratification according to the mechanisms underlying the pain, as reflected in their symptoms. Several promising new drugs produced negative study results in clinical phase III trials. However, retrospective analysis of treatment response based on baseline pain phenotyping could demonstrate positive results for certain subgroups of patients. Thus, a prospective classification of patients according to pain phenotype may play an increasingly important role in personalized treatment of neuropathic pain states. A recent prospective study using stratification based on pain-related sensory abnormalities confirmed the concept of personalized pharmacological treatment of neuropathic pain.