Opioids: The Painful Public Health Reality

Pharmacology and Mechanism of Action of Suzetrigine, a Potent and Selective NaV1.8 Pain Signal Inhibitor for the Treatment of Moderate to Severe Pain

INTRODUCTION

There is a high unmet need for safe and effective non-opioid medicines to treat moderate to severe pain without risk of addiction. Voltage-gated sodium channel 1.8 (NaV1.8) is a genetically and pharmacologically validated pain target that is selectively expressed in peripheral pain-sensing neurons and not in the central nervous system (CNS). Suzetrigine (VX-548) is a potent and selective inhibitor of NaV1.8, which has demonstrated clinical efficacy and safety in multiple acute pain studies. Our study was designed to characterize the mechanism of action of suzetrigine and assess both nonclinical and clinical data to test the hypothesis that selective NaV1.8 inhibition translates into clinical efficacy and safety, including lack of addictive potential.

METHODS

Preclinical pharmacology and mechanism of action studies were performed in vitro using electrophysiology and radiolabeled binding methods in cells recombinantly expressing human NaV channels, human proteins, and primary human dorsal root ganglion (DRG) sensory neurons. Safety and addictive potential assessments included in vitro secondary pharmacology studies, nonclinical repeat-dose toxicity and dependence studies in rats and/or monkeys, and a systematic analysis of adverse event data generated from 2447 participants from phase 3 acute pain studies of suzetrigine.

RESULTS

Suzetrigine is selective against all other NaV subtypes (≥ 31,000-fold) and 180 other molecular targets. Suzetrigine inhibits NaV1.8 by binding to the protein's second voltage sensing domain (VSD2) to stabilize the closed state of the channel. This novel allosteric mechanism results in tonic inhibition of NaV1.8 and reduces pain signals in primary human DRG sensory neurons. Nonclinical and clinical safety assessments with suzetrigine demonstrate no adverse CNS, cardiovascular or behavioral effects and no evidence of addictive potential or dependence.

CONCLUSIONS

The comprehensive pharmacology assessment presented here indicates that suzetrigine represents the first in a new class of non-opioid analgesics that are selective NaV1.8 pain signal inhibitors acting in the peripheral nervous system to safely treat pain without addictive potential.

Analgesia After Vestibular Schwannoma Surgery in Europe-Potential for Reduction of Postoperative Opioid Usage

OBJECTIVE

Excessively prescribed opioids promote chronic drug abuse and worsen a highly prevalent public health problem in the era of the opioid epidemic. This study aimed to (a) determine general analgesic prescription patterns after surgery for vestibular schwannoma (VS) with a focus on opioid prescription rates, (b) identify risk factors for receiving narcotics for postoperative pain management, and (c) highlight the feasibility of opioid-free analgesic treatment strategies.

STUDY DESIGN

Retrospective chart review.

SETTING

Tertiary referral center.

PATIENTS

A total of 105 adult inpatients who underwent VS surgery.

INTERVENTIONS

Analgesic prescription patterns were evaluated, and factors associated with opioid prescriptions were identified.

MAIN OUTCOME MEASURE

Number of prescribed analgesics.

RESULTS

Metamizole (=dipyrone) and acetaminophen (=paracetamol) were the most frequently prescribed non-opioid drugs. Sixty-three (60%) patients received an opioid with a median intake of 23.2 ± 24 mg of oral morphine equivalents. Only 10 (9.5%) individuals received opioids for longer than postoperative day 1. Subjects with small tumors undergoing middle cranial fossa tumor removal (p = 0.007) were more likely to receive opioid drugs. In contrast, patients undergoing retrosigmoid craniotomy required fewer opioids for pain control (p = 0.004). Furthermore, individuals receiving opioids were prone to obtain higher dosages of acetaminophen (odds ratio 1.054, 95% confidence interval 1.01-1.10, p = 0.022).

CONCLUSIONS

Opioids for acute postoperative analgesia after VS surgery may be necessary in many patients. However, middle- and long-term pain control can be accomplished using non-opioid treatment regimens, resulting in a reduction in opioid prescriptions and the accompanying negative effects on individual and public health.

Multinational appraisal of the epidemiological distribution of opioid fatalities: a systematic review and meta-analysis

Background

The global or multinational scientific evidence on the distribution of opioid fatality is unknown. Hence, the current study collects epidemiological characteristics to shed light on the ongoing global or multinational opioid crisis and to promote the development of public health prevention/management strategies.

Method

All documents on PRISMA standards were retrieved via electronic databases.

Results

Among the 47 articles relevant to our studies, which depict a total population size of 10,191 individuals, the prevalence of opioid fatal overdose was 15,022 (14.74%). Among the 47 articles, 14 of them reported the gender of the participants, with 22,125 (15.79%) male individuals and 7,235 (5.17%) female individuals, and the age distribution of the participants that was most affected by the overdose was as follows: 29,272 (31.13%) belonged to the 18-34-year-old age group and 25,316 (26.92%) belonged to the less than 18-year-old age group. Eighteen studies qualified for the meta-analysis of the multinational prevalence of fatal opioid overdose, depicting an overall pooled prevalence estimate of 19.66%, with 95% CIs (0.13-0.29), I2 = 99.76% determined using the random-effects model, and Q statistic of 7198.77 (p < 0.0001). The Egger test models of publication bias revealed an insubstantial level of bias (p = 0.015). The subgroup analysis of the study design (cohort or other) revealed that others have the highest prevalence estimate of 34.37, 95% CIs (0.1600-0.5901), I2 = 97.04%, and a sample size of less than 1,000 shows the highest prevalence of 34.66, 95% CIs (0.2039-0.5234), I2 = 97.82%, compared to that of more than 1,000 with a prevalence of 12.28, 95% CIs (0.0675-0.2131), I2 = 99.85%. The meta-regression analysis revealed that sample size (less-than or greater-than 1,000), (p = 0.0098; R2 = 3.83%) is significantly associated with the observed heterogeneity.

Conclusion

Research-based findings of fatal opioid overdose are grossly lacking in middle- and low-income nations. We established that there is a need for opioid fatality surveillance systems in developing nations.

Predictive Modelling of Susceptibility to Substance Abuse, Mortality and Drug-Drug Interactions in Opioid Patients

Objective: Opioids are a class of drugs that are known for their use as pain relievers. They bind to opioid receptors on nerve cells in the brain and the nervous system to mitigate pain. Addiction is one of the chronic and primary adverse events of prolonged usage of opioids. They may also cause psychological disorders, muscle pain, depression, anxiety attacks etc. In this study, we present a collection of predictive models to identify patients at risk of opioid abuse and mortality by using their prescription histories. Also, we discover particularly threatening drug-drug interactions in the context of opioid usage.

Methods and Materials: Using a publicly available dataset from MIMIC-III, two models were trained, Logistic Regression with L2 regularization (baseline) and Extreme Gradient Boosting (enhanced model), to classify the patients of interest into two categories based on their susceptibility to opioid abuse. We’ve also used K-Means clustering, an unsupervised algorithm, to explore drug-drug interactions that might be of concern.

Results: The baseline model for classifying patients susceptible to opioid abuse has an F1 score of 76.64% (accuracy 77.16%) while the enhanced model has an F1 score of 94.45% (accuracy 94.35%). These models can be used as a preliminary step towards inferring the causal effect of opioid usage and can help monitor the prescription practices to minimize the opioid abuse.

Discussion and Conclusion: Results suggest that the enhanced model provides a promising approach in preemptive identification of patients at risk for opioid abuse. By discovering and correlating the patterns contributing to opioid overdose or abuse among a variety of patients, machine learning models can be used as an efficient tool to help uncover the existing gaps and/or fraudulent practices in prescription writing. To quote an example of one such incidental finding, our study discovered that insulin might possibly be interacting with opioids in an unfavourable way leading to complications in diabetic patients. This indicates that diabetic patients under long term opioid usage might need to take increased amounts of insulin to make it more effective. This observation backs up prior research studies done on a similar aspect. To increase the translational value of our work, the predictive models and the associated software code are made available under the MIT License.

Ten-year trend of opioid and nonopioid analgesic use in the French adult population

AIMS

Analgesics are the most widely used medicines worldwide. In parallel, opioid abuse has increased and is of major concern. The accessibility of pharmacologically powerful medicines and the addictovigilance signals in France about the risk of opiates addiction call for an overview of analgesic use. The objective of this study was to investigate the use of analgesics reimbursed in France over a 10-year period through its prevalence.

METHODS

A cross-sectional study repeated yearly was conducted by using data from the French reimbursement database from 2006 to 2015. Analgesics were classified according to their pharmacological potency: prevalence of use for each category and sociodemographic characteristics of patients treated were analysed.

RESULTS

The annual prevalence of analgesic use was high and increased during the study period (59.8%, 253 976 users in 2015). In 2015, prevalence was always higher in women and increased with age, except for those older than 84 years. Peripheral analgesics were the most used (55.3%, 234 739 users). The prevalence of weak analgesic use decreased (21.3%, 90 257 users), mainly due to the definitive withdrawal of dextropropoxyphene in France in 2011, which was not offset by an increase in the consumption of other weak analgesics. For strong analgesics (1.2%, 5129 users), morphine was the most widely used, with a dramatic increase in oxycodone use, especially in the elderly.

CONCLUSION

The prevalence of analgesic use is high: approximately 31 million adults had at least 1 analgesic reimbursed in 2015. The most widely used analgesics were peripheral analgesics, far ahead of opioid analgesics.

Higher doses of naloxone are needed in the synthetic opiod era

There has been a dramatic increase of deaths due to illicit fentanyl. We examined the pharmacology of fentanyl and reviewed data on the number of repeat doses of naloxone used to treat fentanyl overdoses. Multiple sequential doses of naloxone have been required in a certain percentage of opioid overdoses due to fentanyl. In addition, fentanyl appears to differ from other opioids as having a very rapid onset with high systemic levels found in overdose victims. A rapid competition is required by naloxone to out-compete large numbers of opioid receptors occupied by fentanyl in the CNS. Taken together, we propose that higher doses of naloxone are needed to combat the new era of overdoses due to the more potent synthetic opioids such as fentanyl.