Maternal use of oral narcotics during breastfeeding can cause infant drowsiness, central nervous system depression and even death. Newborn infants seem to be particularly sensitive to the effects of even small dosages of propoxyphene may be particularly prone to causing these effects. Propoxyphene should be avoided during breastfeeding.[1]

The term opiate, or more appropriately opioids, is commonly referred to as a class of compounds, such as the alkaloids morphine, codeine, and thebaine, derived from the opium poppy (Papaver somniferum), and known and utilized by humankind for millennia for both analgesia and sedation. This class of substances also includes semi-synthetic compounds such as heroin, oxycodone, hydrocodone, and hydromorphone, obtained from these natural molecules as well as fully synthetic compounds, including fentanyl, pethidine, levorphanol, methadone, tramadol, and dextropropoxyphene. Morphine was first isolated in 1806, followed by the isolation of codeine several years later. Following the development of the hypodermic needle and hollow needle in the 1850s, physicians began to use morphine for various surgical procedures as well for the treatment of chronic pain and postoperative pain.[1] With the discovery of different opioid agonists, antagonists, and partial agonist compounds such as nalorphine, various researchers postulated and later proved that there are multiple stereospecific opioid binding sites in the central nervous system (CNS) through which they exert their physiological effects. Researchers further surmised that these receptors were most likely targets of endogenous opioid compounds, which researchers then began to isolate and study.[2] In 1975, John Hughes and Hans Kosterlitz reported the first evidence of endogenous opioids in brain extracts that they noted were able to inhibit acetylcholine release from nerves in the guinea pig ileum. Further, they indicated that when treated with the opioid receptor antagonist naloxone, the inhibition was blocked. The compounds that they first isolated were termed enkephalins. Structurally, the enkephalins are pentapeptides that are distinguished into two subgroups by their carboxy-terminal amino acids, leucine, or methionine. As a consequence, the enkephalins either classify as met-encephalins and leu-encephalins, respectively: The met-enkephalins present the amino acid sequence Tyr-Gly-Gly-Phe-Met. The leu-enkephalins present the amino acid sequence Tyr-Gly-Gly-Phe-Leu. The enkephalins are one of the three peptide systems that also include beta-endorphins and dynorphins. Of note, the three classes of endogenous opioid peptides share a common N terminus sequence of Tyr-Gly-Gly-Phe and lack a C terminus amide.[3] In molecular terms, Tyr and Phe bind the receptor, and the glycine pair acts as a spacer. These peptides act as neurotransmitters and neuromodulators throughout the nervous system and various end-organ targets.[4] Additionally, research has found that met-enkephalin has an essential role in cell proliferation and tissue organization during development. When discussed in this context, met-enkephalin is often referred to as the opioid growth factor (OGF).[5]

The design of novel, safe, and effective drugs to treat human diseases is a challenging venture, with toxicity being one of the main sources of attrition at later stages of development. Failure due to toxicity incurs a significant increase in costs and time to market, with multiple drugs being withdrawn from the market due to their adverse effects. Cardiotoxicity, for instance, was responsible for the failure of drugs such as fenspiride, propoxyphene, and valdecoxib. While significant effort has been dedicated to mitigate this issue by developing computational approaches that aim to identify molecules likely to be toxic, including quantitative structure-activity relationship models and machine learning methods, current approaches present limited performance and interpretability. To overcome these, we propose a new web-based computational method, cardioToxCSM, which can predict six types of cardiac toxicity outcomes, including arrhythmia, cardiac failure, heart block, hERG toxicity, hypertension, and myocardial infarction, efficiently and accurately. cardioToxCSM was developed using the concept of graph-based signatures, molecular descriptors, toxicophore matchings, and molecular fingerprints, leveraging explainable machine learning, and was validated internally via different cross validation schemes and externally via low-redundancy blind sets. The models presented robust performances with areas under ROC curves of up to 0.898 on 5-fold cross-validation, consistent with metrics on blind tests. Additionally, our models provide interpretation of the predictions by identifying whether substructures that are commonly enriched in toxic compounds were present. We believe cardioToxCSM will provide valuable insight into the potential cardiotoxicity of small molecules early on drug screening efforts. The method is made freely available as a web server at https://biosig.lab.uq.edu.au/cardiotoxcsm.

Objective: To characterize the trend of opioid use (number of users, dispensations and oral morphine milligram equivalents) in Catalonia (Spain). Design, setting, and participants: This population-based cohort study included all individuals aged 18 years or older, registered in the Information System for Research in Primary Care (SIDIAP), which covers >75% of the population in Catalonia, Spain, from 1 January 2007, to 31 December 2019. Main exposure and outcomes: The exposures were all commercialized opioids and their combinations (ATC-codes): codeine, tramadol, oxycodone, tapentadol, fentanyl, morphine, and other opioids (dihydrocodeine, hydromorphone, dextropropoxyphene, buprenorphine, pethidine, pentazocine). The main outcomes were the annual figures per 1,000 individuals of 1) opioid users, 2) dispensations, and 3) oral morphine milligram equivalents (MME). Results were stratified separately by opioid types, age (5-year age groups), sex (male or female), living area (rural or urban), and socioeconomic status (from least, U1, to most deprived, U5). The overall trends were quantified using the percentage change (PC) between 2007 and 2019. Results: Among 4,656,197 and 4,798,114 residents from 2007 to 2019, the number of opioid users, dispensations and morphine milligram equivalents per 1,000 individuals increased 12% (percentage change: 95% confidence interval (CI) 11.9-12.3%), 105% (95% confidence interval 83%-126%) and 339% (95% CI 289%-390%) respectively. Tramadol represented the majority of opioid use in 2019 (61, 59, and 54% of opioid users, dispensations, and total MME, respectively). Individuals aged 80 years or over reported the sharpest increase regarding opioid users (PC: 162%), dispensations (PC: 424%), and MME (PC: 830%). Strong opioids were increasingly prescribed for non-cancer pains over the years. Conclusion: Despite the modest increase of opioid users, opioid dispensations and MME increased substantially, particularly in the older population. In addition, strong opioids were incrementally indicated for non-cancer pains over the years. These findings suggest a transition of opioid prescriptions from intermittent to chronic and weak to strong and call for more rigorous opioid stewardship.

Here we describe the dataset of the first report of pharmacogenomics profiling in an outpatient spine setting with the primary aims to catalog: 1) the genes, alleles, and associated rs Numbers (accession numbers for specific single-nucleotide polymorphisms) analysed and 2) the genotypes and corresponding phenotypes of the genes involved in metabolizing 37 commonly used analgesic medications. The present description applies to analgesic medication-metabolizing enzymes and may be especially valuable to investigators who are exploring strategies to optimize pharmacologic pain management (e.g., by tailoring analgesic regimens to the genetically identified sensitivities of the patient). Buccal swabs were used to acquire tissue samples of 30 adult patients who presented to an outpatient spine clinic with the chief concern of axial neck and/or back pain. Array-based assays were then used to detect the alleles of genes involved in the metabolism of pain medications, including all common (wild type) and most rare variant alleles with known clinical significance. Both CYP450 isozymes - including CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 - and the phase II enzyme UDP-glucuronosyltransferase-2B7 (UGT2B7) were examined. Genotypes/phenotypes were then used to evaluate each patient's relative ability to metabolize 37 commonly used analgesic medications. These medications included both non-opioid analgesics (i.e., aspirin, diclofenac, nabumetone, indomethacin, meloxicam, piroxicam, tenoxicam, lornoxicam, celecoxib, ibuprofen, flurbiprofen, ketoprofen, fenoprofen, naproxen, and mefenamic acid) and opioid analgesics (i.e., morphine, codeine, dihydrocodeine, ethylmorphine, hydrocodone, hydromorphone, oxycodone, oxymorphone, alfentanil, fentanyl, sufentanil, meperidine, ketobemidone, dextropropoxyphene, levacetylmethadol, loperamide, methadone, buprenorphine, dextromethorphan, tramadol, tapentadol, and tilidine). The genes, alleles, and associated rs Numbers that were analysed are provided. Also provided are: 1) the genotypes and corresponding phenotypes of the genes involved in metabolizing 37 commonly used analgesic medications and 2) the mechanisms of metabolism of the analgesic medications by primary and ancillary pathways. In supplemental spreadsheets, the raw and analysed pharmacogenomics data for all 30 patients evaluated in the primary research article are additionally provided. Collectively, the presented data offer significant reuse potential in future investigations of pharmacogenomics for pain management.

Interactions of the analgesic medications dextropropoxyphene (DPP, opioid), paracetamol (PCL, nonnarcotic), tramadol (TDL, nonnarcotic), ibuprofen (IBN, nonsteroidal anti-inflammatory drug (NSAID)), and naproxen (NPX, NSAID) with pristine graphene (GN) and nitrogen-doped GN (NGN; containing only graphitic N atoms) nanosheets were explored using density functional theory (DFT) in the gas and aqueous phases. Calculations in the aqueous phase were performed using the integral equation formalism polarized continuum model (IEFPCM). Calculated geometry-optimized structures, partial atomic charges (determined using Natural Bond Orbital analysis), highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) energy gaps, work functions (determined using time-dependent DFT), and molecular electrostatic potential plots showed that the adsorption process is physical in nature (viz. physisorption), primarily due to noncovalent π-π and van der Waals interactions. In addition, calculated adsorption energies (ΔEad) were exergonic, indicating that formation of the analgesic/GN and analgesic/NGN complexes is thermodynamically favorable in the gas (ΔEad values for analgesic/GN and analgesic/NGN were in the range of -66.56 kJ mol-1 to -106.78 kJ mol-1) and aqueous phases (ΔEad values for analgesic/GN and analgesic/NGN complexes were in the range of -58.75 kJ mol-1 to -100.46 kJ mol-1). Generally, for GN and NGN, adsorption was more endergonic in the aqueous phase by as much as +10.41 kJ mol-1. Calculated solvation energies (ΔEsolvation) were exergonic for all analgesic/GN complexes (ΔEsolvation values were in the range of -56.50 kJ mol-1 to -66.17 kJ mol-1) and analgesic/NGN complexes (ΔEsolvation values were in the range of -77.26 kJ mol-1 to -87.96 kJ mol-1), with analgesic/NGN complexes exhibiting greater stability in aqueous solutions (∼20 kJ mol-1 more stable). In summary, the results of this theoretical study demonstrate that the adsorption and solvation of analgesics on GN and NGN nanosheets is thermodynamically favorable. In addition, generally, analgesic/NGN complexes exhibit higher adsorption affinities and solvation energies in the gas and aqueous phases. Therefore, GN and NGN nanosheets are potential adsorbents for extracting analgesic contaminants from aqueous environments such as aquatic ecosystems.

The opioids are a large class of medications related in structure to the natural plant alkaloids found in opium that are derived from the resin of the opium poppy, Papaver somniferum. The natural alkaloids are also referred to as opiates and include morphine and codeine. Synthetic derivatives include heroin, fentanyl, hydromorphone, methadone, buprenorphine and others. The opioids are highly potent and effective analgesics, but most have a high potential for dependency and abuse. Opioids act by engagement of specific cell surface receptors; the opiate receptors, which are designated µ [mu], κ [kappa] and δ [delta]. These receptors are found predominantly in the central nervous system, brain and spinal column, but are also present on vascular, cardiac, lung, gut and even peripheral blood mononuclear cells. Engagement of the opiate receptors generates a series of intracellular signals, including inhibition of adenylate cyclase, decreased opening of calcium channels, increased potassium currents and activation of protein kinase C (PKC). The major effect of these pathways is reduction in cell excitability and neurotransmission. The natural ligands for the opiate receptors are the so-called endogenous opioid peptides such as the enkephalins, endorphins and endomorphins. The opioids have a variety of clinical effects, but are predominantly known and used for their profound pain relieving effects. Other effects that are often linked to opiate analgesia include euphoria, changes in mood, drowsiness and mental clouding. However, the distinctive feature of the analgesia induced by the opioids is the lack of loss of consciousness. The pain is often described as less intense, but still present although better tolerated. Thus, the opioids do not decrease or treat the cause of the painful stimulus, but rather decrease its perception. Other effects of opioids include respiratory depression, decreased gastrointestinal motility, sedation, nausea, vomiting, constipation and intestinal bloating. Opioids also have direct cardiovascular effects, decreasing blood pressure, causing vasodilation and decreasing cardiac work. Most opioids have similar effects and side effects, although pharmacokinetic differences, tissue distribution, and receptor type specificity probably account for the variation in effects of the various synthetic and semisynthetic derivatives of morphine. Morphine is considered the prototype opiate, against which other agents are measured for their analgesic effects as well as adverse side effects. The opioids can be categorized into subclasses on the basis of their chemical structure as opium alkaloids (opiates: codeine, morphine), semisynthetic derivatives of the natural alkaloids (hydrocodone, hydromorphone, oxycodone, buprenorphine), and various classes of synthetic opioids such as the anililopiperidines (fentanyl, alfentanil, sufentanil, remifentanil), diphenylpropylamine derivatives (propoxyphene, dextropropoxyphene, methadone, diphenoxylate, loperamide), and others (pentazocine, butorphanol, nalbuphine, levorphanol, tramadol), and, the opioid antagonists (nalmefene, naloxone and naltrexone). They can also be informally classified based upon their major use such as anesthesia (fentanyl, alfentanil, remifentanil, sufentanil), severe pain (morphine, hydromorphone, levorphanol, meperidine), moderate-to-severe acute or chronic pain (transdermal or transbuccal fentanyl, codeine, oxycodone, hydrocodone, levorphanol, methadone), diarrhea (loperamide, diphenoxylate), and cough (codeine, hydrocodone). Finally, opioids can be categorized on the basis of their action as full agonists, partial agonists or mixed agonists/antagonists, and antagonists of opiate receptors. Opioid receptor antagonists are used to reverse the effects of opioids and are invaluable in the management of opioid overdose (naloxone, naltrexone, nalmefene). Specialized opioid antagonists can be used to reverse unwanted opioid effects, such as constipation in patients with chronic pain on long-term opioids. These agents (naldemedine, naloxegol) are generally modified so as not to cross the blood brain and reverse the central nervous system effects of opiates. Opioids are rare causes of drug induced liver disease and are not mentioned in large case series of clinically apparent liver injury caused by medications. In physiological, pain relieving doses, opioids have not been implicated in causing clinically apparent liver injury, acute liver failure, chronic hepatitis or vanishing bile duct syndrome. However, overdoses of the more potent opioids have been linked to cases of acute liver injury, usually with a precipitous onset and pattern of acute toxicity with marked elevations in serum aminotransferase levels and early onset of signs of hepatic failure. This syndrome has been best characterized after buprenorphine overdose or abuse, but likely occurs with others. It is possible that the implicated opioids are not directly toxic to the liver, but cause ischemic liver injury due to respiratory failure, cardiovascular collapse, shock and anoxia that can occur with severe opioid overdose. The clinical syndrome resembles acute hepatic necrosis and liver failure, but is rapidly reversible and rarely the primary cause of death from overdose. A special form of liver injury linked to opioid use occurs with their fixed drug combinations with acetaminophen. These combinations are commonly used for moderate to moderately severe pain and can lead to abuse. If taken too frequently, acetaminophen doses may reach toxic levels, particularly with overuse for several days in the face of malnutrition, alcohol abuse or intercurrent illness. These other stresses can lower hepatic glutathione levels and predispose to acetaminophen hepatotoxicity. This constellation of events is referred to as inadvertent or unintended acetaminophen overdose or more colloquially as a “therapeutic misadventure”. Because of their potential for hepatotoxicity, opioid combinations in which the dose of acetaminophen is greater than 325 mg per tablet or capsule were discontinued. References to the safety and hepatotoxic potential of the various opiate agonists are given together at the end of this overview section. References to the opioids and the opiate antagonists used to treat substance abuse are given separately with each agent (buprenorphine, methadone, nalmefene, naloxone, naltrexone). The opioids are discussed individually or as groups of agents and links to each are given below. Full and partial agonists: • Alfentanil • Buprenorphine • Butorphanol • Codeine • Diphenoxylate • Fentanyl • Heroin • Hydrocodone • Hydromorphone • Levorphanol • Loperamide • Meperidine • Methadone • Morphine • Oliceridine • Opium • Oxycodone • Oxymorphone • Pentazocine • Remifentanil • Sufentanil • Tramadol Opiate antagonists: • Naldemedine • Nalmefene • Naloxegol • Naloxone • Naltrexone

Acute soft tissue injuries are common and costly. The best drug treatment for such injuries is not certain, although non-steroidal anti-inflammatory drugs (NSAIDs) are often recommended. There is concern about the use of oral opioids for acute pain leading to dependence. This is an update of a Cochrane Review published in 2015.

France is experiencing an increase in the number of opioid prescriptions and related fatalities. We carried out a retrospective observational study using data from the Paris PCC over a 10-year period. The main objective was to obtain an epidemiological description of the severe reported cases. The secondary objectives were to assess the evolution of the number of these cases and their severity defined by the use of fentanyl and its derivatives, the use of the opioid-poisoning treatment naloxone, and the number of fatalities. During 2008-2017, 268 511 cases were recorded, including 1 122 cases of opioid-related poisoning that required medical management. These poisonings involved tramadol (43%), codeine (25%), dextropropoxyphene (13%), and morphine (8%); most resulted from self-exposure (60%). During the 10-year study period, 130 opioid-related fatalities were recorded in the Paris area, mainly resulting from suicides (39%) in men and were attributed to morphine (27%), tramadol (24%), and methadone (21%). We did not identify an increase in the number of severe opioid-related poisonings or fatalities or in the use of fentanyl or its derivatives. Conversely, we observed an increase in the use of naloxone, suggesting an increase in the severity of opioid poisonings. Our findings show that, until 2017, the opioid overdose epidemiology in the Paris area is different to that in the USA. The systematic analysis of data from the PCCs could be a good tool for health monitoring. To assess trends in France, a national study over a longer period would also be useful.