Contribution of dihydrocodeine and dihydromorphine to analgesia following dihydrocodeine administration in man: a PK-PD modelling analysis

Dihydrocodeine for detoxification and maintenance treatment in individuals with opiate use disorders

BACKGROUND

Medical treatment and detoxification from opiate disorders includes oral administration of opioid agonists. Dihydrocodeine (DHC) substitution treatment is typically low threshold and therefore has the capacity to reach wider groups of opiate users. Decisions to prescribe DHC to patients with less severe opiate disorders centre on its perceived safety, reduced toxicity, shorter half-life and more rapid onset of action, and potential retention of patients. This review set out to investigate the effects of DHC in comparison to other pharmaceutical opioids and placebos in the detoxification and substitution of individuals with opiate use disorders.

OBJECTIVES

To investigate the effectiveness of DHC in reducing illicit opiate use and other health-related outcomes among adults compared to other drugs or placebos used for detoxification or substitution therapy.

SEARCH METHODS

In February 2019 we searched Cochrane Drugs and Alcohol's Specialised Register, CENTRAL, PubMed, Embase and Web of Science. We also searched for ongoing and unpublished studies via ClinicalTrials.gov, the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) and Trialsjournal.com. All searches included non-English language literature. We handsearched references of topic-related systematic reviews and the included studies.

SELECTION CRITERIA

We included randomised controlled trials that evaluated the effect of DHC for detoxification and maintenance substitution therapy for adolescent (aged 15 years and older) and adult illicit opiate users. The primary outcomes were abstinence from illicit opiate use following detoxification or maintenance therapy measured by self-report or urinalysis. The secondary outcomes were treatment retention and other health and behaviour outcomes.

DATA COLLECTION AND ANALYSIS

We followed the standard methodological procedures that are outlined by Cochrane. This includes the GRADE approach to appraise the quality of evidence.

MAIN RESULTS

We included three trials (in five articles) with 385 opiate-using participants that measured outcomes at different follow-up periods in this review. Two studies with 150 individuals compared DHC with buprenorphine for detoxification, and one study with 235 participants compared DHC to methadone for maintenance substitution therapy. We downgraded the quality of evidence mainly due to risk of bias and imprecision. For the two studies that compared DHC to buprenorphine, we found low-quality evidence of no significant difference between DHC and buprenorphine for detoxification at six-month follow-up (risk ratio (RR) 0.59, 95% confidence interval (CI) 0.25 to 1.39; P = 0.23) in the meta-analysis for the primary outcome of abstinence from illicit opiates. Similarly, low-quality evidence indicated no difference for treatment retention (RR 1.29, 95% CI 0.99 to 1.68; P = 0.06). In the single trial that compared DHC to methadone for maintenance substitution therapy, the evidence was also of low quality, and there may be no difference in effects between DHC and methadone for reported abstinence from illicit opiates (mean difference (MD) -0.01, 95% CI -0.31 to 0.29). For treatment retention at six months' follow-up in this single trial, the RR calculated with an intention-to-treat analysis also indicated that there may be no difference between DHC and methadone (RR 1.04, 95% CI 0.94 to 1.16). The studies that compared DHC to buprenorphine reported no serious adverse events, while the DHC versus methadone study reported one death due to methadone overdose.

AUTHORS' CONCLUSIONS

We found low-quality evidence that DHC may be no more effective than other commonly used pharmacological interventions in reducing illicit opiate use. It is therefore premature to make any conclusive statements about the effectiveness of DHC, and it is suggested that further high-quality studies are conducted, especially in low- to middle-income countries.

Rat brain CYP2D activity alters in vivo central oxycodone metabolism, levels and resulting analgesia

Oxycodone is metabolized by CYP2D to oxymorphone. Despite oxymorphone being a more potent opioid-receptor agonist, its contribution to oxycodone analgesia may be minor because of low peripheral production, low blood-brain barrier permeability and central nervous system efflux. CYP2D metabolism within the brain may contribute to variation in central oxycodone and oxymorphone levels, thereby affecting analgesia. Brain CYP2D expression and activity are subject to exogenous regulation; nicotine induces rat brain, but not liver, CYP2D consistent with higher brain CYP2D in smokers. We assessed the role of rat brain CYP2D in orally administered oxycodone metabolism (in vivo brain microdialysis) and analgesia (tail-flick test) by inhibiting brain CYP2D selectively with intracerebroventricular propranolol (mechanism-based inhibitor) and inducing brain CYP2D with nicotine. Inhibiting brain CYP2D increased brain oxycodone levels (1.8-fold; P < 0.03) and analgesia (1.5-fold AUC0-60 ; P < 0.001) after oxycodone, while inducing brain CYP2D increased brain oxymorphone levels (4.6-fold; P < 0.001) and decreased analgesia (0.8-fold; P < 0.02). Inhibiting the induced brain CYP2D reversed the change in oxycodone levels (1.2-fold; P > 0.1) and analgesia (1.1-fold; P > 0.3). Brain, but not plasma, metabolic ratios were affected by pre-treatments. Peak analgesia was inversely correlated with ex vivo brain (P < 0.003), but not hepatic (P > 0.9), CYP2D activity. Altering brain CYP2D did not affect analgesia from oral oxymorphone (P > 0.9 for AUC0-60 across all groups), which is not a CYP2D substrate. Thus, brain CYP2D metabolism alters local oxycodone levels and response, suggesting that people with increased brain CYP2D activity may have reduced oxycodone response. Factors that alter individual oxycodone response may be useful for optimizing treatment and minimizing abuse liability.

Pharmacogenomic considerations in opioid analgesia

Translating pharmacogenetics to clinical practice has been particularly challenging in the context of pain, due to the complexity of this multifaceted phenotype and the overall subjective nature of pain perception and response to analgesia. Overall, numerous genes involved with the pharmacokinetics and dynamics of opioids response are candidate genes in the context of opioid analgesia. The clinical relevance of CYP2D6 genotyping to predict analgesic outcomes is still relatively unknown; the two extremes in CYP2D6 genotype (ultrarapid and poor metabolism) seem to predict pain response and/or adverse effects. Overall, the level of evidence linking genetic variability (CYP2D6 and CYP3A4) to oxycodone response and phenotype (altered biotransformation of oxycodone into oxymorphone and overall clearance of oxycodone and oxymorphone) is strong; however, there has been no randomized clinical trial on the benefits of genetic testing prior to oxycodone therapy. On the other hand, predicting the analgesic response to morphine based on pharmacogenetic testing is more complex; though there was hope that simple genetic testing would allow tailoring morphine doses to provide optimal analgesia, this is unlikely to occur. A variety of polymorphisms clearly influence pain perception and behavior in response to pain. However, the response to analgesics also differs depending on the pain modality and the potential for repeated noxious stimuli, the opioid prescribed, and even its route of administration.

Pain management in patients with cancer: focus on opioid analgesics

Cancer pain is generally treated with pharmacological measures, relying on using opioids alone or in combination with adjuvant analgesics. Weak opioids are used for mild-to-moderate pain as monotherapy or in a combination with nonopioids. For patients with moderate-to-severe pain, strong opioids are recommended as initial therapy rather than beginning treatment with weak opioids. Adjunctive therapy plays an important role in the treatment of cancer pain not fully responsive to opioids administered alone (ie, neuropathic, bone, and visceral colicky pain). Supportive drugs should be used wisely to prevent and treat opioids’ adverse effects. Understanding the pharmacokinetics, pharmacodynamics, interactions, and cautions with commonly used opioids can help determine appropriate opioid selection for individual cancer patients.

Pharmacokinetic/pharmacodynamic modeling of biomarker response to sunitinib in healthy volunteers

A pharmacokinetic/pharmacodynamic (PK/PD) study of the tyrosine kinase inhibitor sunitinib was conducted in 12 healthy volunteers using blood pressure and circulating biomarker levels as PD markers. Blood pressure was measured, and plasma concentration-time courses of sunitinib, its major metabolite SU12662, vascular endothelial growth factors VEGF-A and VEGF-C, and soluble VEGF receptor-2 (sVEGFR-2) were studied in healthy subjects receiving 50 mg of sunitinib orally for 3-5 consecutive days. Using NONMEM, PK/PD models were established that predicted changes (expressed as multiples relative to baseline values) in systolic blood pressure, diastolic blood pressure, VEGF-A level, and sVEGFR-2 level, of 1.10, 1.18, 2.24, and 0.76, respectively, for a typical subject after 4 weeks of treatment with 50 mg/day. Simulated blood pressure-time courses compare excellently with published data in patients, whereas changes in circulating biomarkers were greater in patients than simulations suggest for healthy subjects. In conclusion, the tumor-independent pharmacological response to sunitinib could be described by PK/PD models, thereby facilitating model-based investigations with antiangiogenic drugs, using blood pressure and circulating proteins as biomarkers.

Role of active metabolites in the use of opioids

The opioid class of drugs, a large group, is mainly used for the treatment of acute and chronic persistent pain. All are eliminated from the body via metabolism involving principally CYP3A4 and the highly polymorphic CYP2D6, which markedly affects the drug's function, and by conjugation reactions mainly by UGT2B7. In many cases, the resultant metabolites have the same pharmacological activity as the parent opioid; however in many cases, plasma metabolite concentrations are too low to make a meaningful contribution to the overall clinical effects of the parent drug. These metabolites are invariably more water soluble and require renal clearance as an important overall elimination pathway. Such metabolites have the potential to accumulate in the elderly and in those with declining renal function with resultant accumulation to a much greater extent than the parent opioid. The best known example is the accumulation of morphine-6-glucuronide from morphine. Some opioids have active metabolites but at different target sites. These are norpethidine, a neurotoxic agent, and nordextropropoxyphene, a cardiotoxic agent. Clinicians need to be aware that many opioids have active metabolites that will become therapeutically important, for example in cases of altered pathology, drug interactions and genetic polymorphisms of drug-metabolizing enzymes. Thus, dose individualisation and the avoidance of adverse effects of opioids due to the accumulation of active metabolites or lack of formation of active metabolites are important considerations when opioids are used.

Pharmacogenetics of analgesics: toward the individualization of prescription

The use of analgesics is based on the empiric administration of a given drug with clinical monitoring for efficacy and toxicity. However, individual responses to drugs are influenced by a combination of pharmacokinetic and pharmacodynamic factors that can sometimes be regulated by genetic factors. Whereas polymorphic drug-metabolizing enzymes and drug transporters may affect the pharmacokinetics of drugs, polymorphic drug targets and disease-related pathways may influence the pharmacodynamic action of drugs. After a usual dose, variations in drug toxicity and inefficacy can be observed depending on the polymorphism, the analgesic considered and the presence or absence of active metabolites. For opioids, the most studied being morphine, mutations in the ABCB1 gene, coding for P-glycoprotein (P-gp), and in the µ-opioid receptor reduce morphine potency. Cytochrome P450 (CYP) 2D6 mutations influence the analgesic effect of codeine and tramadol, and polymorphism of CYP2C9 is potentially linked to an increase in nonsteroidal anti-inflammatory drug-induced adverse events. Furthermore, drug interactions can mimic genetic deficiency and contribute to the variability in response to analgesics. This review summarizes the available data on the pharmacokinetic and pharmacodynamic consequences of known polymorphisms of drug-metabolizing enzymes, drug transporters, drug targets and other nonopioid biological systems on central and peripheral analgesics.

The chemical and pharmacological importance of morphine analogues

The object of this review is to summarize the efforts which resulted in the discovery of therapeutically useful morphine-like drugs. The search for new analgesics can be divided into three stages: (a) search for analgesics with high efficacy and reduced unwanted side-effects; (b) understanding of structure-activity relationships; (c) studies on the mechanism of pain perception and its alleviation by investigation of the pharmacology of opioids. An immense body of literature has been produced on the syntheses of thousands of new compounds which resulted in the development of detailed structure-activity relationships. The physical and psychologic dependence of opioid analgesics also facilitated investigators to solve the problem of the separation of strong analgesia from addiction liability. In the past decades more mixed agonist-antagonist analgesics, pure antagonists devoid of agonist action and potent opioids like the 6,14-ethenomorphinan derivatives were developed. Naloxone, Naltrexone, Buprenorphine and Pentazocine are the outstanding representatives which are introduced into clinical therapy.

Comparison of analgesic effects and patient tolerability of nabilone and dihydrocodeine for chronic neuropathic pain: randomised, crossover, double blind study

OBJECTIVE

To compare the analgesic efficacy and side effects of the synthetic cannabinoid nabilone with those of the weak opioid dihydrocodeine for chronic neuropathic pain.

DESIGN

Randomised, double blind, crossover trial of 14 weeks' duration comparing dihydrocodeine and nabilone.

SETTING

Outpatient units of three hospitals in the United Kingdom.

PARTICIPANTS

96 patients with chronic neuropathic pain, aged 23-84 years.

MAIN OUTCOME MEASURES

The primary outcome was difference between nabilone and dihydrocodeine in pain, as measured by the mean visual analogue score computed over the last 2 weeks of each treatment period. Secondary outcomes were changes in mood, quality of life, sleep, and psychometric function. Side effects were measured by a questionnaire.

INTERVENTION

Patients received a maximum daily dose of 240 mg dihydrocodeine or 2 mg nabilone at the end of each escalating treatment period of 6 weeks. Treatment periods were separated by a 2 week washout period. Results Mean baseline visual analogue score was 69.6 mm (range 29.4-95.2) on a 0-100 mm scale. 73 patients were included in the available case analysis and 64 patients in the per protocol analysis. The mean score was 6.0 mm longer for nabilone than for dihydrocodeine (95% confidence interval 1.4 to 10.5) in the available case analysis and 5.6 mm (10.3 to 0.8) in the per protocol analysis. Side effects were more frequent with nabilone.

CONCLUSION

Dihydrocodeine provided better pain relief than the synthetic cannabinoid nabilone and had slightly fewer side effects, although no major adverse events occurred for either drug.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN15330757 controlled-trials.com] .

Pharmacokinetic–pharmacodynamic modeling of the miotic effects of dihydrocodeine in humans

AIM

The purpose of this study was to evaluate the pharmacokinetic-pharmacodynamic interrelations of pupillary effects of dihydrocodeine by two different analytic approaches.

METHODS

Dihydrocodeine plasma concentrations and miotic effects were available from a previous study with 24-h measurements after administration of 60 mg dihydrocodeine to nine healthy young men. Plasma concentration versus time course was described either by a one-compartment model or by linear splines using NONMEM. Dihydrocodeine concentrations at the effect site were obtained by convolution of a first-order transfer function with the function describing the plasma concentration versus time courses, and miotic effects were related to effect-site concentrations by a sigmoidal pharmacodynamic model.

RESULTS

Bayesian individual fits of miotic effects were only slightly better with the spline approach than with the compartmental approach (median individual absolute weighted residuals 0.046 versus 0.058, respectively, Wilcoxon test p = 0.008; residual errors of an additive error model 0.0979 versus 0.184, respectively). Both approaches provided similar pharmacokinetic-pharmacodynamic population parameter values. The transfer half-life between plasma and effect site was 21.1 min (95% CI 11.1-34.7 min) and 19.8 min (95% CI 11.9-34 min) with spline and compartmental approaches, respectively, and miosis occurred with EC50 of 207 or 230 ng/ml, respectively.

CONCLUSION

Two modeling approaches to the miotic effects of dihydrocodeine provided similar transfer half-lives between plasma and effect site, which also agreed with previous independently estimated values obtained from analgesic effects, suggesting that pupil size is a valid biomarker to estimate the value of ke0 for opioid central nervous system (CNS) effects.

Pharmacogenetics of Opioids

Opioids are used for acute and chronic pain and dependency. They have a narrow therapeutic index and large interpatient variability in response. Genetic factors regulating their pharmacokinetics (metabolizing enzymes, transporters) and pharmacodynamics (receptors and signal transduction elements) are contributors to such variability. The polymorphic CYP2D6 regulates the O-demethylation of codeine and other weak opioids to more potent metabolites with poor metabolizers having reduced antinociception in some cases. Some opioids are P-glycoprotein substrates, whereas, ABCB1 genotypes inconsistently influence opioid pharmacodynamics and dosage requirements. Single-nucleotide polymorphisms in the mu opioid receptor gene are associated with increasing morphine, but not methadone dosage requirements and altered efficacy of mu opioid agonists and antagonists. As knowledge regarding the interplay between genes affecting opioid pharmacokinetics including cerebral kinetics and pharmacodynamics increases, our understanding of the role of pharmacogenomics in mediating interpatient variability in efficacy and side effects to this important class of drugs will be better informed. Opioid drugs as a group have withstood the test of time in their ability to attenuate acute and chronic pain. Since the isolation of morphine in the early 1800s by Friedrich Sertürner, a large number of opioid drugs beginning with modification of the 4,5-epoxymorphinan ring structure were developed in order to improve their therapeutic margin, including reducing dependence and tolerance, ultimately without success.

Individualizing analgesic prescription Part I: pharmacogenetics of opioid analgesics

The current use of analgesics is based on the empiric administration of a given drug with clinical monitoring for efficacy and toxicity. However, individual responses to drugs are influenced by a combination of pharmacokinetic and pharmacodynamic processes, and each of these components, in addition to pain perception and processing, seem to be regulated by genetic factors. Whereas polymorphic drug-metabolizing enzymes and drug transporters may affect the pharmacokinetics of drugs, polymorphic drug targets and disease-related pathways may influence the pharmacodynamic action of drugs. After usual dose, drug toxicity, as well as inefficacy, can be observed depending on the polymorphism, the analgesic considered and the presence or absence of active metabolites. Thus, cytochrome P450 (CYP)2D6 polymorphism influences codeine and tramadol analgesic effects, CYP2C9 has an impact on the disposition of some nonsteroidal anti-inflammatory drugs, and opioid receptor polymorphism (118A>G) may reduce morphine potency. Moreover, drug interaction mimics genetic deficiency and contributes to the variability in response to analgesics. This two-part review summarizes the available data on the pharmacokinetic-pharmacodynamic consequences of known polymorphisms of drug-metabolizing enzymes (CYP and uridine diphosphate glucuronosyltransferase), drug transporters (multidrug resistance proteins, multidrug resistance-associated proteins, organic anion-transporting polypeptides, and serotonin transporters), relevant drug targets (such as µ-opioid receptor, serotonin receptor and cyclooxygenases) and other nonopioid biological systems, on currently prescribed central and peripheral analgesics.

Extended-release opioids for the management of chronic non-malignant pain

Recent clinical trials have documented the use of extended-release (ER) opioids in the management of chronic non-malignant pain. This manuscript reviews the clinical pharmacology of investigational and current marketed ER opioids. Recent randomised clinical trials of ER opioids that document the efficacy and safety of opioid therapy for chronic pain are reviewed. Finally, the abuse liability of ER opioids is discussed. Current technologies aimed at defeating the abuse of ER opioids will also be presented.

Influence of dose, cigarette smoking, age, sex, and metabolic activity on plasma clozapine concentrations: a predictive model and nomograms to aid clozapine dose adjustment and to assess compliance in individual patients

The measurement of plasma clozapine concentrations is useful in assessing compliance, optimizing therapy, and minimizing toxicity. We measured plasma clozapine and norclozapine (N-desmethylclozapine) concentrations in samples from 3782 patients (2648 male, 1127 female). No clozapine was detected in 291 samples (227 patients, median prescribed dose 300 mg/d). In 4963 (50.2 %) samples (2222 patients); plasma clozapine concentration ranged from 10 to 350 ng/mL.Step-wise backward multiple regression analysis (37 % of the total samples) of log10 plasma clozapine concentration against log10 clozapine dose (mg/d), age (year), sex (male = 0, female = 1), cigarette smoking habit (nonsmokers = 0; smokers = 1), body weight (kg), and plasma clozapine/norclozapine ratio (clozapine metabolic ratio, MR) showed that these covariates explained 48% of the observed variation in plasma clozapine concentration (C = ng/mL x 10-3) (P < 0.001) according to the following equation: log 10 (C) = 0.811 log 10 (dose) + 0.332 (MR) + 69.42 X 10 (-3) (sex) + 2.263 x 10 (-3) (age) + 1.976 x 10(-3) (weight) - 0.171 (smoking habit) - 3.180. This model and its associated confidence intervals were used to develop nomograms of plasma clozapine concentration versus dose for male and female smokers and nonsmokers. Predicted plasma clozapine changes by +48% in nonsmokers, +17% in females, +/-8 % for every 0.1 change in MR (reference 1.32), +/-4% for every 5 years (reference 40 years), and +/-5 % for every 10 kg body weight (reference 80 kg). The nomograms can be used (i) to individualize dosage to achieve a given target plasma clozapine concentration, and (ii) for quantitative evaluation of adherence by estimating the likelihood of an observed concentration being achieved by a given dosage regimen. The model has been validated against published data.

Pharmacokinetic drug interactions of morphine, codeine, and their derivatives: theory and clinical reality, Part II

Pharmacokinetic drug-drug interactions with codeine, dihydrocodeine, hydrocodone, oxycodone, and buprenorphine are reviewed in this column. These compounds have a very similar chemical structure to morphine. Unlike morphine, which is metabolized chiefly through conjugation reactions with uridine diphosphate glucuronosyl transferase (UGT) enzymes, these five drugs are metabolized both through oxidative reactions by the cytochrome P450 (CYP450) enzyme and conjugation by UGT enzymes. There is controversy as to whether codeine, dihydrocodeine, and hydrocodone are actually prodrugs requiring activation by the CYP450 2D6 enzyme or UGT enzymes. Oxycodone and buprenorphine, however, are clearly not prodrugs and are metabolized by the CYP450 2D6 and 3A4 enzymes, respectively. Knowledge of this metabolism assists in the understanding for the potential of drug-drug interactions with these drugs. This understanding is important so that clinicians can choose the proper dosages for analgesia and anticipate potential drug-drug interactions.

Physiologically based modelling of inhibition of metabolism and assessment of the relative potency of drug and metabolite: dextromethorphan vs. dextrorphan using quinidine inhibition

AIMS

To define the relative antitussive effect of dextromethorphan (DEX) and its primary metabolite dextrorphan (DOR) after administration of DEX.

METHODS

Data were analysed from a double-blind, randomized cross-over study in which 22 subjects received the following oral treatments: (i) placebo; (ii) 30 mg DEX hydro-bromide; (iii) 60 mg DEX hydro-bromide; and (iv) 30 mg DEX hydro-bromide preceded at 1 h by quinidine HCl (50 mg). Cough was elicited using citric acid challenge. Pharmacokinetic data from all non-placebo arms of the study were fitted simultaneously. The parameters were then used as covariates in a link PK-PD model of cough suppression using data from all treatment arms.

RESULTS

The best-fit PK model assumed two- and one-compartment PK models for DEX and DOR, respectively, and competitive inhibition of DEX metabolism by quinidine. The intrinsic clearance of DEX estimated from the model ranged from 59 to 1536 l x h(-1), which overlapped with that extrapolated from in vitro data (12-261 l x h(-1)) and showed similar variation (26- vs. 21-fold, respectively). The inhibitory effect of quinidine ([I]/Ki) was 19 (95% confidence interval of mean: 18-20) with an estimated average Ki of 0.017 microM. Although DEX and DOR were both active, the potency of the antitussive effect of DOR was 38% that of DEX. A sustained antitussive effect was related to slow removal of DEX/DOR from the effect site (ke0 = 0.07 h(-1)).

CONCLUSIONS

Physiologically based PK modelling with perturbation of metabolism using an inhibitor allowed evaluation of the antitussive potency of DOR without the need for separate administration of DOR.