Comparative metabolism of tramadol and tapentadol: a toxicological perspective

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Abstract

Tramadol and tapentadol are centrally acting, synthetic opioid analgesics used in the treatment of moderate to severe pain. Main metabolic patterns for these drugs in humans are well characterized. Tramadol is mainly metabolized by cytochrome P450 CYP2D6 to O-desmethyltramadol (M1), its main active metabolite. M1 and tapentadol undergo mainly glucuronidation reactions. On the other hand, the pharmacokinetics of tramadol and tapentadol are dependent on multiple factors, such as the route of administration, genetic variability in pharmacokinetic components and concurrent consumption of other drugs. This review aims to comparatively discuss the metabolomics of tramadol and tapentadol, namely by presenting all their known metabolites. An exhaustive literature search was performed using textual and structural queries for tramadol and tapentadol, and associated known metabolizing enzymes and metabolites. A thorough knowledge about tramadol and tapentadol metabolomics is expected to provide additional insights to better understand the interindividual variability in their pharmacokinetics and dose-responsiveness, and contribute to the establishment of personalized therapeutic approaches, minimizing side effects and optimizing analgesic efficacy.

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Most cited references 111

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Clinical Pharmacology of Tramadol

Stefan Grond, Armin Sablotzki (2004)

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Opioid metabolism.

Howard S Smith (2009)

Clinicians understand that individual patients differ in their response to specific opioid analgesics and that patients may require trials of several opioids before finding an agent that provides effective analgesia with acceptable tolerability. Reasons for this variability include factors that are not clearly understood, such as allelic variants that dictate the complement of opioid receptors and subtle differences in the receptor-binding profiles of opioids. However, altered opioid metabolism may also influence response in terms of efficacy and tolerability, and several factors contributing to this metabolic variability have been identified. For example, the risk of drug interactions with an opioid is determined largely by which enzyme systems metabolize the opioid. The rate and pathways of opioid metabolism may also be influenced by genetic factors, race, and medical conditions (most notably liver or kidney disease). This review describes the basics of opioid metabolism as well as the factors influencing it and provides recommendations for addressing metabolic issues that may compromise effective pain management. Articles cited in this review were identified via a search of MEDLINE, EMBASE, and PubMed. Articles selected for inclusion discussed general physiologic aspects of opioid metabolism, metabolic characteristics of specific opioids, patient-specific factors influencing drug metabolism, drug interactions, and adverse events.

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Polymorphism of human cytochrome P450 2D6 and its clinical significance: Part I.

Shu-Feng Zhou (2009)

Cytochrome P450 (CYP) 2D6 is one of the most investigated CYPs in relation to genetic polymorphism, but accounts for only a small percentage of all hepatic CYPs (approximately 2-4%). There is a large interindividual variation in the enzyme activity of CYP2D6. The enzyme is largely non-inducible and metabolizes approximately 25% of current drugs. Typical substrates for CYP2D6 are largely lipophilic bases and include some antidepressants, antipsychotics, antiarrhythmics, antiemetics, beta-adrenoceptor antagonists (beta-blockers) and opioids. The CYP2D6 activity ranges considerably within a population and includes ultrarapid metabolizers (UMs), extensive metabolizers (EMs), intermediate metabolizers (IMs) and poor metabolizers (PMs). There is a considerable variability in the CYP2D6 allele distribution among different ethnic groups, resulting in variable percentages of PMs, IMs, EMs and UMs in a given population. To date, 74 allelic variants and a series of subvariants of the CYP2D6 gene have been reported and the number of alleles is still growing. Among these are fully functional alleles, alleles with reduced function and null (non-functional) alleles, which convey a wide range of enzyme activity, from no activity to ultrarapid metabolism of substrates. As a consequence, drug adverse effects or lack of drug effect may occur if standard doses are applied. The alleles *10, *17, *36 and *41 give rise to substrate-dependent decreased activity. Null alleles of CYP2D6 do not encode a functional protein and there is no detectable residual enzymatic activity. It is clear that alleles *3, *4, *5, *6, *7, *8, *11, *12, *13, *14, *15, *16, *18, *19, *20, *21, *38, *40, *42, *44, *56 and *62 have no enzyme activity. They are responsible for the PM phenotype when present in homozygous or compound heterozygous constellations. These alleles are of clinical significance as they often cause altered drug clearance and drug response. Among the most important variants are CYP2D6*2, *3, *4, *5, *10, *17 and *41. On the other hand, the CYP2D6 gene is subject to copy number variations that are often associated with the UM phenotype. Marked decreases in drug concentrations have been observed in UMs with tramadol, venlafaxine, morphine, mirtazapine and metoprolol. The functional impact of CYP2D6 alleles may be substrate-dependent. For example, CYP2D6*17 is generally considered as an allele with reduced function, but it displays remarkable variability in its activity towards substrates such as dextromethorphan, risperidone, codeine and haloperidol. The clinical consequence of the CYP2D6 polymorphism can be either occurrence of adverse drug reactions or altered drug response. Drugs that are most affected by CYP2D6 polymorphisms are commonly those in which CYP2D6 represents a substantial metabolic pathway either in the activation to form active metabolites or clearance of the agent. For example, encainide metabolites are more potent than the parent drug and thus QRS prolongation is more apparent in EMs than in PMs. In contrast, propafenone is a more potent beta-blocker than its metabolites and the beta-blocking activity during propafenone therapy is more prominent in PMs than EMs, as the parent drug accumulates in PMs. Since flecainide is mainly eliminated through renal excretion, and both R- and S-flecainide possess equivalent potency for sodium channel inhibition, the CYP2D6 phenotype has a minor impact on the response to flecainide. Since the contribution of CYP2D6 is greater for metoprolol than for carvedilol, propranolol and timolol, a stronger gene-dose effect is seen with this beta-blocker, while such an effect is lesser or marginal in other beta-blockers. Concordant genotype-phenotype correlation provides a basis for predicting the phenotype based on genetic testing, which has the potential to achieve optimal pharmacotherapy. However, genotype testing for CYP2D6 is not routinely performed in clinical practice and there is uncertainty regarding genotype-phenotype, gene-concentration and gene-dose relationships. Further prospective studies on the clinical impact of CYP2D6-dependent metabolism of drugs are warranted in large cohorts of subjects.