Different Pharmacokinetics of Tramadol, O-Demethyltramadol and N-Demethyltramadol in Postoperative Surgical Patients From Those Observed in Medical Patients

Role of CYP2D6 polymorphisms in tramadol metabolism in a context of co-medications and overweight

Very few quantitative data exist on tramadol metabolites, which hampers our understanding of their role in efficacy and safety of tramadol. We aimed to provide quantitative data on tramadol and its 5 main metabolites in a patient cohort and to determine whether metabolite ratios can be predictive of a CYP2D6 metabolism phenotype. We also aimed to investigate the influence of co-medications and patient profile (BMI, glycemia, lipid levels) on tramadol metabolite ratios. Overall, 37 patient samples from the CONSTANCES cohort contained tramadol and its 5 metabolites. Mean concentrations found tramadol at 343.2 ± 223.2 μg/L, M1 at 62.4 ± 41.4 μg/L, M2 at 210.0 ± 272.3, M3 at 1.76 ± 3.0 μg/L, M4 at 1.8 ± 2.8 μg/L and M5 at 31.8 ± 28.4 μg/L. The most frequent CYP2D6 phenotype was extensive metabolizers (51.3%), followed by intermediate metabolizers (24.3%) and poor metabolizers (10.8%). CYP2D6-inhibiting co-medications impacted tramadol metabolism independently of CYP2D6 metabolism phenotype. Lipid parameters and glycemia were significantly associated with changes in tramadol metabolic ratios. Metabolic ratios are not sufficient to determine the CYP2D6 metabolic phenotype in patients. CYP2D6 inhibitors and obesity/NAFLD/diabetes impact tramadol metabolism. These factors are likely to impact the analgesic efficacy and safety profile of tramadol, justifying the need for further studies in this area.

The relation between inflammatory biomarkers and drug pharmacokinetics in the critically ill patients: a scoping review

BACKGROUND

The level of inflammation alters drug pharmacokinetics (PK) in critically ill patients. This might compromise treatment efficacy. Understanding the specific effects of inflammation, measured by biomarkers, on drug absorption, distribution, metabolism, and excretion is might help in optimizing dosing strategies.

OBJECTIVES

This review investigates the relationship between inflammatory biomarkers and PK parameters absorption, distribution, metabolism and excretion (ADME) in critically ill patients, providing insight in the complexity of dosing drugs in critically ill patients.

METHOD

Following PRISMA guidelines, we conducted a comprehensive search of Medline, Embase, Web of Science, and Cochrane databases (January 1946-November 2023). Studies examining inflammatory biomarkers, PK parameters, or drug exposure in critically ill patients were included. Records were screened by title, abstract, and full text, with any discrepancies resolved through discussion or consultation with a third reviewer.

RESULTS

Of the 4479 records screened, 31 met our inclusion criteria: 2 on absorption, 7 on distribution, 17 on metabolism, and 6 on excretion. In general, results are only available for a limited number of drugs, and most studies are done only looking at one of the components of ADME. Higher levels of inflammatory biomarkers may increase or decrease drug absorption depending on whether the drug undergoes hepatic first-pass elimination. For drug distribution, inflammation is negatively correlated with drug protein binding capacity, positively correlated with cerebrospinal fluid penetration, and negatively correlated with peritoneal penetration. Metabolizing capacity of most drugs was inversely correlated with inflammatory biomarkers. Regarding excretion, inflammation can lead to reduced drug clearance, except in the neonatal population.

CONCLUSION

Inflammatory biomarkers can offer valuable information regarding altered PK in critically ill patients. Our findings emphasize the need to consider inflammation-driven PK variability when individualizing drug therapy in this setting, at the same time research is limited to certain drugs and needs further research, also including pharmacodynamics.

Unraveling Catechol-O-Methyltransferase rs4680 SNP's Role in Patients' Response to Tramadol and Its Adverse Effects: A Pharmacogenetics Insight into Postoperative Pain Management

Effective postoperative pain management is essential for patient well-being and an efficient healthcare system. Variations in the Catechol O-Methyltransferase (COMT) gene, specifically rs4680, play a crucial role in pain perception and opioid response. This study seeks to elucidate the impact of rs4680 polymorphism on tramadol efficacy and adverse reactions in post-surgical patients. We performed an uncontrolled cohort pharmacogenetics study in which participants underwent postoperative tramadol administration. The frequencies of rs4680 alleles were determined and the association between rs4680 genotypes and the efficacy of tramadol analgesic as pain relief, measured by the Numeric Rating Scale (NRS), was analyzed. Secondary outcomes included tramadol-induced sedation levels, opioid-induced nausea and vomiting, and other adverse effects of tramadol. Data analysis, using IBM SPSS Statistics 23, focused on pain and side effect differences across genotypes, with statistical significance set to p ≤ 0.05. The COMT (rs4680) genotype distribution exhibited a 'G' allele frequency of 41.5% and an 'A' allele frequency of 58.5%, with the AA genotype present in 44% of individuals, adhering to the Hardy-Weinberg equilibrium (p = 0.788). Patients with the AA genotype reported lower pain scores post-tramadol administration across all times examined (p < 0.001), but also experienced statistically significant (p < 0.001) higher incidences of tramadol-induced nausea, vomiting, and sedation. However, GG genotype individuals experienced poor pain relief from tramadol, requiring more supplemental analgesia. These significant findings underscore the critical role of COMT rs4680 polymorphism in response to tramadol and the necessity of a personalized approach to postoperative pain management.

A Validated UHPLC-MS/MS Method for Determination of Nalbuphine in Human Plasma and Application for Pharmacokinetic Study of Patients Undergoing General Anesthesia

Nalbuphine was a semisynthetic opioid analgesic widely used in the treatment of both acute and chronic pain. We developed and validated a rapid, simple and sensitive method by ultra-performance liquid chromatography-tandem mass spectrometry (MS/MS) for the simultaneous quantitation of nalbuphine in human plasma, and we reported the pharmacokinetic features of patients during general anesthesia for abdominal surgery. Sample separation was achieved on a Kinetex Phenyl-Hexyl column (50 × 2.1 mm, 1.7 μm) after simple protein precipitation with acetonitrile. The mobile phase was composed of acetonitrile and 3 mM of ammonium acetate aqueous solution with 0.1% formic acid. Gradient elution was used in 4.5 min with a flow rate of 0.5 mL/min at 40°C. MS detection using AB Sciex QTRAP 5500 mass spectrometer was characterized by electrospray ionization for positive ions in multiple reaction monitoring mode. Quantitative ion pairs were m/z 358.4 → 340.1 for nalbuphine and m/z 340.0 → 268.3 for nalmefene, which were used as the internal standard (IS). The calibration curves showed good linearity (r2>0.99) over concentration range of 0.1-500 ng/mL. The intra-and inter-batch precisions were within 10.67%, and accuracy ranged from 94.07 to 105.34%. The IS-normalized matrix factors were 1.02-1.03 with RSD% (≤5.82%). The recoveries ranged from 101.09 to 106.30%. In conclusion, a rapid, simple, sensitive and economical analytical method was developed and validated to detect the concentration in plasma samples obtained from patients receiving nalbuphine intravenous injection and was successfully applicated to human pharmacokinetic studies of nalbuphine.

The Role of Pharmacogenomics in Postoperative Pain Management

Pharmacogenomics can improve pain management by considering individual variations in pain perception and susceptibility and sensitivity to medicines related to genetic diversity. Due to the subjective nature of pain and the fact that people respond differently to medicines, it can be challenging to develop a consistent and successful regimen for pain disorders. Numerous factors influence the outcome of pain treatment programs, but two stand out: altered perception of pain and varying responsiveness to analgesic medicines. Numerous polymorphisms in genes such as CYP2D6, OPRM1, and ABCB1 have been identified, culminating in a heterogeneous response to pain medication in people who have these genetic polymorphisms. Improved treatment regimens that factor in pharmacogenetic differences in patients would help reduce the risk of opioid dependency and help effectively treat postoperative pain.