No significant influence of OCT1 genotypes on the pharmacokinetics of morphine in adult surgical patients.

We investigated the impact of genetic variants in OCT1 (SLC22A1) on morphine, morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G) pharmacokinetics in adult patients scheduled for major surgery. Blood samples were taken before and 5, 10, 15, 30, 45, 60 and 90 min after a bolus of morphine (0.15 mg/kg). Patients were genotyped for the genetic variants (rs12208357, rs34059508, rs72552763 and rs34130495) in OCT1. Eighty-six patients completed the trial. The mean difference (95% confidence interval) for dose adjusted morphine, M3G and M6G AUC was 0.9 (-0.7-2.4), -5.9 (-11.8 to -0.03) and -1.1 (-2.5-0.4) h/L*10-6 , respectively, in patients with two reduced function alleles compared to patients with no reduced function alleles in OCT1. Accordingly, the (AUCM3G/Dose )/(AUCmorphine/Dose ) and (AUCM6G/Dose )/(AUCmorphine/Dose ) ratio was reduced, -1.8 (-3.2 to -0.4) and -0.4 (-0.7 to -0.03), respectively, when comparing the same groups. OCT1 variants had no influence on the experience of pain, adverse events or the number of PCA doses used. In conclusion, genetic variants in OCT1 had a small and clinically unimportant impact on the exposure of morphine after intravenous administration. Our results do not support pre-emptive genotyping for OCT1 prior to morphine administration in patients scheduled for major surgery.

Oral and intravenous pharmacokinetics of metformin with and without oral codeine intake in healthy subjects: A cross-over study.

The aim of the study was to investigate if there is a clinically relevant drug interaction between metformin and codeine. Volunteers were randomized to receive on four separate occasions: (A) orally administered metformin (1 g), (B) intravenously administered metformin (0.5 g), (C) five doses of tablet codeine 25 mg; the last dose was administered together with oral metformin (1 g), and (D) five doses of tablet codeine 25 mg; the last dose was administered together with metformin (0.5 g) intravenously. Blood samples were drawn for 24 h after administration of metformin, and for 6 h after administration of codeine and analyzed using liquid chromatography and tandem mass spectrometry. Healthy volunteers genotyped as CYP2D6 normal metabolizers (*1/*1) without known reduced function variants in the OCT1 gene (rs12208357, rs34130495, rs34059508, and rs72552763) were invited. The median absorption fraction of metformin was 0.31 and was not influenced by codeine intake. The median time to maximum concentration ( T max ) after oral intake of metformin was 2 h without, and 3 h with codeine (p = 0.06). The geometric mean ratios of the areas under the plasma concentration time-curve (AUCs) for morphine and its metabolites M3G and M6G for oral intake of metformin-to-no metformin were 1.21, 1.31, and 1.27, respectively, and for i.v. metformin-to-no metformin 1.28, 1.34, and 1.30, respectively. Concomitant oral and i.v. metformin increased the plasma levels of morphine, M3G and M6G. These small pharmacokinetic changes may well contribute to an increased risk of early discontinuation of metformin. Hence, a clinically relevant drug-drug interaction between metformin and codeine seems plausible.

Using a limited sampling strategy to investigate the interindividual pharmacokinetic variability in metformin: A large prospective trial.

AIMS: Recently a limited sampling strategy (LSS) for determination of metformin' pharmacokinetics was developed. The LSS utilizes the plasma concentration of metformin 3 and 10 hours after oral intake of a single dose to estimate the area under the concentration-time curve up to 24 hours (AUC0-24h ). The main purpose of this study was to support the feasibility of this strategy in a large prospective trial. METHODS: Volunteers orally ingested two 500-mg tablets of metformin hydrochloride. A blood sample was drawn three and ten hours after the ingestion. Urine was collected for 0-10 and 10-24 hours and urine volumes recorded. The AUC0-24h was calculated using the equation AUC0-24h = 4.779 * C3 + 13.174 * C10 . Additionally, all participants were genotyped for the single-nucleotide polymorphism A270S in OCT2, g.-66 T > C in MATE1, R61C, G465R, G401S and the deletion M420del in OCT1. RESULTS: In total, 212 healthy volunteers participated. The median (25th - 75th interquartile range) AUC0 - 24h , CLrenal , C3 and C10 , were 10 600 (8470-12 500) ng* hr* mL-1 , 29 (24-34) L* hour-1 , 1460 (1180-1770) and 260 (200-330) ng* mL-1 , respectively, which is in agreement with our previous results. GFRi was correlated with metformin AUC and CLrenal (P < .001). As expected, we found a great pharmacokinetic interindividual variability among the volunteers and no effect of the OCT1 genotype on the AUC0 - 24h . We were unable to reproduce our previous finding of a gene-gene interaction (OCT2 and MATE1) effect on CLrenal in this cohort. CONCLUSION: This study further supports the use of the 2-point LSS algorithm in large pharmacokinetic trials.

Interaction potential between clarithromycin and individual statins-A systematic review.

The high prevalence of statin and clarithromycin utilization creates potential for overlapping use. The objectives of this MiniReview were to investigate the evidence base for drug-drug interactions between clarithromycin and currently marketed statins and to present management strategies for these drug combinations. We conducted a systematic literature review following PRISMA guidelines with English language studies retrieved from PubMed and EMBASE (from inception through March 2019). We included 29 articles (16 case reports, 5 observational, 5 clinical pharmacokinetic and 3 in vitro studies). Based on mechanistic/clinical studies involving clarithromycin or the related macrolide erythromycin (both strong inhibitors of CYP3A4 and of hepatic statin uptake transporters OATP1B1 and OATP1B3), clarithromycin is expected to substantially increase systemic exposure to simvastatin and lovastatin (>5-fold increase in area under the plasma concentration-time curve (AUC)), moderately increase AUCs of atorvastatin and pitavastatin (2- to 4-fold AUC increase) and slightly increase pravastatin exposure (≈2-fold AUC increase) while having little effect on fluvastatin or rosuvastatin. The 16 cases of statin-clarithromycin adverse drug reactions (rhabdomyolysis (n = 14) or less severe clinical myopathy) involved a CYP3A4-metabolized statin (simvastatin, lovastatin or atorvastatin). In line, a cohort study found concurrent use of clarithromycin and CYP3A4-metabolized statins to be associated with a doubled risk of hospitalization with rhabdomyolysis or other statin-related adverse events as compared with azithromycin-statin co-administration. If clarithromycin is necessary, we recommend (a) avoiding co-administration with simvastatin, lovastatin or atorvastatin; (b) withholding or dose-reducing pitavastatin; (c) continuing pravastatin therapy with caution, limiting pravastatin dose to 40 mg daily; and (d) continuing fluvastatin or rosuvastatin with caution.

In Vivo Imaging of Human 11C-Metformin in Peripheral Organs: Dosimetry, Biodistribution, and Kinetic Analyses.

Metformin is the most widely prescribed oral antiglycemic drug, with few adverse effects. However, surprisingly little is known about its human biodistribution and target tissue metabolism. In animal experiments, we have shown that metformin can be labeled by 11C and that 11C-metformin PET can be used to measure renal function. Here, we extend these preclinical findings by a first-in-human 11C-metformin PET dosimetry, biodistribution, and tissue kinetics study. METHODS: Nine subjects (3 women and 6 men) participated in 2 studies: in the first study, human radiation dosimetry and biodistribution of 11C-metformin were estimated in 4 subjects (2 women and 2 men) by whole-body PET. In the second study, 11C-metformin tissue kinetics were measured in response to both intravenous and oral radiotracer administration. A dynamic PET scan with a field of view covering target tissues of metformin (liver, kidneys, intestines, and skeletal muscle) was obtained for 90 (intravenous) and 120 (oral) min. RESULTS: Radiation dosimetry was acceptable, with effective doses of 9.5 µSv/MBq (intravenous administration) and 18.1 µSv/MBq (oral administration). Whole-body PET revealed that 11C-metformin was primarily taken up by the kidneys, urinary bladder, and liver but also to a lesser extent in salivary glands, skeletal muscle, and intestines. Reversible 2-tissue-compartment kinetics was observed in the liver, and volume of distribution was calculated to be 2.45 mL/mL (arterial input) or 2.66 mL/mL (portal and arterial input). In the kidneys, compartmental models did not adequately fit the experimental data, and volume of distribution was therefore estimated by a linear approach to be 6.83 mL/mL. Skeletal muscle and intestinal tissue kinetics were best described by 2-tissue-compartment kinetics and showed only discrete tracer uptake. Liver 11C-metformin uptake was pronounced after oral administration of the tracer, with tissue-to-blood ratio double what was observed after intravenous administration. Only slow accumulation of 11C-metformin was observed in muscle. There was no elimination of 11C-metformin through the bile both during the intravenous and during the oral part of the study. CONCLUSION: 11C-metformin is suitable for imaging metformin uptake in target tissues and may prove a valuable tool to assess the impact of metformin treatment in patients with varying metformin transport capacity.