Drug Metabolism and Drug Interactions最新文献

A growing awareness exists that informatics competencies are essential skills for healthcare professionals today, yet the development of these competencies lags behind the need. The Technology Informatics Guiding Education Reform (TIGER) Initiative represents a comprehensive, interdisciplinary effort that is well suited to the integration of informatics into education, practice, administration, and research environments. This article briefly discusses the background and significance of the TIGER Initiative and why it may be used as a model to instill informatics among the healthcare professionals globally.

Background: The success of an immunosuppressive drug therapy depends on the extent of exposure to the drugs (the blood levels and duration), which is measured as the area under the curve (AUC). Tacrolimus shows considerable variability in its pharmacokinetics, with poor correlation between the tacrolimus trough level and systemic exposure, as measured by the AUC of concentration time. Monitoring trough levels helps not only in reducing nephrotoxiicity but also in reducing the chances of acute rejection; although there is no international consensus, the trough concentration is used to determine dosing and the AUC for calculating the exposure of the patient to the drug. The major objective of this study was to find the best sampling time for an abbreviated AUC0-6 (area under the concentration time curve) to predict the total body exposure to tacrolimus in adult renal transplantation recipients.

Methods: The study involved retrospective analysis of 14 renal transplant patients (2 female and 12 male) that were on triple immunosuppressive therapy, methyl prednisolone, mycophenolate mofetil and tacrolimus. To determine trough concentrations, blood samples were collected before administration of tacrolimus (0 h) and at fixed time points of 2 h, 4 h and 6 h after administration of oral tacrolimus and analyzed in duplicate by microparticle enzyme immunoassay. AUC0-6 was determined using the linear trapezoidal rule. The association between the blood concentration and AUC6 were evaluated by the Pearson correlation coefficient. All statistical analyses were performed using the SPSS software (IBM Corp., NY, USA) program.

Results: Trough levels were fairly consistent at 7.9-18 ng·h/mL in all the patients included in this study, and this did not show variation with age or sex. The AUC0-6 was higher [202-290 ng/mL at 3-8 mg bis-daily (b.d.) dosage] in patients who received kidneys from cadavers compared to recipients from live donors (60.5-171 ng/mL at 3-8 mg b.d. dosage), but the clinical significance of this is not known. The highest AUC0-6 was 246 ng/mL, observed at 4.5 mg b.d. dosage. Dosages higher than 2 mg b.d. did not result in a noticeable increase in AUC0-6. Peak blood levels of tacrolimus were obtained 4 h after administration.

Conclusions: Trough level determination and a C2, C4 two-point limited sampling strategy may be useful to plan the dosing strategy and estimate the exposure of renal transplant patients to tacrolimus.

Background: Interspecies differences in biliary excretion and the differences in bile flow rates make scaling across species difficult for drugs that are excreted in the bile. The objective of this study is to predict clearance (CL) and volume of distribution (V) for humans from animals for drugs that are excreted in the bile.

Methods: Clearance values of 10 drugs known to be excreted in the bile were selected from the literature. Scaling of CL was performed using at least three animal species. Using simple allometry and the rule of exponents (ROE), clearances of studied drugs were predicted in humans. Besides using the ROE, a 'correction factor' was applied adjusting bile flow rate based on the species body weight (bile flow mL/day/kg body weight) or liver weight (bile flow mL/day/kg liver weight). Using the ROE and combining it with the 'correction factor', the clearances of biliary excreted drugs were predicted for humans. V for 15 drugs (without any correction factor) that are excreted in the bile was also predicted for humans.

Results: The results of the study indicated that the ROE in association with the correction factors developed for the biliary excreted drugs substantially improved the prediction of human clearance for drugs that are excreted in the bile. In this study, there was no indication (unlike clearance) that the prediction of volume of drug distribution was affected (systematically under- or over-prediction) because of biliary excretion.

Conclusions: The clearance of drugs that are excreted in the bile can be predicted with reasonable accuracy using ROE and a correction factor.

Background: Statins and coumarins are prescribed in combination on a regular basis. Some case reports suggested that statins might affect the dose requirements of coumarins. The aim of the study was to investigate whether acenocoumarol and phenprocoumon maintenance doses are influenced by statin use.

Methods: The Pre-EU-PACT database was used, which contains information on 471 acenocoumarol and 624 phenprocoumon users. The influence of individual statins on the acenocoumarol and phenprocoumon maintenance dose was investigated by comparing unadjusted and adjusted mean differences of the maintenance dose between statin and non-statin users.

Results: Lower adjusted acenocoumarol dose requirements were observed for patients using atorvastatin, simvastatin, pravastatin, and rosuvastatin. These patients had a reduction in adjusted mean acenocoumarol maintenance dose of 0.11, 0.29, 0.38, and 0.69 mg/day, respectively, compared with a mean adjusted dose of 2.60 mg/day for the patients not using a statin. There was no significant effect of statin use on unadjusted and adjusted phenprocoumon maintenance dose (p=0.23 and p=0.35, respectively).

Conclusions: Mean acenocoumarol maintenance dosages were decreased when acenocoumarol is co-administered with the different statins. Statin use does not affect phenprocoumon maintenance doses significantly.

Background: An increasing number of crystal structures for eukaryotic P450s have been published, which provided the chance to explore more structural features and construct some knowledge-based methods to facilitate modeling.

Methods: The crystal structures of 14 cytochrome P450s (CYP450) were selected to extract generic spatial anchors typical for three-dimensional (3D) structures of eukaryotic P450s. Multiple sequence alignment and structural superimposition were applied to recognize evolutionarily conserved regions.

Results: Regions containing uninterrupted helical components were identified as structurally conservative blocks (SCBs). The reliability and robustness of the SCBs were further evaluated by sequence entropy and structural deviation. Finally, these SCBs were applied and tested directly in constructing the homology model of the P450 1B1.

Conclusions: SCBs could potentially be applied as universal template to standardize the homology modeling procedure and help predict drug metabolism preferences for eukaryotic P450s.

Background: Methocarbamol is a skeletal muscle relaxant and is widely used to relieve pain in muscles. Many drugs may have interactions with each other when used at the same time. Yeast sucrase is taken as a drug by patients with congenital sucrase-isomaltase deficiency (CSID).

Methods: In this study, the interaction between methocarbamol and yeast sucrase was investigated.

Results: Our results showed that methocarbamol can inhibit sucrase activity and reduce the maximum reaction velocity (Vmax) of the enzyme by a non-competitive pattern. Measurement of IC50 and Ki of the drug revealed that methocarbamol did not bind the enzyme with high affinity. Fluorescence measurement showed that the drug binds to free enzyme and enzyme-substrate complexes that were accompanied by structural changes on the enzyme. Guaifenesin, which has a similar structure to methocarbamol, does not affect the activity of sucrase.

Conclusions: Methocarbamol inhibits sucrase activity and its carbamate group plays a main role in the binding of drug to sucrase.

CYP2E1 activates several hepatotoxins and contributes to alcoholic liver damage. In this report, we review our studies on whether induction of CYP2E1 can potentiate liver injury in obesity. Acetone- or pyrazole-induced severe liver injury in obese mice as compared to obese controls and lean mice. Severe liver injury was associated with elevated oxidative and nitrosative stress and could be blunted by inhibitors of CYP2E1 and inducible nitric oxide synthase (iNOS). S-Adenosyl-L-methionine (SAM) lowered the elevated oxidative and nitrosative stress, steatosis, liver injury and mitochondrial dysfunction in the pyrazole-treated obese mice. The protection by SAM may have therapeutic applications against metabolic complications caused by obesity. The role of CYP2E1 in chronic ethanol-induced liver injury was studied using wild-type (WT) mice, CYP2E1 knockout (KO) mice and humanized CYP2E1 knockin (KI) mice. Ethanol produced fatty liver and oxidant stress in WT mice; these effects were blunted in the CYP2E1 KO mice but restored in the CYP2E1 KI mice. Significant liver injury was produced in the ethanol-fed KI mice in association with elevated oxidant stress and levels of human CYP2E1. Collectively, these studies show that CYP2E1 contributes to ethanol-induced and obesity-induced oxidant stress and liver injury.