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Plasma metformin concentrations (geometric mean ± CV%)
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Purpose:
Concomitant treatment with the glucose-lowering drug metformin and the platelet aggregation inhibitor dipyridamole often occurs in patients with type 2 diabetes mellitus who have suffered a cerebrovascular event. The gastrointestinal uptake of metformin is mediated by the human equilibrative nucleoside transporter 4 (ENT4), which is inhib...
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Background:
Disorder of locomotor function is universal in patients with spinal cord injury (SCI) and has a severe impairment on their quality of life. Metformin, the first-line antidiabetic drug, has been used to improve locomotor function in SCI rats through antioxidative mechanisms recently.
Methods:
A search strategy was conducted from datab...
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Citations
... Based on the results of sitagliptin dispensatory Januvia ® , the within-subject coefficient of variations (CV) for the area under the plasma-concentration time curve AUC was 5.8%, and the CV for maximum plasma concentration (C max ) was not reported (Januvia, 2006). The CV for the PK parameters (C max , AUC) was assumed to be 20% for metformin immediate release (IR) based on previous studies (Park et al., 2015;El Messaoudi et al., 2016), and the CV was reported equivalent between extended released (XR) and IR metformin (Timmins et al., 2005). To achieve a statistical power of 80% that a two-sided 90% confidence interval (CI) for the ratio of PK parameters (C max , AUC) between two treatments would be contained within the 0.80-1.25 limit, the study required Study design. ...
Background and Objectives: Janumet® XR is the combination of sitagliptin and extended metformin hydrochloride produced by Merck Sharp & Dohme. It is specially designed for diabetes mellitus patients taking both drugs already. Janumet® XR exhibited clinically significant blood glucose lowering efficacy and long-term use safety. However, no generic form of Janumet® XR has been approved in western countries. The relatively high cost made the medication less prescribed. A more affordable form of this drug may benefit an immense diabetes mellitus population. The current study compared the bioequivalence (BE) of sitagliptin 100 mg and metformin 1000 mg produced by Nanjing Chia-Tai Tianqing Pharmaceutical Company to Janumet® XR in healthy Chinese subjects. Methods: Twenty-eight healthy Chinese subjects were enrolled in Study 1 and 2, respectively. Both studies were conducted with an open, randomized, two-period crossover design using the test (T) or the reference (R) drug. Study 1 is conducted under the fasting state, and Study 2 is under the fed state. Subjects received an oral dose of sitagliptin 100 mg and metformin 1000 mg, and plasma concentrations of sitagliptin and metformin were determined up to 72 h post-dose. Pharmacokinetic (PK) parameters, including maximum serum concentration (Cmax) and area under the concentration-time curve up to the last quantifiable concentration (AUC0-t) of both sitagliptin and metformin, were calculated and compared between the T and R treatments. Results: In the fasting study, the geometric mean ratios of Cmax, AUC0-t, and AUC0-∞ for sitagliptin were 109.42%, 101.93%, and 101.95%, respectively; the corresponding ratios for metformin were 98.69%, 94.12%, and 93.42%, respectively. In the fed study, the geometric mean ratios of Cmax, AUC0-t, and AUC0-∞ for sitagliptin were 98.41%, 100.30%, and 100.24%, respectively; the corresponding ratios for metformin were 97.79%, 99.28%, and 100.69%, respectively. The 90% CIs of Cmax, AUC0-t, and AUC0-∞ in both studies were all within acceptance limits (80.00%-125.00%). Conclusion: The results demonstrated for the first time that sitagliptin 100 mg and metformin 1000 mg produced by Nanjing Chia-Tai Tianqing Pharmaceutical Company was bioequivalent to the branded Janumet® XR, and both drugs were well tolerated.
... Yet, at the time of writing of this article, no placebo-controlled trial that aims to address the use of metformin and dipyridamole in SLE has been published. In the non-lupus population, metformin and dipyridamole are often used in combination, particularly in patients with a history of type II diabetes and cerebrovascular diseases, for secondary and tertiary prevention against vascular events [98]. As patients with SLE have increased cardiovascular risk and incidence of vascular accidents compared to demographically-matched healthy subjects [99], the use of metformin and an antiplatelet agent (e.g., dipyridamole) in combination should be considered in diabetic SLE patients who are indicated for secondary cardiovascular protection. ...
Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune condition that can potentially affect every single organ during the course of the disease, leading to increased morbidity and mortality, and reduced health-related quality of life. While curative treatment is currently non-existent for SLE, therapeutic agents such as glucocorticoids, mycophenolate, azathioprine, cyclosporine, cyclophosphamide and various biologics are the mainstay of treatment based on their immunomodulatory and immunosuppressive properties. As a result of global immunosuppression, the side-effect profile of the current therapeutic approach is unfavourable, with adverse effects including myelosuppression, infection and malignancies. Hydroxychloroquine, one of the very few Food and Drug Administration (FDA)-approved medications for the treatment of SLE, has been shown to offer a number of therapeutic benefits to SLE patients independent of its immunomodulatory effect. As such, it is worth exploring drugs similar to hydroxychloroquine that confer additional clinical benefits unrelated to immunosuppressive mechanisms. Indeed, apart from hydroxychloroquine, a number of studies have explored the use of a few conventionally non-immunosuppressive drugs that are potentially useful in the management of SLE. In this review, non-immunosuppressive therapeutic agents, namely metformin, dipyridamole, N-acetylcysteine and statins, will be critically discussed with regard to their mechanisms of action and efficacy pertaining to their potential therapeutic role in SLE.
... The concentration of metformin applied in our study is high compared with the micromolar concentrations of metformin (Hussey et al., 2013;Kajbaf and Lalau, 2013;Lalau et al., 2011;DeFronzo et al., 2016;El Messaoudi et al., 2016) found in plasma from metformintreated patients. However, after long-term treatment at least of mice, the tissue metformin concentration has been reported to reach up to 4 mM (Wilcock and Bailey, 1994). ...
Metformin is an antidiabetic drug that is used daily by millions of patients worldwide. Metformin is able to cross the blood-brain barrier and has recently been shown to increase glucose consumption and lactate release in cultured astrocytes. However, potential effects of metformin on mitochondrial tricarboxylic acid (TCA) cycle metabolism in astrocytes are unknown. We investigated this by mapping 13C labeling in TCA cycle intermediates and corresponding amino acids after incubation of primary rat astrocytes with [U-13C]glucose. The presence of metformin did not compromise the viability of cultured astrocytes during 4 hr of incubation, but almost doubled cellular glucose consumption and lactate release. Compared with control cells, the presence of metformin dramatically lowered the molecular 13C carbon labeling (MCL) of the cellular TCA cycle intermediates citrate, α-ketoglutarate, succinate, fumarate, and malate, as well as the MCL of the TCA cycle intermediate-derived amino acids glutamate, glutamine, and aspartate. In addition to the total molecular 13C labeling, analysis of the individual isotopomers of TCA cycle intermediates confirmed a severe decline in labeling and a significant lowering in TCA cycling ratio in metformin-treated astrocytes. Finally, the oxygen consumption of mitochondria isolated from metformin-treated astrocytes was drastically reduced in the presence of complex I substrates, but not of complex II substrates. These data demonstrate that exposure to metformin strongly impairs complex I–mediated mitochondrial respiration in astrocytes, which is likely to cause the observed decrease in labeling of mitochondrial TCA cycle intermediates and the stimulation of glycolytic lactate production.
... Considering the extended clinical use of metformin (Loos et al., 2017;Li et al., 2016;Castillo-Quan & Blackwell, 2016), the risks of unwanted drug-drug interactions and drug adverse reactions associated with metformin-based polypharmacy treatment for patients should be thoroughly evaluated. However, previous studies predominantly focus on how other drugs may affect the pharmacokinetics of metformin as a victim (Zack et al., 2015;El Messaoudi et al., 2016), with limited data available regarding the influence of metformin as a perpetrator on the metabolism and clearance of other co-administered drugs. ...
Type 2 diabetes mellitus (T2D) is a complex metabolic disorder requiring polypharmacy treatment in clinic, with metformin being widely used antihyperglycemic drug. However, the mechanisms of metformin as a perpetrator inducing potential drug-drug interactions and adverse drug reactions are scarcely known to date. Carboxylesterases (CESs) are major hydrolytic enzymes highly expressed in the liver, including mouse carboxylesterase 1d (Ces1d) and Ces1e. In the present study, experiments are designed to investigate the effects and mechanisms of metformin on Ces1d and Ces1e in vivo and in vitro. In results, metformin suppresses the expression and activity of Ces1d and Ces1e in a dose- and time-dependent manner. The decreased expression of nuclear receptor PXR and its target gene P-gp indicates the involvements of PXR in the suppressed expression of carboxylesterases by metformin. Furthermore, metformin significantly suppresses the phosphorylation of AMPK and JNK, and the suppression of carboxylesterases induced by metformin is repeatedly abolished by AMPK inhibitor Compound C and JNK inhibitor SP600125. It implies that the activation of AMPK and JNK pathways mediates the suppression of carboxylesterases by metformin. The findings deserve further elucidation including clinical trials and have a potential to make contribution for the rational medication in the treatment of T2D patients.
Metformin is the primary drug for type 2 diabetes treatment and a promising candidate for other disease treatment. It has significant deviations between individuals in therapy efficiency and pharmacokinetics, leading to the administration of an unnecessary overdose or an insufficient dose. There is a lack of data regarding the concentration-time profiles in various human tissues that limits the understanding of pharmacokinetics and hinders the development of precision therapies for individual patients. The physiologically based pharmacokinetic (PBPK) model developed in this study is based on humans’ known physiological parameters (blood flow, tissue volume, and others). The missing tissue-specific pharmacokinetics parameters are estimated by developing a PBPK model of metformin in mice where the concentration time series in various tissues have been measured. Some parameters are adapted from human intestine cell culture experiments. The resulting PBPK model for metformin in humans includes 21 tissues and body fluids compartments and can simulate metformin concentration in the stomach, small intestine, liver, kidney, heart, skeletal muscle adipose, and brain depending on the body weight, dose, and administration regimen. Simulations for humans with a bodyweight of 70kg have been analyzed for doses in the range of 500-1500mg. Most tissues have a half-life (T 1/2 ) similar to plasma (3.7h) except for the liver and intestine with shorter T 1/2 and muscle, kidney, and red blood cells that have longer T 1/2 . The highest maximal concentrations (C max ) turned out to be in the intestine (absorption process) and kidney (excretion process), followed by the liver. The developed metformin PBPK model for mice does not have a compartment for red blood cells and consists of 20 compartments. The developed human model can be personalized by adapting measurable values (tissue volumes, blood flow) and measuring metformin concentration time-course in blood and urine after a single dose of metformin. The personalized model can be used as a decision support tool for precision therapy development for individuals.
Diabetes mellitus is one of the most prevalent metabolic diseases globally and it is increasing in prevalence. It is one of the most expensive diseases with respect to total health care costs per patient as a result of its chronic nature and its severe complications. To provide a more effective treatment of type 2 diabetes mellitus (T2DM), this study aims to compare different efficacies of six kinds of hypoglycemic drugs based on metformin, including glimepiride, pioglitazone, exenatide, glibenclamide, rosiglitazone, and vildagliptin, in T2DM by a network meta-analysis that were verified by randomized-controlled trials (RCTs). Eight eligible RCT in consistency with the aforementioned six hypoglycemic drugs for T2DM were included. The results of network meta-analysis demonstrated that the exenatide + metformin and vildagliptin + metformin regimens presented with better efficacy. Patients with T2DM with unsatisfactory blood glucose control based on diet control, proper exercise, and metformin treatment were included. The original regimen and dose of medication were unchanged, followed by the addition of glimepiride, pioglitazone, exenatide, glibenclamide, rosiglitazone, and vildagliptin. The results of RCTs showed that all these six kinds of drugs reduced the HbA1c level. Compared with other regimens, exenatide + metformin reduced fasting plasma glucose (FPG), fasting plasma insulin (FPI), total cholesterol (TC), and homeostasis model assessment insulin resistance index (HOMA-IR) levels, but increased the high-density lipoprotein (HDL) level; vildagliptin + metformin decreased FPI and low-density lipoprotein (LDL) levels; glibenclamide + metformin decreased the FPG level, but promoted HDL; and glimepiride + metformin decreased the TC level and rosiglitazone + metformin reduced the LDL level. Our findings indicated that exenatide + metformin and vildagliptin + metformin have better efficacy in T2DM since they can improve insulin sensitivity.
Background
The aim of this study was to explore the pharmacokinetic-pharmacodynamic (PK-PD) relationship of metformin on glucose levels after the administration of 250 mg and 1000 mg of metformin in healthy volunteers.
Methods
A total of 20 healthy male volunteers were randomized to receive two doses of either a low dose (375 mg followed by 250 mg) or a high dose (1000 mg followed by 1000 mg) of metformin at 12-h intervals. The pharmacodynamics of metformin was assessed using oral glucose tolerance tests before and after metformin administration. The PK parameters after the second dose were evaluated through noncompartmental analyses. Four single nucleotide polymorphisms in MATE1, MATE2-K, and OCT2 were genotyped, and their effects on PK characteristics were additionally evaluated.
Results
The plasma exposure of metformin increased as the metformin dose increased. The mean values for the area under the concentration-time curve from dosing to 12 hours post-dose (AUC0-12h) were 3160.4 and 8808.2 h·μg/L for the low- and high-dose groups, respectively. Non-linear relationships were found between the glucose-lowering effect and PK parameters with a significant inverse trend at high metformin exposure. The PK parameters were comparable among subjects with the genetic polymorphisms.
Conclusions
This study showed a non-linear PK-PD relationship on plasma glucose levels after the administration of metformin. The inverse relationship between systemic exposure and the glucose-lowering effect at a high exposure indicates a possible role for the intestines as an action site for metformin.
Trial registration
ClinicalTrials.gov NCT02712619
Pregnancy is associated with numerous physiologic changes that influence absorption, distribution, metabolism and excretion. Moreover, the magnitude of these effects changes as pregnancy matures. For most medications, there is limited information available about changes in drug disposition that can occur in pregnant patients, yet most women are prescribed one or more medications during pregnancy. In this investigation, PBPK modeling was used to assess the impact of pregnancy on the pharmacokinetic profiles of three medications (metformin, tacrolimus, oseltamivir) using the Simcyp® Simulator. The Simcyp pregnancy-PBPK model accounts for the known physiologic changes that occur during pregnancy. For each medication, plasma concentration-time profiles were simulated using Simcyp® virtual populations of healthy volunteers and pregnant patients. Predicted systemic exposure metrics (Cmax, AUC) were compared to published clinical data, and the fold error (FE, ratio of predicted and observed data) was calculated. The PBPK model was able to capture observed changes in Cmax and AUC across each trimester of pregnancy compared to post-partum for metformin (FE range 0.86 - 1.19), tacrolimus (FE range 1.03 - 1.64) and oseltamivir (FE range 0.54 - 1.02). Simcyp model outputs were used to correlate these findings with pregnancy-induced alterations in renal blood flow (metformin, oseltamivir), hepatic CYP3A4 activity (tacrolimus) and reduced plasma protein levels and hemodilution (tacrolimus). The results illustrate how PBPK modeling can help establish appropriate dosing guidelines for pregnant patients and to predict potential changes in systemic exposure during pregnancy for compounds undergoing clinical development.
