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PBPK model simulations of plasma and tissue concentration–time profiles of an oral administration of three-times daily 1000 mg metformin (highest recommended dose according to the German prescribing information [21]) at 07:00, 15:00 and 23:00 hours (indicated by arrows). (a–e) Comparison of metformin levels in (a) plasma, (b) kidney tissue, (c) liver tissue, (d) fat tissue and (e) muscle tissue. Respective simulations with a mean parameter set of OCT2 kcat, amplitude and acrophase are shown as dark lines, simulations with individual parameter sets (n=26) are shown as light lines. Grey areas indicate night-time. (f) Comparison of metformin peak-to-trough ratios for simulations in plasma and tissues. The three box plots per tissue give peak-to-trough ratios after metformin administration at 07:00, 15:00 and 23:00 hours. Dots (peak 1), triangles (peak 2) and squares (peak 3) show individual peak-to-trough ratios (n=26), crosses indicate mean values. Boxes represent the distance between first and third quartiles (IQR). Whiskers range from smallest to highest value (<1.5 × IQR)

PBPK model simulations of plasma and tissue concentration–time profiles of an oral administration of three-times daily 1000 mg metformin (highest recommended dose according to the German prescribing information [21]) at 07:00, 15:00 and 23:00 hours (indicated by arrows). (a–e) Comparison of metformin levels in (a) plasma, (b) kidney tissue, (c) liver tissue, (d) fat tissue and (e) muscle tissue. Respective simulations with a mean parameter set of OCT2 kcat, amplitude and acrophase are shown as dark lines, simulations with individual parameter sets (n=26) are shown as light lines. Grey areas indicate night-time. (f) Comparison of metformin peak-to-trough ratios for simulations in plasma and tissues. The three box plots per tissue give peak-to-trough ratios after metformin administration at 07:00, 15:00 and 23:00 hours. Dots (peak 1), triangles (peak 2) and squares (peak 3) show individual peak-to-trough ratios (n=26), crosses indicate mean values. Boxes represent the distance between first and third quartiles (IQR). Whiskers range from smallest to highest value (<1.5 × IQR)

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Aims/hypothesis The objective was to investigate if metformin pharmacokinetics is modulated by time-of-day in humans using empirical and mechanistic pharmacokinetic modelling techniques on a large clinical dataset. This study also aimed to generate and test hypotheses on the underlying mechanisms, including evidence for chronotype-dependent interin...

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... In terms of pharmacological treatment, even though the evidence is still lacking, chronotherapy that consists of optimized circadian rhythm and regulating the timing of drug medications has emerged in various conditions to achieve more treatment efficacy and fewer side effects [119,120]. For example, the experimental studies demonstrated the time-dependent effects of metformin on blood glucose and its interaction with the circadian rhythm [121]. Accordingly, future research is needed to investigate the impact of ALAN on diabetes medication strategies in patients with T2DM through clinical trials, considering that both are influenced by circadian rhythm. ...
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... Finally, renal elimination of drugs, via the regulation of blood flow, tubular secretions, and urinary pH, also contributes to rhythmic variations in the pharmacodynamics of drugs and may be more efficient during the active phase [70]. Chronotherapy has been applied toward the treatment of hypertension and hyperlipidemia [71], major depressive disorder and seasonal affective disorder [72,73], obesity and Type 2 diabetes [74,75], and several cancers [76,77]. Adjusting the timing of therapeutic delivery to match the specific drug target allows for enhanced outcomes and often reduced off-target effects and detrimental side effects. ...
... Chronotherapy has been applied toward the treatment of hypertension and hyperlipidemia [71], major depressive disorder and seasonal affective disorder [72,73], obesity and Type 2 diabetes [74,75], and several cancers [76,77]. Adjusting the timing of therapeutic delivery to match the specific drug target allows for enhanced outcomes and often reduced off-target effects and detrimental side effects. ...
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... The present protocol substantiates that metformin's toxicity [44] via interactions with the GM potentiated its effect to toxic level. Though, it is well established that Metformin is not metabolized by liver enzymes, but multidrug and toxin extrusion protein 1 (MATE1) expressed in hepatocytes participates in elimination of unchanged drug with the bile or its transport with blood to kidney and is excreted urine [45,46]. Nevertheless, Gut microbes can directly metabolize the drug [47], expressing more than 100-fold genes than the human genomes [48], including many enzymes capable to metabolize the drug [49,50], and consequences of microbiome mediated drug transformation are often distinct from those of liver-enzyme mediated [51]. ...
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... Histological examination employing both H&E staining and Masson's trichrome staining further confirmed a substantial reduction in glandular fibrosis by day 12 in the metformin-treated group (p < 0.01), along with mitigation of acinar atrophy ( Figure 5C,D,F). Additionally, given that metformin is primarily metabolized by the kidneys [25], we conducted H&E staining of kidney tissues from each experimental group and found no discernible pathological alterations, indicating that the drug's toxicity at the administered concentration is within the acceptable limits ( Figure 5E). Lastly, IHC analysis indicated that α-SMA (p < 0.05) and TGF-β1 (p < 0.05) expression levels were markedly decreased in the metformin-treated group, corroborating the in vitro findings ( Figure 6A-J). ...
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