Metformin Transport Rates Between Plasma and Red Blood Cells in Humans - PubMed
Metformin Transport Rates Between Plasma and Red Blood Cells in Humans
Janis Kurlovics et al. Clin Pharmacokinet. 2022 Jan.
Abstract
Background: Metformin has been used for the treatment of type 2 diabetes for over 60 years; however, its mechanism of pharmacological action is not fully clear. Different hypotheses exist regarding metformin distribution and redistribution mechanisms between plasma and erythrocytes/red blood cells (RBCs).
Objective: We aimed to test the hypothesis that the metformin distribution between plasma and RBC occurs via concentration difference-driven passive transport and estimated transport rate coefficient values based on metformin concentration time series in plasma and RBCs from in vivo studies.
Methods: An ordinary differential equation (ODE) system with two compartments was used to describe diffusion-based passive transport between plasma and RBCs. Metformin concentration time series in plasma and RBCs of 35 individuals were used for metformin transport parametrization. Plasma concentration has been approximated by biexponential decline.
Results: A single passive transport coefficient, k = 0.044 ± 0.014 (h-1), can be applied, describing the uptake and release transport rate versus the linear equation v = k × (Mpl - MRBC), where Mpl is the metformin concentration in plasma and MRBC is the metformin concentration in RBCs.
Conclusions: Our research suggests that passive transport can explain metformin distribution dynamics between plasma and RBCs because transport speed is proportional to the metformin concentration difference and independent of the transport direction. Concentration difference-driven passive transport can explain the mechanism of faster metformin distribution to RBCs the first few hours after administration, and faster release and domination of the redistribution transport rate after metformin concentration in plasma becomes smaller than in RBCs.
© 2021. The Author(s).
Conflict of interest statement
Janis Kurlovics, Darta Maija Zake, Linda Zaharenko, Kristaps Berzins, Janis Klovins, and Egils Stalidzans have no conflicts of interest that are directly relevant to the contents of this article.
Figures

Two-compartment model of metformin transport between plasma and RBCs with absorption (vin) and release (vout) fluxes. kin transport rate coefficient to RBCs from plasma (h−1), kout transport rate coefficient from RBCs to plasma (h−1), Mpl metformin concentration in plasma (ng/mL), MRBC metformin concentration in RBCs (ng/mL), RBC red blood cells

Parameter estimation results of the average curve. Dots show experimental values while lines represent the model simulation. a Single k-value (kave = 0.044 h–1, mean square error = 286); and b independent kin and kout values (kin/ave = 0.044 and kout/ave = 0.039 h–1, mean square error = 273). RBCs red blood cells

Diffusion coefficient k, kin and kout values per individual (average values are represented by lines). The average values of k and kin were identical.

Tmax and Cmax of individual plasma curves. Tmax time to reach maximum concentration, Cmax maximum concentration

Parameter estimation results of the best-fit, individual 16. The dots show the experimental values, while the lines represent the model simulation. a Single k-value (k = 0.040, mean square error = 67); b different kin and kout values (kin = 0.040 and kout = 0.038, mean square error = 65)

Parameter estimation results of the worst-fit, individual 31. The dots show the experimental values, while the lines represent model simulation. a Single k-value (k = 0.058 h–1, mean square error = 9244); b different kin and kout values (kin = 0.055 h–1 and kout = 0.031 h–1, mean square error = 6271).

Dynamics of concentrations in a plasma and RBCs, and b influx (blue), outflux (red), and summary flux (green) to RBCs in the case of the average curve with a single coefficient. RBCs red blood cells
Similar articles
-
Exercise-induced stimulation of K(+) transport in human erythrocytes.
Lindinger MI, Horn PL, Grudzien SP. Lindinger MI, et al. J Appl Physiol (1985). 1999 Dec;87(6):2157-67. doi: 10.1152/jappl.1999.87.6.2157. J Appl Physiol (1985). 1999. PMID: 10601163
-
Sustained release of metformin via red blood cell accumulated sulfenamide prodrug.
Peura L, Huttunen KM. Peura L, et al. J Pharm Sci. 2014 Jul;103(7):2207-2210. doi: 10.1002/jps.24040. Epub 2014 Jun 2. J Pharm Sci. 2014. PMID: 24891115
-
A mathematical model for lactate transport to red blood cells.
Wahl P, Yue Z, Zinner C, Bloch W, Mester J. Wahl P, et al. J Physiol Sci. 2011 Mar;61(2):93-102. doi: 10.1007/s12576-010-0125-8. Epub 2010 Dec 22. J Physiol Sci. 2011. PMID: 21181323 Free PMC article.
-
Whole blood or plasma: what is the ideal matrix for pharmacokinetic-driven drug candidate selection?
Dash RP, Veeravalli V, Thomas JA, Rosenfeld C, Mehta N, Srinivas NR. Dash RP, et al. Future Med Chem. 2021 Jan;13(2):157-171. doi: 10.4155/fmc-2020-0187. Epub 2020 Dec 4. Future Med Chem. 2021. PMID: 33275044 Review.
-
Jensen FB. Jensen FB. Acta Physiol Scand. 2004 Nov;182(3):215-27. doi: 10.1111/j.1365-201X.2004.01361.x. Acta Physiol Scand. 2004. PMID: 15491402 Review.
Cited by
-
Curating models from BioModels: Developing a workflow for creating OMEX files.
Xu J, Smith L. Xu J, et al. bioRxiv [Preprint]. 2024 Nov 6:2024.03.15.585236. doi: 10.1101/2024.03.15.585236. bioRxiv. 2024. PMID: 38559029 Free PMC article. Updated. Preprint.
-
The development and benefits of metformin in various diseases.
Dong Y, Qi Y, Jiang H, Mi T, Zhang Y, Peng C, Li W, Zhang Y, Zhou Y, Zang Y, Li J. Dong Y, et al. Front Med. 2023 Jun;17(3):388-431. doi: 10.1007/s11684-023-0998-6. Epub 2023 Jul 4. Front Med. 2023. PMID: 37402952 Review.
-
Espnes KA, Hønnås A, Løvvik TS, Gundersen POM, Naavik A, Skogvoll E, Westin AA, Spigset O, Vanky E. Espnes KA, et al. Basic Clin Pharmacol Toxicol. 2022 Mar;130(3):415-422. doi: 10.1111/bcpt.13703. Epub 2022 Jan 18. Basic Clin Pharmacol Toxicol. 2022. PMID: 34964262 Free PMC article.
References
-
- Martin D, Az Eddine T, Mohammed A, Attari Ahmed E, Youssef K, Farida A. Determination of concentration intra-erythrocyte of metformin in type 2 diabetic patients with or without renal impairment: comparative study of concentrations intra-erythrocytes between two groups of diabetic patients. IOSR J Pharm. 2015;5:50–6.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical