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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\u2019 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<jats:sub>1\/2<\/jats:sub>) similar to plasma (3.7h) except for the liver and intestine with shorter T<jats:sub>1\/2<\/jats:sub> and muscle, kidney, and red blood cells that have longer T<jats:sub>1\/2<\/jats:sub>. The highest maximal concentrations (C<jats:sub>max<\/jats:sub>) 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.<\/jats:p>","DOI":"10.1371\/journal.pone.0249594","type":"journal-article","created":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T18:47:07Z","timestamp":1617821227000},"page":"e0249594","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":48,"title":["Physiologically based metformin pharmacokinetics model of mice and scale-up to humans for the estimation of concentrations in various tissues"],"prefix":"10.1371","volume":"16","author":[{"given":"Darta Maija","family":"Zake","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janis","family":"Kurlovics","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linda","family":"Zaharenko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vitalijs","family":"Komasilovs","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janis","family":"Klovins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6063-0184","authenticated-orcid":true,"given":"Egils","family":"Stalidzans","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2021,4,7]]},"reference":[{"key":"pone.0249594.ref001","doi-asserted-by":"crossref","first-page":"49","DOI":"10.3109\/00498259409043220","article-title":"Accumulation of metformin by tissues of the normal and diabetic mouse","volume":"24","author":"C Wilcock","year":"1994","journal-title":"Xenobiotica"},{"key":"pone.0249594.ref002","doi-asserted-by":"crossref","first-page":"1963","DOI":"10.2337\/dc06-9912","article-title":"Management of hyperglycemia in type 2 diabetes: A consensus algorithm for the initiation and adjustment of therapy. 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