Compound file updated to V11 and evaluation plan

Evaluation/Input/Content/Concentration_time_profiles.md

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+Simulated versus observed concentration-time profiles of all data listed in [Section 2.2.2](#clinical-data) are presented below.

Evaluation/Input/Content/Concentration_time_profiles_building.md

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+
+
+
+

Evaluation/Input/Content/Concentration_time_profiles_verification.md

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+

Evaluation/Input/Content/GOF_diagnostics.md

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+Below you find the goodness-of-fit visual diagnostic plots for the PBPK model performance of all data used presented in [Section 2.2.2](#clinical-data).
+
+The first plot shows observed versus simulated plasma concentration, the second weighted residuals versus time. 
+

Evaluation/Input/Content/Input_table.md

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+The compound parameter values of the final PBPK model are illustrated below.
+
+
+

Evaluation/Input/Content/References.md

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+
+
+**Block  2008** Block LC, Schemling LO, Couto AG, et al (2008) Pharmaceutical equivalence of metformin tablets with various binders. Revista de Ciências Farmacêuticas Básica e Aplicada 29(1):29–35
+
+**Boehringer Ingelheim 2018** Boehringer Ingelheim Pharma GmbH & Co KG (2018) The effect of potent inhibitors of drug transporters (verapamil, rifampin, cimetidine, probenecid) on pharmacokinetics of a transporter probe drug cocktail consisting of digoxin, furosemide, metformin and rosuvastatin. BI Trial No. 0352-2100. EudraCT 2017-001549-29
+
+**Caillé 1993** Caillé G, Lacasse Y, Raymond M, et al (1993) Bioavailability of metformin in tablet form using a new high pressure liquid chromatography assay method. Biopharm Drug Dispos 14:257–263. https://doi.org/10.1002/bdd.2510140308
+
+**Chen 2009** Chen Y, Li S, Brown C, et al (2009) Effect of genetic variation in the organic cation transporter 2 on the renal elimination of metformin. Pharmacogenet Genomics 19:497–504. https://doi.org/10.1097/fpc.0b013e32832cc7e9
+
+**Cho 2011** Cho SK, Yoon JS, Lee MG, et al (2011) Rifampin enhances the glucose-lowering effect of metformin and increases OCT1 mRNA levels in healthy participants. Clin Pharmacol Ther 89:416–421. https://doi.org/10.1038/clpt.2010.266
+
+**Cho 2014** Cho SK, Kim CO, Park ES, Chung J-Y (2014) Verapamil decreases the glucose-lowering effect of metformin in healthy volunteers. Br J Clin Pharmacol 78:1426–1432. https://doi.org/10.1111/bcp.12476
+
+**Desai 2014** Desai D, Wong B, Huang Y, et al (2014) Surfactant-Mediated Dissolution of Metformin Hydrochloride Tablets: Wetting Effects Versus Ion Pairs Diffusivity. Journal of Pharmaceutical Sciences 103:920–926. https://doi.org/10.1002/jps.23852
+
+**Di Cicco 2000** Di Cicco RA, Allen A, Carr A, et al (2000) Rosiglitazone Does Not Alter the Pharmacokinetics of Metformin. The Journal of Clinical Pharmacology 40:1280–1285. https://doi.org/10.1177/009127000004001113
+
+**Ding 2014** Ding Y, Jia Y, Song Y, et al (2014) The effect of lansoprazole, an OCT inhibitor, on metformin pharmacokinetics in healthy subjects. Eur J Clin Pharmacol 70:141–146. https://doi.org/10.1007/s00228-013-1604-7
+
+**FDA 2017** US Food and Drug Administration (2017) Drug development and drug interactions: Table
+of substrates, inhibitors and inducers. https://www.fda.gov/drugs/drug-interactions/labeling/drug-development-and-drug-interactions-table-substrates-inhibitors-and-inducers
+
+**Gan 2016** Gan L, Jiang X, Mendonza A, et al (2016) Pharmacokinetic drug-drug interaction assessment of LCZ696 (an angiotensin receptor neprilysin inhibitor) with omeprazole, metformin or levonorgestrel-ethinyl estradiol in healthy subjects. Clin Pharmacol Drug Dev 5:27–39. https://doi.org/10.1002/cpdd.181
+
+**Gormsen 2016** Gormsen LC, Sundelin EI, Jensen JB, et al (2016) In Vivo Imaging of Human 11C-Metformin in Peripheral Organs: Dosimetry, Biodistribution, and Kinetic Analyses. J Nucl Med 57:1920–1926. https://doi.org/10.2967/jnumed.116.177774
+
+**Graham 2011** Graham GG, Punt J, Arora M, et al (2011) Clinical pharmacokinetics of metformin. Clin Pharmacokinet 50:81–98. https://doi.org/10.2165/11534750-000000000-00000
+
+**Gusler 2001** Gusler G, Gorsline J, Levy G, et al (2001) Pharmacokinetics of metformin gastric-retentive tablets in healthy volunteers. J Clin Pharmacol 41:655–661. https://doi.org/10.1177/00912700122010546
+
+**Hanke 2020** Hanke N, Türk D, Selzer D, et al (2020) A Comprehensive Whole-Body Physiologically Based Pharmacokinetic Drug-Drug-Gene Interaction Model of Metformin and Cimetidine in Healthy Adults and Renally Impaired Individuals. Clin Pharmacokinet. 59:1419-1431. doi: 10.1007/s40262-020-00896-w. 
+
+**Hibma 2016** Hibma JE, Zur AA, Castro RA, et al (2016) The Effect of Famotidine, a MATE1-Selective Inhibitor, on the Pharmacokinetics and Pharmacodynamics of Metformin. Clin Pharmacokinet 55:711–721. https://doi.org/10.1007/s40262-015-0346-3
+
+**Jang 2016** Jang K, Chung H, Yoon J-S, et al (2016) Pharmacokinetics, Safety, and Tolerability of Metformin in Healthy Elderly Subjects. J Clin Pharmacol 56:1104–1110. https://doi.org/10.1002/jcph.699
+
+**Johansson 2014** Johansson S, Read J, Oliver S, et al (2014) Pharmacokinetic evaluations of the co-administrations of vandetanib and metformin, digoxin, midazolam, omeprazole or ranitidine. Clin Pharmacokinet 53:837–847. https://doi.org/10.1007/s40262-014-0161-2
+
+**Kim 2014** Kim A, Chung I, Yoon SH, et al (2014) Effects of proton pump inhibitors on metformin pharmacokinetics and pharmacodynamics. Drug Metab Dispos 42:1174–1179. https://doi.org/10.1124/dmd.113.055616
+
+**Kolesnikov 2015**Kolesnikov N, Hastings E, Keays M, et al (2015) ArrayExpress update—simplifying data submissions. Nucleic Acids Research 43:D1113–D1116. https://doi.org/10.1093/nar/gku1057
+
+**Manitpisitkul 2014** Manitpisitkul P, Curtin CR, Shalayda K, et al (2014) Pharmacokinetic interactions between topiramate and pioglitazone and metformin. Epilepsy Res 108:1519–1532. https://doi.org/10.1016/j.eplepsyres.2014.08.013
+
+**Masuda 2006** Masuda S, Terada T, Yonezawa A, et al (2006) Identification and functional characterization of a new human kidney-specific H+/organic cation antiporter, kidney-specific multidrug and toxin extrusion 2. J Am Soc Nephrol 17:2127–2135. https://doi.org/10.1681/asn.2006030205
+
+**Meyer 2012** Meyer M, Schneckener S, Ludewig B, et al (2012) Using expression data for quantification of active processes in physiologically based pharmacokinetic modeling. Drug Metab Dispos 40:892–901. https://doi.org/10.1124/dmd.111.043174
+
+**Morrissey 2016** Morrissey KM, Stocker SL, Chen EC, et al (2016) The Effect of Nizatidine, a MATE2K Selective Inhibitor, on the Pharmacokinetics and Pharmacodynamics of Metformin in Healthy Volunteers. Clin Pharmacokinet 55:495–506. https://doi.org/10.1007/s40262-015-0332-9
+
+**NCHS 1997** National Center for Health Statistics (NCHS) (1997) Third National Health and Nutrition Examination
+Survey (NHANES III). Tech. rep., Hyattsville, MD 20782
+
+**Najib 2002** Najib N, Idkaidek N, Beshtawi M, et al (2002) Bioequivalence evaluation of two brands of metformin 500 mg tablets (Dialon & Glucophage)--in healthy human volunteers. Biopharm Drug Dispos 23:301–306. https://doi.org/10.1002/bdd.326
+
+**NCBI 2019** National Center for Biotechnology Information (NCBI) (2019) Expressed Sequence Tags (EST) from UniGene
+
+**Nishimura 2005** Nishimura M, Naito S (2005) Tissue-specific mRNA Expression Profiles of Human ATP-binding Cassette and Solute Carrier Transporter Superfamilies. Drug Metabolism and Pharmacokinetics 20:452–477. https://doi.org/10.2133/dmpk.20.452
+
+**Nishimura 2006** Nishimura M, Naito S (2006) Tissue-specific mRNA expression profiles of human phase I metabolizing enzymes except for cytochrome P450 and phase II metabolizing enzymes. Drug Metab Pharmacokinet 21:357–374. https://doi.org/10.2133/dmpk.21.357
+
+**Oh 2016** Oh J, Chung H, Park S-I, et al (2016) Inhibition of the multidrug and toxin extrusion (MATE) transporter by pyrimethamine increases the plasma concentration of metformin but does not increase antihyperglycaemic activity in humans. Diabetes Obes Metab 18:104–108. https://doi.org/10.1111/dom.12577
+
+**Otsuka 2005** Otsuka M, Matsumoto T, Morimoto R, et al (2005) A human transporter protein that mediates the final excretion step for toxic organic cations. Proc Natl Acad Sci U S A 102:17923–17928. https://doi.org/10.1073/pnas.0506483102
+
+**Pentikäinen 1979** Pentikäinen PJ, Neuvonen PJ, Penttilä A (1979a) Pharmacokinetics of metformin after intravenous and oral administration to man. Eur J Clin Pharmacol 16:195–202. https://doi.org/10.1007/BF00562061
+
+**PK-Sim Ontogeny Database Version 7.3** PK-Sim Ontogeny Database Version 7.3 (https://github.com/Open-Systems-Pharmacology/OSPSuite.Documentation/blob/38cf71b384cfc25cfa0ce4d2f3addfd32757e13b/PK-Sim%20Ontogeny%20Database%20Version%207.3.pdf)
+
+**Robert 2003** Robert F, Fendri S, Hary L, et al (2003) Kinetics of plasma and erythrocyte metformin after acute administration in healthy subjects. Diabetes Metab 29:279–283. https://doi.org/10.1016/s1262-3636(07)70037-x
+
+**Sambol 1996** Sambol NC, Brookes LG, Chiang J, et al (1996) Food intake and dosage level, but not tablet vs solution dosage form, affect the absorption of metformin HC1 in man. British Journal of Clinical Pharmacology 42:510–512. https://doi.org/10.1111/j.1365-2125.1996.tb00017.x
+
+**Sambol 1995** Sambol NC, Chiang J, Lin ET, et al (1995) Kidney function and age are both predictors of pharmacokinetics of metformin. J Clin Pharmacol 35:1094–1102. https://doi.org/10.1002/j.1552-4604.1995.tb04033.x
+
+**Sirtori 1978** Sirtori CR, Franceschini G, Galli-Kienle M, et al (1978a) Disposition of metformin (N,N-dimethylbiguanide) in man. Clinical Pharmacology & Therapeutics 24:683–693. https://doi.org/10.1002/cpt1978246683
+
+**Somogyi 1987** Somogyi A, Stockley C, Keal J, et al (1987) Reduction of metformin renal tubular secretion by cimetidine in man. British Journal of Clinical Pharmacology 23:545–551. https://doi.org/10.1111/j.1365-2125.1987.tb03090.x
+
+**Stopfer 2016** Stopfer P, Giessmann T, Hohl K, et al (2016) Pharmacokinetic Evaluation of a Drug Transporter Cocktail Consisting of Digoxin, Furosemide, Metformin, and Rosuvastatin. Clin Pharmacol Ther 100:259–267. https://doi.org/10.1002/cpt.406
+
+**Stopfer 2018** Stopfer P, Giessmann T, Hohl K, et al (2018) Effects of Metformin and Furosemide on Rosuvastatin Pharmacokinetics in Healthy Volunteers: Implications for Their Use as Probe Drugs in a Transporter Cocktail. Eur J Drug Metab Pharmacokinet 43:69–80. https://doi.org/10.1007/s13318-017-0427-9
+
+**Tucker 1981** Tucker GT, Casey C, Phillips PJ, et al (1981a) Metformin kinetics in healthy subjects and in patients with diabetes mellitus. Br J Clin Pharmacol 12:235–246. https://doi.org/10.1111/j.1365-2125.1981.tb01206.x
+
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+reference values: ICRP Publication 89. Annals of the ICRP 32:1–277
+
+**Vidon 1988** Vidon N, Chaussade S, Noel M, Franchisseur C, Huchet B, Bernier JJ (1988) Metformin in the
+digestive tract. Diabetes Research and Clinical Practice 4:223–229
+
+**Wang 2008** Wang Z-J, Yin OQP, Tomlinson B, Chow MSS (2008) OCT2 polymorphisms and in-vivo renal functional consequence: studies with metformin and cimetidine. Pharmacogenet Genomics 18:637–645. https://doi.org/10.1097/FPC.0b013e328302cd41
+
+**Willmann 2007** Willmann S, Hohn K, Edginton A, et al (2007) Development of a physiology-based whole-body population model for assessing the influence of individual variability on the pharmacokinetics of drugs. Journal of pharmacokinetics and pharmacodynamics 34:401–31. https://doi.org/10.1007/s10928-007-9053-5
+
+**Wishart 2006** Wishart DS, Knox C, Guo AC, et al (2006) DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res 34:D668-672. https://doi.org/10.1093/nar/gkj067
+
+**Yin 2016** Yin J, Duan H, Wang J (2016) Impact of Substrate-Dependent Inhibition on Renal Organic Cation Transporters hOCT2 and hMATE1/2-K-Mediated Drug Transport and Intracellular Accumulation. J Pharmacol Exp Ther 359:401–410. https://doi.org/10.1124/jpet.116.236158
+
+**Zhou 2007** Zhou M, Xia L, Wang J (2007) Metformin Transport by a Newly Cloned Proton-Stimulated Organic Cation Transporter (Plasma Membrane Monoamine Transporter) Expressed in Human Intestine. Drug Metab Dispos 35:1956–1962 https://doi: 10.1124/dmd.107.015495.
+
+**Zhou 2009** Zhou SF, Zhou ZW, Yang LP, Cai JP (2009) Substrates, inducers, inhibitors and structure-activity relationships of human cytochrome P450 2C9 and implications in drug development. Current Medicinal Chemistry 16:3480–3675. https://doi.org/10.2174/092986709789057635

Evaluation/Input/Content/Section1_Introduction.md

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+The presented model building and evaluation report evaluates the performance of a PBPK model for metformin in healthy adults.
+
+The herein presented model was developed and published by Hanke et al. ([Hanke 2020](#5-references)) and adjusted later on to PK-Sim V11 by re-optimizing OCT2.
+
+Metformin is widely used as first-line treatment of type 2 diabetes. It is a highly hydrophilic compound, positively
+charged at physiological pH and depends on active transport for its absorption, distribution and
+excretion. The absorption of metformin is saturable and reported to be restricted to the upper
+intestine ([Vidon 1988](#5-references)). The excretion of metformin is mainly mediated via the sequential action of OCT2 and
+MATE in the kidney, with a moderate contribution of renal glomerular filtration (approximately
+20 %). Metformin is recommended by the FDA as OCT2/MATE victim drug for the use in clinical
+DDI studies and drug labeling ([FDA 2017](#5-references)).
+
+The herein presented PBPK model of metformin PBPK model has been developed and evaluated by comparing simulations to observed data of both intravenously and orally administered metformin covering a dosing range from 0.001 to 2550 mg.
+
+The presented model includes the following features:
+
+- transport by PMAT,
+- transport by OCT1,
+- transport by OCT2,
+- transport by MATE,
+- renal clearance by glomerular filtration,
+- oral absorption with dissolution rate assigned to a Weibull function.

Evaluation/Input/Content/Section2.1_Modeling_Strategy.md

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+The general concept of building a PBPK model has previously been described by Kuepfer et al. ([Kuepfer 2016](#5-references)). Relevant information on anthropometric (height, weight) and physiological parameters (e.g., blood flows, organ volumes, binding protein concentrations, hematocrit, cardiac output) in adults was gathered from the literature and has been previously published ([Willmann 2007](#5-references)). The information was incorporated into PK-Sim® and was used as default values for the simulations in adults.
+
+Transporters and metabolizing enzymes relevant to the pharmacokinetics of the modeled drugs were
+implemented in agreement with current literature, utilizing the PK-Sim® expression database ([PK-Sim Ontogeny Database Version 7.3](#5-references)) or otherwise referenced for the specific process.
+
+A model was built based on clinical data from studies with intravenous and oral administration of metformin. The studies reported individual or mean plasma concentrations of metformin,  and some of the studies reported fraction excreted to urine. For the studies reporting intravenous administration, metformin was administered in doses of 0.001 to 1000 mg. For the studies reporting oral administration, metformin was administered in doses of 0.001–2550 mg.
+
+Virtual mean individuals were generated for each study according to the published demographic information, with corresponding age, weight, height, sex, ethnicity, hematocrit and GFR, if available. If no information was provided, a default virtual individual was applied (30 years of age, male, European, mean weight, height, hematocrit and GFR characteristics from the PK-Sim® population database).
+
+The clinical datasets for metformin PBPK modeling were divided into a model building dataset for model building and a test dataset for model evaluation and verification. Both datasets are presented in [Section 2.2](#22-data-used).
+
+A specific set of parameters ([Section 2.3.4.](#model-parameters-and-assumptions-identification)) were optimized to describe the disposition of metformin using the Parameter Identification module provided in PK-Sim®. To limit the parameters to be optimized during model building, the minimal number of processes necessary to mechanistically describe the pharmacokinetics and drug-drug interactions (DDIs) of the modeled drugs were implemented into the models. The saturable absorption is implemented via PMAT and OCT1 in the small intestine. As late absorption of orally administered metformin is neither consistent with the reported plasma concentration time-profiles nor with the incomplete absorption of metformin, the relative expression of PMAT and OCT1 in the large intestinal mucosa was set to zero. Furthermore, no information regarding active transport processes at the basolateral side of the intestinal mucosa could be obtained. Therefore, the passive permeability from the intracellular to the interstitial space of the small intestinal mucosa was optimized.
+
+Details about input data (physicochemical, *in vitro* and clinical) can be found in [Section 2.2](#22-data-used).
+
+Details about the structural model and its parameters can be found in [Section 2.3](#23-model-parameters-and-assumptions).
+
+
+
+