Generic placeholder image

Current Drug Metabolism

Editor-in-Chief

ISSN (Print): 1389-2002
ISSN (Online): 1875-5453

Mini-Review Article

Physiologically Based Pharmacokinetic Model for Older Adults and Its Application in Geriatric Drug Research

Author(s): Xinyi Wu*, Jie En Valerie Sia, Min Hai, Xuan Lai, Haiyan Li, Cheng Cui* and Dongyang Liu*

Volume 24, Issue 3, 2023

Published on: 05 June, 2023

Page: [211 - 222] Pages: 12

DOI: 10.2174/1389200224666230509104404

Price: $65

Abstract

Drug-related adverse events are higher in older patients than in non-older patients, increasing the risk of medication and reducing compliance. Aging is accompanied by a decline in physiological functions and metabolic weakening. Most tissues and organs undergo anatomical and physiological changes that may affect the pharmacokinetic (PK) and pharmacodynamic (PD) characteristics of drugs. Clinical trials are the gold standard for selecting appropriate dosing regimens. However, older patients are generally underrepresented in clinical trials, resulting in a lack of evidence for establishing an optimal dosing regimen for older adults. The physiologically based pharmacokinetic (PBPK) model is an effective approach to quantitatively describe the absorption, distribution, metabolism, and excretion of drugs in older adults by integrating physiological parameters, drug physicochemical properties, and preclinical or clinical PK data. The PBPK model can simulate the PK/PD characteristics of clinical drugs in different scenarios, ultimately compensating for inadequate clinical trial data in older adults, and is recommended by the Food and Drug Administration for clinical pharmacology studies in older adults. This review describes the effects of physiological changes on the PK/PD process in older adults and summarises the research progress of PBPK models. Future developments of PBPK models are also discussed, together with the application of PBPK models in older adults, aiming to assist the development of clinical study strategies in older adults.

Graphical Abstract

[1]
National Bureau of Statistics. The head of the Office of the Leading Group for the Seventh National Census of the State Council accepts an exclusive interview with China News Agency. Available From: http://www.stats.gov.cn/ztjc/zdtjgz/zgrkpc/dqcrkpc/ggl/202105/t20210519_1817705.html
[2]
National Medical Products Administration National ADR Monitoring Annual Report. , 2020. Available from : [https://www.nmpa.gov.cn/xxgk/fgwj/gzwj/gzwjyp/20210325170127199.html
[3]
Shi, S.; Klotz, U. Age-related changes in pharmacokinetics. Curr. Drug Metab., 2011, 12(7), 601-610.
[http://dx.doi.org/10.2174/138920011796504527] [PMID: 21495970]
[4]
Thürmann, P.A. Pharmacodynamics and pharmacokinetics in older adults. Curr. Opin. Anaesthesiol., 2020, 33(1), 109-113.
[http://dx.doi.org/10.1097/ACO.0000000000000814] [PMID: 31789903]
[5]
Diener, L.; Hugonot-Diener, L.; Alvino, S.; Baeyens, J.P.; Bone, M.P.; Chirita, D.; Husson, J.M.; Maman, M.; Piette, F.; Tinker, A.; Von Raison, F. Guidance synthesis. Medical research for and with older people in Europe: Proposed ethical guidance for good clinical practice: Ethical considerations. J. Nutr. Health Aging, 2013, 17(7), 625-627.
[http://dx.doi.org/10.1007/s12603-013-0340-0] [PMID: 23933874]
[6]
Liu, Q.; Schwartz, J.B.; Slattum, P.W.; Lau, S.W.J.; Guinn, D.; Madabushi, R.; Burckart, G.; Califf, R.; Cerreta, F.; Cho, C.; Cook, J.; Gamerman, J.; Goldsmith, P.; van der Graaf, P.H.; Gurwitz, J.H.; Haertter, S.; Hilmer, S.; Huang, S.M.; Inouye, S.K.; Kanapuru, B.; Pirmohamed, M.; Posner, P.; Radziszewska, B.; Keipp Talbot, H.; Temple, R. Roadmap to 2030 for drug evaluation in older adults. Clin. Pharmacol. Ther., 2022, 112(2), 210-223.
[http://dx.doi.org/10.1002/cpt.2452] [PMID: 34656074]
[7]
Food and Drug Administration. Physiologically Based Pharmacokinetic Analyses - Format and Content Guidance for Industry. Available from : https://www.fda.gov/regulatory-information/search-fda-guidance-documents/physiologically-based-pharmacokinetic-analyses-format-and-content-guidance-industry [Accessed on: May 23, 2022].
[8]
European Medicines Agency. Guideline on the qualification and reporting of physiologically based pharmacokinetic (PBPK) modelling and simulation. Available from : https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-qualification-reporting-physiologically-based-pharmacokinetic-pbpk-modelling-simulation_en.pdf [Accessed on : May 23, 2022].
[9]
Abuhelwa, A.Y.; Williams, D.B.; Upton, R.N.; Foster, D.J.R. Food, gastrointestinal pH, and models of oral drug absorption. Eur. J. Pharm. Biopharm., 2017, 112, 234-248.
[http://dx.doi.org/10.1016/j.ejpb.2016.11.034] [PMID: 27914234]
[10]
Patel, D.; Bertz, R.; Ren, S.; Boulton, D.W.; Någård, M. A systematic review of gastric acid-reducing agent-mediated drug-drug interactions with orally administered medications. Clin. Pharmacokinet., 2020, 59(4), 447-462.
[http://dx.doi.org/10.1007/s40262-019-00844-3] [PMID: 31788764]
[11]
Mangoni, A.A.; Jackson, S.H.D. Age-related changes in pharmacokinetics and pharmacodynamics: Basic principles and practical applications. Br. J. Clin. Pharmacol., 2004, 57(1), 6-14.
[http://dx.doi.org/10.1046/j.1365-2125.2003.02007.x] [PMID: 14678335]
[12]
Rivera, R.; Antognini, J.F.; Riou, B. Perioperative drug therapy in elderly patients. Anesthesiology, 2009, 110(5), 1176-1181.
[http://dx.doi.org/10.1097/ALN.0b013e3181a10207] [PMID: 19352149]
[13]
Schnider, T.W.; Minto, C.F.; Shafer, S.L.; Gambus, P.L.; Andresen, C.; Goodale, D.B.; Youngs, E.J. The influence of age on propofol pharmacodynamics. Anesthesiology, 1999, 90(6), 1502-1516.
[http://dx.doi.org/10.1097/00000542-199906000-00003] [PMID: 10360845]
[14]
Kharasch, E.D.; Hoffer, C.; Whittington, D. Influence of age on the pharmacokinetics and pharmacodynamics of oral transmucosal fentanyl citrate. Anesthesiology, 2004, 101(3), 738-743.
[http://dx.doi.org/10.1097/00000542-200409000-00023] [PMID: 15329599]
[15]
Cepeda, M.; Farrar, J.T.; Baumgarten, M.; Boston, R.; Carr, D.B.; Strom, B.L. Side effects of opioids during short-term administration: Effect of age, gender, and race. Clin. Pharmacol. Ther., 2003, 74(2), 102-112.
[http://dx.doi.org/10.1016/S0009-9236(03)00152-8] [PMID: 12891220]
[16]
Cui, C.; Valerie Sia, J.E.; Tu, S.; Li, X.; Dong, Z.; Yu, Z.; Yao, X.; Hatley, O.; Li, H.; Liu, D. Development of a physiologically based pharmacokinetic (PBPK) population model for Chinese elderly subjects. Br. J. Clin. Pharmacol., 2021, 87(7), 2711-2722.
[http://dx.doi.org/10.1111/bcp.14609] [PMID: 33068053]
[17]
Thompson, C.M.; Johns, D.O.; Sonawane, B.; Barton, H.A.; Hattis, D.; Tardif, R.; Krishnan, K. Database for physiologically based pharmacokinetic (PBPK) modeling: Physiological data for healthy and health-impaired elderly. J. Toxicol. Environ. Health B Crit. Rev., 2009, 12(1), 1-24.
[http://dx.doi.org/10.1080/10937400802545060] [PMID: 19117207]
[18]
Schlender, J.F.; Meyer, M.; Thelen, K.; Krauss, M.; Willmann, S.; Eissing, T.; Jaehde, U. Development of a whole-body physiologically based pharmacokinetic approach to assess the pharmacokinetics of drugs in elderly individuals. Clin. Pharmacokinet., 2016, 55(12), 1573-1589.
[http://dx.doi.org/10.1007/s40262-016-0422-3] [PMID: 27351180]
[19]
Stader, F.; Siccardi, M.; Battegay, M.; Kinvig, H.; Penny, M.A.; Marzolini, C. Repository Describing an aging population to inform physiologically based pharmacokinetic models considering anatomical, physiological, and biological age-dependent changes. Clin. Pharmacokinet., 2019, 58(4), 483-501.
[http://dx.doi.org/10.1007/s40262-018-0709-7] [PMID: 30128967]
[20]
Li, G.F.; Zheng, Q.S.; Yu, Y.; Zhong, W.; Zhou, H.H.; Qiu, F.; Wang, G.; Yu, G.; Derendorf, H. Impact of ethnicity-specific hepatic microsomal scaling factor, liver weight, and cytochrome P450 (CYP) 1A2 content on physiologically based prediction of CYP1A2-mediated pharmacokinetics in young and elderly chinese adults. Clin. Pharmacokinet., 2019, 58(7), 927-941.
[http://dx.doi.org/10.1007/s40262-019-00737-5] [PMID: 30767128]
[21]
Chetty, M.; Johnson, T.N.; Polak, S.; Salem, F.; Doki, K.; Rostami-Hodjegan, A. Physiologically based pharmacokinetic modelling to guide drug delivery in older people. Adv. Drug Deliv. Rev., 2018, 135, 85-96.
[http://dx.doi.org/10.1016/j.addr.2018.08.013] [PMID: 30189273]
[22]
Russell, T.L.; Berardi, R.R.; Barnett, J.L.; Dermentzoglou, L.C.; Jarvenpaa, K.M.; Schmaltz, S.P.; Dressman, J.B. Upper gastrointestinal pH in seventy-nine healthy, elderly, North American men and women. Pharm. Res., 1993, 10(2), 187-196.
[http://dx.doi.org/10.1023/A:1018970323716] [PMID: 8456064]
[23]
Wu, B.; Wang, M.; Li, Y. Characteristics of 24-hour gastric pH rhythm changes in the elderly. Chin. J. Geriatr., 1999, 18(03), 18-19.
[24]
Li, Y.; Wu, B. Analysis of 24-hour intragastric pH in elderly subjects over 85 year-old. Chin. J. Heal. Care Med., 2018, 20(01), 4-6.
[25]
Madsen, J.L.; Graff, J. Effects of ageing on gastrointestinal motor function. Age Ageing, 2004, 33(2), 154-159.
[http://dx.doi.org/10.1093/ageing/afh040] [PMID: 14960431]
[26]
Pham, H.; Phillips, L.; Trahair, L.; Hatzinikolas, S.; Horowitz, M.; Jones, K.L. Longitudinal changes in the blood pressure responses to, and gastric emptying of, an oral glucose load in healthy older subjects. J. Gerontol. A Biol. Sci. Med. Sci., 2020, 75(2), 244-248.
[PMID: 30689778]
[27]
Liu, S.; Zhou, Y.; Chen, M.; Zhou, Y.; Wang, J.; Ji, R.; Yang, P.; Liu, C.; Yan, X. Effects of increasing age on gastric emptying and food distribution in the stomach. Acta Acad. Med. Mil. Tertiae, 2015, 37(17), 1771-1775.
[28]
Zhao, L.; Liu, S.; Wang, J.; Yang, P.; Liu, C.; Yan, X. Effects of aging on gastric emptying and its relationship with plasma gastrin and motilin. Zhongguo Laonianxue Zazhi, 2017, 37(15), 3800-3801.
[29]
Qu, B.; Wang, H.; Pan, J.; Qiao, R.; Ren, G. Application of OMOM capsule endoscopy in the inspection of stomach and small intestine in the elderly. Chin. J. Gastroenterol. Hepatol., 2013, 22(06), 575-577.
[30]
Grandison, M.K.; Boudinot, F.D. Age-related changes in protein binding of drugs: Implications for therapy. Clin. Pharmacokinet., 2000, 38(3), 271-290.
[http://dx.doi.org/10.2165/00003088-200038030-00005] [PMID: 10749520]
[31]
Tian, C.; Shen, X.; Wen, J.; Liu, Q.; Nie, M.; Xu, B. Factors influencing serum albumin in the elderly. Chin. J. Mult. Organ Dis. Elderly, 2012, 11(1), 36-39.
[32]
Benedetti, M.S.; Whomsley, R.; Poggesi, I.; Cawello, W.; Mathy, F.X.; Delporte, M.L.; Papeleu, P.; Watelet, J.B. Drug metabolism and pharmacokinetics. Drug Metab. Rev., 2009, 41(3), 344-390.
[http://dx.doi.org/10.1080/10837450902891295] [PMID: 19601718]
[33]
Achour, B.; Barber, J.; Rostami-Hodjegan, A. Expression of hepatic drug-metabolizing cytochrome p450 enzymes and their intercorrelations: A meta-analysis. Drug Metab. Dispos., 2014, 42(8), 1349-1356.
[http://dx.doi.org/10.1124/dmd.114.058834] [PMID: 24879845]
[34]
Achour, B.; Russell, M.R.; Barber, J.; Rostami-Hodjegan, A. Simultaneous quantification of the abundance of several cytochrome P450 and uridine 5′-diphospho-glucuronosyltransferase enzymes in human liver microsomes using multiplexed targeted proteomics. Drug Metab. Dispos., 2014, 42(4), 500-510.
[http://dx.doi.org/10.1124/dmd.113.055632] [PMID: 24408517]
[35]
Court, M.H. Interindividual variability in hepatic drug glucuronidation: Studies into the role of age, sex, enzyme inducers, and genetic polymorphism using the human liver bank as a model system. Drug Metab. Rev., 2010, 42(1), 209-224.
[http://dx.doi.org/10.3109/03602530903209288] [PMID: 19821798]
[36]
Burt, H.J.; Riedmaier, A.E.; Harwood, M.D.; Crewe, H.K.; Gill, K.L.; Neuhoff, S. Abundance of hepatic transporters in caucasians: A meta-analysis. Drug Metab. Dispos., 2016, 44(10), 1550-1561.
[http://dx.doi.org/10.1124/dmd.116.071183] [PMID: 27493152]
[37]
Waring, R.H.; Harris, R.M.; Mitchell, S.C. Drug metabolism in the elderly: A multifactorial problem? Maturitas, 2017, 100, 27-32.
[http://dx.doi.org/10.1016/j.maturitas.2017.03.004] [PMID: 28539174]
[38]
Klotz, U. Pharmacokinetics and drug metabolism in the elderly. Drug Metab. Rev., 2009, 41(2), 67-76.
[http://dx.doi.org/10.1080/03602530902722679] [PMID: 19514965]
[39]
Changjie, G.; Xusheng, Z.; Feng, H.; Shuguang, Q.; Jianwen, L.; Junzhou, F. Evaluation of glomerular filtration rate by different equations in Chinese elderly with chronic kidney disease. Int. Urol. Nephrol., 2017, 49(1), 133-141.
[http://dx.doi.org/10.1007/s11255-016-1359-z] [PMID: 27401985]
[40]
Guan, C.; Liang, M.; Liu, R.; Qin, S.; He, F.; Li, J.; Zhu, X.; Dai, H.; Fu, J. Assessment of creatinine and cystatin C-based eGFR equations in Chinese older adults with chronic kidney disease. Int. Urol. Nephrol., 2018, 50(12), 2229-2238.
[http://dx.doi.org/10.1007/s11255-018-1909-7] [PMID: 29948865]
[41]
National physical fitness and health database, 2006-2011. Available From:. http://cnphd.bmicc.cn/chs/cn/analysis.php [Accessed on: May 23, 2022]
[42]
Stader, F.; Battegay, M.; Marzolini, C. Physiologically-based pharmacokinetic modeling to support the clinical management of drug-drug interactions with bictegravir. Clin. Pharmacol. Ther., 2021, 110(5), 1231-1239.
[http://dx.doi.org/10.1002/cpt.2221] [PMID: 33626178]
[43]
Stader, F.; Courlet, P.; Decosterd, L.A.; Battegay, M.; Marzolini, C. Physiologically-based pharmacokinetic modeling combined with swiss HIV cohort study data supports no dose adjustment of bictegravir in elderly individuals living with HIV. Clin. Pharmacol. Ther., 2021, 109(4), 1025-1029.
[http://dx.doi.org/10.1002/cpt.2178] [PMID: 33521960]
[44]
Stader, F.; Courlet, P.; Kinvig, H.; Battegay, M.; Decosterd, L.A.; Penny, M.A.; Siccardi, M.; Marzolini, C. Effect of ageing on antiretroviral drug pharmacokinetics using clinical data combined with modelling and simulation. Br. J. Clin. Pharmacol., 2021, 87(2), 458-470.
[http://dx.doi.org/10.1111/bcp.14402] [PMID: 32470203]
[45]
Scotcher, D.; Galetin, A. PBPK simulation-based evaluation of Ganciclovir Crystalluria risk factors: Effect of renal impairment, old age, and low fluid intake. AAPS J., 2022, 24(1), 13.
[http://dx.doi.org/10.1208/s12248-021-00654-1] [PMID: 34907479]
[46]
De Sousa Mendes, M.; Chetty, M. Are standard doses of renally-excreted antiretrovirals in older patients appropriate: A PBPK Study comparing exposures in the elderly population with those in renal impairment. Drugs R D., 2019, 19(4), 339-350.
[http://dx.doi.org/10.1007/s40268-019-00285-0] [PMID: 31602556]
[47]
Sia, J.E.V.; Lai, X.; Wu, X.; Zhang, F.; Li, H.; Cui, C.; Liu, D. Physiologically-based pharmacokinetic modeling to predict drug-drug interactions of dabigatran etexilate and rivaroxaban in the Chinese older adults. Eur. J. Pharm. Sci., 2023, 182, 106376.
[http://dx.doi.org/10.1016/j.ejps.2023.106376] [PMID: 36626944]
[48]
Wen, H.N.; He, Q.F.; Xiang, X.Q.; Jiao, Z.; Yu, J.G. Predicting drug-drug interactions with physiologically based pharmacokinetic/pharmacodynamic modelling and optimal dosing of apixaban and rivaroxaban with dronedarone co-administration. Thromb. Res., 2022, 218, 24-34.
[http://dx.doi.org/10.1016/j.thromres.2022.08.007] [PMID: 35985100]
[49]
Wang, Z.; Cheong, E.J.Y.; Kojodjojo, P.; Chan, E.C.Y. Model-Based Risk Prediction of Rivaroxaban with Amiodarone for Moderate Renal Impaired Elderly Population. Cardiovasc. Drugs Ther, 2021. Available from : https://link.springer.com/article/10.1007/s10557-021-07266-z
[50]
Wang, Z.; Chan, E.C.Y. Physiologically‐based pharmacokinetic modeling‐guided dose management of oral anticoagulants when initiating nirmatrelvir/ritonavir (Paxlovid) for COVID‐19 treatment. Clin. Pharmacol. Ther., 2022, 112(4), 803-807.
[http://dx.doi.org/10.1002/cpt.2687] [PMID: 35712802]
[51]
Alsmadi, M.M. The investigation of the complex population-drug-drug interaction between ritonavir-boosted lopinavir and chloroquine or ivermectin using physiologically-based pharmacokinetic modeling. rug Metab Pers Ther,, 2022. Available from : www.degruyter.com/document/doi/10.1515/dmpt-20220130/html
[http://dx.doi.org/10.1515/dmpt-2022-0130]
[52]
Wang, Z.; Chan, E.C.Y. Physiologically‐based pharmacokinetic modelling to investigate baricitinib and tofacitinib dosing recommendations for COVID‐19 in geriatrics. Clin. Pharmacol. Ther., 2022, 112(2), 291-296.
[http://dx.doi.org/10.1002/cpt.2600] [PMID: 35380176]
[53]
Ammar, H.O.; Tadros, M.; Salam, N.; Ghoneim, A. Ethosome-derived invasomes as a potential transdermal delivery system for vardenafil hydrochloride: Development, optimization and application of physiologically based pharmacokinetic modeling in Adults and geriatrics. Int. J. Nanomedicine, 2020, 15, 5671-5685.
[http://dx.doi.org/10.2147/IJN.S261764] [PMID: 32821096]
[54]
Mukherjee, D.; Zha, J.; Menon, R.M.; Shebley, M. Guiding dose adjustment of amlodipine after co-administration with ritonavir containing regimens using a physiologically-based pharmacokinetic/pharmacodynamic model. J. Pharmacokinet. Pharmacodyn., 2018, 45(3), 443-456.
[http://dx.doi.org/10.1007/s10928-018-9574-0] [PMID: 29427135]
[55]
Rhee, S.; Chung, H.; Yi, S.; Yu, K.S.; Chung, J.Y. Physiologically based pharmacokinetic modelling and prediction of metformin pharmacokinetics in renal/Hepatic-impaired young adults and elderly populations. Eur. J. Drug Metab. Pharmacokinet., 2017, 42(6), 973-980.
[http://dx.doi.org/10.1007/s13318-017-0418-x] [PMID: 28536774]
[56]
Kim, C.; Lo Re, V.; Rodriguez, M.; Lukas, J.C.; Leal, N.; Campo, C.; García-Bea, A.; Suarez, E.; Schmidt, S.; Vozmediano, V. Application of a dual mechanistic approach to support bilastine dose selection for older adults. CPT Pharmacometrics Syst. Pharmacol., 2021, 10(9), 1006-1017.
[http://dx.doi.org/10.1002/psp4.12671] [PMID: 34157202]
[57]
Shen, C.; Liang, D.; Wang, X.; Shao, W.; Geng, K.; Wang, X.; Sun, H.; Xie, H. Predictive performance and verification of physiologically based pharmacokinetic model of propylthiouracil. Front. Pharmacol., 2022, 13, 1013432.
[http://dx.doi.org/10.3389/fphar.2022.1013432] [PMID: 36278167]
[58]
Konishi, K.; Minematsu, T.; Nagasaka, Y.; Tabata, K. Application of a physiologically based pharmacokinetic model for the prediction of mirabegron plasma concentrations in a population with severe renal impairment. Biopharm. Drug Dispos., 2019, 40(5-6), 176-187.
[http://dx.doi.org/10.1002/bdd.2181] [PMID: 30985942]
[59]
Cui, C.; Qu, Y.; Sia, J.E.V.; Zhu, Z.; Wang, Y.; Ling, J.; Li, H.; Jiang, Y.; Pan, J.; Liu, D. Assessment of aging-related function variations of P-gp transporter in old-elderly chinese CHF patients based on modeling and simulation. Clin. Pharmacokinet., 2022, 61(12), 1789-1800.
[http://dx.doi.org/10.1007/s40262-022-01184-5] [PMID: 36378486]
[60]
Stader, F.; Courlet, P.; Kinvig, H.; Penny, M.A.; Decosterd, L.A.; Battegay, M.; Siccardi, M.; Marzolini, C. Clinical data combined with modeling and simulation indicate unchanged drug‐drug interaction magnitudes in the elderly. Clin. Pharmacol. Ther., 2021, 109(2), 471-484.
[http://dx.doi.org/10.1002/cpt.2017] [PMID: 32772364]
[61]
Pilla Reddy, V.; El-Khateeb, E.; Jo, H.; Giovino, N.; Lythgoe, E.; Sharma, S.; Tang, W.; Jamei, M.; Rastomi-Hodjegan, A. Pharmacokinetics under the COVID‐19 storm. Br. J. Clin. Pharmacol., 2023, 89(1), 158-186.
[http://dx.doi.org/10.1111/bcp.14668] [PMID: 33226664]
[62]
Konishi, K.; Minematsu, T.; Nagasaka, Y.; Tabata, K. Physiologically-based pharmacokinetic modeling for mirabegron: A multi-elimination pathway mediated by cytochrome P450 3A4, uridine 5′-diphosphate-glucuronosyltransferase 2B7, and butyrylcholinesterase. Xenobiotica, 2019, 49(8), 912-921.
[http://dx.doi.org/10.1080/00498254.2018.1523489] [PMID: 30301385]
[63]
Rowland Yeo, K.; Aarabi, M.; Jamei, M.; Rostami-Hodjegan, A. Modeling and predicting drug pharmacokinetics in patients with renal impairment. Expert Rev. Clin. Pharmacol., 2011, 4(2), 261-274.
[http://dx.doi.org/10.1586/ecp.10.143] [PMID: 22115405]
[64]
Maddineni, V.R.; Mirakhur, R.K.; McCoy, E.P. Plasma cholinesterase activity in elderly and young adults. Br. J. Anaesth., 1994, 72(4), 497.
[http://dx.doi.org/10.1093/bja/72.4.497-a] [PMID: 8155461]
[65]
Hunt, C.M.; Westerkam, W.R.; Stave, G.M. Effect of age and gender on the activity of human hepatic CYP3A. Biochem. Pharmacol., 1992, 44(2), 275-283.
[http://dx.doi.org/10.1016/0006-2952(92)90010-G] [PMID: 1642641]
[66]
Hunt, C.M.; Westerkam, W.R.; Stave, G.M.; Wilson, J.A.P. Hepatic cytochrome P-4503A (CYP3A) activity in the elderly. Mech. Ageing Dev., 1992, 64(1-2), 189-199.
[http://dx.doi.org/10.1016/0047-6374(92)90106-N] [PMID: 1630156]
[67]
Hunt, C.M.; Strater, S.; Stave, G.M. Effect of normal aging on the activity of human hepatic cytochrome P450IIE1. Biochem. Pharmacol., 1990, 40(7), 1666-1669.
[http://dx.doi.org/10.1016/0006-2952(90)90470-6] [PMID: 2222520]
[68]
Herd, B.; Wynne, H.; Wright, P.; James, O.; Woodhouse, K. The effect of age on glucuronidation and sulphation of paracetamol by human liver fractions. Br. J. Clin. Pharmacol., 1991, 32(6), 768-770.
[PMID: 1768573]
[69]
Treluyer, J.M.; Jacqz-Aigrain, E.; Alvarez, F.; Cresteil, T. Expression of CYP2D6 in developing human liver. Eur. J. Biochem., 1991, 202(2), 583-588.
[http://dx.doi.org/10.1111/j.1432-1033.1991.tb16411.x] [PMID: 1722149]
[70]
Tanaka, E. In vivo age-related changes in hepatic drug-oxidizing capacity in humans. J. Clin. Pharm. Ther., 1998, 23(4), 247-255.
[http://dx.doi.org/10.1046/j.1365-2710.1998.00164.x] [PMID: 9867310]
[71]
George, J.; Byth, K.; Farrell, G.C. Age but not gender selectively affects expression of individual cytochrome P450 proteins in human liver. Biochem. Pharmacol., 1995, 50(5), 727-730.
[http://dx.doi.org/10.1016/0006-2952(95)00192-3] [PMID: 7669077]
[72]
Lee, J.; Yang, Y.; Zhang, X.; Fan, J.; Grimstein, M.; Zhu, H.; Wang, Y. Usage of in vitro Metabolism data for drug‐drug interaction in physiologically based pharmacokinetic analysis submissions to the US Food and drug administration. J. Clin. Pharmacol., 2021, 61(6), 782-788.
[http://dx.doi.org/10.1002/jcph.1819] [PMID: 33460193]
[73]
Guest, E.J.; Aarons, L.; Houston, J.B.; Rostami-Hodjegan, A.; Galetin, A. Critique of the two-fold measure of prediction success for ratios: application for the assessment of drug-drug interactions. Drug Metab. Dispos., 2011, 39(2), 170-173.
[74]
Kennerfalk, A.; Ruigómez, A.; Wallander, M.A.; Wilhelmsen, L.; Johansson, S. Geriatric drug therapy and healthcare utilization in the United kingdom. Ann. Pharmacother., 2002, 36(5), 797-803.
[http://dx.doi.org/10.1345/aph.1A226] [PMID: 11978154]
[75]
Lau, S.W.J.; Schlender, J.F.; Slattum, P.W.; Heald, D.L.; O’Connor-Semmes, R. Geriatrics 2030: developing drugs to care for older persons—A neglected and growing population. Clin. Pharmacol. Ther., 2020, 107(1), 53-56.
[http://dx.doi.org/10.1002/cpt.1663] [PMID: 31667834]
[76]
Jones, H.M.; Chen, Y.; Gibson, C.; Heimbach, T.; Parrott, N.; Peters, S.A.; Snoeys, J.; Upreti, V.V.; Zheng, M.; Hall, S.D. Physiologically based pharmacokinetic modeling in drug discovery and development: A pharmaceutical industry perspective. Clin. Pharmacol. Ther., 2015, 97(3), 247-262.
[http://dx.doi.org/10.1002/cpt.37] [PMID: 25670209]
[77]
Wagner, C.; Zhao, P.; Pan, Y.; Hsu, V.; Grillo, J.; Huang, S.M.; Sinha, V. Application of physiologically based pharmacokinetic (PBPK) modeling to support dose selection: Report of an FDA public woRKSHOP on PBPK. CPT Pharmacometrics Syst. Pharmacol., 2015, 4(4), 226-230.
[http://dx.doi.org/10.1002/psp4.33] [PMID: 26225246]
[78]
Sager, J.E.; Yu, J.; Ragueneau-Majlessi, I.; Isoherranen, N. Physiologically based pharmacokinetic (PBPK) modeling and simulation approaches: a systematic review of published models, applications, and model verification. Drug Metab. Dispos., 2015, 43(11), 1823-1837.
[http://dx.doi.org/10.1124/dmd.115.065920] [PMID: 26296709]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy