A Further Example Showing Efficiency of a Modeling Method Based on the Theory of Dynamic Systems in Pharmacokinetics
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Abstract
Aims: To present a further example showing an efficiency of a modeling method based on the theory of dynamic systems in pharmacokinetics.
Study design:The goals of the current study were twofold: to present (1) a further example showing efficiency of a modeling method based on the theory of dynamic systems in pharmacokinetics, an to perform (2) a next step in tutoring the use of computational and modeling tools from the theory of dynamic systems in pharmacokinetics.
The data available in the study by Plusquellec et al. published in the October Issue of the Journal Medical Engineering & Physics were used to exemplify the method considered here. For modeling purpose an advanced mathematical modeling method was employed. Modeling was performed using the computer program named CTDB described in the study by Dedík et al. published in September 2007 issue of the Journal Diabetes Research and Clinical Practice.
Main outcome: Modeling results revealed that computational and modeling tools from the theory of dynamic systems can be successfully used in the development of a mathematical model of such a complicated process as is a multiple sites discontinuous gastrointestinal absorption.
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Copyright (c) 2017 Durisova M.
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Dammann HG, Müller P, Kather H, Simon B. The new histamine H2-receptor antagonist ranitidine. Duration of action. Res Exp Med (Berl). 1981; 178: 151-154. Ref.: https://goo.gl/47Zy9Y
Dawson J, Richards DA, Stables R, Dixon GT, Cockel R. Ranitidine --pharmacology and clinical use. J Clin Hosp Pharm Ther. 1983; 8: 1-13. Ref.: https://goo.gl/bkzNwF
Eckardt VF, Cordes I, Janish HD, Wiemann H. Daytime acid secretion after a single dose of ranitidine and cimetidine--a double blind crossover study. Eur J Clin Pharmacol. 1984; 26: 177-182. Ref.: https://goo.gl/9HoAnV
Brittain RT, Jack D. Histamine H2-antagonists--past, present and future. J Clin Gastroenterol. 1983, 5: 71-79. Ref.: https://goo.gl/EXuI0O
Gaginella TS, Bauman JH. Ranitidine hydrochloride. Drug Intell Clin Pharm 1983; 17: 873-885. Ref.: https://goo.gl/ptOQfC
Merki HS, Witzel L, Walt RP, Neumann J, Scheurle E, et al. Comparison of ranitidine 300 mg twice daily, 300 mg at night and placebo on 24-hour intragastric acidity of duodenal ulcer patients. Aliment. Pharmacol Ther. 1987; 1: 217-223. Ref.: https://goo.gl/bEZhOc
Plusquellec Y, Efthymiopoulos C, Duthil P, Houin G. A pharmacokinetic model for multiple sites discontinuous gastrointestinal absorption. Med Eng Phys. 1999; 21: 525-532. Ref.: https://goo.gl/BkULJt
Reid SR, Bayliff CD. The comparative efficacy of cimetidine and ranitidine in controlling gastric pH in critically ill patients. Canad Anaesth. 1986; 33: 287-293. Ref.: https://goo.gl/Wcm42c
Higuchi K, Watanabe T, Tominaga K, Shiba M, Nakagawa K, et al. Effects of ranitidine on quality of gastric ulcer healing compared with famotidine: a randomized, controlled, multicenter trial. Int J Clin Pharmacol Res. 2005; 25: 187-194. Ref.: https://goo.gl/i6D1S1
Chrenova J, Durisova M, Mirciou C, Dedik L. Effect of gastric emptying and entero-hepatic circulation on bioequivalence assessment of. Methods Find Exp Clin Pharmacol. 2010; 32: 413-419. Ref.: https://goo.gl/OanMbq
van Rossum JM, de Bie JE, van Lingen G, Teeuwen HW. Pharmacokinetics from a dynamical systems point of view. J Pharmacokinet Biopharm. 1989; 17: 365-392. Ref.: https://goo.gl/VAVsFe
Dedík L, Ďurišová M. CXT-MAIN: a software package for the determination of the analytical form of the pharmacokinetic system weighting function. Comput Methods Programs Biomed. 51: 183-192. Ref.: https://goo.gl/iAvtNQ
Dedík L, Ďurišová M. Frequency response method in pharmacokinetics. J Pharmacokin Biopharm. 1994; 22: 237-307. Ref.: https://goo.gl/flpLxF
Ďurišová M, Dedík L. Modeling in frequency domain used for assessment of in vivo dissolution profile. Pharm Res. 1997; 14: 860-864. Ref.: https://goo.gl/p6uWjQ
Ďurišová M, Dedík L. A system-approach method for the adjustment of time-varying continuous drug infusion in individual patients: A simulation study. J Pharmacokinet Pharmacodyn. 2002; 29: 427-444. Ref.: https://goo.gl/1XtK6n
Ďurišová M, Dedík L. New mathematical methods in pharmacokinetic modeling. Basic Clin Pharmacol Toxicol. 2005; 96: 335-342. Ref.: https://goo.gl/UNFNoG
Yates JW. Structural identifiability of physiologically based pharmacokinetic models. J Pharmacokinet Pharmacodyn. 2006; 33: 421-439. Ref.: https://goo.gl/qf3HvZ
Ďurišová M, Dedík L, Kristová V, Vojtko R. Mathematical model indicates nonlinearity of noradrenaline effect on rat renal artery. Physiol Res. 2008; 57: 785-788. Ref.: https://goo.gl/UW4Ees
Ďurišová M. Physiologically based structure of mean residence time. Scientific World Journal. 2012. Ref.: https://goo.gl/DjpTgU
Ďurišová M. A physiological view of mean residence times. Gen Physiol Biophys. 2014; 33: 75-80. Ref.: https://goo.gl/SFZu6S
Ďurišová M. Mathematical model of pharmacokinetic behavior of orally administered prednisolone in healthy volunteers. J Pharmaceut & Pharmacol. 2014; 2: 1-5.
Ďurišová M. Further worked out examples that illustrated the successful use of an advanced mathematical modeling method based on the theory of dynamic systems in pharmacokinetics. Int J Res Sci Res. 2015; 6: 4873-4879. Ref.: https://goo.gl/eB8xLo
Ďurišová M. Mathematical model of pharmacokinetic behavior of warfarin. Adv Pharm Clin Trials. 2016; 1: 1-7. Ref.: https://goo.gl/1Zd7zi
Ďurišová M. Computational analysis of pharmacokinetic behavior of ampicillin. J Appl Bioanal. 2016; 2: 84-89. Ref.: https://goo.gl/9uhDJ6
Levitt DG. PK Quest: a general physiologically based pharmacokinetic model. Introduction and application to propranolol. BMC Clin Pharmacol. 2002; 15: 2-5. Ref.: https://goo.gl/2UCayb
Howell BA, Yang Y, Kumar R, Woodhead JL, Harill AH, et al. In vitro to in vivo extrapolation and species response comparisons for drug-indused liver injury (DILI) using DILsymTM: a mechanistic model of DILI. J Pharmacokinet Pharmacodyn. 2012; 39: 527-541. Ref.: https://goo.gl/LveVQu
Dedík L, Ďurišová M, Penesová A, Miklovičová D, Tvrdoňová M. Estimation of influence of gastric emptying on shape of glucose concentration-time profile measured in oral glucose tolerance test. Diabetes Research and Clinical Practice. 2007; 77: 377-384. Ref.: https://goo.gl/0koO9F
Ďurišová M. Physiologically based structure of mean residence time. The Sci World Journal. 2012. Ref.: https://goo.gl/xPqy08
Ďurišová M. A physiological view of mean residence times. Gen Physiol Biophys. 2014; 33: 75-80. Ref.: https://goo.gl/44tImL
Weiss M, Pang KS. Dynamics of drug distribution. I. Role of the second and third curve moments. J Pharmacokinet Biopharm. 1992; 20: 253-278. Ref.: https://goo.gl/wiYtGU
Verotta D. Concepts, properties, and applications of linear systems to describe distribution, identify input, and control endogenous substances and drugs in biological systems. Crit Rev Biomed Eng. 1996; 24: 73-139. Ref.: https://goo.gl/6lGcmI
Xiao H, Song H, Yang Q, Cai H, Qi R,et al. A prodrug strategy to deliver cisplatin (IV) and paclitaxel in nanomicelles to improve efficacy and tolerance. Biomaterials. 2012; 33: 6507-6519. Ref.: https://goo.gl/UthCGZ
Beckermann B, Kaliaguine V. The diagonal of the Padé table and the approximation of the Weyl function of second-order difference operators. Constr Approx. 1997; 13: 481-510. Ref.: https://goo.gl/AgA5a2
Levy EC. Complex curve fitting. IRE Trans Automat Contr. 1959; 4: 37-43. Ref.: https://goo.gl/5g3G6d
Akaike H. A new look at the statistical model identification. IEEE Trans Automat Contr. 1974; 19: 716-723. Ref.: https://goo.gl/KM0Sbt
Lampariello F, Sciandrone M. Use of the minimum-norm search direction in a nonmonotone version of the Gauss-Newton method. J Optim Ther Appl. 2003; 119: 65-82. Ref.: https://goo.gl/JwG01Y
Boyle P. Options: A Monte Carlo approach. J Fin Econom. 1977; 4: 323-338. Ref.: https://goo.gl/g8gMCC
Varvel JR, Donoho DL, Shafer SL. Measuring of the predictive performance of computer controlled infusion pumps. J Pharmacokin Biopharm. 1992; 20: 63-84. Ref.: https://goo.gl/vsRmMu
Siegel RA. Pharmacokinetic transfer functions and generalized clearances. J Pharmacokin Biopharm. 1986; 14: 511-521. Ref.: https://goo.gl/aRrc7I
Segre G. The sojourn time and its prospective use in pharmacology.J Pharmacokin Bio- pharm. 1988; 16: 657-666. https://goo.gl/7yZs2V
Yates JW. Structural identifiability of physiologically based pharmacokinetic models. J Pharmacokinet Pharmacodyn. 2006; 33: 421-439. Ref.: https://goo.gl/VPEqJ0
Rescigno A. Compartmental analysis and its manifold applications to pharmacokinetics. AAPS J. 2010; 12: 61-72. Ref.: https://goo.gl/qJ6h5r
Gillespie WR, Veng-Pedersen P, Berg MJ, Schkottelius DD. Linear systems approach to the analysis of an induced drug removal process. Phenobarbital removal by oral activated charcoal. J Pharmacokin Biopharm. 1986; 14: 19-28. Ref.: https://goo.gl/vL520R