Pharmacokinetic-pharmacodynamic (PK-PD) modeling has emerged as a major tool in clinical pharmacology to optimize drug use by designing rational dosage forms and dosage regimes. Quantitative representation of the dose-concentration-response relationship should provide information for the prediction of the level of response to a certain level of drug dose. This paper describes the experimental details of the preformulation study, tablet manufacture, optimization, and bioanalytical methods for the estimation of dexibuprofen in human plasma. The hydrophilic matrix was prepared with xanthen gum with additives Avicel PH 102. The effect of the concentration of the polymer and different filler, on the in vitro drug release, was studied. Various pharmacokinetic parameters including AUC0–t, AUC0–∞, , , , and elimination rate constant ( ) were determined from the plasma concentration of both formulations of test (dexibuprofen 300？mg) and reference (dexibuprofen 300？mg tablets). The merits of PK-PD in the development of dosage forms and how PK-PD model development necessitates the development of new drugs and bio analytical method development and validation are discussed. The objectives of the present study, namely, to develop and validate the methods to estimate the selected drugs in the biological fluids by HPLC, the development of in vitro dissolution methods, and PK-PD model development have been described. 1. Introduction Dexibuprofen, S(+)-ibuprofen, is a pharmacologically active form and is more potent than ibuprofen, which has equal quantities of R(？)- and S(+)-enantiomers [1]. Ibuprofen is an NSAID and is widely used to reduce pain, fever, and inflammation. This drug inhibits cyclooxygenases and activates peroxisome proliferators-activated receptors; both of these actions result in reduced inflammation [2–4]. Pharmacokinetic-pharmacodynamic (PK-PD) modeling is a scientific tool to help developers selecte a rational dosage regimen for confirmatory clinical testing. PK/PD modeling can be executed using various approaches, such as direct versus indirect response models and parametric versus nonparametric models. PK/PD concepts can be applied to the individual dose optimization. The limits of PK/PD approaches include the development of appropriate models, the validity of surrogate endpoints, and the acceptance of these models in a regulatory environment. PK-PD modeling allows the estimation of PK-PD parameters and the prediction of these derived, clinically relevant parameters as well. PK-PD simulations allow the assessment of the descriptive parameters as
References
[1]
A. Bonabello, M. R. Galmozzi, R. Canaparo et al., “Dexibuprofen (S(+)-isomer ibuprofen) reduces gastric damage and improves analgesic and antiinflammatory effects in rodents,” Anesthesia and Analgesia, vol. 97, no. 2, pp. 402–408, 2003.
[2]
W. E. Kaufmann, K. I. Andreasson, P. C. Isakson, and P. F. Worley, “Cyclooxygenases and the central nervous system,” Prostaglandins, vol. 54, no. 3, pp. 601–624, 1997.
[3]
J. M. Lehmann, J. M. Lenhard, B. B. Oliver, G. M. Ringold, and S. A. Kliewer, “Peroxisome proliferator-activated receptors α and γ are activated by indomethacin and other non-steroidal anti-inflammatory drugs,” Journal of Biological Chemistry, vol. 272, no. 6, pp. 3406–3410, 1997.
[4]
H. Kojo, M. Fukagawa, K. Tajima et al., “Evaluation of human peroxisome proliferator-activated receptor (PPAR) subtype selectivity of a variety of anti-inflammatory drugs based on a novel assay for PPARδ(β),” Journal of Pharmacological Sciences, vol. 93, no. 3, pp. 347–355, 2003.
[5]
J. Venitz, “Pharmacokinetic-pharmacodynamic modeling of reversible drug effects,” in Handbook of Pharmacokinetic/Pharmacodynamic Correlation, H. Derendorf and G. Hochhaus, Eds., vol. 1, CRC Press, New York, NY, USA, 1995.
[6]
A. Van Peer, E. Snoeck, M. L. Huang, and J. Heykants, “Pharmacokinetic-pharmacodynamic relationships in Phase I/Phase II of drug development,” European Journal of Drug Metabolism and Pharmacokinetics, vol. 18, no. 1, pp. 49–59, 1993.
[7]
J. L. Steimer, M. E. Ebelin, and J. Van Bree, “Pharmacokinetic and pharmacodynamic data and models in clinical trials,” European Journal of Drug Metabolism and Pharmacokinetics, vol. 18, no. 1, pp. 61–76, 1993.
[8]
R. Lieberman and J. McMichael, “Role of pharmacokinetic-pharmacodynamic principles in rational and cost-effective drug development,” Therapeutic Drug Monitoring, vol. 18, no. 4, pp. 423–428, 1996.
[9]
H. A. El-Masri, R. S. Thomas, S. A. Benjamin, and R. S. H. Yang, “Physiologically based pharmacokinetic/pharmacodynamic modeling of chemical mixtures and possible applications in risk assessment,” Toxicology, vol. 105, no. 2-3, pp. 275–282, 1995.
[10]
E. A. Van Schaick, H. J. M. M. De Greef, A. P. Ijzerman, and M. Danhof, “Physiological indirect effect modeling of the antilipolytic effects of adenosine A1-receptor agonists,” Journal of Pharmacokinetics and Biopharmaceutics, vol. 25, no. 6, pp. 673–694, 1997.
[11]
H. Boxenbaum and C. DiLea, “First-time-in-human dose selection: allometric thoughts and perspectives,” Journal of Clinical Pharmacology, vol. 35, no. 10, pp. 957–966, 1995.
[12]
J. L. Gabrielsson and D. L. Weiner, “Methodology for pharmacokinetic/pharmacodynamic data analysis,” Pharmaceutical Science and Technology Today, vol. 2, no. 6, pp. 244–252, 1999.
[13]
B. Meibohm and H. Dorendorf, “Basic concepts of pharmacokinetic/pharmacodynamic (PK/PD) modelling,” International Journal of Clinical Pharmacology and Therapeutics, vol. 35, no. 10, pp. 401–413, 1997.
[14]
G. Levy, “Mechanism-based pharmacodynamic modeling,” Clinical Pharmacology & Therapeutics, vol. 56, pp. 356–358, 1994.
[15]
G. Levy, “Predicting effective drug concentrations for individual patients: determinants of pharmacodynamic variability,” Clinical Pharmacokinetics, vol. 34, no. 4, pp. 323–333, 1998.
[16]
L. B. Sheiner, D. R. Stanski, and S. Vozeh, “Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine,” Clinical Pharmacology & Therapeutics, vol. 25, no. 3, pp. 358–371, 1979.
[17]
J. W. Mandema, B. Tuk, A. L. Van Steveninck, D. D. Breimer, A. F. Cohen, and M. Danhof, “Pharmcokinetic-pharmacodynamic modeling of the central nervous system effects of midazolam and its main metabolite α-hydroxymidazolam in healthy volunteers,” Clinical Pharmacology & Therapeutics, vol. 51, no. 6, pp. 715–728, 1992.
[18]
D. Y. Lee, K. U. Lee, J. S. Kwon et al., “Pharmacokinetic-pharmacodynamic modeling of risperidone effects on electroencephalography in healthy volunteers,” Psychopharmacology, vol. 144, no. 3, pp. 272–278, 1999.
[19]
N. L. Dayneka, V. Garg, and W. J. Jusko, “Comparison of four basic models of indirect pharmacodynamic responses,” Journal of Pharmacokinetics and Biopharmaceutics, vol. 21, no. 4, pp. 457–478, 1993.
[20]
W. J. Jusko and H. C. Ko, “Physiologic indirect response models characterize diverse types of pharmacodynamic effects,” Clinical Pharmacology & Therapeutics, vol. 56, no. 4, pp. 406–419, 1994.
[21]
J. A. Bauer, J. P. Balthasar, and H. L. Fung, “Application of pharmacodynamic modeling for designing time-variant dosing regimens to overcome nitroglycerin tolerance in experimental heart failure,” Pharmaceutical Research, vol. 14, no. 9, pp. 1140–1145, 1997.
[22]
J. J. Lima, J. J. Krukemyer, and H. Boudoulas, “Drug- or hormone-induced adaptation: model of adrenergic hypersensitivity,” Journal of Pharmacokinetics and Biopharmaceutics, vol. 17, no. 3, pp. 347–364, 1989.
[23]
I. Ragueneau, C. Laveille, R. Jochemsen, G. Resplandy, C. Funck-Brentano, and P. Jaillon, “Pharmacokinetic-pharmacodynamic modeling of the effects of ivabradine, a direct sinus node inhibitor, on heart rate in healthy volunteers,” Clinical Pharmacology & Therapeutics, vol. 64, no. 2, pp. 192–203, 1998.
[24]
P. D. Sethi, High Performance Liquid Chromatography, New Delhi, India, 1st edition, 2001.
[25]
J. kiyokatsu, Chromatographic Separations Based on Molecular Recognition, Wiley-VCH, New York, NY, USA, 1997.
[26]
L. R. Snyder, J. J. Kirkland, and J. L. Glajch, Practical HPLC Method Development, New York, NY, USA, 2nd edition.
[27]
J. M. Miller, Chromatography Concepts and Contrasts, John Wiley & Sons, 2nd edition, 2005.
[28]
D. A. Skoog, D. M. West, and F. J. Holler, Fundamentals of Analytical Chemistry, Saunders, Philadelphia, Pa, USA, 7th edition, 1996.
[29]
M. E. Wewers and N. K. Lowe, “A critical review of visual analogue scales in the measurement of clinical phenomena,” Research in Nursing & Health, vol. 13, no. 4, pp. 227–236, 1990.
