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Optimal design for population pk/pd models

.: Optimum Experimental Design. Clarendon Press, Oxford, 1992. [4] ATWOOD, C. L.: Sequences converging to D-optimal designs of experiments, Ann. Stat. 1 (1973), 342-352. [5] BATES, D. M.-WATTS, D. G.: Nonlinear Regression Analysis and its Applications. Wiley, New York, 1988. [6] BAZZOLI, C.-RETOUT, S.-MENTR´ E, F.: Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model, Stat. Med. 28 (2009

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General Anaesthesia for Renal Transplantation in Latvia: A Critical Analysis Based on Clinical Experience

of Renal Transplantation (pp. 87-100) . New York, Heidelberg, Berlin: Springer-Verlag. de Gasperi, A., Mazza, E., Noe, L., Corti, A., Cristalli, A., Prosperi, M., Sabbadini, D., Savi, M. C., Vai, S. (1996). Pharmacokinetic profile of the induction dose of propofol in chronic renal failure patients undergoig renal transplantation. Minerva Anaesthesiol ., 62 , 25-31. Eger, E., 2nd, Koblin, D. D., Bowland, T., Ionescu, P., Laster, M.J., Fang, Z., Gong, D., Sonner, J., Weiskopf, R. B. (1977). Nephrotoxicity of sevoflurane versus

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Colistin Use Patterns and Toxicity in Critically Ill Patients in Pauls Stradiņš Clinical University Hospital

., Li, J., Thamlikitkul, V., Paterson, D. L., Shoham, S., Jacob, J., Silveira, F. P., Forrest, A., Nation, R. L. (2011). Population pharmacokinetics of colistin methanesulfonate and formed colistin in critically ill patients from a multicenter study provide dosing suggestions for various categories of patients. Antimicrob. Agents Chemother ., 55 (7), 3284–3294. Gauthier, T. P., Wolowich, W. R., Reddy, A., Cano, E., Abbo, L., Smith, L. B. (2012). Incidence and predictors of nephrotoxicity associated with intravenous colistin in overweight and obese patients

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Comparison of Effectiveness and Safety of Antiarrhythmic Drugs Class IC and III in Patients After Electrical Cardioversion

and pharmacokinetics of rivaroxaban. Int. J. Clin. Pharmacol. Ther ., 51 (7), 549–561. Stewart, S., Murphy, N., Walker, A., McGuire, A., McMurray, J. J. V. (2004). Cost of an emerging epidemic: An economic analysis of atrial fibrillation in the UK. Heart , 90 , 286–292 Strēlnieks, A., Vīnkalna, I., Lituņenko, O., Pupkevica, I., Šime, I., Vikmane, M., Kovaļova, M., Rancāne, M., Dormidontova, G., Sakne, S., Pudulis, J., Mintāle, I., Kalējs, O., Lejnieks, A. (2014). Atrial fibrillation and risk factors of recurrent paroxysms after electrical

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Characterisation and In Vivo Safety of Canine Adipose-Derived Stem Cells

. G., Kassem, M. (2005). Tissue distribution and engraftment of human mesenchymal stem cells immortalized by human telomerase reverse transcriptase gene. Biochem. Biophys. Res. Comm., 330 , 633–640. Blythe, L. L., Craig, A. M., Christensen, J. M., Appell, L. H., Slizeski, M. L. (1986). Pharmacokinetic disposition of dimethyl sulfoxide administered intravenously to horses. Amer. J. Vet. Res., 47 , 1739–1743. Bogdanova, A., Berzins, U., Nikulshin, S., Skrastina, D., Ezerta, A., Legzdina, D., Kozlovska, T. (2014). Characterization of human adipose

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Optimal control problems for differential equations applied to tumor growth: state of the art

cytotoxic agents to increase the selectivity of therapy. Reference [ 46 ] models the proliferation cycle of leukemia. Eisen [ 14 ] also gives some introductory discussion of cell-cycle specific chemotherapy and compartmental models (distinguishing between proliferating and quiescent cells), but mostly in the context of pharmacokinetics and clearly the emphasis is more on modeling than on analysis. After that, a great effort was done to study the development and analysis of compartmental models which describe and analyze the actions of drugs on specific compartments from

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Applied mathematics and nonlinear sciences in the war on cancer

, also applicable to cancer. They claim that the mention of population analysis or pharmacokinetic and pharmacodynamic (PKPD) modelling often sends clinicians and clinical pharmacologists running, not wanting to know about mathematics and understanding complexity. Individualized dosing, optimal design of studies and mechanistic models of physiological processes are all ‘too hard’ . Our modern society relies on advanced technology, but we only apply it as common users (ie, GPS) and not struggling to understand it. If we want to advance, some clinicians need involved

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