Advanced Methods of Pharmacokinetic and Pharmacodynamic by Doo-Man Oh, Patrick J. Sinko, Gordon L. Amidon (auth.),

By Doo-Man Oh, Patrick J. Sinko, Gordon L. Amidon (auth.), David Z. D’Argenio (eds.)

This quantity files the court cases of the Workshop on complicated Meth­ ods of Pharmacokinetic and Pharmacodynamic structures research, equipped by way of the Biomedical Simulations source in may possibly 1990. The assembly introduced jointly over one hundred twenty investigators from a few disciplines, together with medical pharmacology, scientific pharmacy, pharmaceutical technology, biomathematics, facts and biomed­ ical engineering with the aim of supplying a high-level discussion board to facilitate the trade of principles among simple and scientific study scientists, experimentalists and modelers engaged on difficulties in pharmacokinetics and pharmacodynamics. it's been my adventure that during many parts of biomedical learn, while a gathering of this kind is held, the overall angle of these experimentalists keen to wait is one in every of severe skepticism: as a gaggle they consider that mathematical modeling has little to provide them in furthering their figuring out of the actual organic procedures they're learning. this is often under no circumstances the existing view whilst the subject is pharmacokinetics and drug reaction. fairly the opposite, using mathemati­ cal modeling and linked info research and computational equipment has been a crucial function of pharmacokinetics virtually from its beginnings. actually, the sphere has borrowed thoughts of modeling from different disciplines together with utilized math­ ematics, information and engineering, with the intention to higher describe and comprehend the methods of drug disposition and drug response.

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4,6, 7). The disposition function of a drug may vary considerably with the sampling site employed (Figs. 7,8); this is in sharp contrast to the conventional concept of only one disposition function for a given drug in a subject. 6. The size and number of the compartment as well as the micro rate constants in conventional multi-compartmental analysis may vary tremendously with the sampling site chosen. The scientific significance of these micro constants becomes highly questionable. 7. One should also be cautious about the use of the so-called noncompartmental or statistical moment analysis if venous data are employed.

However, the interpretation of the effect 57 compartment model in terms of distribution of terbutaline to an effect site where it is able to produce instantaneous changes in potassium is not reasonable. It is believed that beta-agonists enhance the clearance of potassium from the plasma by stimulating Na-K ATPase at the cell surface. Potassium is then transported into cells and the plasma concentration decreases. The time course of potassium concentra tion, POT( t), can be defined with a model similar to that for peA changes caused by warfarin but in this case the drug action is to increase removal rather than decrease synthesis: dPOT (t) dt = Rin - POT (t)Kpot PO [Ter(t)] (9) Rin is the pre-terbutalinepotassium input rate (equivalent to KpotPOTo, where PO To is the potassium concentration prior to terbutaline administration), Kpot is the removal rate constant for potassium (it is assumed that excretion of potassium is negligible over the observed time period) and Ter( t) is a pharmacokinetic model for terbutaline.

This prediction is similar to but not identical to that of model proposed by Ekblad and Licko [5]. REFERENCES 1. D. R. Stanski, J. Ham, R. D. Miller, and L. B. Sheiner. Pharmacokinetics and pharmacodynamics 2. 3. 4. 5. of d-tubocurarine during nitrous oxide-narcotic and halothane anesthesia in man. Anesthesiology 51:235-241 (1979). N. H. G. Holford. Clinical pharmacokinetics and pharmacodynamics of warfarin. c/in. Pharmacokinet. 11:483-504 (1986). R. E. Jonkers, C. J. van Boxtel, R. P. Koopmans, and B.

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