Drug , anticoagulant modeling

Model I has been applied to a wide variety of drug responses, such as the reduction of fever (8, 20) or pain (19) by anti-inflammatory drugs, anticoagulant action of warfarin (3,9), reduction in blood sorbitol levels by inhibitors of aldose reductase (21), cortisol suppressive effects of corticosteroids (22), luteinizing hormone suppression by the synthetic hormone cetrorelix (23), reduction in the levels of tumoral phospho-EGFR (epidermal growth factor receptor) by cetuximab (24), inhibition of dihydrotestosterone (25), the suppression of T-lymphocyte influx into the blood by corticosteroids (26), and the acid-inhibitory effects of H2-receptor antagonists (27). 

Modeling, Parameter Identification, and Adaptive Control of Anticoagulant Drug Therapy... 

The purpose of this paper is to illustrate how mathematical modeling and control theory can be applied to the problem of optimizing the administration of the anticoagulant drug heparin. 

A pharmacokinetic model which describes a patienf s response to the widely used anticoagulant drug, heparin, is discussed. The model contains several unknown parameters. A patients own past data can be used to identify these parameters and thus tailor-make a model for each individual under treatment. Once such a model is available it can be used to calculate optimum dosing policies to achieve a specified therapeutic goal. 

Ariens [432] was the first to describe drug action through indirect mechanisms. Later on, Nagashima et al. [433] introduced the indirect response concept to pharmacokinetic-dynamic modeling with their work on the kinetics of the anticoagulant effect of warfarin, which is controlled by the change in the prothrombin complex synthesis rate. Today, indirect-response modeling finds extensive... 

Thrombin and factor Xa are prominent players in the blood clotting cascade. They are, therefore, important targets for the development of new anticoagulant/antithrombotic drugs. Trypsin is an enzyme excreted by the pancreas for helping in digestion, and has classically been used as a model enzyme for the whole serine protease family. Thus, in order to minimize side-effects of thrombin/factorXa inhibitors, and to enhance their bioavailability, potential drugs should exhibit selectivity towards thrombin/factorXa with respect to trypsin. 

It is important to note that an accurate economic model of this problem is impossible to construct. Adverse events are not caused by unusual or rare circumstances (Johnson and Bootman, 1997). Rather, these events make up a familiar list, including wound infections, drug overdoses, administration of the wrong drugs, bleeding from anticoagulation, insulin reactions, missed diagnoses, and falls. Because these risks and events are known and predictable, they are also preventable. It is estimated that these preventable events represent 69.6 percent of medical accidents (Leape and others, 1993). 

McAvoy, T. J., Modeling and Control of the Anticoagulant Drug Heparin, J. Process Control, 17, 590 (2007). 

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