Physiologically based pharmacokinetic structure

Physiologically based pharmacokinetic models provide a format to analyze relationships between model parameters and physicochemical properties for a series of drug analogues. Quantitative structure-pharmacokinetic relationships based on PB-PK model parameters have been pursued [12,13] and may ultimately prove useful in the drug development process. In this venue, such relationships, through predictions of tissue distribution, could expedite drug design and discovery. 

Poulin and Krishnan (1995) developed a method to predict tissue blood PCs for incorporation into physiologically based pharmacokinetic (PBPK) models. Tissue blood partitioning was calculated as an additive function of partitioning into the water, neutral lipids and phospholipids constituent of individual tissues. These were calculated using published values for lipid and water content of tissues and the octanol-water PC of the compounds. Poulin and Krishnan (1998 1999) used this method to predict tissue blood PCs that were subsequently incorporated into a quantitative structure-toxicokinetic model. The prediction of tissue plasma PCs to describe distribution processes and as input parameters for PBPK models has been extensively researched by Poulin and coworkers a great deal of further information can be obtained from their references (Poulin and Theil, 2000 Poulin et al., 2001 Poulin and Theil, 2002a Poulin and Theil, 2002b). 

Beliveau M, Tardif R, Krishnan K. 2003. Quantitative structure-property relationships for physiologically based pharmacokinetic modeling of volatile organic chemicals in rats. Toxicol Appl Pharmacol 189 221-232. 

Many types of modeling techniques are available in the discovery phase of drug development, from structure activity relationships (SAR) to physiology based pharmacokinetics (PBPK) and pharmacokinetics-/pharmacodynamics (PK/PD) to help choosing some of the lead compounds. Some tests that are carried out by discovery include techniques related to structure determination, metabolism, and permeability NMR, MS/MS, elemental analysis, PAMPA, CACO-2, and in vitro metabolic stability. Although they are important as a part of physicochemical molecular characterization under the biopharmaceutics umbrella, they will not be discussed here. The reader can find relevant information in numerous monographs [9,10]. 

Hazard identification is the step in the risk assessment that qualitatively characterizes the inherent toxicity of a chemical. Scientific data are evaluated to establish a possible causal relationship between the occurrence of adverse health effects and chemical exposure. This step includes characterization of acute, subchronic, and chronic effects the potential for local versus systemic effects the influence of the route of exposure the relevance, to humans, of effects seen in animals an evaluation of the biological importance of the observed effects the likelihood of the effects occurring under certain conditions and the potential implications for public health. This step should be based on a thorough review of all the data that may provide information that is relevant to evaluating the potential chemical hazard. This may include data describing the effects on a variety of test animals, in vitro studies that characterize mechanisms of toxicity, metabolism, physiologically based pharmacokinetic studies, structure-activity relationships, short-term human studies, and epidemiological studies. Animal studies may focus on particular types of effects and may include reproductive toxicity studies,... 

This chapter reviews some of the in silico attempts to predict oral bioavailability. However, bioavailability is a complex property, and various pros and cons of current quantitative structure-activity relationship (QSAR) based approaches will be discussed here. As an alternative, physiologically-based pharmacokinetic (PBPK) modeling is discussed as a promising approach to predict and simulate pharmacokinetics (PK), including estimating bioavailability. 

Parham FM, Portier CJ. 1998. Using structural information to create physiologically based pharmacokinetic models for all polychlorinated biphenyls. E-Rates of metabolism. Toxicol Appl Pharmacol 151(1) 110-116. 

Nestorov, I. A. (1999). Sensitivity analysis of [4iarmacokinetic and pharmacodynamic systems 1. A structural approach to sensitivity analysis of physiologically based pharmacokinetic models. J Pharmacokinet Biopharm 27, 577-596. 

Figure 3.2-5. Model structure of a hypothetical physiologically based pharmacokinetic model. Tissue blood flows are shown (Q) along with renal (CIr) and nonrenal (01 0 drug clearance pathways.

Poulin P, Krishnan K. 1996b. Molecular structure-based prediction of the partition coefficients of organic chemicals for physiologically-based pharmacokinetic models. Toxicol Method 6 117-137. 

While ejqierimental methods always require sufficient amount of chemicals for the estimation of drag absorption, computational in silico) methods can lead to the prediction of intestinal absorption based on chemical structure, and can thus be used before synthesis of compoimds. In silico predictions could be based both on relatively simple quantitative structure-activity relationships (QSAR) analysis and more complex physiologically based pharmacokinetic and/or pharmacodynamic models. Whichever the approach used for model building, computational methods should be based on experimental data that were obtained for a wide range of structurally diverse compoimds (training set). It should be noted, however, that current in silico methods, are not as reliable as experimental models. 

Blakey GE, Nestorov lA, Arundel PA, Aarons LJ, Rowland M. Quantitative structure-pharmacokinetics relationships I. Development of a whole-body physiologically based model to characterize changes in pharmacokinetics across a homologous series of barbiturates in the rat. J Pharmacokinet Biopharm 1997 Jun 25(3) 277-312. Erratum in J Pharmacokinet Biopharm 1998 Feb 26(l) 131. 

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