Distribution rate constant difference

FIGURE 3.6 Compartmental analysis for different terms of volume of distribution. (Adapted from Kwon, Y., Handbook of Essential Pharmacokinetics, Pharmacodynamics and Drug Metabolism for Industrial Scientists, Kluwer Academic/Plenum Publishers, New York, 2001. With permission.) (a) Schematic diagram of two-compartment model for compound disposition. Compound is administrated and eliminated from central compartment (compartment 1) and distributes between central compartment and peripheral compartment (compartment 2). Vj and V2 are the apparent volumes of the central and peripheral compartments, respectively. kI0 is the elimination rate constant, and k12 and k21 are the intercompartmental distribution rate constants, (b) Concentration versus time profiles of plasma (—) and peripheral tissue (—) for two-compartmental disposition after IV bolus injection. C0 is the extrapolated concentration at time zero, used for estimation of V, The time of distributional equilibrium is fss. Ydss is a volume distribution value at fss only. Vj, is the volume of distribution value at and after postdistribution equilibrium, which is influenced by relative rates of distribution and elimination, (c) Time-dependent volume of distribution for the corresponding two-compart-mental disposition. Vt is the starting distribution space and has the smallest value. Volume of distribution increases to Vdss at t,s. Volume of distribution further increases with time to Vp at and after postdistribution equilibrium. Vp is influenced by relative rates of distribution and elimination and is not a pure term for volume of distribution. 

Intrinsic non-RRKM behavior occurs when an initial microcanonical ensemble decays nonexponentially or exponentially with a rate constant different from that of RRKM theory. The former occurs when there is a bottleneck (or bottlenecks) in the classical phase space so that transitions between different regions of phase space are less probable than that for crossing the transition state [fig. 8.9(e)]. Thus, a micro-canonical ensemble is not maintained during the unimolecular decomposition. A limiting case for intrinsic non-RRKM behavior occurs when the reactant molecule s phase space is metrically decomposable into two parts, for example, one part consisting of chaotic trajectories which can decompose and the other of quasiperiodic trajectories which are trapped in the reactant phase space (Hase et al., 1983). If the chaotic motion gives rise to a uniform distribution in the chaotic part of phase space, the unimolecular decay will be exponential with a rate constant k given by... 

When an administered drug exhibits the characteristics of a two-compartment model, the difference between the distribution rate constant (a) and the slow (post-) distribution rate constant (/ ) plays a critical role. The greater the difference between these, the more conspicuous is the existence of a two-compartment model and, therefore, the greater is the need to apply all the equations for a two-compartment model. Failure to do so will, undoubtedly, result in inaccurate clinical predictions. If, however, the difference between the distribution and the slow post-distribution rate constant is small and will not cause any significant difference in the clinical predictions, regardless of the model chosen to describe the pharmacokinetics of a drug, then it may be prudent to follow the principle of... 

Figure 13.12 A semilogarithmic plot of the difference between pbsma concentrations measured and those obtained by extrapolation [(Cp)diff] for a drug that obeys a two

Table 13.4 gives data for the difference between the observed and the extrapolated plasma concentrations (Cp)diff at various times, from which the distribution rate constant (a) and the empirical constant A can be obtained. 

A somewhat different approach to hot atom reactions has been taken by Keizra, who examined the evolution with time of the probability distribution of hot-atom energies. If the reaction rate is much smaller than the collision frequenqy the probability distribution relaxes to a steady state, which can be used to d ne hot-atom rate constants. The characterization of the hot-atom distribution in terms of a time-dependent hot-atom temperature was explored, and it was shown that under conditions where the hot-atom distribution becomes steady the pseudo-first-order rate constant differs from the equilibrium rate constant only by the appearance of the steady-state temperature. 

The activity of antioxidants in food [ 1 ] emulsions and in some biological systems [2] is depends on a multitude of factors including the localisation of the antioxidant in the different phases of the system. The aim of this study is determining antioxidant distributions in model food emulsions. For the purpose, we measured electrochemically the rate constant of hexadecylbenzenediazonium tetrafluorborate (16-ArN,BF ) with the antioxidant, and applied the pseudophase kinetic model to interpret the results. 

The distribution of open channel times is mainly determined by the rate constants S and K (2 is assumed to be very small). Mutations which change the C to O transition (e.g., the burst size of channel opening) have not been characterized yet. However, structural alterations which affect k and thereby the level of steady state inactivation have been described for Sh channels [29,60]. Different splice variants of Sh channels... 

This value is considerably higher than the experimental value (0.17) obtained from rate measurements on different size particles, but several factors may be invoked to explain the inconsistency. There will be a distribution of both pore radii and pore lengths present in the actual catalyst rather than uniquely specified values. Alumina catalysts often have a bimodal pore-size distribution. Our estimate of an apparent first-order rate constant using the method outlined above will be somewhat in error. The catalyst surface may not be equally active throughout if selective deactivation has taken place and the peripheral region is less active than the catalyst core. Other sources of error are the... 

This additional Eq. (18) was discretized at the same resolution as the flow equations, typical grids comprising 1203 and 1803 nodes. At every time step, the local particle concentration is transported within the resolved flow field. Furthermore, the local flow conditions yield an effective 3-D shear rate that can be used for estimating the local agglomeration rate constant /10. Fig. 10 (from Hollander et al., 2003) presents both instantaneous and time-averaged spatial distributions of /i0 in vessels agitated by two different impellers color versions of these plots can be found in Hollander (2002) and in Hollander et al. (2003). 

The situation is different for reactions of very hydrophilic ions, e.g. hydroxide and fluoride, because here overall rate constants increase with increasing concentration of the reactive anion even though the substrate is fully micellar bound (Bunton et al., 1979, 1980b, 1981a). The behavior is similar for equilibria involving OH" (Cipiciani et al., 1983a, 1985 Gan, 1985). In these systems the micellar surface does not appear to be saturated with counterions. The kinetic data can be treated on the assumption that the distribution between water and micelles of reactive anion, e.g. Y, follows a mass-action equation (9) (Bunton et al., 1981a). 

Although we cannot clearly determine the reaction order from Figure 3.9, we can gain some insight from a residual plot, which depicts the difference between the predicted and experimental values of cA using the rate constants calculated from the regression analysis. Figure 3.10 shows a random distribution of residuals for a second-order reaction, but a nonrandom distribution of residuals for a first-order reaction (consistent overprediction of concentration for the first five datapoints). Consequently, based upon this analysis, it is apparent that the reaction is second-order rather than first-order, and the reaction rate constant is 0.050. Furthermore, the sum of squared residuals is much smaller for second-order kinetics than for first-order kinetics (1.28 X 10-4 versus 5.39 xl0 4). 

Reactions in solution proceed in a similar manner, by elementary steps, to those in the gas phase. Many of the concepts, such as reaction coordinates and energy barriers, are the same. The two theories for elementary reactions have also been extended to liquid-phase reactions. The TST naturally extends to the liquid phase, since the transition state is treated as a thermodynamic entity. Features not present in gas-phase reactions, such as solvent effects and activity coefficients of ionic species in polar media, are treated as for stable species. Molecules in a liquid are in an almost constant state of collision so that the collision-based rate theories require modification to be used quantitatively. The energy distributions in the jostling motion in a liquid are similar to those in gas-phase collisions, but any reaction trajectory is modified by interaction with neighboring molecules. Furthermore, the frequency with which reaction partners approach each other is governed by diffusion rather than by random collisions, and, once together, multiple encounters between a reactant pair occur in this molecular traffic jam. This can modify the rate constants for individual reaction steps significantly. Thus, several aspects of reaction in a condensed phase differ from those in the gas phase ... 

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