Pharmacokinetics correlations

G. Maksay, L. Otvos, Bioactivation of Prodrugs Structure-Pharmacokinetic Correlations of Benzodiazepine Esters , Drug Metab. Rev. 1983, 14, 1165-1192. 

Csernansky JG, Lombrozo L, Gulevich GD, et al. Treatment of negative schizophrenic symptoms with alprazolam a preliminary open-label study. J Clin Psychopharmacol 1984 4 349-352. Douyon R, Angrist B, Peselow E, et al. Neuroleptic augmentation with alprazolam clinical effects and pharmacokinetic correlates. Am J Psychiatry 1989 146 231-234. 

Tzimas G, Thiel R, Chahoud I, Nau H (1997) The area under the concentration-time curve of all-trans-retinoic acid is the most suitable pharmacokinetic correlate to the embryotoxicity of this retinoid in the rat. Toxicol Appl Pharmacol, 143(2) 436-444. 

Lecointre K, Pisante L, Fauvelle F, Mazouz S. Digoxin toxicity evaluation in clinical practice with pharmacokinetic correlations. Clin Drug Invest 2001 21 225-32. 

Maillart P, Allain YM, Minier JF, Dubin J. Toxicite cardiaque aigue du 5-fluorouracile correlation pharma-cocinetique. [Acute cardiac toxicity of 5-fluorouracil pharmacokinetic correlation.] Bull Cancer... 

Useful discussions reviewing PK model structure [12] and PK correlations [13] and describing applications or PK models [14,15] are recommended. Comprehensive reviews of pharmacokinetic modeling are given by Lin and Lu [16] and Sheiner and Steimer [17]. 

Hochhaus G, Barrett JS, Derendorf H. Evolution of pharmacokinetics and phar-macokinetic/dynamic correlations during the 20th century. J Clin Pharmacol. 2000 Sep 40(9) 908-17. 

Octanol-water partition (log P) and distribution (log D) coefficients are widely used to make estimates for membrane penetration and permeability, including gastrointestinal absorption [77, 78], BBB crossing [60, 69] and correlations to pharmacokinetic properties [1]. The two major components of lipophilicity are molecular size and H-bonding [57], which each have been discussed above (see Sections 2.5 and 2.6). 

There was a significant negative correlation between (log) admission urinary PCP level and self-reported time since last PCP use (r= -0.53, p<0.001). Visual inspection of a graph of these two variables suggested a possible biphasic elimination curve, with the initial phase having a half-life of 5 to 7 days, and the later phase a half-life of about 30 days. However, formal curve fitting of these data to standard pharmacokinetic models (using BMDP... 

H. Derendorf and G. Hochhaus, Handbook of Pharmacokinetic / Pharmacodynamic Correlation, CRC Press, Boca Raton, FL, 1995. 

The information requirements for products such as prolonged-release oral dosage forms will depend on whether or not it has been possible, during the development of the product, to establish an in vivo-in vitro correlation between clinical data and dissolution studies. In vivo-in vitro correlations should be attempted using product at different stages of development, but bioavailability and pharmacokinetics data from pivotal clinical studies using at least pilot-scale production materials and possibly routine production material are particularly important. Where it is not possible to establish an in vivo-in vitro correlation, additional data will be required to compare the bioavailability of product developed at laboratory scale, pilot scale, and production scale. In the absence of an in vivo-in vitro correlation, the dissolution test will be a quality control tool rather than a surrogate marker for in vivo performance of the product. 

The advantage of the mixing tank model approach is its relative simplicity, intuitive accessibility, and easy correlation with pharmacokinetic models. However, the physical basis for considering a segment of the small intestine as one or more serial mixing tanks is limited, although such an assumption has been commonly and successfully utilized in the physical and biological sciences. 

PBPK and classical pharmacokinetic models both have valid applications in lead risk assessment. Both approaches can incorporate capacity-limited or nonlinear kinetic behavior in parameter estimates. An advantage of classical pharmacokinetic models is that, because the kinetic characteristics of the compartments of which they are composed are not constrained, a best possible fit to empirical data can be arrived at by varying the values of the parameters (O Flaherty 1987). However, such models are not readily extrapolated to other species because the parameters do not have precise physiological correlates. Compartmental models developed to date also do not simulate changes in bone metabolism, tissue volumes, blood flow rates, and enzyme activities associated with pregnancy, adverse nutritional states, aging, or osteoporotic diseases. Therefore, extrapolation of classical compartmental model simulations... 

While these models simulate the transfer of lead between many of the same physiological compartments, they use different methodologies to quantify lead exposure as well as the kinetics of lead transfer among the compartments. As described earlier, in contrast to PBPK models, classical pharmacokinetic models are calibrated to experimental data using transfer coefficients that may not have any physiological correlates. Examples of lead models that use PBPK and classical pharmacokinetic approaches are discussed in the following section, with a focus on the basis for model parameters, including age-specific blood flow rates and volumes for multiple body compartments, kinetic rate constants, tissue dosimetry,... 

One of the most frequently used methods for predicting human pharmacokinetics from animal data is allometry. This technique was initially used to explain the relationship between body size and organ weights in animals [62-67]. The approach is based on finding a correlation between a physiological and the pharmacokinetic parameter of interest. Generally the relationship takes the form of ... 

Another method of predicting human pharmacokinetics is physiologically based pharmacokinetics (PB-PK). The normal pharmacokinetic approach is to try to fit the plasma concentration-time curve to a mathematical function with one, two or three compartments, which are really mathematical constructs necessary for curve fitting, and do not necessarily have any physiological correlates. In PB-PK, the model consists of a series of compartments that are taken to actually represent different tissues [75-77] (Fig. 6.3). In order to build the model it is necessary to know the size and perfusion rate of each tissue, the partition coefficient of the compound between each tissue and blood, and the rate of clearance of the compound in each tissue. Although different sources of errors in the models have been... 

Lave, T., Coassolo, P., Reigner, B., Prediction of hepatic metabolic clearance based on interspecies allometric scaling techniques and in vitro-in vivo correlations, Clin. Pharmacokinet. 1999, 36, 211-321 and references cited therein. 

Calculated molecular properties from 3D molecular fields of interaction energies are a novel approach to correlate 3D molecular structures with pharmacodynamic, pharmacokinetic and physico-chemical properties. The novel VolSurf descriptors quantitatively characterize size, shape, polarity, hydrophobicity and the balance between them. 

Hirono, S., Nakagome, I., Hirano, H. Matsuhita, Y., Yoshi, F., Moriguchi, I., Non-congeneric structure-pharmacokinetic property correlation studies using fuzzy adaptive least squared oral bioavailability, Biol. Pharm. Bull. 1994, 37, 306—309. 

Gamelin E, Boisdron-Celle M, Guer-in-Meyer V et al. Correlation between uracil and dihydrouracil plasma ratio, fluorouracil (5-FU) pharmacokinetic parameters, and tolerance in patients with advanced colorectal cancer a potential interest for predicting 5-FU toxicity and determining optimal 5-FU dosage. J Clin Oncol 1999 17 1105-1110. 

Iyer L, Janisch L, Das S et al. UGT1A1 promoter genotype correlates with pharmacokinetics of irinotecan (CPT-11). Proc Am Soc Clin Oncol 2000 19 178a (abstract). 

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