Sun Kao-xiang

Bio: Sun Kao-xiang is an academic researcher from Yantai University. The author has an hindex of 1, co-authored 1 publications receiving 35 citations.

The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data

Abstract: Comprehensive retrospective approaches in which the abilities of several methods by which human pharmacokinetic parameters are predicted from preclinical pharmacokinetic data and/or in vitro metabolism data were reviewed.The prediction methods reviewed included those methods from scientific literatures.The prediction of main human pharmacokinetics parameters includes clearance(CL),volume of distribution(V_d),half life(t_(1/2)) and bioavailability using allometric scaling,animal-human proportionality,molecular structural parameters,physicochemical measurements,metabolism data in vitro.Such approaches should find utility in the drug discovery and development processes in the identification and selection of compounds that will possess appropriate pharmacokinetic characteristics in humans for progression to clinical trials.

Prediction of human drug clearance from in vitro and preclinical data using physiological-based and empirical approaches.

Abstract: No HeadingPurpose.The aim of this study is to compare the accuracy of five methods for predicting in vivo intrinsic clearance (CLint) and seven for predicting hepatic clearance (CLh) in humans using in vitro microsomal data and/or preclinical animal data.Methods.The human CLint was predicted for 33 drugs by five methods that used either in vitro data with a physiologic scaling factor (SF), with an empirical SF, with the physiologic and drug-specific (the ratio of in vivo and in vitro CLint in rats) SFs, or rat CLint directly and with allometric scaling. Using the estimated CLint, the CLh in humans was calculated according to the well-stirred liver model. The CLh was also predicted using additional two methods: using direct allometric scaling or drug-specific SF and allometry.Results.Using in vitro human microsomal data with a physiologic SF resulted in consistent underestimation of both CLint and CLh . This bias was reduced by using either an empirical SF, a drug-specific SF, or allometry. However, for allometry, there was a substantial decrease in precision. For drug-specific SF, bias was less reduced, precision was similar to an empirical SF. Both CLint and CLh were best predicted using in vitro human microsomal data with empirical SF. Use of larger data set of 52 drugs with the well-stirred liver model resulted in a best-fit empirical SF that is 9-fold increase on the physiologic SF.Conclusions.Overall, the empirical SF method and the drug-specific SF method appear to be the best methods; they show lower bias than the physiologic SF and better precision than allometric approaches. The use of in vitro human microsomal data with an empirical SF may be preferable, as it does not require extra information from a preclinical study.

Comparison of the use of liver models for predicting drug clearance using in vitro kinetic data from hepatic microsomes and isolated hepatocytes

Abstract: Purpose. To compare three liver models (well-stirred, parallel tube, and dispersion) for the prediction of in vivo intrinsic clearance (CLint), hepatic clearance (CLh), and hepatic availability (Fh) of a wide range of drugs in the rat using in vitro data from two in vitro sources. Methods. In vitro CLint was obtained from studies using isolated rat hepatocytes (35 drugs) or rat liver microsomes (52 drugs) and used to predict in vivo CLint using reported scaling factors, and subsequently CLh and Fh were predicted based on the three liver models. In addition, in vivo CLint values were calculated from the reported values of CLh based on each of the three models. Results. For all of the parameters, predictions from hepatocyte data were consistently more accurate than those from microsomal data. Comparison of in vitro and in vivo CLint values demonstrated that the dispersion model and the parallel tube model were comparable and more accurate (less bias, more precise) than the well-stirred model. For CLh and Fh prediction, the three models performed similarly. Conclusions. Considering the statistics of the predictions for three liver models, the use of parallel tube model is recommended for the evaluation of in vitro CLint values both from microsomes and hepatocytes. However, for the prediction of the in vivo drug (hepatic) clearance from in vitro data, as there are minimal differences between the models, the use of the well-stirred liver model is recommended.

Modelling and PBPK Simulation in Drug Discovery

Abstract: Physiologically based pharmacokinetic (PBPK) models are composed of a series of differential equations and have been implemented in a number of commercial software packages. These models require species-specific and compound-specific input parameters and allow for the prediction of plasma and tissue concentration time profiles after intravenous and oral administration of compounds to animals and humans. PBPK models allow the early integration of a wide variety of preclinical data into a mechanistic quantitative framework. Use of PBPK models allows the experimenter to gain insights into the properties of a compound, helps to guide experimental efforts at the early stages of drug discovery, and enables the prediction of human plasma concentration time profiles with minimal (and in some cases no) animal data. In this review, the application and limitations of PBPK techniques in drug discovery are discussed. Specific reference is made to its utility (1) at the lead development stage for the prioritization of compounds for animal PK studies and (2) at the clinical candidate selection and “first in human” stages for the prediction of human PK.

CYP3A4 Substrate Selection and Substitution in the Prediction of Potential Drug-Drug Interactions

Abstract: The complexity of in vitro kinetic phenomena observed for CYP3A4 substrates (homo- or heterotropic cooperativity) confounds the prediction of drug-drug interactions, and an evaluation of alternative and/or pragmatic approaches and substrates is needed. The current study focused on the utility of the three most commonly used CYP3A4 in vitro probes for the prediction of 26 reported in vivo interactions with azole inhibitors (increase in area under the curve ranged from 1.2 to 24, 50% in the range of potent inhibition). In addition to midazolam, testosterone, and nifedipine, quinidine was explored as a more "pragmatic" substrate due to its kinetic properties and specificity toward CYP3A4 in comparison with CYP3A5. Ki estimates obtained in human liver microsomes under standardized in vitro conditions for each of the four probes were used to determine the validity of substrate substitution in CYP3A4 drug-drug interaction prediction. Detailed inhibitor-related (microsomal binding, depletion over incubation time) and substrate-related factors (cooperativity, contribution of other metabolic pathways, or renal excretion) were incorporated in the assessment of the interaction potential. All four CYP3A4 probes predicted 69 to 81% of the interactions with azoles within 2-fold of the mean in vivo value. Comparison of simple and multisite mechanistic models and interaction prediction accuracy for each of the in vitro probes indicated that midazolam and quinidine in vitro data provided the best assessment of a potential interaction, with the lowest bias and the highest precision of the prediction. Further investigations with a wider range of inhibitors are required to substantiate these findings.

Comparison of Intrinsic Clearance in Liver Microsomes and Hepatocytes from Rats and Humans: Evaluation of Free Fraction and Uptake in Hepatocytes

Abstract: Apparent intrinsic clearance (CL(int,app)) of 7-ethoxycoumarin, phenacetin, propranolol, and midazolam was measured using rat and human liver microsomes and freshly isolated and cryopreserved hepatocytes to determine factors responsible for differences in rates of metabolism in these systems. The cryopreserved and freshly isolated hepatocytes generally provided similar results, although there was greater variability using the latter system. The CL(int,app) values in hepatocytes are observed to be lower than that in microsomes, and this difference becomes greater for compounds with high CL(int,app). This could partly be attributed to the differences in the free fraction (fu). The fu in hepatocyte incubations (fu,hep-inc) was influenced not only by the free fraction of compounds in the incubation buffer (fu,buffer) but also by the rate constants of uptake (k(up)) and metabolism (k(met)). This report provides a new derivation for fu,hep-inc, which can be expressed as fu,hep-inc = [k(up)/(k(met) + k(up))]/[1 + (C(hep)/C(buffer)) x (V(hep)/V(buffer))], where the C(hep), C(buffer), V(hep), and V(buffer) represent the concentrations of a compound in hepatocytes and buffer and volumes of hepatocytes and buffer, respectively. For midazolam, the fu,hep-inc was calculated, and the maximum metabolism rate in hepatocytes was shown to be limited by the uptake rate.