A Pharmacokinetic Study On Rats’ Liver Of Sorafenib Solid Lipid Nanoparticle Based On Artificial Neural Network Model

In the last twenty years,development of novel targeting drug delivery system(TDDS)is the hotspot in drug research and development globally.Up to date,however,there is few research about the pharmacokinetic properties of the drug on the targeting site,which is the main reason why TDDS preparations were not used widely in clinic.Therefore,it is difficult to evaluate and improve the quality of TDDS’s preparations and adjust drug dosage according to the drug concentrations on the target site.Indeed,the drug concentration on target site and plasma drug concentrations nonlinear for TDDS’s preparations,which is different from the common preparations.Thus,the plasma drug concentration-time profile of TDDS’s preparations can not directly reflect the physiological disposition of drug in vivo.Therefore,how to dynamically and continuously obtain the drug concentration on the targeting site in one individual is the basis for clarify the physiological disposition of TDDS’s preparations.It is also the main technical bottleneck in building a pharmacokinetic model for drug on targeting site..In this study,solid lipid nanoparticles(SLN)was used as a new drug delivery system,sorafenib(SRF)and SLN loaded SRF(SRF-SLN)were the objects of in this research.After rats were orally administer SRF(and SRF-SLN),an artificial neural network(ANN)in high prediction accuracy was developed and validated.The blood concentrations of SRF and its metabolites were regarded as the ANN input parameters,whereas the contents of the in vivo drugs at the target sites and at different time points were designated as the output parameters.On this basis,the established ANN model allowed the determination of the hepatic contents of SRF in the same experimental animal at different time points from the blood SRF and its metabolites concentrations after drug treatment.The resultant data were adopted to generate hepatic SRF content–time curves and the pharmacokinetic parameters of SRF(and SLFN-SLN)in liver could be obtained.This method is novel and has never been reported previously.It may also provide new approach for pharmacokinetic study,thereby adding potential value to the targeting preparations under investigation.In this dissertation,the main research works are as follows:1.A HPLC-UV method was established for determination of the concentration of SRF and its metabolites in blood,liver and kidney tissue extracts.The HPLC conditions are as follows:Venusil AA C18 chromatographic column was used in this dissertation;mobile phase was acetonitrile:0.1%formic acid=40:60;flow rate was0.8 ml/min;detected wavelength was 265 nm;column temperature was 38℃.The calibration curve of the SRF is linear over the low(0.1μg/m L)and high concentration(20.0μg/m L)ranges,with r~2>0.999.This HPLC-UV method was validated to be good repeatability and stability for measuring SRF and its metabolites in vivo.The relative standard deviation(R.S.D.)of intra-day and inter-day assays were less than 3%and the method recovery was from 83.21%to96.10%in low and high concentrations.Our results indicated that the developed method was satisfactory for simultaneously measuring SRF and its metabolites in blood,liver and kidney tissue extracts.2.The main metabolites of SRF in rats after oral administration were identify and confirmed by a LC/MS/MS method.Our results showed that N-methylhydroxylation sorafenib(OH-SRF)and N-demethylation sorafenib(DM-SRF)were the main metabolites of SRF in rats.3.Glyceryl behenate,soybean lecithin,poloxamer 188 and SRF were used as the raw materials to prepare SRF-SLN by the high-speed shear combination of ultrasonic method.The recipes of SRF-SLN was optimized and various parameters such as particle size,zeta-potential,entrapment efficiency,stability and release behavior in vitro were employed to evaluate the products.Our results showed that the average entrapment efficiency of SRF-SLN was 89.87%,determined by flocculation method which is simple,feasible and accurate.The average particle size was 77.16nm,polydispersity(PDI)was 0.28 and the zeta potential was-18.1.Stability test showed that SRF-SLN could keep stable for more than 1 month at room temperature.The distribution characteristics showed that the SRF-SLN had a good liver targeting property.4.An ANN model for prediction of hepatic SRF content from SRF and its metabolites concentrations in plasma were developed and validated with high prediction accuracy.Time,plasma concentration of SRF and its metabolites were selected as neural network input parameters,the SRF content in liver was the output parameter.The results revealed that the Elman neural network using time,plasma concentration of SRF and sorafenib metabolites(three parameters)as the input parameters had the highest prediction accuracy,the average prediction accuracy of sorafenib suspension in liver and kidney were 91.54%and 93.62%respectively,and the average prediction accuracy of SRF-SLN in liver was 91.32%.The pharmacokinetic parameters of SRF suspension and SRF-SLN in targeting site were obtained based on the ANN model.The experimental results could provide a new method for evaluation of SRF-SLN and obtaining pharmacokinetic parameters in targeting sites in vivo.