Development and validation of a sensitive UPLC-MS/MS analytical method for GFH009 in rat plasma and its application to toxicokinetics studies.

GFH009 is a potent, highly selective, small molecule that targets and inhibits the activity of the CDK9/cyclin T1 regulatory complex of P-TEFb. This study aimed to develop and validate a highly selective and sensitive ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for precise quantification of GFH009 in rat plasma. This method was subsequently employed for conducting toxicokinetic studies of GFH009 in rats. Plasma was prepared using a simple protein precipitation method by acetonitrile. Chromatographic separation of the analytes was achieved on a BEH C18 analytical column with a rapid 3.0 min run time and a flow rate of 0.5 ml/min. The calibration curves for plasma samples exhibited excellent linearity over a wide concentration range of 1.0-1,000 ng/ml for GFH009. Intra- and inter-day accuracies were within 92.7-105.7%, and precisions were no more than 6.7%. Furthermore, the analyte demonstrated stability under four different storage conditions, with variations of <15.0%. This study pioneers a methodological innovation by introducing a highly reliable, specific and sensitive analytical method for GFH009 in rat plasma. The successful application of this method in toxicokinetic studies further underscores its significance, offering valuable insights for the methodology of clinical pharmacokinetic research.

Enhancing drug-drug Interaction Prediction by Integrating Physiologically-Based Pharmacokinetic Model with Fraction Metabolized by CYP3A4.

BACKGROUND: Enhancing the precision of drug-drug interaction (DDI) prediction is essential for improving drug safety and efficacy. The aim is to identify the most effective fraction metabolized by CY3A4 (fm) for improving DDI prediction using physiologically based pharmacokinetic (PBPK) models. RESEARCH DESIGN AND METHODS: The fm values were determined for 33 approved drugs using a human liver microsome for in vitro measurements and the ADMET Predictor software for in silico predictions. Subsequently, these fm values were integrated into PBPK models using the GastroPlus platform. The PBPK models, combined with a ketoconazole model, were utilized to predict AUCR (AUCcombo with ketoconazole/AUCdosing alone), and the accuracy of these predictions was evaluated by comparison with observed AUCR. RESULTS: The integration of in vitro fm method demonstrates superior performance compared to the in silico fm method and fm of 100% method. Under the Guest-limits criteria, the integration of in vitro fm achieves an accuracy of 76%, while the in silico fm and fm of 100% methods achieve accuracies of 67% and 58%, respectively. CONCLUSIONS: Our study highlights the importance of in vitro fm data to improve the accuracy of predicting DDIs and demonstrates the promising potential of in silico fm in predicting DDIs.

Mechanism-Based Pharmacokinetic Model for the Deglycosylation Kinetics of 20(S)-Ginsenosides Rh2.

Aim: The 20(S)-ginsenoside Rh2 (Rh2) is being developed as a new antitumor drug. However, to date, little is known about the kinetics of its deglycosylation metabolite (protopanoxadiol) (PPD) following Rh2 administration. The aim of this work was to 1) simultaneously characterise the pharmacokinetics of Rh2 and PPD following intravenous and oral Rh2 administration, 2) develop and validate a mechanism-based pharmacokinetic model to describe the deglycosylation kinetics and 3) predict the percentage of Rh2 entering the systemic circulation in PPD form. Methods: Plasma samples were collected from rats after the I.V. or P.O. administration of Rh2. The plasma Rh2 and PPD concentrations were determined using HPLC-MS. The transformation from Rh2 to PPD, its absorption, and elimination were integrated into the mechanism based pharmacokinetic model to describe the pharmacokinetics of Rh2 and PPD simultaneously at 10 mg/kg. The concentration data collected following a 20 mg/kg dose of Rh2 was used for model validation. Results: Following Rh2 administration, PPD exhibited high exposure and atypical double peaks. The model described the abnormal kinetics well and was further validated using external data. A total of 11% of the administered Rh2 was predicted to be transformed into PPD and enter the systemic circulation after I.V. administration, and a total of 20% of Rh2 was predicted to be absorbed into the systemic circulation in PPD form after P.O. administration of Rh2. Conclusion: The developed model provides a useful tool to quantitatively study the deglycosylation kinetics of Rh2 and thus, provides a valuable resource for future pharmacokinetic studies of glycosides with similar deglycosylation metabolism.

Predicting the Drug-Drug Interaction Mediated by CYP3A4 Inhibition: Method Development and Performance Evaluation.

The prediction of drug-drug interactions (DDIs) plays critical roles for the estimation of DDI risk caused by inhibition of CYP3A4. The aim of this paper is to develop a physiologically based pharmacokinetic (PBPK)-DDI model for prediction of the DDI co-administrated with ketoconazole in humans and evaluate the predictive performance of the model. The pharmacokinetic and biopharmaceutical properties of 35 approved drugs, as victims, were collected for the development of a PBPK model, which were linked to the PBPK model of ketoconazole for the DDI prediction. The PBPK model of victims and ketoconazole were validated by matching actual in vivo pharmacokinetic data. The predicted results of DDI were compared with actual data to evaluate the predictive performance. The percentage of predicted ratio of AUC (AUCR), Cmax (CmaxR), and Tmax (TmaxR) was 75%, 69%, and 91%, respectively, which were within the twofold threshold (range, 0.5-2.0×) of the observed values. Only 3% of the predicted AUCRs are obviously underestimated. After integration of the reported fraction of metabolism (fm) into the PBPK-DDI model for limited four cases, the model-predicted AUCRs were improved from the twofold range of the observed AUCRs to the 90% confidence interval. The developed method could reasonably predict drug-drug interaction with a low risk of underestimation. The present accuracy of the prediction was improved compared with that of static mechanistic models. The evaluation of predictive performance increases the confidence using the model to evaluate the risk of DDIs co-administrated with ketoconazole before the in vivo DDI study.

Evaluation of Generic Methods to Predict Human Pharmacokinetics Using Physiologically Based Pharmacokinetic Model for Early Drug Discovery of Tyrosine Kinase Inhibitors.

BACKGROUND: Requirements for predicting human pharmacokinetics in drug discovery are increasing. Developing different methods of human pharmacokinetic prediction will facilitate lead optimization, candidate nomination, and dosing regimens before clinical trials at various early drug discovery stages. OBJECTIVES: To develop and validate generic methods of human pharmacokinetic prediction to meet the requirements in early drug discovery. METHODS: The physiologically based pharmacokinetic (PBPK) model implemented in Gastroplus™ was used for human pharmacokinetic predictions. The absorption, distribution, metabolism, and excretion properties of drugs in humans predicted from molecular structure and extrapolated from tested preclinical data were used as inputs in the PBPK model. The approaches were validated by comparison of the predicted pharmacokinetic parameters with actual pharmacokinetic parameters of 15 marketed small-molecule compounds approved by the US Food and Drug Administration. Based on the validation and reported approaches, we proposed a strategy for human pharmacokinetic prediction at different drug discovery stages. RESULTS: Obvious underestimation of exposure (< 1/3 of actual exposure) was not observed using in silico prediction as inputs, which may reduce the probability of missing the potential compounds with predicted false low exposure. The simulated human pharmacokinetic results using tested data as inputs were superior to those obtained via in silico prediction. Both methods similarly predicted the multiphasic shape of pharmacokinetic profiles. CONCLUSION: These generic PBPK approaches of full in silico prediction or perdition using a combination of tested in vivo and in vitro data were validated and proved useful for human pharmacokinetic predictions.

Correction to: Evaluation of Generic Methods to Predict Human Pharmacokinetics Using Physiologically Based Pharmacokinetic Model for Early Drug Discovery of Tyrosine Kinase Inhibitors.

The original version of this article unfortunately contained a mistake. Conflict of interest statement was incorrect. The corrected COI statement is given below.

Sensitive determination of 20(S)-protopanaxadiol in rat plasma using HPLC-APCI-MS: application of pharmacokinetic study in rats.

20(S)-Protopanaxadiol (PPD), the main metabolite of protopanoxadiol type ginsenosides (e.g. Rg3 and Rh2), is a very promising anti-cancer drug candidate. To evaluate the pharmacokinetic property of PPD, we reported a reliable, sensitive and simple method utilizing liquid chromatography (HPLC)-atmospheric pressure chemical ionization-mass spectrometry (APCI-MS) to determine PPD. PPD and the internal standard, panoxadiol (PD) were extracted from plasma with acetic ether, separated on a C18 reverse column, and then analyzed by APCI-MS. Targeting fragment ion at m/z 425 for both PPD and PD was monitored in selected-ion monitoring (SIM) mode. PPD can be quantitatively determined at the concentration as low as 1 ng/mL using 200 microL plasma. And the sensitive method showed excellent linearity over a range from 1 to 1000 ng/mL, high recovery, accuracy and precision at the concentrations of 2.5, 100.0 and 1000.0 ng/mL, respectively. The method was successfully applied to pharmacokinetic study of PPD in rats. Pharmacokinetic parameters were calculated and absolute bioavailability of PPD was 36.8+/-12.4%, at least ten times higher than that of Rg3 and Rh2, indicating its good absorption in gastrointestinal tract. It was further suggested that PPD be a promising anti-cancer candidate and probably responsible for the observed pharmacological activity of Rg3 and Rh2.

Simultaneous determination of GFA and its active metabolites in human plasma by liquid chromatography electrospray ionization mass spectrometry and its application to pharmacokinetic studies.

A sensitive and rapid liquid chromatography electrospray ionization mass spectrometry (LC-ESI-MS) method has been developed and validated for simultaneous quantification of guanfu base A (GFA) and its metabolites guanfu base I (GFI) and guanfu alcohol-amine (AA) in human plasma with phenoprolamine hydrochloride (DDPH) as the internal standard. The analytes were extracted from human plasma by using liquid-liquid extraction with ethyl acetate and the LC separation was performed on a Diamonsil C(18) analytical column (150 mm x 2.1 mm i.d., 5 microm). The MS acquisition was performed in selected ion monitoring (SIM) mode of positive ions. Analysis was carried out in SIM mode at m/z 430.25 for GFA [M+H](+), m/z 388.25 for GFI [M+H](+), m/z 346.25 for AA [M+H](+) and m/z 344.20 for the IS DDPH [M+H](+). The calibration curves were linear over the range of 50-5000 ng/mL for GFA and 5-1000 ng/mL for GFI and AA, with coefficients of correlation above 0.999. The lower limit of quantification for GFA was 1 ng/mL, while for GFI and AA were both 5 ng/mL. The intra- and inter-day precisions (CV) of analysis were within 9%, and the accuracy ranged from 91% to 108%. The overall recoveries for GFA, GFI and AA were about 94.2%, 87.8% and 80.6%, respectively. The total LC-MS run-time was only 5.5 min. This quantitation method was successfully applied to the simultaneous determination of GFA and its metabolites in human plasma for the metabolic study and pharmacokinetic evaluation.

Pharmacokinetic study with N-Ile1-Thr2-63-desulfato-r-hirudin in rabbits by means of bioassay.

AIM: To study the pharmacokinetic (PK) properties in rabbits treated with N-Ile(1)-Thr(2)-63-desulfato-r-hirudin (rH) newly developed in China by means of bioassay in order to provide preclinical experiment basis for its development as a novel anticoagulant agent. METHODS: rH plasma concentration was determined using bioassay based on ex vivo antithrombin activity of rH. Normal rabbits received iv rH 4.0, 2.0 and 1.0 mg/kg or sc rH 2.0 mg/kg, respectively. The rabbits with acute severe renal failure were given iv rH 2.0 mg/kg. RESULTS: The bioassay described in this paper met requirements for study of PK in rabbits. The major PK parameters after iv dosing were as follows: t(1/2beta) 58.4-59 min. V(d) 0.09-0.12 L/kg, CL 0.0035-0.0040 L/(kg.min); AUC were proportional to the doses, t(1/2) and CL did not change significantly with the doses. The sc bioavailability reached 94%. The rabbits suffering from acute severe renal failure presented 11-fold longer t(1/2beta) and 13-fold greater AUC than normal healthy rabbits. CONCLUSION: rH exhibited rapid elimination, distribution was only limited to extracellular space and good absorption from sc site. The excretion of rH by kidneys played a very important role in the elimination of rH. The PK of rH could be described by the two- and one-compartment model after iv and sc dosing, respectively, and followed linear kinetics.