PBPK Modeling Characterizes the Impact of Administration Form and Drug-Drug Interaction on Aconitine

Research Article

Austin J Biotechnol Bioeng. 2024; 11(1): 1128.

PBPK Modeling Characterizes the Impact of Administration Form and Drug-Drug Interaction on Aconitine

Yue Gao1,2*; Yun-xuan Ge 1,2#; Zhuo Zhang2#; Xiao-Mei Zhuang3; Jia-Yi Yan2; Jing Gao2; Zeng-chun Ma2; Yu-guang Wang2

¹Faculty of Environment and Life, Beijing University of Technology, China

²Department of Pharmacology and Toxicology, Beijing Institute of Radiation Medicine, China

³State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, China

*Corresponding author: Yue Gao Faculty of Environment and Life, Beijing University of Technology, No. 100 Pingleyuan, Beijing 100124, China. Tel: +86 010 66931312 Email: gaoyue@nic.bmi.ac.cn

#These authors equally contributed this article

Received: January 11, 2024 Accepted: February 13, 2024 Published: February 20, 2024

Abstract

Aconitine (AC), the main efficient and toxic components of FUZI, has been studied extensively, but the investigation of appropriate in vivo pharmacokinetic model are limited. The aim of this study was to develop Physiologically Based Pharmacokinetic models (PBPK) to predict organ exposure in different doses and methods of administration. Moreover, Paeoniflorin (PAE) and Glycyrrhetinic Acid (GA) were selected to develop a Drug-Drug Interaction (DDI) model with AC. The developed AC-PBPK and relative DDI model of multiple perpetrator drugs was able to adequately describe plasma concentrations and tissue distribution in rats. Furthermore, drug exposure by different administration forms were compared. The effects of drug compatibility on the pharmacokinetics of AC in rats were revealed. This study constructed accurate AC-PBPK and its relative DDI model for the first time, which is suitable for rats with multi-doses and routes of administration. It can be extrapolated to predict the in vivo exposure of AC, solve the problem that the drug concentration in tissue is difficult to obtain, which is applied to clarify the ADME process and toxicity mechanism of AC.

Keywords: Aconitine; Physiologically based pharmacokinetic model; Drug-drug Interaction; Tissue distribution.

Introduction

Aconiti Lateralis Radix Praeparata (FUZI), is one of the famous traditional Chinese medicine, which known as "the primary medicine to restore yang and save reverse". The clinical application of FUZI in traditional Chinese medicine has a history of thousands of years and was mainly used for the deficiency of vital energy and the exhaustion of pulse. Aconitine (AC), is mainly pharmacologically active compounds and toxic ingredients of Aconiti Lateralis Radix Praeparata (FUZI). As the quality control components of FUZI, AC is closely related to the toxicity and efficacy of FUZI related preparations. For instance, according to the announcement on the catalogue of several drug standards issued by the China Food and drug administration (CFDA, Ws3-b - 3427-98-2013 Shenfu injection), the content of AC in Shenfu injection should be regulated at 0.1mg/ml to maintain the balance between efficacy and toxicity. However, the strong cardiotoxicity and neurotoxicity of AC make it severely resistant in clinical therapy, meanwhile, hepatotoxicity has been reported frequently. Scholars all over the world have studied the toxicity mechanism of AC. Wang et al. found aconitine induce apoptosis through mitochondrial-mediated and death receptor signaling pathways in HT22 cells [1]. Qing Xia discussed the developmental toxicity in zebrafish embryo/larvae induced by AC [2]. AC can prolong cardiac QT interval and induce liver cell apoptosis [3], resulting in cardiac and liver toxicity. With a narrow therapeutic index, serious toxic effect may occur even if the oral dose of AC is a little bit higher than the therapeutic dose. Existing research focused on the toxicological mechanisms of AC, but limited data are available on its Absorption, Distribution, Metabolism and Excretion (ADME) processes. Besides, the relationship between the change of in vivo concentration and compatibility detoxification was rarely reported. AC are mainly transported by P-glycoprotein (P-gp) [4]. P-gp is expressed in small intestinal epithelium, heart, liver and brain, which hinders in vivo absorption of AC. Cytochrome P450 enzyme (CYP450) is involved in the metabolism of diester Aconitum alkaloids in human liver [5]. As the metabolic substrate of CYP3A, AC is mainly metabolized by CYP3A1/2 in rats, which could decrease the toxicity after metabolism [6,7]. Licorice and Chinese herbaceous peony impact on the expression of metabolic enzymes, mainly CYP3A1/2 in rat liver [8,9], and accelerate the metabolism of AC in rat liver microsomes, which reduce the toxicity of AC [10,11]. Glycyrrhetinic Acid (GA) and Paeoniflorin (PAE), the main component of licorice and Chinese herbaceous peony, can also affect the expression of CYP450 enzyme and P-gp [9,12]. Above all, we hypothesis the reduction exposure of AC may be induced by GA and PAE through CYP3A and P-gp.

Lack of effective methods to predict toxicity limited the application of AC. In recent years, Physiologically Based Pharmacokinetic (PBPK) model has been widely concerned for a powerful tool to quantitatively delineate how certain extrinsic and intrinsic factors might influence the nonproportional systemic exposures [13,14]. Because it can accurately predict the ADME process and organ exposure based on drug-dependent physicochemical and PK parameters as well as drug-independent physiologic systemic parameters, PBPK model is widely used in the prediction of new Drug-Drug Interaction (DDI) [15,16]. However, there are few reports on the prediction of target organ exposure of toxic components of traditional Chinese medicine by PBPK model. This study intends to establish a PBPK model approach to predict AC exposures in rats after various routes of administration and the effect of GA and PAE on the in vivo concentration of AC. To achieve this, key in vitro and in vivo paraments for AC were collected. Then a bottom-up combined with top-down PBPK model was developed and applied in the assessment of linear PK in rats, at least from the range of 0.5mg/ kg to 1.5mg/ kg. Finally, a DDI-PBPK model was built to predict the effect of DDI drug on the in vivo process of AC.

Materials and Methods

Simulation of PBPK Models

The physicochemical and biopharmaceutical parameters required for drug modeling were obtained by consulting the literature. The missing parameters are predicted by ADMET predictor (Table 1). Import the modeled compound structure into gastro plus software (simulations plus, Inc., California, United States), and input the parameters obtained from literature, predicted parameters and relevant pharmacokinetic parameters obtained from experiments (including metabolism, transport related parameters and measured tissue/plasma partition coefficient) into the software. Advanced Atrioventricular Absorption and Transport (ACAT) model was used to simulate the concentration time curve, and the individual PBPK models of each compound were established respectively. The established rat PBPK model was further optimized by the observed values and work flow was listed as (Figure 1).