Metabolic profiles for the pyrrolizidine alkaloid neopetasitenine and its metabolite petasitenine in humans extrapolated from rat in vivo and in vitro data sets using a simplified physiologically based pharmacokinetic model

PBPK Modeling as an Alternative Method of Interspecies Extrapolation that Reduces the Use of Animals: A Systematic Review

INTRODUCTION

Physiologically based pharmacokinetic (PBPK) modeling is a computational approach that simulates the anatomical structure of the studied species and presents the organs and tissues as compartments interconnected by arterial and venous blood flows.

AIM

The aim of this systematic review was to analyze the published articles focused on the development of PBPK models for interspecies extrapolation in the disposition of drugs and health risk assessment, presenting to this modeling an alternative to reduce the use of animals.

METHODS

For this purpose, a systematic search was performed in PubMed using the following search terms: "PBPK" and "Interspecies extrapolation". The revision was performed according to PRISMA guidelines.

RESULTS

In the analysis of the articles, it was found that rats and mice are the most commonly used animal models in the PBPK models; however, most of the physiological and physicochemical information used in the reviewed studies were obtained from previous publications. Additionally, most of the PBPK models were developed to extrapolate pharmacokinetic parameters to humans and the main application of the models was for toxicity testing.

CONCLUSION

PBPK modeling is an alternative that allows the integration of in vitro and in silico data as well as parameters reported in the literature to predict the pharmacokinetics of chemical substances, reducing in large quantity the use of animals that are required in traditional studies.

Revisiting Migraine: The Evolving Pathophysiology and the Expanding Management Armamentarium

Migraine affects about one billion people worldwide yearly and is one of the most common neurologic illnesses, with a high prevalence and morbidity, particularly among young adults and females. Migraine is associated with many comorbidities, including stress, sleep difficulties, and suicidal ideation. Migraine, despite its widespread occurrence, is underdiagnosed and undertreated. Because of the complicated and primarily unknown mechanisms of migraine formation, several social and biological risk factors, such as hormone imbalances, genetic and epigenetic impacts, and cardiovascular, neurological, and autoimmune illnesses, have been proposed. Through the mid-20th century diversion of the now-defunct vascular theory, the pathophysiology of migraine has developed from a historical study of the "humours" to a distinct entity as a neurological disorder. The range of therapeutic targets has broadened significantly, increasing the number of specialized clinical trials. Understanding the biology of migraine through careful research has resulted in the identification of major therapeutic classes: (i) triptans, serotonin 5-HT1B/1D receptor agonists, (ii) gepants, calcitonin gene-related peptide (CGRP) receptor antagonists, (iii) ditans, 5-HT1F receptor agonists, (iv) CGRP monoclonal antibodies, and (v) glurants, mGlu5 modulators, with further targets being explored. This review provides a comprehensive overview of the most recent literature on epidemiology and risk factors and exposes knowledge gaps.

Utilization of Physiologically Based Pharmacokinetic Modeling in Pharmacokinetic Study of Natural Medicine: An Overview

Natural medicine has been widely used for clinical treatment and health care in many countries and regions. Additionally, extracting active ingredients from traditional Chinese medicine and other natural plants, defining their chemical structure and pharmacological effects, and screening potential druggable candidates are also uprising directions in new drug research and development. Physiologically based pharmacokinetic (PBPK) modeling is a mathematical modeling technique that simulates the absorption, distribution, metabolism, and elimination of drugs in various tissues and organs in vivo based on physiological and anatomical characteristics and physicochemical properties. PBPK modeling in drug research and development has gradually been recognized by regulatory authorities in recent years, including the U.S. Food and Drug Administration. This review summarizes the general situation and shortcomings of the current research on the pharmacokinetics of natural medicine and introduces the concept and the advantages of the PBPK model in the study of pharmacokinetics of natural medicine. Finally, the pharmacokinetic studies of natural medicine using the PBPK models are summed up, followed by discussions on the applications of PBPK modeling to the enzyme-mediated pharmacokinetic changes, special populations, new drug research and development, and new indication adding for natural medicine. This paper aims to provide a novel strategy for the preclinical research and clinical use of natural medicine.

Updated in Silico Prediction Methods for Fractions Absorbed and Key Input Parameters of 355 Disparate Chemicals for Physiologically Based Pharmacokinetic Models for Time-Dependent Plasma Concentrations after Virtual Oral Doses in Humans

Human metabolic profiles for substances such as toxic food-derived compounds are usually allometrically extrapolated from traditionally determined in vivo rat concentration profiles. To evaluate internal exposures in humans without any reference to experimental data, physiologically based pharmacokinetic (PBPK) modeling could be used if the model input parameters could be estimated in silico. This approach would simplify the use of PBPK models for forward dosimetry after oral doses. In this study, the in silico estimation of input parameters for PBPK models (i.e., fraction absorbed × intestinal availability, absorption rate constants, and volumes of the systemic circulation) was updated for an panel of 355 chemicals (212 previously analyzed and 143 additional substances) using a light gradient boosting machine learning algorithms (LightGBM) based on between 11 and 29 in silico-calculated chemical descriptors. Simplified human PBPK models were then used to calculate virtual maximum plasma concentrations (C_max) and areas under the concentration-time curve (AUC) based on two sets of input parameters, i.e., traditionally derived values from in vivo data and those calculated in silico using the current updated systems. Both sets of C_max and AUC data were well correlated (r = 0.87 and r = 0.73, respectively; p < 0.01, n = 355). Therefore, input parameters for human PBPK models for a diverse range of compounds could be successfully estimated using chemical descriptors and in silico tools. This approach to pharmacokinetic modeling has potential for application in computational toxicology and in the clinical setting for assessing the potential risk of general chemicals.

A review on the ethnobotany, phytochemistry, pharmacology and toxicology of butterbur species (Petasites L.)

ETHNOPHARMACOLOGICAL RELEVANCE

Petasites (butterbur, Asteraceae) species have been used since Ancient times in the traditional medicine of Asian and European countries to treat central nervous system (migraine), respiratory (asthma, allergic rhinitis, bronchitis, spastic cough), cardiovascular (hypertension), gastrointestinal (ulcers) and genitourinary (dysmenorrhea) disorders.

AIM OF THE REVIEW

This study summarized and discussed the traditional uses, phytochemical, pharmacological and toxicological aspects of Petasites genus.

MATERIALS AND METHODS

A systematic search of Petasites in online databases (Scopus, PubMed, ScienceDirect, Google Scholar) was performed, with the aim to find the phytochemical, toxicological and bioactivity studies. The Global Biodiversity Information Facility, Plants of the World Online, World Flora Online and The Plant List databases were used to describe the taxonomy and geographical distribution.

RESULTS

The detailed phytochemistry of the potentially active compounds of Petasites genus (e.g. sesquiterpenes, pyrrolizidine alkaloids, polyphenols and essential oils components) was presented. The bioactivity studies (cell-free, cell-based, animal, and clinical) including the traditional uses of Petasites (e.g. anti-spasmolytic, hypotensive, anti-asthmatic activities) were addressed and followed by discussion of the main pharmacokinetical and toxicological issues related to the administration of butterbur-based formulations.

CONCLUSIONS

This review provides a complete overview of the Petasites geographical distribution, traditional use, phytochemistry, bioactivity, and toxicity. More than 200 different sesquiterpenes (eremophilanes, furanoeremophilanes, bakkenolides), 50 phenolic compounds (phenolic acids, flavonoids, lignans) and volatile compounds (monoterpenes, sesquiterpenes) have been reported within the genus. Considering the phytochemical complexity and the polypharmacological potential, there is a growing research interest to extend the current therapeutical applications of Petasites preparations (anti-migraine, anti-allergic) to other human ailments, such as central nervous system, cardiovascular, malignant or microbial diseases. This research pathway is extremely important, especially in the recent context of the pandemic situation, when there is an imperious need for novel drug candidates.

Plasma concentration profiles for hepatotoxic pyrrolizidine alkaloid senkirkine in humans extrapolated from rat data sets using a simplified physiologically based pharmacokinetic model

AIM

The main aim of the current study was to obtain forward dosimetry assessments of pyrrolizidine alkaloid senkirkine plasma and liver concentrations by setting up a human physiologically based pharmacokinetic (PBPK) model based on the limited information available.

BACKGROUND

The risks associated with plant-derived pyrrolizidine alkaloids as natural toxins have been assessed.

OBJECTIVE

The pyrrolizidine alkaloid senkirkine was investigated because it was analyzed in a European transcriptomics study of natural hepatotoxins and in a study of the alkaloidal constituents of traditional Japanese food plants Petasites japonicus. The in silico human plasma and liver concentrations of senkirkine were modeled using doses reported for acute-term toxicity in humans.

METHODS

Using a simplified PBPK model established using rat pharmacokinetic data, forward dosimetry was conducted. Since in vitro rat and human intrinsic hepatic clearances were similar; an allometric scaling approach was applied to rat parameters to create a human PBPK model.

RESULTS

After oral administration of 1.0 mg/kg in rats in vivo, water-soluble senkirkine was absorbed and cleared from plasma to two orders of magnitude below the maximum concentration in 8 h. Human in silico senkirkine plasma concentration curves were generated after virtual daily oral administrations of 3.0 mg/kg senkirkine (the dose involved in an acute fatal hepatotoxicity case). A high concentration of senkirkine in the culture medium caused in vitro hepatotoxicity as evidenced by lactate dehydrogenase leakage from human hepatocyte-like HepaRG cells.

CONCLUSION

Higher virtual concentrations of senkirkine in human liver and plasma than those in rat plasma were estimated using the current rat and human PBPK models. Current simulations suggest that if P. japonicus (a water-soluble pyrrolizidine alkaloid-producing plant) is ingested daily as food, hepatotoxic senkirkine could be continuously present in human plasma and liver.

Pharmacokinetics of primary metabolites 5-hydroxythalidomide and 5'-hydroxythalidomide formed after oral administration of thalidomide in the rabbit, a thalidomide-sensitive species

The teratogenicity of the chemotherapeutic drug thalidomide is species-specific and affects humans, non-human primates, and rabbits. The primary oxidation of thalidomide in previously investigated rodents predominantly resulted in the formation of deactivated 5'-hydroxythalidomide. In the current study, similar in vivo biotransformations to 5-hydroxythalidomide and 5'-hydroxythalidomide were confirmed by the analysis of blood plasma from male rabbits, a thalidomide-sensitive species, after oral administration of thalidomide (2.0 mg/kg). Similar levels of thalidomide in seminal plasma and in blood plasma were detected using liquid chromatography-tandem mass spectrometry at 4 hr and 7 hr after oral doses in male rabbits. Seminal plasma concentrations of 5-hydroxythalidomide and 5'-hydroxythalidomide were also seen in male rabbits in a roughly similar time-dependent manner to those in the blood plasma after oral doses of thalidomide (2.0 mg/kg). Furthermore, the values generated by a simplified physiologically based pharmacokinetic rabbit model were in agreement with the measured in vivo blood plasma data under metabolic ratios of 0.01 for the hepatic intrinsic clearance of thalidomide to both unconjugated 5-hydroxythalidomide and 5'-hydroxythalidomide. These results suggest that metabolic activation of thalidomide may be dependent on rabbit liver enzymes just it was for cytochrome P450 enzymes in humanized-liver mice; in contrast, rodent livers predominantly mediate biotransformation of thalidomide to 5'-hydroxythalidomide. A developmental toxicity test system with experimental animals that involves intravaginal exposures to the chemotherapeutic drug thalidomide via semen should be considered in the future.

Machine Learning Prediction of the Three Main Input Parameters of a Simplified Physiologically Based Pharmacokinetic Model Subsequently Used to Generate Time-Dependent Plasma Concentration Data in Humans after Oral Doses of 212 Disparate Chemicals

Physiologically based pharmacokinetic (PBPK) modeling has the potential to play significant roles in estimating internal chemical exposures. The three major PBPK model input parameters (i.e., absorption rate constants, volumes of the systemic circulation, and hepatic intrinsic clearances) were generated in silico for 212 chemicals using machine learning algorithms. These input parameters were calculated based on sets of between 17 and 65 chemical properties that were generated by in silico prediction tools before being processed by machine learning algorithms. The resulting simplified PBPK models were used to estimate plasma concentrations after virtual oral administrations in humans. The estimated absorption rate constants, volumes of the systemic circulation, and hepatic intrinsic clearance values for the 212 test compounds determined traditionally (i.e., based on fitting to measured concentration profiles) and newly estimated had correlation coefficients of 0.65, 0.68, and 0.77 (p < 0.01, n = 212), respectively. When human plasma concentrations were modeled using traditionally determined input parameters and again using in silico estimated input parameters, the two sets of maximum plasma concentrations (r = 0.85, p < 0.01, n = 212) and areas under the curve (r = 0.80, p < 0.01, n = 212) were correlated. Virtual chemical exposure levels in liver and kidney were also estimated using these simplified PBPK models along with human plasma levels. These results indicate that the PBPK model input parameters for humans of a diverse set of compounds can be reliability estimated using chemical descriptors calculated using in silico tools.