動注化学療法における pharmacokinetics と臨床

Background: The importance of polyphenols in human health is well known; these compounds are common in foods, such as fruits, vegetables, spices, extra virgin olive oil and wine. On the other hand, the different factors that modulate the biological activity of these compounds are less well known. Conceptualization of the work: In this review we took into account about 200 relevant and recent papers on the following topics: “polyphenols bioavailability”, “polyphenols matrix effect”, “food matrix effect”, “polyphenols-cytochromes interaction”, after having reviewed and updated information on chemical classification and main biological properties of polyphenols, such as the antioxidant, anti-radical and anti-inflammatory activity, together with the tricky link between in vitro tests and clinical trials. Key findings: the issue of polyphenols bioavailability and matrix effect should be better taken into account when health claims are referred to polyphenols, thus considering the matrix effect, enzymatic interactions, reactions with other foods or genetic or gender characteristics that could interfere. We also discovered that in vitro studies often underrate the role of phytocomplexes and thus we provided practical hints to describe a clearer way to approach an investigation on polyphenols for a more resounding transfer to their use in medicine.

Polyphenols: From Theory to Practice

Millions of experimental animals are widely used in the assessment of toxicological or biological effects of manufactured nanomaterials in medical technology. However, the animal consciousness has increased and become an issue for debate in recent years. Currently, the principle of the 3Rs (i.e., reduction, refinement, and replacement) is applied to ensure the more ethical application of humane animal research. In order to avoid unethical procedures, the strategy of alternatives to animal testing has been employed to overcome the drawbacks of animal experiments. This article provides current alternative strategies to replace or reduce the use of experimental animals in the assessment of nanotoxicity. The currently available alternative methods include in vitro and in silico approaches, which can be used as cost-effective approaches to meet the principle of the 3Rs. These methods are regarded as non-animal approaches and have been implemented in many countries for scientific purposes. The in vitro experiments related to nanotoxicity assays involve cell culture testing and tissue engineering, while the in silico methods refer to prediction using molecular docking, molecular dynamics simulations, and quantitative structure–activity relationship (QSAR) modeling. The commonly used novel cell-based methods and computational approaches have the potential to help minimize the use of experimental animals for nanomaterial toxicity assessments.

Current Strategies in Assessment of Nanotoxicity: Alternatives to In Vivo Animal Testing

Abstract Background Conventional preclinical models often miss drug toxicities, meaning the harm these drugs pose to humans is only realized in clinical trials or when they make it to market. This has caused the pharmaceutical industry to waste considerable time and resources developing drugs destined to fail. Organ-on-a-Chip technology has the potential to improve success in drug development pipelines, as it can recapitulate organ-level pathophysiology and clinical responses; however, systematic and quantitative evaluations of Organ-Chips’ predictive value have not yet been reported. Methods 870 Liver-Chips were analyzed to determine their ability to predict drug-induced liver injury caused by small molecules identified as benchmarks by the Innovation and Quality consortium, who has published guidelines defining criteria for qualifying preclinical models. An economic analysis was also performed to measure the value Liver-Chips could offer if they were broadly adopted in supporting toxicity-related decisions as part of preclinical development workflows. Results Here, we show that the Liver-Chip met the qualification guidelines across a blinded set of 27 known hepatotoxic and non-toxic drugs with a sensitivity of 87% and a specificity of 100%. We also show that this level of performance could generate over $3 billion annually for the pharmaceutical industry through increased small-molecule R&amp;D productivity. Conclusions The results of this study show how incorporating predictive Organ-Chips into drug development workflows could substantially improve drug discovery and development, allowing manufacturers to bring safer, more effective medicines to market in less time and at lower costs. 

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Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology

Targeted extracellular vesicle delivery systems employing superparamagnetic iron oxide nanoparticles.

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

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Computational Approaches in Preclinical Studies on Drug Discovery and Development.

Objective: The aim of this study was to establish a population pharmacokinetic (PPK) model of valproic acid (VPA) in pediatric patients with epilepsy in southern China, and provide guidance for individualized medication of VPA therapy. Methods: A total of 376 VPA steady-state trough concentrations were collected from 103 epileptic pediatric patients. The PPK parameter values for VPA were calculated by using the nonlinear mixed-effects modeling (NONMEM) method, and a one-compartment model with first-order absorption and elimination processes was applied. Covariates included demographic information, concomitant medications and selected gene polymorphisms. Goodness-of-fit (GOF), bootstrap analysis, and visual predictive check (VPC) were used for model evaluation. In addition, we used Monte Carlo simulations to propose dose recommendations for different subgroup patients. Results: A significant effect of the patient age and ABCB1 genotypes was observed on the VPA oral clearance (CL/F) in the final PPK model. Compared with patients with the ABCB1 rs3789243 AA genotype, CL/F in patients with GG and AG genotypes was increased by 8% and reduced by 4.7%, respectively. The GOF plots indicated the satisfactory predictive performance of the final model, and the evaluation by bootstrap and VPC showed that a stable model had been developed. A table of individualized dosing regimens involving age and ABCB1 genotype was constructed based on the final PPK model. Conclusion: This study quantitatively investigated the effects of patient age and ABCB1 rs3789243 variants on the pharmacokinetic variability of VPA. The PPK models could be beneficial to individual dose optimization in epileptic children on VPA therapy.

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Pharmacogenetics-based population pharmacokinetic analysis and dose optimization of valproic acid in Chinese southern children with epilepsy: Effect of ABCB1 gene polymorphism

Xianhuan Shen

Papers

Computational Approaches in Preclinical Studies on Drug Discovery and Development.

Pharmacogenetics-based population pharmacokinetic analysis and dose optimization of valproic acid in Chinese southern children with epilepsy: Effect of ABCB1 gene polymorphism

SCN1A Polymorphisms and Haplotypes Are Associated With Valproic Acid Treatment Outcomes in Chinese Children With Epilepsy.