Výsledky vyhledávání - "Kentaro Handa"

An Updated In Silico Prediction Method for Volumes of Systemic Circulation of 323 Disparate Chemicals for Use in Physiologically Based Pharmacokinetic Models to Estimate Plasma and Tissue Concentrations after Oral Doses in Rats

Autor: Yusuke Kamiya, Junya Ohori, Fumiaki Shono, Hiroshi Yamazaki, Kimito Funatsu, Tomonori Miura, Masato Kitajima, Makiko Shimizu, Kentaro Handa

Publikováno v: Chemical Research in Toxicology. 34:2180-2183

Updated algorithms for predicting the volumes of systemic circulation (V1), along with absorption rate constants and hepatic intrinsic clearances, as input parameters for physiologically based pharmacokinetic (PBPK) models were established to improve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b14c6e1400ec26e6aaeb7ea68c33b0e6
https://doi.org/10.1021/acs.chemrestox.1c00249

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In Silico Prediction of Input Parameters for Simplified Physiologically Based Pharmacokinetic Models for Estimating Plasma, Liver, and Kidney Exposures in Rats after Oral Doses of 246 Disparate Chemicals

Autor: Tomonori Miura, Hiroshi Yamazaki, Makiko Shimizu, Yusuke Kamiya, Fumiaki Shono, Shiori Hina, Kazuki Shigeta, Kentaro Handa, Kimito Funatsu, Masato Kitajima, Mayu Yanagi

Publikováno v: Chemical Research in Toxicology. 34:507-513

Recently developed computational models can estimate plasma, hepatic, and renal concentrations of industrial chemicals in rats. Typically, the input parameter values (i.e., the absorption rate constant, volume of systemic circulation, and hepatic int

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4f7927d9db1fd624515ec9842beb7fe4
https://doi.org/10.1021/acs.chemrestox.0c00336

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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

Autor: Kentaro Handa, Masato Kitajima, Makiko Shimizu, Hiroshi Yamazaki, Tomonori Miura, Airi Kato, Yusuke Kamiya, Junya Ohori

Publikováno v: Biologicalpharmaceutical bulletin. 45(1)

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 circula

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09a2b599c674885fa51a7a44c960691e
https://pubmed.ncbi.nlm.nih.gov/34732590

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Prediction Models for Agonists and Antagonists of Molecular Initiation Events for Toxicity Pathways Using an Improved Deep-Learning-Based Quantitative Structure–Activity Relationship System

Autor: Shin Totoki, Kentaro Handa, Yoshihiro Uesawa, Yasunari Matsuzaka, Tetsuyoshi Shiota, Kota Kurosaki

Publikováno v: International Journal of Molecular Sciences, Vol 22, Iss 10821, p 10821 (2021)
International Journal of Molecular Sciences
Volume 22
Issue 19

In silico approaches have been studied intensively to assess the toxicological risk of various chemical compounds as alternatives to traditional in vivo animal tests. Among these approaches, quantitative structure–activity relationship (QSAR) analy

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68211270236a0f8f16721bd67e4e1329
https://www.mdpi.com/1422-0067/22/19/10821

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An Updated

Autor: Yusuke, Kamiya, Kentaro, Handa, Tomonori, Miura, Junya, Ohori, Makiko, Shimizu, Masato, Kitajima, Fumiaki, Shono, Kimito, Funatsu, Hiroshi, Yamazaki

Publikováno v: Chemical research in toxicology. 34(10)

Updated algorithms for predicting the volumes of systemic circulation (

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::0cf5cdaa3007017e8bc9cc231bf6ed43
https://pubmed.ncbi.nlm.nih.gov/35905009

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Prediction of permeability across intestinal cell monolayers for 219 disparate chemicals using in vitro experimental coefficients in a pH gradient system and in silico analyses by trivariate linear regressions and machine learning

Autor: Riku Hayasaka, Junya Ohori, Hiroshi Yamazaki, Kimito Funatsu, Izumi Sano, Masato Kitajima, Rie Saito, Fumiaki Shono, Yusuke Kamiya, Asuka Omura, Kentaro Handa

Publikováno v: Biochemical pharmacology. 192

For medicines, the apparent membrane permeability coefficients (Papp) across human colorectal carcinoma cell line (Caco-2) monolayers under a pH gradient generally correlate with the fraction absorbed after oral intake. Furthermore, the in vitro Papp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9538ccf97b757a1ec9f2a9c0679d18b3
https://pubmed.ncbi.nlm.nih.gov/34461115

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Correction to 'An Updated In Silico Prediction Method for Volumes of Systemic Circulation of 323 Disparate Chemicals for Use in Physiologically Based Pharmacokinetic Models to Estimate Plasma and Tissue Concentrations after Oral Doses in Rats'

Autor: Yusuke Kamiya, Kentaro Handa, Tomonori Miura, Junya Ohori, Makiko Shimizu, Masato Kitajima, Fumiaki Shono, Kimito Funatsu, Hiroshi Yamazaki

Publikováno v: Chemical Research in Toxicology. 35:1433-1433

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cf9eeedb638786eba4f6cc8d0c05d643
https://doi.org/10.1021/acs.chemrestox.2c00225

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Akademický článek

Updated in silico prediction methods for fractions absorbed and absorption rate constants of 372 disparate chemicals for use in physiologically based pharmacokinetic models for estimating internal concentrations in rats.

Autor: Koichiro Adachi¹, Makiko Shimizu¹, Hiroshi Yamazaki¹ hyamazak@ac.shoyaku.ac.jp

Publikováno v: Journal of Toxicological Sciences. 2022, Vol. 47 Issue 11, p453-456. 4p.

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Akademický článek

Prediction Models for Agonists and Antagonists of Molecular Initiation Events for Toxicity Pathways Using an Improved Deep-Learning-Based Quantitative Structure–Activity Relationship System.

Autor: Matsuzaka, Yasunari^1,2 (AUTHOR) yasunari80808@ims.u-tokyo.ac.jp, Totoki, Shin³ (AUTHOR) totoki.shin@fujitsu.com, Handa, Kentaro³ (AUTHOR) handa.kentaro@fujitsu.com, Shiota, Tetsuyoshi³ (AUTHOR) shiota@fujitsu.com, Kurosaki, Kota¹ (AUTHOR) d196955@std.my-pharm.ac.jp, Uesawa, Yoshihiro¹ (AUTHOR) uesawa@my-pharm.ac.jp

Publikováno v: International Journal of Molecular Sciences. Oct2021, Vol. 22 Issue 19, p10821. 1p.

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