Literature DB >> 28609624

In Silico Absorption, Distribution, Metabolism, Excretion, and Pharmacokinetics (ADME-PK): Utility and Best Practices. An Industry Perspective from the International Consortium for Innovation through Quality in Pharmaceutical Development.

Franco Lombardo1, Prashant V Desai2, Rieko Arimoto3, Kelly E Desino4, Holger Fischer5, Christopher E Keefer6, Carl Petersson7, Susanne Winiwarter8, Fabio Broccatelli9.   

Abstract

In silico tools to investigate absorption, distribution, metabolism, excretion, and pharmacokinetics (ADME-PK) properties of new chemical entities are an integral part of the current industrial drug discovery paradigm. While many companies are active in the field, scientists engaged in this area do not necessarily share the same background and have limited resources when seeking guidance on how to initiate and maintain an in silico ADME-PK infrastructure in an industrial setting. This work summarizes the views of a group of industrial in silico and experimental ADME scientists, participating in the In Silico ADME Working Group, a subgroup of the International Consortium for Innovation through Quality in Pharmaceutical Development (IQ) Drug Metabolism Leadership Group. This overview on the benefits, caveats, and impact of in silico ADME-PK should serve as a resource for medicinal chemists, computational chemists, and DMPK scientists working in drug design to increase their knowledge in the area.

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Year:  2017        PMID: 28609624     DOI: 10.1021/acs.jmedchem.7b00487

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  12 in total

Review 1.  Advances in the study of drug metabolism - symposium report of the 12th Meeting of the International Society for the Study of Xenobiotics (ISSX).

Authors:  Laura E Russell; Mary Alexandra Schleiff; Eric Gonzalez; Aaron G Bart; Fabio Broccatelli; Jessica H Hartman; W Griffith Humphreys; Volker M Lauschke; Iain Martin; Chukwunonso Nwabufo; Bhagwat Prasad; Emily E Scott; Matthew Segall; Ryan Takahashi; Mitchell E Taub; Jasleen K Sodhi
Journal:  Drug Metab Rev       Date:  2020-05-26       Impact factor: 4.518

2.  Efficient Hit-to-Lead Searching of Kinase Inhibitor Chemical Space via Computational Fragment Merging.

Authors:  Grigorii V Andrianov; Wern Juin Gabriel Ong; Ilya Serebriiskii; John Karanicolas
Journal:  J Chem Inf Model       Date:  2021-11-11       Impact factor: 4.956

3.  Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches.

Authors:  Kevin M Crofton; Arianna Bassan; Mamta Behl; Yaroslav G Chushak; Ellen Fritsche; Jeffery M Gearhart; Mary Sue Marty; Moiz Mumtaz; Manuela Pavan; Patricia Ruiz; Magdalini Sachana; Rajamani Selvam; Timothy J Shafer; Lidiya Stavitskaya; David T Szabo; Steven T Szabo; Raymond R Tice; Dan Wilson; David Woolley; Glenn J Myatt
Journal:  Comput Toxicol       Date:  2022-03-17

4.  Computational exploration of maternal embryonic leucine zipper kinase (MELK) as a cancer drug target.

Authors:  Nahlah Makki Almansour
Journal:  Saudi J Biol Sci       Date:  2022-06-01       Impact factor: 4.052

5.  Multi-task convolutional neural networks for predicting in vitro clearance endpoints from molecular images.

Authors:  Andrés Martínez Mora; Vigneshwari Subramanian; Filip Miljković
Journal:  J Comput Aided Mol Des       Date:  2022-05-27       Impact factor: 4.179

6.  Clinical pharmacokinetic study of latrepirdine via in silico sublingual administration.

Authors:  Joana Santos; Luísa Lobato; Nuno Vale
Journal:  In Silico Pharmacol       Date:  2021-04-05

7.  Direct Comparison of the Prediction of the Unbound Brain-to-Plasma Partitioning Utilizing Machine Learning Approach and Mechanistic Neuropharmacokinetic Model.

Authors:  Yohei Kosugi; Kunihiko Mizuno; Cipriano Santos; Sho Sato; Natalie Hosea; Michael Zientek
Journal:  AAPS J       Date:  2021-05-18       Impact factor: 4.009

8.  Discovery of novel inhibitors against main protease (Mpro) of SARS-CoV-2 via virtual screening and biochemical evaluation.

Authors:  Sheng Guo; Hang Xie; Yu Lei; Bin Liu; Li Zhang; Yechun Xu; Zhili Zuo
Journal:  Bioorg Chem       Date:  2021-02-24       Impact factor: 5.307

9.  Computational screening of phytochemicals from three medicinal plants as inhibitors of transmembrane protease serine 2 implicated in SARS-CoV-2 infection.

Authors:  Omotayo O Oyedara; Joseph M Agbedahunsi; Folasade M Adeyemi; Alfredo Juárez-Saldivar; Olatomide A Fadare; Charles O Adetunji; Gildardo Rivera
Journal:  Phytomed Plus       Date:  2021-09-29

Review 10.  Structure-Based Design of Antivirals against Envelope Glycoprotein of Dengue Virus.

Authors:  Mohd Ishtiaq Anasir; Babu Ramanathan; Chit Laa Poh
Journal:  Viruses       Date:  2020-03-26       Impact factor: 5.048

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