Výsledky vyhledávání - "Graham F. Smith"

The Landscape of Potential Small and Drug Substance Related Nitrosamines in Pharmaceuticals

Autor: Joerg Schlingemann, Michael J. Burns, David J. Ponting, Carolina Martins Avila, Naiffer E. Romero, Mrunal A. Jaywant, Graham F. Smith, Ian W. Ashworth, Stephanie Simon, Christoph Saal, Andrzej Wilk

Publikováno v: Journal of Pharmaceutical Sciences. 112:1287-1304

This article reports the outcome of an in silico analysis of more than 12,000 small molecule drugs and drug impurities, identifying the nitrosatable structures, assessing their potential to form nitrosamines under relevant conditions and the challeng

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da45a3df822dccf8629262f20bfad6a7
https://doi.org/10.1016/j.xphs.2022.11.013

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Prediction of In Vivo Pharmacokinetic Parameters and Time–Exposure Curves in Rats Using Machine Learning from the Chemical Structure

Autor: Olga Obrezanova, Anton Martinsson, Tom Whitehead, Samar Mahmoud, Andreas Bender, Filip Miljković, Piotr Grabowski, Ben Irwin, Ioana Oprisiu, Gareth Conduit, Matthew Segall, Graham F. Smith, Beth Williamson, Susanne Winiwarter, Nigel Greene

Publikováno v: Molecular Pharmaceutics. 19:1488-1504

Animal pharmacokinetic (PK) data as well as human and animal in vitro systems are utilized in drug discovery to define the rate and route of drug elimination. Accurate prediction and mechanistic understanding of drug clearance and disposition in anim

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb9bd2b4cfbc81205355cb3ed27f5a7e
https://doi.org/10.1021/acs.molpharmaceut.2c00027

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Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes and machine learning

Autor: Hongbin Yang, Olga Obrezanova, Amy Pointon, Will Stebbeds, Jo Francis, Kylie A. Beattie, Peter Clements, James S. Harvey, Graham F. Smith, Andreas Bender

Publikováno v: Toxicology and applied pharmacology. 459

Functional changes to cardiomyocytes are undesirable during drug discovery and identifying the inotropic effects of compounds is hence necessary to decrease the risk of cardiovascular adverse effects in the clinic. Recently, approaches leveraging cal

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0701a3e2e313a100eb27016eaf86803
https://pubmed.ncbi.nlm.nih.gov/36502871

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Retrospective analysis of the potential use of virtual control groups in preclinical toxicity assessment using the eTOX database

Autor: Peter S.R. Wright, Graham F. Smith, Katharine A. Briggs, Robert Thomas, Gareth Maglennon, Paulius Mikulskis, Melissa Chapman, Nigel Greene, Benjamin U. Phillips, Andreas Bender

Publikováno v: Regulatory Toxicology and Pharmacology. 138:105309

Virtual Control Groups (VCGs) based on Historical Control Data (HCD) in preclinical toxicity testing have the potential to reduce animal usage. As a case study we retrospectively analyzed the impact of replacing Concurrent Control Groups (CCGs) with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df6a8d0bc1f1938928ac682adf89ef87
https://doi.org/10.1016/j.yrtph.2022.105309

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Statistical analysis of preclinical inter-species concordance of histopathological findings in the eTOX database

Autor: Peter S.R. Wright, Katharine A. Briggs, Robert Thomas, Graham F. Smith, Gareth Maglennon, Paulius Mikulskis, Melissa Chapman, Nigel Greene, Benjamin U. Phillips, Andreas Bender

Publikováno v: Regulatory Toxicology and Pharmacology. 138:105308

Preclinical inter-species concordance can increase the predictivity of observations to the clinic, potentially reducing drug attrition caused by unforeseen adverse events. We quantified inter-species concordance of histopathological findings and targ

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c9287b4a9f7dd7001a658be97ded020
https://doi.org/10.1016/j.yrtph.2022.105308

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Artificial Intelligence in Drug Safety and Metabolism

Autor: Graham F, Smith

Publikováno v: Methods in molecular biology (Clifton, N.J.). 2390

The use of artificial intelligence methods in drug safety began in the early 2000s with applications such as predicting bacterial mutagenicity and hERG inhibition. The field has been endlessly expanding ever since and the models have become more comp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::4e017e2b9862a77e371677f02b33506b
https://pubmed.ncbi.nlm.nih.gov/34731484

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