Comparative Evaluation of In Silico Models to Assess Cardiac Pro-arrhythmic Risk in Early Drug Development

2017 ◽  
Vol 88 ◽  
pp. 208
Author(s):  
Pierre Morissette ◽  
Jeffrey Travis ◽  
Pamela Gerenser ◽  
Patrick Fanelli ◽  
Anne Chain ◽  
...  
Keyword(s):  
Drug Development ◽  
In Silico ◽  
Comparative Evaluation ◽  
In Silico Models ◽  
Early Drug

scholarly journals In silico models in drug development: where we are

2018 ◽  
Vol 42 ◽  
pp. 111-121 ◽  
Author(s):  
Janet Piñero ◽  
Laura I Furlong ◽  
Ferran Sanz
Keyword(s):  
Drug Development ◽  
In Silico ◽  
In Silico Models

scholarly journals Verifying and Validating Quantitative Systems Pharmacology and In Silico Models in Drug Development: Current Needs, Gaps, and Challenges

2020 ◽  
Vol 9 (4) ◽  
pp. 195-197
Author(s):  
Flora T. Musuamba ◽  
Roberta Bursi ◽  
Efthymios Manolis ◽  
Kristin Karlsson ◽  
Alexander Kulesza ◽  
...  
Keyword(s):  
Drug Development ◽  
In Silico ◽  
Systems Pharmacology ◽  
Quantitative Systems Pharmacology ◽  
In Silico Models

Incorporation of in silico biodegradability screening in early drug development—a feasible approach?

2010 ◽  
Vol 18 (4) ◽  
pp. 610-619 ◽  
Author(s):  
Thomas Steger-Hartmann ◽  
Reinhard Länge ◽  
Klaus Heuck
Keyword(s):  
Drug Development ◽  
In Silico ◽  
Early Drug

Comparative evaluation of 11 in silico models for the prediction of small molecule mutagenicity: role of steric hindrance and electron-withdrawing groups

2016 ◽  
Vol 27 (1) ◽  
pp. 24-35 ◽  
Author(s):  
Kevin A. Ford ◽  
Gregory Ryslik ◽  
Bryan K. Chan ◽  
Sock-Cheng Lewin-Koh ◽  
Davi Almeida ◽  
...  
Keyword(s):  
Small Molecule ◽  
Steric Hindrance ◽  
In Silico ◽  
Comparative Evaluation ◽  
In Silico Models

Current trends in in silico, in vitro toxicology, and safety biomarkers in early drug development

2017 ◽  
Vol 42 (2) ◽  
pp. 113-121 ◽  
Author(s):  
Simon Loiodice ◽  
Andre Nogueira da Costa ◽  
Franck Atienzar
Keyword(s):  
Drug Development ◽  
In Silico ◽  
In Vitro Toxicology ◽  
Current Trends ◽  
Early Drug

scholarly journals The Combination of Cell Cultured Technology and In Silico Model to Inform the Drug Development

Pharmaceutics ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 704
Author(s):  
Zhengying Zhou ◽  
Jinwei Zhu ◽  
Muhan Jiang ◽  
Lan Sang ◽  
Kun Hao ◽  
...  
Keyword(s):  
Drug Development ◽  
In Silico ◽  
In Vitro Models ◽  
Clinical Settings ◽  
Culture Methods ◽  
Physiologically Based Pharmacokinetic ◽  
Induced Pluripotent ◽  
In Silico Models

Human-derived in vitro models can provide high-throughput efficacy and toxicity data without a species gap in drug development. Challenges are still encountered regarding the full utilisation of massive data in clinical settings. The lack of translated methods hinders the reliable prediction of clinical outcomes. Therefore, in this study, in silico models were proposed to tackle these obstacles from in vitro to in vivo translation, and the current major cell culture methods were introduced, such as human-induced pluripotent stem cells (hiPSCs), 3D cells, organoids, and microphysiological systems (MPS). Furthermore, the role and applications of several in silico models were summarised, including the physiologically based pharmacokinetic model (PBPK), pharmacokinetic/pharmacodynamic model (PK/PD), quantitative systems pharmacology model (QSP), and virtual clinical trials. These credible translation cases will provide templates for subsequent in vitro to in vivo translation. We believe that synergising high-quality in vitro data with existing models can better guide drug development and clinical use.

Toward In Silico Prediction of Glass-Forming Ability from Molecular Structure Alone: A Screening Tool in Early Drug Development

2011 ◽  
Vol 8 (2) ◽  
pp. 498-506 ◽  
Author(s):  
Denny Mahlin ◽  
Sopana Ponnambalam ◽  
Mina Heidarian Höckerfelt ◽  
Christel A. S. Bergström
Keyword(s):  
Molecular Structure ◽  
Drug Development ◽  
In Silico ◽  
Screening Tool ◽  
Glass Forming Ability ◽  
In Silico Prediction ◽  
Glass Forming ◽  
Early Drug

In Silico Machine Learning Methods in Drug Development

2014 ◽  
Vol 14 (16) ◽  
pp. 1913-1922 ◽  
Author(s):  
Dimitar Dobchev ◽  
Girinath Pillai ◽  
Mati Karelson
Keyword(s):  
Machine Learning ◽  
Drug Development ◽  
In Silico ◽  
Learning Methods ◽  
Machine Learning Methods
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