کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8918135 | 1642819 | 2017 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Systems pharmacology-based identification of pharmacogenomic determinants of adverse drug reactions using human iPSC-derived cell lines
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
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چکیده انگلیسی
Few pharmacogenomic predictors of adverse drug reactions (ADRs) are currently available. Pharmacogenomic ADR studies are challenged by the multifactorial nature of ADRs and by insufficient sample sizes. Identification of pharmacogenomic predictors for personalized prediction of ADR risk may be enabled by development of large-scale libraries of patient-derived induced pluripotent stem cells. Using such libraries, ADR-related transcriptomic signatures can be mapped to the pharmacokinetics and pharmacodynamics of drugs, and correlated with clinical datasets and genomic profiles of individuals. Integration of these different data using computational quantitative systems pharmacology models based on machine learning-based algorithms can enable systematic mechanism-based characterization of ADRs. Establishing large scale cell line libraries, and databases and development of algorithms will lead to a knowledge-base that can be used to predict ADR risk in individual patients and for new drug candidates.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Current Opinion in Systems Biology - Volume 4, August 2017, Pages 9-15
Journal: Current Opinion in Systems Biology - Volume 4, August 2017, Pages 9-15
نویسندگان
J.G. Coen van Hassselt, Ravi Iyengar,