In silico prediction of adverse drug reactions and toxicities based on structural, biological and clinical data

Xin Liu; Zhe Shi; Ying Xue; Ze Rong Li; Sheng Yong Yang; Yu Quan Wei; Yu Zong Chen

doi:10.2174/157488612803251351

In silico prediction of adverse drug reactions and toxicities based on structural, biological and clinical data

Xin Liu, Zhe Shi, Ying Xue, Ze Rong Li, Sheng Yong Yang, Yu Quan Wei, Yu Zong Chen

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

Drug adverse effects (ADEs) and toxicities have been extensively studied from chemical structure, genetic, biological systems and clinical perspectives. The rapid accumulation of chemical, biological and clinical data are highly useful for characterizing and predicting ADEs, and have enabled increasing exploration of computational methods as low cost tools for predicting various ADEs and toxicities. This article reviews the strategies, current progresses, underlying difficulties and future prospects in using computational methods for predicting ADEs and toxicities.

Original language	English
Pages (from-to)	225-237
Number of pages	13
Journal	Current Drug Safety
Volume	7
Issue number	3
DOIs	https://doi.org/10.2174/157488612803251351
Publication status	Published - 2012
Externally published	Yes

Keywords

Adverse drug effects
Adverse drug reaction
Drug discovery
Drug testing
Pharmaceutical
Risk assessment
Side effect
Toxicity
Toxicology

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10.2174/157488612803251351

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abstract = "Drug adverse effects (ADEs) and toxicities have been extensively studied from chemical structure, genetic, biological systems and clinical perspectives. The rapid accumulation of chemical, biological and clinical data are highly useful for characterizing and predicting ADEs, and have enabled increasing exploration of computational methods as low cost tools for predicting various ADEs and toxicities. This article reviews the strategies, current progresses, underlying difficulties and future prospects in using computational methods for predicting ADEs and toxicities.",

keywords = "Adverse drug effects, Adverse drug reaction, Drug discovery, Drug testing, Pharmaceutical, Risk assessment, Side effect, Toxicity, Toxicology",

author = "Xin Liu and Zhe Shi and Ying Xue and Li, {Ze Rong} and Yang, {Sheng Yong} and Wei, {Yu Quan} and Chen, {Yu Zong}",

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doi = "10.2174/157488612803251351",

language = "English",

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T1 - In silico prediction of adverse drug reactions and toxicities based on structural, biological and clinical data

AU - Liu, Xin

AU - Shi, Zhe

AU - Xue, Ying

AU - Li, Ze Rong

AU - Yang, Sheng Yong

AU - Wei, Yu Quan

AU - Chen, Yu Zong

PY - 2012

Y1 - 2012

N2 - Drug adverse effects (ADEs) and toxicities have been extensively studied from chemical structure, genetic, biological systems and clinical perspectives. The rapid accumulation of chemical, biological and clinical data are highly useful for characterizing and predicting ADEs, and have enabled increasing exploration of computational methods as low cost tools for predicting various ADEs and toxicities. This article reviews the strategies, current progresses, underlying difficulties and future prospects in using computational methods for predicting ADEs and toxicities.

AB - Drug adverse effects (ADEs) and toxicities have been extensively studied from chemical structure, genetic, biological systems and clinical perspectives. The rapid accumulation of chemical, biological and clinical data are highly useful for characterizing and predicting ADEs, and have enabled increasing exploration of computational methods as low cost tools for predicting various ADEs and toxicities. This article reviews the strategies, current progresses, underlying difficulties and future prospects in using computational methods for predicting ADEs and toxicities.

KW - Adverse drug effects

KW - Adverse drug reaction

KW - Drug discovery

KW - Drug testing

KW - Pharmaceutical

KW - Risk assessment

KW - Side effect

KW - Toxicity

KW - Toxicology

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SN - 1574-8863

VL - 7

SP - 225

EP - 237

JO - Current Drug Safety

JF - Current Drug Safety

IS - 3

ER -

In silico prediction of adverse drug reactions and toxicities based on structural, biological and clinical data

Abstract

Keywords

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