Abstract
There are numerous small molecular compounds around us to affect our health, such as drugs, pesticides, food additives, industrial chemicals, and environmental pollutants. Over decades, properties related to absorption, distribution, metabolism, excretion, and toxicity (ADMET) have become one of the most important issues to assess the effects or risks of these compounds on human body. Recent high-rate drug withdrawals increase the pressure on regulators and pharmaceutical industry to improve preclinical safety testing. Since in vivo and in vitro evaluations are costly and laborious, in silico techniques have been widely used to estimate these properties. In this review, we would briefly describe the recent advances of in silico ADMET prediction, with emphasis on substructure pattern recognition method that we developed recently. Challenges and limitations in the area of in silico ADMET prediction were further discussed, such as application domain of models, models validation techniques, and global versus local models. At last, several new promising research directions were provided, such as computational systems toxicology (toxicogenomics), data-integration and meta-decision making systems, which could be used for systemic in silico ADMET prediction in drug discovery and hazard risk assessment.
Keywords: ADMET, drug discovery, hazard risk assessment, systems toxicology, QSAR, data-integration, combined classifier, substructure pattern recognition.
Current Topics in Medicinal Chemistry
Title:In Silico ADMET Prediction: Recent Advances, Current Challenges and Future Trends
Volume: 13 Issue: 11
Author(s): Feixiong Cheng, Weihua Li, Guixia Liu and Yun Tang
Affiliation:
Keywords: ADMET, drug discovery, hazard risk assessment, systems toxicology, QSAR, data-integration, combined classifier, substructure pattern recognition.
Abstract: There are numerous small molecular compounds around us to affect our health, such as drugs, pesticides, food additives, industrial chemicals, and environmental pollutants. Over decades, properties related to absorption, distribution, metabolism, excretion, and toxicity (ADMET) have become one of the most important issues to assess the effects or risks of these compounds on human body. Recent high-rate drug withdrawals increase the pressure on regulators and pharmaceutical industry to improve preclinical safety testing. Since in vivo and in vitro evaluations are costly and laborious, in silico techniques have been widely used to estimate these properties. In this review, we would briefly describe the recent advances of in silico ADMET prediction, with emphasis on substructure pattern recognition method that we developed recently. Challenges and limitations in the area of in silico ADMET prediction were further discussed, such as application domain of models, models validation techniques, and global versus local models. At last, several new promising research directions were provided, such as computational systems toxicology (toxicogenomics), data-integration and meta-decision making systems, which could be used for systemic in silico ADMET prediction in drug discovery and hazard risk assessment.
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Cite this article as:
Cheng Feixiong, Li Weihua, Liu Guixia and Tang Yun, In Silico ADMET Prediction: Recent Advances, Current Challenges and Future Trends, Current Topics in Medicinal Chemistry 2013; 13(11) . https://dx.doi.org/10.2174/15680266113139990033
DOI https://dx.doi.org/10.2174/15680266113139990033 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |

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