목차
목차
1. 연구동향
1) In silicotoxicology models and databases as FDA Critical Path Initiative toolkits. (2011)
2) The Pros and Cons of the In-silico Pharmaco-toxicology in Drug Discovery and Development. (2013)
3) In Silico ADMET Prediction: Recent Advances, Current Challenges and Future Trends. (2013)
4) In silico ADME/T modelling for rational drug design. (2015)
5) In silico approaches to genetic toxicology: progress and future, Mutagenesis. (2019)
6) Computational Approaches in Preclinical Studies on Drug Discovery and Development. (2020)
7) Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures. (2022)
8) Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT—NAMs Symposium. (2022)
9) The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery. Pharmaceutics. (2023)
2. 출처 및 참고문헌
1. 연구동향
1) In silicotoxicology models and databases as FDA Critical Path Initiative toolkits. (2011)
2) The Pros and Cons of the In-silico Pharmaco-toxicology in Drug Discovery and Development. (2013)
3) In Silico ADMET Prediction: Recent Advances, Current Challenges and Future Trends. (2013)
4) In silico ADME/T modelling for rational drug design. (2015)
5) In silico approaches to genetic toxicology: progress and future, Mutagenesis. (2019)
6) Computational Approaches in Preclinical Studies on Drug Discovery and Development. (2020)
7) Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures. (2022)
8) Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT—NAMs Symposium. (2022)
9) The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery. Pharmaceutics. (2023)
2. 출처 및 참고문헌
본문내용
-toxicology in Drug Discovery and Development. International Journal of Pharmacology, 9: 176-181.https://doi.org/10.3923/ijp.2013.176.181
Valerio, L.G. In silicotoxicology models and databases as FDA Critical Path Initiative toolkits. Hum Genomics 5, 200 (2011). https://doi.org/10.1186/1479-7364-5-3-200
Komura H, Watanabe R, Mizuguchi K. The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery. Pharmaceutics. 2023; 15(11):2619. https://doi.org/10.3390/pharmaceutics15112619
Wu F, Zhou Y, Li L, Shen X, Chen G, Wang X, Liang X, Tan M and Huang Z (2020) Computational Approaches in Preclinical Studies on Drug Discovery and Development. Front. Chem. 8:726. https://doi.org/10.3389/fchem.2020.00726
Wang Y, Xing J, Xu Y, et al. In silico ADME/T modelling for rational drug design. Quarterly Reviews of Biophysics. 2015;48(4):488-515. https://doi.org/10.1017/S0033583515000190
Cheng , Feixiong,Li , Weihua,Liu , Guixia,Tang , Yun,In Silico ADMET Prediction: Recent Advances, Current Challenges and Future Trends,Current Topics in Medicinal Chemistry, volume 13, issue 11, pages 1273-1289, year 2013, https://doi.org/10.2174/15680266113139990033
Valerio, L.G. In silicotoxicology models and databases as FDA Critical Path Initiative toolkits. Hum Genomics 5, 200 (2011). https://doi.org/10.1186/1479-7364-5-3-200
Komura H, Watanabe R, Mizuguchi K. The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery. Pharmaceutics. 2023; 15(11):2619. https://doi.org/10.3390/pharmaceutics15112619
Wu F, Zhou Y, Li L, Shen X, Chen G, Wang X, Liang X, Tan M and Huang Z (2020) Computational Approaches in Preclinical Studies on Drug Discovery and Development. Front. Chem. 8:726. https://doi.org/10.3389/fchem.2020.00726
Wang Y, Xing J, Xu Y, et al. In silico ADME/T modelling for rational drug design. Quarterly Reviews of Biophysics. 2015;48(4):488-515. https://doi.org/10.1017/S0033583515000190
Cheng , Feixiong,Li , Weihua,Liu , Guixia,Tang , Yun,In Silico ADMET Prediction: Recent Advances, Current Challenges and Future Trends,Current Topics in Medicinal Chemistry, volume 13, issue 11, pages 1273-1289, year 2013, https://doi.org/10.2174/15680266113139990033
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