ADME/Tox Predictions in Drug Design
- Authors: Ricardo Pereira Rodrigues1, Jonathan Resende de Almeida2, Evandro Pizeta Semighini3, Flávio Roberto Pinsetta4, Susimaire Pedersoli Mantoani5, Vinicius Barreto da Silva6, Carlos Henrique Tomich de Paula da Silva7
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View Affiliations Hide Affiliations1 School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil; 2 School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil; 3 Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil 4 School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil; 5 School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil 6 Catholic University of Goiás, Goiânia, Brazil 7 School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
- Source: New Developments in Medicinal Chemistry: Volume 2 , pp 192-212
- Publication Date: October 2014
- Language: English
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Most drug candidate failures during clinical trials occur due to inappropriate ADMET properties. In this way, there is a major concern to identify possible ADMET failures during the early stages of drug design projects and optimize such properties in order to reduce time and costs. In silico ADMET predictions comprise various strategies that play a central role when considering the task of profiling lead compounds regarding potential ADMET failures. We will discuss the computational strategies, methods and softwares used, actually, to profile ADMET and how they could be helpful during drug design.
Hardbound ISBN:
9781608059553
Ebook ISBN:
9781608059546
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