9 Statistical methods for in silico tools used for risk assessment and toxicology
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Nermin A Osman
Abstract
In silico toxicology is one type of toxicity assessment that uses computational methods to visualize, analyze, simulate, and predict the toxicity of chemicals. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. Animal studies for the type of toxicological information needed are both expensive and time-consuming, and to that, ethical consideration is added. Many different types of in silico methods have been developed to characterize the toxicity of chemical materials and predict their catastrophic consequences to humans and the environment. In light of European legislation such as Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) and the Cosmetics Regulation, in silico methods for predicting chemical toxicity have become increasingly important and used extensively worldwide e.g., in the USA, Canada, Japan, and Australia. A popular problem, concerning these methods, is the deficiency of the necessary data for assessing the hazards. REACH has called for increased use of in silico tools for non-testing data as structure-activity relationships, quantitative structureactivity relationships, and read-across. The main objective of the review is to refine the use of in silico tools in a risk assessment context of industrial chemicals.
Abstract
In silico toxicology is one type of toxicity assessment that uses computational methods to visualize, analyze, simulate, and predict the toxicity of chemicals. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. Animal studies for the type of toxicological information needed are both expensive and time-consuming, and to that, ethical consideration is added. Many different types of in silico methods have been developed to characterize the toxicity of chemical materials and predict their catastrophic consequences to humans and the environment. In light of European legislation such as Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) and the Cosmetics Regulation, in silico methods for predicting chemical toxicity have become increasingly important and used extensively worldwide e.g., in the USA, Canada, Japan, and Australia. A popular problem, concerning these methods, is the deficiency of the necessary data for assessing the hazards. REACH has called for increased use of in silico tools for non-testing data as structure-activity relationships, quantitative structureactivity relationships, and read-across. The main objective of the review is to refine the use of in silico tools in a risk assessment context of industrial chemicals.
Kapitel in diesem Buch
- Frontmatter I
- Contents V
- List of contributing authors XI
- 1 Pharmaceutical interest of in-silico approaches 1
- 2 Novel drug design and bioinformatics: an introduction 15
- 3 In silico drug design: application and success 37
- 4 Protein modeling 85
- 5 Fragment based drug design 101
- 6 An overview of in silico methods used in the design of VEGFR-2 inhibitors as anticancer agents 115
- 7 Molecular docking and MD: mimicking the real biological process 133
- 8 Molecular docking studies of tea (Thea sinensis Linn.) polyphenols inhibition pattern with Rat P-glycoprotein 145
- 9 Statistical methods for in silico tools used for risk assessment and toxicology 157
- 10 Systems biology–the transformative approach to integrate sciences across disciplines 171
- Index 195
Kapitel in diesem Buch
- Frontmatter I
- Contents V
- List of contributing authors XI
- 1 Pharmaceutical interest of in-silico approaches 1
- 2 Novel drug design and bioinformatics: an introduction 15
- 3 In silico drug design: application and success 37
- 4 Protein modeling 85
- 5 Fragment based drug design 101
- 6 An overview of in silico methods used in the design of VEGFR-2 inhibitors as anticancer agents 115
- 7 Molecular docking and MD: mimicking the real biological process 133
- 8 Molecular docking studies of tea (Thea sinensis Linn.) polyphenols inhibition pattern with Rat P-glycoprotein 145
- 9 Statistical methods for in silico tools used for risk assessment and toxicology 157
- 10 Systems biology–the transformative approach to integrate sciences across disciplines 171
- Index 195
