AI Medical Compendium Journal:
Regulatory toxicology and pharmacology : RTP

Showing 11 to 14 of 14 articles

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

Regulatory toxicology and pharmacology : RTP Feb 13, 2016
Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guidelin...
Humans Databases, Factual Computer Simulation Animals Risk Assessment Models, Molecular Molecular Structure Knowledge Bases Data Mining Pattern Recognition, Automated Mutagens Quantitative Structure-Activity Relationship Mutagenesis Mutagenicity Tests Amines
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(Q)SAR assessments of potentially mutagenic impurities: a regulatory perspective on the utility of expert knowledge and data submission.

Regulatory toxicology and pharmacology : RTP Dec 26, 2014
(Quantitative) structure activity relationship [(Q)SAR] modeling is the primary tool used to evaluate the mutagenic potential associated with drug impurities. General recommendations regarding the use of (Q)SAR in regulatory decision making have rece...
Humans Databases, Factual Expert Systems Mutagens Quantitative Structure-Activity Relationship Drug Contamination Mutagenicity Tests
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Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

Regulatory toxicology and pharmacology : RTP Dec 12, 2014
This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of ...
Neural Networks, Computer Animals Caustics Rabbits Cosmetics Quantitative Structure-Activity Relationship Animal Testing Alternatives Eye Injuries
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Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

Regulatory toxicology and pharmacology : RTP Dec 8, 2014
Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant...
Neural Networks, Computer Animals Rabbits Cosmetics Quantitative Structure-Activity Relationship Animal Testing Alternatives Irritants Eye Injuries
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