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Home > MDL® Discovery Predictive Science > MDL® Carcinogenicity Module
 
Discovery Predictive Science
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MDL® Carcinogenicity Module | Printer Friendly    
Cooperatively developed with the USFDA, Center for Drug Evaluation and Research
New drug applications (NDAs) that fail due to unexpected rodent carcinogenicity results* after successful Phase 1 clinical studies can cost millions of dollars in retesting and years of delay in reaching the market. The MDL Carcinogenicity Module was developed in cooperation with the US Food and Drug Administration (FDA) to prevent this scenario.
*Rodent carcinogenicity studies typically cost $2 million-$5 million and take approximately two years to complete.
In silico risk assessment based on FDA expert rules and data
In determining if a new drug presents an unacceptable carcinogenic risk to humans, the FDA analyzes raw and summary data from rodent carcinogenicity studies. The MDL Carcinogenicity Module uses the expert rules and decision-making process designed by the FDA Center for Drug Evaluation and Research (CDER) to make this evaluation based on structural properties. The module includes:
  • A predictive algorithm that flags compounds most likely to present an unacceptable risk to humans: high risk/low risk
  • The CDER Rodent Carcinogenicity database: the largest database of structure-searchable two-year rodent data available
The CDER Rodent Carcinogenicity database also allows users to add and leverage their own data to create new models. Data fields include FDA ratings on all compounds for two-year male and female mouse and rat studies.
Watch for future modules
MDL has entered into an agreement with the FDA to create predictive modules for toxicological endpoints of interest to the pharmaceutical industry. In addition to the Carcinogenicity Module, MDL and CDER/FDA plan to develop the following modules for MDL QSAR:
  • Human Adverse Effects (cardiovascular, liver toxicity, etc)
  • Developmental Toxicology
  • Mutagenicity
Additional Info

MDL Carcinogenicity Module datasheet (PDF)

 
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Events:
 
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