Abstract
Introduction: Drug-Induced Liver Injury (DILI) challenges drug development, clinical practice and drug safety regulation. The Liver Toxicity Knowledge Base (LTKB) provides essential data to support the study of DILI.
Areas Covered: The LTKB brings together diverse data sources that can be used to assess and predict DILI. Among the extensive information available, reference drug lists with annotated human DILI risk are of great value. The LTKB DILI classification describes DILI severity concern (most, less and no DILI-concern) determined by integrating FDA drug labeling, DILI severity score from the NIH LiverTox database, and other DILI classification schemes described in published literature. Overall, over 1000 drugs are described in at least one classification scheme, and around 750 drugs were flagged for some degree of DILI risk.
Expert Commentary: The LTKB provides a centralized repository of information for the study of DILI and the development of predictive models. DILI classification data in LTKB could be a useful resource to connect phenotype with molecular and mechanistic data for developing biomarkers, predictive models and assessing data from emerging technologies such as high-throughput screening, high-content screening and in silico methodologies. In coming years, streamlining the prediction process by including DILI predictive models for both DILI severity and also including DILI types in LTKB would enhance the identification of chemicals with the potential to cause DILI earlier in drug development and risk assessment.
Areas Covered: The LTKB brings together diverse data sources that can be used to assess and predict DILI. Among the extensive information available, reference drug lists with annotated human DILI risk are of great value. The LTKB DILI classification describes DILI severity concern (most, less and no DILI-concern) determined by integrating FDA drug labeling, DILI severity score from the NIH LiverTox database, and other DILI classification schemes described in published literature. Overall, over 1000 drugs are described in at least one classification scheme, and around 750 drugs were flagged for some degree of DILI risk.
Expert Commentary: The LTKB provides a centralized repository of information for the study of DILI and the development of predictive models. DILI classification data in LTKB could be a useful resource to connect phenotype with molecular and mechanistic data for developing biomarkers, predictive models and assessing data from emerging technologies such as high-throughput screening, high-content screening and in silico methodologies. In coming years, streamlining the prediction process by including DILI predictive models for both DILI severity and also including DILI types in LTKB would enhance the identification of chemicals with the potential to cause DILI earlier in drug development and risk assessment.
Original language | English |
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Journal | Expert review of gastroenterology & hepatology |
Volume | 12 |
Issue number | 1 |
Early online date | 9 Oct 2017 |
DOIs | |
Publication status | Published - 1 Jan 2018 |
Keywords
- Drug-Induced Liver Injury (DILI)
- Drug Classification for DILI
- Human Liver Injury
- Liver Toxicity Knowledgebase (LTKB)
- Computational Toxicology