Etiology of New-Onset Jaundice: How Often Is It Caused by Idiosyncratic Drug-Induced Liver Injury in The United States?

Background & Aims: The United States Food and Drug Administration (FDA) regulates a broad range of consumer products, which account for about 25% of the United States market. The FDA regulatory activities often involve producing and reading of a large number of documents, which is time consuming and labor intensive. To support regulatory science at FDA, we evaluated artificial intelligence (AI)-based natural language processing (NLP) of regulatory documents for text classification and compared deep learning-based models with a conventional keywords-based model.Methods: FDA drug labeling documents were used as a representative regulatory data source to classify drug-induced liver injury (DILI) risk by employing the state-of-the-art language model BERT. The resulting NLP-DILI classification model was statistically validated with both internal and external validation procedures and applied to the labeling data from the European Medicines Agency (EMA) for cross-agency application.Results: The NLP-DILI model developed using FDA labeling documents and evaluated by cross-validations in this study showed remarkable performance in DILI classification with a recall of 1 and a precision of 0.78. When cross-agency data were used to validate the model, the performance remained comparable, demonstrating that the model was portable across agencies. Results also suggested that the model was able to capture the semantic meanings of sentences in drug labeling.Conclusion: Deep learning-based NLP models performed well in DILI classification of drug labeling documents and learned the meanings of complex text in drug labeling. This proof-of-concept work demonstrated that using AI technologies to assist regulatory activities is a promising approach to modernize and advance regulatory science.

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Liver transplantation for acute liver failure from drug induced liver injury in the United States

Liver Transplantation ◽

10.1002/lt.20204 ◽

2004 ◽

Vol 10 (8) ◽

pp. 1018-1023 ◽

Cited By ~ 300

Author(s):

Mark W. Russo ◽

Joseph A. Galanko ◽

Roshan Shrestha ◽

Michael W. Fried ◽

Paul Watkins

Keyword(s):

United States ◽

Liver Transplantation ◽

Liver Injury ◽

Liver Failure ◽

Acute Liver Failure ◽

The United States ◽

Drug Induced ◽

Drug Induced Liver Injury

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Case series and review of Ayurvedic medication induced liver injury

BMC Complementary Medicine and Therapies ◽

10.1186/s12906-021-03251-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Christopher M. Karousatos ◽

Justin K. Lee ◽

David R. Braxton ◽

Tse-Ling Fong

Keyword(s):

Liver Injury ◽

Plant Extracts ◽

Significant Proportion ◽

Case Series ◽

The United States ◽

Tinospora Cordifolia ◽

Individual Plant ◽

Medicine Use ◽

Drug Induced ◽

Drug Induced Liver Injury

Abstract Background Complementary and alternative medicine use among Americans is prevalent. Originating in India, Ayurvedic medicine use in the United States has grown 57% since 2002. CAM accounts for a significant proportion of drug induced liver injury in India and China, but there have been only three reports of drug induced liver injury from Ayurvedic medications in the U.S. We report three cases of suspected Ayurvedic medication associated liver injury seen at a Southern California community hospital and review literature of Ayurvedic medication induced liver injury. Case presentations Three patients presented with acute hepatocellular injury and jaundice after taking Ayurvedic supplements for 90–120 days. First patient took Giloy Kwath consisting solely of Tinospora cordifolia. Second patient took Manjishthadi Kwatham and Aragwadhi Kwatham, which contained 52 and 10 individual plant extracts, respectively. Third patient took Kanchnar Guggulu, containing 10 individual plant extracts. Aminotransferase activities decreased 50% in < 30 days and all 3 patients made a full recovery. Roussel Uclaf Causality Assessment Method (RUCAM) scores were 7–8, indicating probable causality. These products all contained ingredients in other Ayurvedic and traditional Chinese medicines with previously reported associations with drug induced liver injury. Conclusions These patients highlight the risk of drug induced liver injury from Ayurvedic medications and the complexity of determining causality. There is a need for a platform like LiverTox.gov to catalog Ayurvedic ingredients causing liver damage.

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