Jeffery L. Painter

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Over a quarter of drugs that enter clinical development fail because they are ineffective. Growing insight into genes that influence human disease may affect how drug targets and indications are selected. However, there is little guidance about how much weight should be given to genetic evidence in making these key decisions. To answer this question, we(More)
BACKGROUND Potential severe liver injury is identified in clinical trials by ALT >3 × upper limits of normal (ULN) and total bilirubin >2 × ULN, and termed 'Hy's Law' by the US FDA. However, there is limited evidence or validation of these thresholds in clinical trial populations. Using liver chemistry data from clinical trials, decision boundaries were(More)
PURPOSE Identifying drug-induced liver injury is a critical task in drug development and postapproval real-world care. Severe liver injury is identified by the liver chemistry threshold of alanine aminotransferase (ALT) >3× upper limit of normal (ULN) and bilirubin >2× ULN, termed Hy's law by the Food and Drug Administration. These thresholds require(More)
Most modern biomedical vocabularies employ some hierarchical representation that provides a "broader/narrower" meaning relationship among the "codes" or "concepts" found within them. Often, however, we may find within the clinical setting the creation and curation of unstructured custom vocabularies used in the everyday practice of classifying and(More)
— By employing a notion of semantic closeness to create a multi-phase mapping between one biomedical taxonomy and another, we are able to determine various levels of proximity for mapping term based structures which may fail to map using traditional mapping techniques. The multi-phase approach allows for defining the appropriate-ness of applying the maps to(More)
OBJECTIVE Active drug safety surveillance may be enhanced by analysis of multiple observational healthcare databases, including administrative claims and electronic health records. The objective of this study was to develop and evaluate a common data model (CDM) enabling rapid, comparable, systematic analyses across disparate observational data sources to(More)
INTRODUCTION Post-marketing safety surveillance primarily relies on data from spontaneous adverse event reports, medical literature, and observational databases. Limitations of these data sources include potential under-reporting, lack of geographic diversity, and time lag between event occurrence and discovery. There is growing interest in exploring the(More)
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