The industry has adopted Clinical Data Interchange Standards Consortium standards for clinical trial data and the Food and Drug Administration electronic common technical document standard for documents for many years but still faces many challenges....
OBJECTIVES: We develop a fuzzy evaluation model that provides managers at different responsibility levels in pharmaceutical laboratories with a rich picture of their innovation risk as well as that of competitors. This would help them take better str...
First published in 2016, predictors of chronological and biological age developed using deep learning (DL) are rapidly gaining popularity in the aging research community. These deep aging clocks can be used in a broad range of applications in the pha...
PURPOSE: The Tufts Center for the Study of Drug Development (CSDD) and the Drug Information Association (DIA) in collaboration with 8 pharmaceutical and biotechnology companies conducted a study examining the adoption and effect of artificial intelli...
Artificial intelligence (AI) has achieved human-level capabilities and continues to rapidly improve. For the pharmaceutical industry, AI can improve decision-making and transform the quest for better medicines. The keys are investing in data manageme...
Artificial intelligence (AI) uses personified knowledge and learns from the solutions it produces to address not only specific but also complex problems. Remarkable improvements in computational power coupled with advancements in AI technology could ...
Deep Learning has boosted artificial intelligence over the past 5 years and is seen now as one of the major technological innovation areas, predicted to replace lots of repetitive, but complex tasks of human labor within the next decade. It is also e...
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