AIMC Topic: Drug Industry

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Automation With Intelligence in Drug Research.

Clinical therapeutics
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....

On strategic choices faced by large pharmaceutical laboratories and their effect on innovation risk under fuzzy conditions.

Artificial intelligence in medicine
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...

Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity.

Trends in pharmacological sciences
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...

A Study on the Application and Use of Artificial Intelligence to Support Drug Development.

Clinical therapeutics
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 for Pharma: Time for Internal Investment.

Trends in pharmacological sciences
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 in drug development: present status and future prospects.

Drug discovery today
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 ...

Developing Deep Learning Applications for Life Science and Pharma Industry.

Drug research
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...