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Recognizing the Real People Behind the Big Data and Artificial Intelligence in Clinical Research

ACRP blog

If you hadn’t already noticed, the clinical research enterprise has well and truly entered the era of “big data,” artificial intelligence (AI), and machine learning. Undoubtedly, the expectations for precision medicine are high,” Olsen adds.

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How big data analytics can make personalised care a reality

Drug Discovery World

Johannes Goll, Global Head of Emmes’ Biomedical Data Science and Bioinformatics department, explains how big data analytics can deliver improved therapies and bring clinical research one step close to realising the potential of personalised care.

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Big data – charting a new path to drug discovery and development

Drug Discovery World

Drug discovery and development timelines can span 10-15 years or more from initial discovery to market approval and typically require the analysis of massive amounts of data. Advances in quantum computing are also showing early promise for increasingly complex data analyses.

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The future of AI drug discovery & development in immunology and GPCR research

pharmaphorum

Alphabet subsidiary and precision health company Verily recently announced a breakthrough in its AI drug discovery GPCR research collaboration with Sosei Heptares. The companies hope that in the year to come those data targets will be entered for validation, hit generation, and lead selection. What, then, is the solution?

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Digitalising drug discovery

pharmaphorum

As data and digital technology become vital to every aspect of life sciences, the industry is increasingly looking beyond biologists, chemists, and doctors to drive its drug development – and finding that technology has a chief role to play in the future of medicine. on Big data: astronomical or genomical? ,

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Medical Informatics: a bridge between two worlds

pharmaphorum

This is where modern technologies and data-driven medical informatics can bridge gaps in RD research. . The webinar will also cover: How the necessary routine and research data can be collected in registries in a further processable form by patients and healthcare professionals.

Genome 63
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Takeda, Daiichi-backed wearable study planned in Japan

pharmaphorum

The results generated in the study will be combined with data from Tohoku’s Medical Megabank Project (TMM), a wide-ranging national project that is tracking the health of the Japanese population, originally set up in response to the 2011 earthquake and tsunami.