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AI and the Big Data paradigm – big ambitions in novel drug discovery

pharmaphorum

Over the past few decades, data generation has veritably exploded. However, the ‘Big Data paradigm’ is not so much concerned with the volume of that data, but how businesses and, indeed, industries can derive meaningful insights from what has become a glut of information. A slow journey to drug discovery.

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BIO-Europe Spring Digital: Big data and AI panel discussion

pharmaphorum

The combination of big data and artificial intelligence/machine learning is a powerful one and nowhere more so than in healthcare. As part of BIO-Europe Spring Digital , pharmaphorum founder Dr. Paul Tunnah moderated a panel discussion about big data, AI and applications in the real world. About Bio-Europe Spring Digital.

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Critical tools that support drug discovery and development

Drug Discovery World podcast

This is the latest episode of the free DDW narrated podcast, titled Critical tools that support drug discovery and development, which covers two articles written for DDW Volume 24 Issue 3, Summer 2023.They and Big data: Charting a new path to drug discovery and development .

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AI, big data and real world evidence – the challenges and opportunities

pharmaphorum

One of the main reasons to use RWE is to counter a common criticism of the large phase 3 trials that for so long have been the ‘gold standard’ when developing drugs and gaining authorisations from regulators. BREATHE’s Jenni Quint said that the power is not just in information from wearables but the ability to link them with other data.

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Revolutionizing Medicine and Public Health: The Emergence of Big Data in Healthcare

Roots Analysis

Big Data in healthcare refers to the vast amount of data that is continuously expanding and cannot be efficiently stored or processed using traditional tools. It accounts for the majority of big data in healthcare and comprises information, such as medical images, surveys, chats, and written narratives.

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Digitalising drug discovery

pharmaphorum

The oceans of health data out there can be overwhelming for pharma companies to manage – but if extracted correctly, the prospect to develop drugs from scratch in as little as a year is very real, says Lifebit CEO, Dr Maria Chatzou Dunford. . on Big data: astronomical or genomical? ,

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Synthetic control arms in clinical trials: Making it happen

pharmaphorum

David Clifton is professor of clinical machine learning in the Department of Engineering Science of the University of Oxford. His research focuses on the development of big data machine learning for tracking the health of complex systems. Mark holds a PhD in biomedicine, and an MSc in biostatistics.