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How using AI in clinical trials accelerates drug development

Pharmaceutical Technology

Drug development is already a difficult endeavor, with the vast majority of R&D efforts failing to produce a market-worthy product. Even reaching the clinical trial phase offers no guarantees, as only 12% of such drugs receive U.S. While this process is essential, it’s also slow, expensive and unpredictable.

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University of Sydney will use AI to boost cancer drug research

Pharmaceutical Technology

The university and Pharos have drawn up a memorandum of understanding (MoU) to use AI technology to identify potential compounds for the rapid development of treatments. The MoU allows Pharos to collaborate with the university’s researchers and gives access to its advanced drug discovery infrastructure.

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Crowdsourced science refines AI prediction of clinical trial outcomes

pharmaphorum

The winning team relied on “handcrafted” features that incorporated their own insights into drug development timelines and which data entries should be discarded, according to MIT. The results were interesting, but the team wanted to do better. .

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Data integrity considerations in Pharma and Life Sciences

European Pharmaceutical Review

Data integrity is the term used to describe the accuracy, consistency and reliability of data throughout its lifecycle. In the pharmaceutical/life sciences industries, maintaining data integrity is crucial given its role in making critical decisions that shape outcomes from drug development to human health.