How data-savvy are you in drug discovery?

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Hey there, drug discovery professionals: Ever wondered where you stand in the grand scheme of drug discovery data-savviness? We’ve created a short quiz to help you get an idea. Drug discovery and development is an increasingly data-intensive field, underscoring the need for data science to be a core drug discovery discipline. The industry has taken notice, and is rewarding professionals who excel at integrating research strategies with data analytics and AI. While this assessment is all in good fun, after we get sufficient data, we’ll crunch the numbers, analyze the percentiles and report back with analysis of the collective results. Your participation not only gives you personal insight but also contributes to a broader understanding that we’ll share in our upcoming reports.

We value your privacy; please be assured that we are not collecting any personal information through…

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Ready, set, analyze: Amazon Omics unveils new Ready2Run workflows

Amazon Web Services (AWS) recently announced a significant expansion of Amazon Omics at the annual AWS Life Sciences Executive Symposium in Boston. Amazon Omics, which the company introduced last year, helps life science organizations to store, query and analyze genomic, transcriptomic and other omics data.

Other similar tools include Qlucore Omics Explorer, Genospace, StrandOmics, Signals Translational and the publicly-funded academic-developed platform Galaxy.

Omics data encompass genomics, transcriptomics and other related fields, providing a comprehensive understanding of the genetic, transcriptional and functional elements of biological systems. Such data, instrumental for researchers studying biological systems, plays a vital role in modern drug discovery and development.

Amazon Omics introduces Ready2Run workflows

AWS aims to distinguish Amazon Omics in the marketplace through its comprehensive managed service approach and unique features such as …

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Harnessing the untapped potential of legacy data in pharma R&D

[Image courtesy of James Thew/Adobe Stock]

Clinical trials for a new therapy cost a median of $41,117 per patient. Costs like this are no surprise to pharma leaders. But during an age of increasing budgetary pressures, drug developers are under pressure to do more with less money and staff. While there are no “simple” answers to this challenge, there is one strategy that offers research and development (R&D) teams a very powerful approach: better leveraging existing legacy data. 

Pharmaceutical companies own petabytes of imaging data, generated by in-house research, investigator-initiated studies or clinical trials. This data is valuable and can yield insights that can help researchers better understand disease mechanisms and inform therapeutic approaches. But in many cases, researchers cannot access this important data, as it remains in silos with CROs, investigator labs, or within a specific research group…

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