Data ecosystems in the cloud

Faisal Mushtaq explains the role of cloud informatics in overcoming the challenges associated with modern pharmaceutical R&D

However, the sustained growth in

Increased automation and powerful bioinformatics have created a pharmaceutical R&D landscape where data can be rapidly generated on a truly remarkable scale. Take genome sequencing, for example. Not long ago, mapping gigabase-sized sequences took scientists years to complete using traditional techniques. Today, this can be accomplished in a matter of hours with next-generation sequencing (NGS) technologies(1)

. Similar

advances in mass spectrometry, synthetic biology and quantitative polymerase chain reaction approaches mean today’s R&D pipelines are bursting at the seams with complex, multi-dimensional data.

24 Scientific Computing World October/November 2018

the volume of information generated by modern R&D workflows presents a challenge for biotech and pharmaceutical companies, in terms of organising and utilising these vast datasets. To truly capitalise on the value of these datasets, information management tools must support integrative thinking and enable fast, informed decision-making by these organisations. Moreover, these tools must not only support innovation today – they must be sufficiently flexible and scalable to adapt to tomorrow’s R&D landscape. Increasingly, forward-thinking biotech and pharmaceutical firms are turning to cloud-based informatics platforms, which overcome data management challenges by integrating R&D streams and centrally organising the information they generate. In particular, platform solutions are gaining

traction as a scalable and cost-effective approach to help laboratories connect individual processes to achieve end- to-end visibility of R&D pipelines. In this article, we look at how these cloud-based tools are ideally placed to help businesses take back control of their data and meet the needs of modern pharmaceutical R&D.

The challenge of managing increasingly complex R&D data Drug discovery today is as challenging as it’s ever been. R&D budgets may be squeezed, yet industry players are under continued pressure to bring safe and effective medicines to market against accelerated timeframes. Meanwhile, regulatory authorities are turning their attention to the integrity of pharmaceutical data, putting additional demands on laboratories to demonstrate

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