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A Holistic Cure for the Pharmaceutical Industry’s Ailments

Posted on June 17th, 2016 by in Pharma R&D

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Since the turn of the century, the pharmaceutical industry has seen dramatic changes, including dwindling drug pipelines, looming patent expirations and rising costs. The current business model cannot continue to function: there are no indications that this is just a hiccup that will self-correct. If things are to improve, pharmaceutical companies will have to change their approach to multiple aspects of the drug development workflow.

In truth, all stages of early drug development are ripe for innovation. That is not to say that all current practices are outmoded! Recent years have seen changes to the ways data is used, with in silico modeling becoming increasingly common in lead optimization. Researchers are demanding and using powerful research and analytics solutions to find answers about disease biology.

The time is right to look at the whole of early drug development and identify all the areas that can benefit from processes founded on using high-quality data, powerful text-mining software, user-friendly research solutions and in silico modeling tools. Even the approach to collaboration should come under scrutiny. Open innovation is more than just a buzzword: it could hugely boost the potential for new discoveries in pharmaceutical research.

One could ask why it is necessary to assess multiple processes within the workflow in order to achieve positive change. Surely it would be possible to improve just one stage—for example, increase the use of high-throughput in silico screening of potential lead.

But just as in medicine, a holistic approach would have the greatest chance of recognizing how changes to each stage would affect the others. If the pharmaceutical industry is to recover from what ails it now, innovative data-focused methods need to become the new standard across the whole of early drug development—and indeed across the whole industry.

If you would like to know more about how aspects of early drug development could be changed, read this white paper, which discusses the potential areas where high-quality data, in silico modeling and a different attitude to collaboration could bring about considerable positive change.


 

All opinions shared in this post are the author’s own.

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