Life sciences companies are spending more on R&D and earning less for their efforts, according to a recent Deloitte survey. While the cost of developing an asset grew by one-third from 2010 to 2015, from around US$1.2bn to $1.6bn, average peak sales per asset declined by half during the same period, from $816m to $416m. These discrepancies reflect, at least in part, pharma’s over-investment in data-producing technologies such as next-generation sequencing, and a concomitant paucity of investment in data management and data analytics technologies that can make sense of all that input.
The authors of a study in Nature rightly state that the pharmaceutical industry is facing ‘unprecedented challenges to its business model’ and that those challenges can be met by shifting investments to the earlier stages of drug discovery. Companies can accomplish this by allocating some of the money they spend in Phase I–III studies – which currently account for 63% of the total R&D budget – to the preclinical stage; increasing spending in the clinical stages does not correlate with improved return on investment – quite the opposite. Moreover, it has been demonstrated that if companies invest in in silico tools that enable the production of more optimised leads, they have a 50% higher probability of technical success in Phase II at a cost reduction of 30% per new medical entity.
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