Unleash AI’s potential, Deloitte’s 14th annual report in Measuring the return from pharmaceutical innovation series, explores the performance of the biopharmaceutical (biopharma) industry and its ability to generate returns from investment in innovative products in the development pipeline. The current biopharma R&D operating model faces several serious challenges, including ongoing regulatory changes, loss of exclusivity of an unprecedented number of high-value assets, and the rapid pace of scientific and technological advancements. However, advances in digitalization and artificial intelligence (AI) present new opportunities to improve R&D productivity, paving the way for a new era of innovation and accelerating patient access to new therapies.
Insights from our year-on-year analysis have demonstrated that transformational change in R&D productivity is essential if improvements in projected returns across the biopharma industry are to be sustained and grow. Our analysis this year shows that this conclusion is as relevant as ever given R&D projected returns remain below the cost of capital which will make R&D leaders’ funding requests continue to be challenging.
The following are the key findings from the report:
Our annual report series Measuring the return from pharmaceutical innovation analyses the projected IRR that biopharma companies can expect to earn from their late-stage pipelines. The past 14 years have demonstrated that transformational change in R&D productivity is required to reverse the declining trends in returns across the biopharma industry while continuing to deliver innovation to patients.
Figure - Opportunities to tackle the drivers of IRR and improve productivity
While R&D executives prioritise expediting the time to market for drugs targeting unmet needs, they also have pressing concerns about the consistently high expenditure and rising costs of R&D. By scaling end-to-end digital transformation and the use of AI and other technology tools, companies have the potential to increase drug development efficiencies dramatically. However, investment in data infrastructure and AI capabilities needs to recognise the importance of maintaining ‘the human in the loop’ in realising value and efficiency gains.
As biopharma companies work to sustain a profitable R&D pipeline and bring new therapeutics to market, they navigate a complex landscape of regulations, looming patent expiries, technological advancements, and competitive pressures. Today the IRA, EU patent laws and the rapid advent of AI across the industry are demanding fast-paced, flexible and collaborative R&D operating models to stay ahead of the curve.
Since 2010, our cohort of companies have struggled to replenish their R&D pipeline with new assets at the same pace, and to the same value, as the assets leaving the pipeline due to successful regulatory approval or late-stage termination. With rising costs, long cycle times, looming patent expiries, a complex M&A landscape and changing regulations, biopharma is nearing the point where the commercial portfolio is unable to sustain innovative R&D and support long-term growth.