Digital drug discovery: Brave new R&D
May 4, 2018
Current R&D productivity levels are unsustainable.
Recent breakthrough advancements in biomedical research—especially in areas like immunology or genetics—are creating therapy options with transformative efficacy profiles. Accenture research expects pipeline revenue replacement to double from a ratio of 2.6 in 2017 to 5.2 by 2021. This is a level last seen in the mid-2000s.1
While science is unlikely to be the limiting factor in coming years, Pharma needs to make its drug discovery and development engine fit for the future. With the underlying economics largely unchanged, Pharma R&D faces a growing productivity gap. The average capitalized R&D cost per new molecular entity (NME) has increased 148 percent from US$1.1 billion in the 1990s to US$ 2.6 billion nowadays.2
The productivity challenge is likely to intensify with the advent of the precision medicine paradigm. This will shift development efforts towards a larger number of smaller, accelerated trials—driving down average target patient population and thus average peak sales volume of new therapies. Most R&D leaders have yet to course correct, instead continuing to top up their R&D investments to deliver their innovation pipeline at an industry average of 8 percent over the last five years.3
Our analysis shows that embracing digitalization—infusing new technology that exists today into the R&D value chain—can dramatically recalibrate R&D economics by improving quality and compliance, time-to-market, cost efficiency and pipeline value.
Forty-three percent of industry executives are comprehensively investing in digital technologies as part of their overall business strategy.4 With 51 percent of industry executives seeing productivity as a benefit of deploying AI in their organization,5 these technologies will be key to a successful R&D operating model overhaul that makes Pharma fit for the future.
Although most R&D leaders recognize the importance of this contribution, clear strategic roadmaps on how to capture value often do not exist—a result of being paralyzed by the complexity, fragmentation and sheer scale of digital opportunities. Nevertheless, R&D leaders need to develop a strategic perspective on major digital value pockets across discovery and development value steps, and priority technologies.
Accenture Strategy analyzed more than 60 digitalization use cases across the R&D value chain—all of which apply technology mature enough to be implemented on a global scale today. Use cases were assessed based on their potential impact across output, speed, quality and costs to identify priority areas, “no regret” opportunities and game changing potential flagship digitalization projects.
Infusing digital technologies into Pharma R&D can help to close the productivity gap, but it remains R&D leaders’ responsibility to align priorities across the R&D value chain, different emerging technologies and against the business’s strategic objectives. The value contribution of digital use cases in R&D needs to be synced with a company’s competitive priorities and take into consideration corporate strategy, digital ambition and investment opportunities. While “Value Innovators” characterized by a strong focus on improving patient and clinical outcomes may prioritize in favor of time-to-market improvements, “Lean Innovators” with a focus on efficient, world-class operations could emphasize a robotics process automation agenda in regulatory affairs or trial execution.6
R&D leaders will win the digital race by developing, continuously refining and boldly executing a digital R&D transformation journey based on a well-informed, holistic and coherent cross-functional view of value cases.
1 Accenture High Performance Business Research July 2017, based on Evaluate Pharma
2 Tufts CSDD Briefing, 2014
3 Accenture High Performance Business Research July 2017, based on Evaluate Pharma
4 Accenture Technology Vision 2017
5 Accenture Strategy Tech-led Change for AI Research, 2018
6 Healthcare Disrupted – Next Generation Business Models and Strategies, Jeff Elton and Anne O’Riordan, 2016