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Measuring the return from pharmaceutical innovation 2020

Seeds of change

Since 2010, we have been tracking the returns on R&D investment that the largest biopharma companies might expect to achieve from their late-stage pipelines. Our latest analysis shows a small uptick for the first time in six years. Is this a sign of reversal in the declining trend and to what extent has the COVID-19 pandemic sowed the seeds of change for pharma R&D productivity still further?

Our latest report looks at the current state of R&D returns for 15 leading biopharma companies from May 2019 to April 2020, the impact of the pandemic on R&D pipelines during 2020 and identifies lessons that can help change the R&D paradigm towards a future with higher returns.

Measuring the return from pharmaceutical innovation 2020

Although biopharma R&D is under mounting pressure, our analysis shows an uptick for the first time in six years (from 1.6 per cent in 2019 to 2.5 per cent in 2020).

While forecast peak sales per pipeline asset have increased by 17.9 per cent (from $357 million in 2019 to $421 million in 2020, companies are still facing rising costs of developing an asset. The average cost to bring an asset to market has risen for the seventh year in a row to $2,442 million, due in part to longer cycle times.

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The growing complexities of drug development and increasing numbers of oncology trials have made it difficult to enrol and retain clinical trial participants. In addition, the rising number of therapies targeted at unmet needs and smaller patient subgroups has further increased the competition to recruit from the limited pool of available trial participants. These factors have created delays and have been contributing to a year-on-year growth in cycle times.

Amid growing cycle times, regulators have put in place several pathways to expedite the development and approval of new drugs and accelerate patient access to life-saving innovative therapies. However, despite this, average clinical cycle times have continued to lengthen.

Nevertheless, the seeds of change have been sown, with moves to integrate the application of AI and other digital technologies to transform drug development and clinical trials. Use of real-world evidence (RWE) and enhanced segmentation of patients and disease can contribute to shorter cycle times, but upscaling their use will be essential.

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The COVID-19 pandemic has had a significant disruptive effect on clinical trial operations, with biopharma companies, clinical research organisations (CROs) and other research organisations being forced to shut down trials, suspend enrolment, or delay planned study start-ups or completions (an estimated 1,210 trials have been negatively affected across the industry).

However, the pandemic has also accelerated the adoption of new approaches to R&D with the development of a number of novel COVID-19 vaccines and therapies in record time through extraordinary collaboration and partnerships, and a wider use of transformative approaches such as master protocols and adaptive trial design, and use of real-world data (RWD).

The positive learnings arising from the COVID-19 pandemic have sown the seeds of change for a more productive future for biopharma R&D. Moreover, the accelerated development of COVID-19 therapies and vaccines is expected to have a positive impact on the industry IRR over the coming years.

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While our analysis has shown some productivity improvements, there is still a way to go for the industry to sustain these green shoots of recovery. The legacy of the pandemic is likely to be an acceleration towards a data-driven future for R&D which embraces new technologies and transformative approaches, potentially reversing the declining trend in IRR. This will require collaboration between organisations and the new regulatory paradigms that emerged during the pandemic being fully embedded, as well as the use of digital and other transformative approaches to expedite drug development being adopted at scale. Improving R&D productivity will also require companies to attract and retain a diverse and digitally literate workforce and deploy AI-friendly and tech-savvy leaders, willing to embrace new business and operating models.

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