By Matthew Thaxter, Centre for Health Solutions


This week, we published our ninth annual report on Measuring the return from pharmaceutical innovation. Our report tracks the projected return on investment that the 12 leading biopharma companies (by 2009 R&D spend) might expect to achieve from their late-stage pipelines. For the fourth consecutive year, we also track the performance of an extension cohort of four more specialised biopharma companies. This week’s blog summarises the key findings from the 2018 report.

Projected returns hit new lows for both cohorts in 2018

This is the third year that I have been part of the project team involved in producing the report, and my involvement in the detailed analysis we undertake has given me an in-depth understanding of the complexities involved in the pharma R&D process. Indeed, the fact that the projected returns for the original cohort of 12 biopharma companies have more than halved over the past three years demonstrates just how challenging the current R&D environment is for biopharma companies.

In 2018, the projected returns of our original cohort have reached a new low of 1.9 per cent, which represents a near two percentage point decline since 2017 (see Figure 1). Although there is some variation in returns between companies, the range in values between the top and bottom performer is the narrowest it has ever been. Since 2014 we have also analysed the R&D returns of four smaller, more specialised biopharma companies (covering the period 2013-18). While the extension cohort has continued to outperform their larger peers, the consolidated returns of 9.3 per cent in 2018, is also the lowest level yet.

Figure 1 – Return on late-stage portfolio, 2010-18 – original and extension cohort
The decline in projected returns from the investment in R&D can broadly be broken down into two factors:

  • rising R&D costs to develop an asset from discovery to launch
  • declining forecast peak sales from pipeline assets once launched.

Together both cohorts have successfully launched some 54 new drugs in the past year (48 from the original cohort and 5 from the extension cohort), however, the value lost to the commercial portfolio is not being replenished by new assets entering the late-stage pipeline from earlier development stages.

The cost of bringing an asset to market continues to rise

R&D productivity is a factor of the cost to develop an asset and the expected sales from approved assets. For the sixth time in eight years, the cost to develop an asset from discovery to launch has increased for the original cohort, hitting a new high of $2,168 million in 2018 - almost double the average cost recorded in 2010 of $1,188 million. Some of this increase can be attributed to the fall in the number of late-stage pipeline assets - the denominator in the calculation. Escalating R&D costs is a trend shared by the extension cohort, with costs hitting $2,805 million in 2018, making it the fourth year in succession of recording an increase in cost to market and the third year in a row where the cost to market is higher than the original cohort.

Forecast peak sales per asset show a slight decline

Forecast peak sales per asset for the original cohort declined to $407 million per asset in 2018 following a slight uptick in 2017 to $446 million per asset. While this represents an overall decline since the record high of $816 per asset in 2010, the forecast peak sales per asset have remained relatively stable over the past four years. Meanwhile, peak sales per asset for the extension cohort remain at blockbuster levels (forecast peak sales of over $1 billion) in 2018 at $1,165 million – the fourth year out of six that these companies have achieved this figure.

Alongside average peak sales per asset, the contribution of blockbuster products to overall forecast revenues can be used as a measure of pipeline quality. For the original cohort, blockbuster assets comprise only 44 per cent of the pipeline in 2018, compared to 68 per cent back in 2010. As highlighted in our 2016 report, blockbuster costs without corresponding blockbuster revenues is not an equation that drives sustainable returns from investment in innovation.i

The trend towards oncology drug development continues

We are continuing to see evidence that the biopharma companies in the original cohort are shifting their focus towards oncology as they look to maximise their return on investment in R&D. These assets are associated with higher pricing and in 2018, the proportion of oncology assets in the late-stage pipeline reached 39 per cent, up from 18 per cent in 2010 (see Figure 2).

Figure 2 – Late-stage pipeline composition by therapeutic area, 2010-18 – original cohort

Clinical cycle times continue to grow

In the face of growing drug development costs, companies across the industry are looking at ways to shorten development timelines through earlier market entry. One such way is through the development of drugs for conditions with limited or no treatment options, or those offering significant advantages over existing treatments. Such drugs are eligible for Fast Track, Breakthrough, Orphan or Priority Review designations, with one of the benefits being quicker time to market. Across both cohorts, the percentage of assets with such a designation has increased to a third of the pipeline by volume in 2018, up from 20 per cent in 2014. However, perhaps unexpectedly, industry clinical cycle times (Phase I, II and III) have increased over the same period from 6.1 years to 6.6 years despite the award of these designations.

This increase in cycle time can partially be explained by the previously mentioned strategic switch towards the development of cancer therapies (Figure 2). Clinical cycle times within oncology tend to be longer due to the complexity associated with developing them, and insufficient eligible patient populations. While clinical cycle times have shortened for oncology over the past few years, they are still around twice the length on average of some other therapy areas (see Figure 3).

Figure 3 – Clinical cycle times by therapeutic area (TA) (selected TAs only), 2016-18

Technology together with new skills and talent can help transform biopharma R&D

In order to reverse the trend of declining trends in investment in R&D across the biopharma industry, a transformational change in R&D productivity is needed. This requires biopharma companies to adopt new approaches to attracting and retaining top talent at all levels of the organisation and for leaders to have a clear vison as to how digital transformation can improve their R&D. While the catalyst for much of this change can come from technology, through either the replacement or augmentation of work previously performed by humans, new workforce skills and sources of talent, alongside partnerships and collaborations with patient advocacy groups, academia and technology companies, are also required.

Technologies such as robotic process automation and natural language processing/generation can help automate tasks to improve their speed, cost and accuracy. Other technologies, such as machine learning can be implemented to support and improve R&D decision-making and clinical trial design. However, implementing these technologies requires shifting skill sets, new sources of talent and a strategy for where and when implementation should begin. It will be interesting to track the rollout of these technologies across the industry, and the impact that they have on improving R&D productivity.

Matthew Thaxter

Matthew Thaxter - Research Analyst, UK Centre for Health Solutions

Matthew is a Research Analyst at Deloitte’s UK Centre for Health Solutions, the independent research arm of Deloitte LLP’s healthcare and life sciences practice. He supports the Healthcare and Life Sciences practice by producing independent and objective business research and analysis into key industry challenges and associated solutions. Matthew’s previous experience is in market research and he has authored a number of reports on the current and future landscape of healthcare and pharmaceutical markets. Matthew holds an MSc in Immunology from King’s College London.

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