R&D productivity: Analytics of a new drug

Try Googling “pharmaceutical crisis” and you’ll find a mass of dire statistics that lays bare the scale of the challenge facing Big Pharma. Recent years have seen key players undergo cycles of restructuring and though they can still make good money for now, can things go on as they are?

Pills Life SciencesThe pressing issue facing pharma is that the value in the pipelines of new drugs is not keeping pace with R&D costs.  Before the patents protecting existing blockbuster drug income  run out, new products must be approved that meet the  innovation and value demands of regulators and payers. You  have to factor in other complex global issues to truly understand  the industry decline, but the inescapable nub at its heart is the  failure to get enough novel, high value drugs to market.

The Tessella “Decisions First, Data Last” analytics mantra  captures the need to understand up front why specific data is  collected and how it helps make better decisions. Pipeline value  needs to be better understood, and the complex decisions by which the right candidates get to market must become better informed. As we will see later, recent research is providing us with a new view on how big pharma is finding to its cost, that this ambition is easily stated but proving hard to achieve.

Our experience from working in diverse areas, such as strategies for toxicity screening, portfolio management and optimised clinical trial design, establishes a clear focus for improvements: concentrating on quantitative decision making, earlier attrition of poor performers and clear tracking of return on investment (ROI) using a value-based analysis.

When it comes to managing drug pipelines, no-one wants their pet candidates to be the ones culled. When facing go / no-go decisions, the temptation is to find reasons to go on rather than stop. Mitigating factors are found to offset negative results. The few stories of eventual success, after fighting off repeated threats of oblivion, are used to console doubters. The value of “seeing things through” is invoked. These intrinsically human factors show that science, logic and evidence-based analytics do not always win the day.

Our own analysis of the barriers to rational decision making shows that no-one is immune to these effects. Those looking for a single answer to this problem, and a simple action to put it right, are liable to be disappointed. Our multi-dimensional approach to tackling this issue is strongly corroborated by new research published by the Boston Consulting Group*. They analysed the difficult journey towards regulatory approval of 842 candidate molecules, trialled between 2002-2011. 18 diverse criteria were used to rate each molecule, covering intrinsic factors, say molecular size, market factors, such as disease type targeted, and corporate factors, like total company spend on R&D.

Insight gained from correlating these factors with the 205 successful candidates, confirm our own picture. Where greater success rate was achieved, it was by companies who “knew what they were doing” and retained a “better focus” on their end goal. As often found in the world of analytics, you cannot measure interesting but subtle factors like these directly. You have to resort to measurement by proxy. Since fundamental science is at the heart of drug discovery, this research chose as a proxy the quality of the research output and the number of patents, for every $ spent on R&D. It also included the record of early termination of underperforming candidates, showing the importance of understanding what success smells like from an early stage. All these factors correlated strongly with greater rates of regulatory approval, irrespective of company size.

This research shows that a “truth-seeking” rather than “progression-seeking” R&D decision making culture is the way forward, steering pipeline management back towards science and a clearer vision of what represents value. A more in-depth Tessella view of this research and on pipeline value are available from our website.

To find out more on how Tessella provides practical ways to support this level of R&D decision-making, read Tom Parke’s view of clinical trial design in this issue, and visit tessella.com for a comprehensive picture of our Life Sciences and Analytics service offerings.

Find Nick on Twitter @Analytics_Lab.

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