The odds of getting a drug to market are not much better than winning in Las Vegas. Only about one in 10 compounds gain FDA approval. 1 The reason why is because while Big Pharma R&D activity and spending increases, the actual number of approvals for new molecular entities (NMEs) is decreasing.
After approving 86 NMEs in 1999-2001, less than a decade later the FDA approved only 77 in a three-year period. In the same time period, global R&D spending by the top 500 pharma companies jumped from $59 billion to $131.7 billion. 2
This phenomenon earned its own name – Eroom’s Law. 3 That’s Moore’s Law spelled backwards because - unlike computer processing power doubling every two years – Big Pharma R&D productivity (measured by FDA new drug approvals per inflation-adjusted billion dollars spent) has halved roughly every nine years since 1950.
Causes of Declining Pharma Productivity
There are four main causes leading to the decrease in drug research and development productivity 4:
- “Better than the Beatles” Problem: we compete against our greatest hits and any new drug needs to be better than the blockbuster (especially if the blockbuster is now available as a low-cost generic).
- “Cautious Regulator” Problem: a progressive lowering of risk tolerance raises the bar on safety for new drugs.
- “Throw Money at It” Tendency: we hope something sticks, which often leads to waste.
- “Basic Research vs. Brute Force” Bias: we overestimate the probability that newer “brute force” efforts (think large-scale screening processes) will show a molecule safe and effective in clinical trials.
With $2.56 billion being the latest estimated cost for developing a single prescription drug (inclusive of failures and capital), everyone is looking to overcome Eroom’s Law – without feeling like it is just a roll of the dice.
Is Pharma R&D on a Winning Streak?
The good news is the FDA reported a bit of a winning streak, with 41 and 45 approvals in 2014 and 2015, respectively, for both NMEs and BLAs (new Biologics License Application), compared to an average of 25 approvals in the preceding eight years.
Lest we fall prey to Gambler’s conceit, it is worth taking a look at what might be changing. And making sure we are placing the right bets.
The Value of Big Data
Importantly, there is recognition that Big Data plays a role in accelerating successful drug discovery and development. Alongside those “brute force” efforts to do more are Big Data efforts to extract more meaning and insights.
Consider the growing volume, velocity, and variety of life science data 5:
- In genomics, there are 3 billion bases per human genome; 25,000 genes and millions of variants; and up to 1 terabyte of data per sample.
- We are imaging millions of compounds using functional screening, with thousands of cells per well and billions of measurements per run.
- Outcomes are measured from 200,000 registered clinical trials from millions of patients, doctor visits, and samples, with both structured and unstructured data. We are gradually shifting towards complete genomic analysis of patients.
Increasingly, the data being analyzed is not exclusively proprietary or new. Therefore, those who are fastest to glean valuable insights are better positioned to win in the marketplace. While it may be difficult to create another “Sgt. Pepper’s Lonely Hearts Club Band” or control what regulators do, there is opportunity to use Big Data to science’s advantage – for personalized medicine, translational research, and, in general, faster insight to action. Data and analytics are at the heart of envisioned improvements in healthcare.
Realizing these improvements has required new tools and solutions to turn Big Data into Big Insights. Particularly in the life sciences, these solutions must address the informatics challenges of data variety, complexity, volume, and the need for more collaboration, more flexible data infrastructure, and less data isolation.
Betting on Pharma R&D
The sure bet for fixing what ails pharmaceutical R&D, and to ensure the NME and BLA approvals keep rising while lowering total cost, involves better scientific informatics – for collaboration, data analysis and visualization, data integration, and scientific smarts.
When data is unified, visualized, contextualized, and operationalized, it unlocks critical insight.
What are the odds your scientists are empowered by informatics solutions to make better decisions from data? Don’t just roll the dice on turning Big Data into Big Insights. Find out how PerkinElmer Informatics is helping to reverse Eroom’s Law with its winning hand of innovative offerings, such as its E-NotebookTM for Biology product, ChemDraw® and ChemOffice® 15.1 software packages, and the PerkinElmer Signals™ platform powered by the TIBCO Spotfire® offering for instant, stunning visualizations of your data on the fly. In combination they leverage advanced tools in big data storage, search, semantics, and analytics to empower scientists to break down the data silos within their organizations and accelerate R&D development decisions to lead the way from scientific questions to making better business decisions. And that, my friends, is a winning hand.
- Daniel Seaton, "New Study Shows The Rate Of Drug Approvals Lower Than Previously Reported,” Bio.org , January 14, 2014.
- Mark P. Mathieu, "Parexel Biopharmaceutical R&D Statistical Sourcebook 2015/2016," Barnett International, 2016.
- Jack W. Scannell, Alex Blanckley, Helen Boldon & Brian Warrington, “Diagnosing The Decline In Pharmaceutical R&D Efficiency,” Nature Reviews Drug Discovery, Vol. 11, pp. 191-200, March 2012.
- Catherine Arnst, “Why Drug Development Is Failing—And How To Fix It,” Techonomy.com.
- Reid J. Robison, “How big is the human genome in megabytes, not base pairs?” Medium.com, January 6, 2014.