What do Las Vegas and Drug Discovery & Development Have in Common?
It’s been said that “the odds of getting a drug to market aren’t much better than winning in Las Vegas. Only one in 5,000 to 10,000 compounds discovered in the lab gains FDA approval.”
The story has been that - while Pharma R&D activity and spending was increasing - the number of approvals for new molecular entities (NMEs) was 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. [source]
This phenomenon earned its own name – Eroom’s Law. That’s Moore’s Law spelled backwards because - unlike computer processing power doubling every two years - 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 were four main causes leading to the decrease in drug research & development productivity:
- “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’s 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’s worth taking a look at what might be changing. And making sure we’re 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:
- •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’re 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’re 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. And 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 pharma 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.