Have you ever worked for (or watched) a company that slowly went from introducing innovative products to just line extensions, possibly without even realizing it? It usually happens to companies that have been in their product space for a while with solid sales and is a result of finance folks pushing the company for predictable revenue to keep shareholders happy.
Combine desire for predictable revenue with portfolio valuation models that don’t or can’t properly assess the value of high-risk early development assets, and you eventually end up with a product portfolio with little innovation and very slow revenue growth, in the classic growth-maturity-decline/extension product lifecycle.
Sadly, most Big Pharma is on this road, especially with all the recent cost-cutting. Depending on which journal or analysis you read, the share of first-in-class (FIC) therapeutics Big Pharma has discovered in-house has dropped over the last 10-15 years to a mere 15-ish percent.
The Cause: Risk Aversity
For decades, the industry has been grappling with the question of why pre-clinical models and testing don’t translate well to clinical success. And there has been much discussion at recent conferences about AI, new diagnostics, and better biomarkers to more accurately model human disease and therefore create more predictable outcomes from research efforts.
That is all well and good. We would all love to have an accurate model of human response to novel molecules! The implications of this holy grail would be enormous. My concern is the undercurrent message: the decreasing amount of risk Big Pharma is willing to take in their pipelines. The trend shows Big Pharma downsizing their early research and leaving the true innovation to startups.
Currently, cutting costs in pharma R&D pipelines, especially early R&D, is rampant. I know from discussions with portfolio managers the thinking is to reduce early development risk and buy small companies to fill in pipeline holes. The problem is that Big Pharma has historically been responsible for many important FIC drugs. So, from a macro-level, the pace of innovation will slow down.
You Don’t Know as Much as You Think You Do
Despite many years of data to the contrary, pharma portfolio managers still seem to think they can predict the value of a therapeutic. They can’t. I remember seeing a presentation at a portfolio management conference years ago given by a Big Pharma portfolio leader on the actual cumulative revenue of their drugs five years after launch versus the prediction at launch. The R-squared value of their scatter plot was 2 percent, meaning their valuations, even at launch, were almost worthless.
Let’s look at some other examples of trying to predict a therapeutic’s revenue:
- Keytruda’s predicted 2025 sales are $31 billion, yet in early 2010, Merck terminated its development before reactivating the program at the end of 2010.
- While Big Pharma guards its valuations, Evaluate Pharma, a well-respected pharma analytics company, in 2021 predicted 2026 sales of Lilly’s tirzepatide to be $4.8 billion. Actual 2024 sales were close to $14 billion, and that could double in 2025.
- The same report predicted 2026 sales of Reata/Kyowa Kirin’s bardoxolone at $2.3 billion. The actual sales are zero because the drug was abandoned.
Balance Your Pipeline and Take Some Risks
Most pharma companies’ mission statements use the words “breakthroughs,” “innovation,” or “discovery.” And everyone’s trying to do it smarter. But predictability, especially around innovation, is a fallacy. Not that they shouldn’t keep trying. But there is also a numbers game here, and more money in early R&D will result in more FIC therapeutics.
Drug companies need to get back to standard balanced portfolio practices. Trust your instincts and the instincts and insights of your early research teams. You have capabilities and knowledge startup companies don’t have. It’ll be better for your investors as well as patients in the long run.
We need Big Pharma to stay true to their mission, spur innovation, and bring critical new therapeutics to patients. That is what will increase sales and revenue, not R&D cost cutting.
That means taking more risks, not fewer, and not waiting for the holy grail of an accurate human model for disease.
April 15, 2025
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