If you sit in a Big Pharma boardroom during a pipeline review, you will inevitably see a beautifully formatted spreadsheet. It multiplies a projected market share by a calculated price tag, applies a standard probability of success (PoS), and cleanly outputs a predictable, multi-billion-dollar future.

There is only one problem: It’s almost entirely artificial.

In a recent episode of the Flot.Bio Show, Hervé Hoppenot, the legendary ex-CEO of Incyte and veteran of Novartis, pulled back the curtain on how biopharma companies actually make pipeline decisions. From navigating the “Big Bang” of competitive breakthroughs to dealing with the extreme margins of error in forecasting, Hoppenot argues that the industry’s reliance on rigid financial modeling is fundamentally flawed.

Here is why biotech forecasting is an illusion—and what real market validation looks like when you are running through a dark forest at night.

1. The Kitchen Accounting of Pipeline Ranking

Many pharma companies pride themselves on using highly methodical, rational systems to rank their drug candidates. They assign a mathematical probability of success to a molecule, map out the projected market size, and let an algorithm decide which projects live and which ones die.

But according to Hoppenot, that “rationality” is often a front for human bias.

“You look at the ranking and you say, ‘No, because I like that one.’ So you go back to the forecasting guy and you tell them, ‘Okay, put some different stuff in it.’ And it comes back, and you say, ‘Yeah, look, it’s very rational. We can go for this thing.’ There is a lot of that happening in the kitchen.”

Because a spreadsheet can be manipulated to tell any story, using financial forecasts to justify early-stage scientific decisions is a dangerous trap.

2. The 10x Forecasting Delta: Priceless vs. Predictable

In almost any other commercial space—whether it’s retail, software, or real estate—market research can predict demand within a reasonable margin of error. In biotech, the delta between a forecast and reality is routinely 5x to 10x.

Consider some of the industry’s historical anomalies:

• The Downside Illusion: Gleevec (Imatinib) for Chronic Myeloid Leukemia (CML) was initially written off by analysts as a minuscule, low-value indication because the flow of new patients per year was tiny. It went on to become a $6 billion-dollar drug because it radically extended patient survival, expanding the prevalent market.
• The Upside Mirage: Conversely, mega-pharma pipelines are littered with highly anticipated blockbusters predicted to bring in $5 billion that ultimately yield a fraction of that amount when they hit the real world.

Biotech is one of the few industries on Earth where companies must deploy hundreds of millions of dollars over a 10-to-12-year development cycle, completely blind to what the macroeconomic landscape will look like when they cross the finish line.

3. Running Through the Forest at Night: The Threat of Obsolescence

Even if your epidemiology data is perfect, you cannot account for what your competitors are doing six years ahead in the clinic. Hoppenot describes managing a biotech pipeline as a race through a dense forest at night: you simply do not know what is coming around the bend.

The most dramatic example of this was the arrival of PD-1 inhibitors in oncology.

Before the immuno-oncology “Big Bang,” dozens of biotechs were developing highly sophisticated, targeted small molecules for melanoma. When PD-1 therapy hit the market, the entire treatment paradigm shifted overnight. Perfectly valid, scientifically sound projects suddenly became completely obsolete in a matter of minutes—not because the science failed, but because the race moved in an entirely different direction.

4. The Ultimate Directives: Focus on Strong Biology and Patient Impact

If spreadsheets lie, forecasts are off by 10x, and competitive blockbusters can make your asset obsolete overnight, how should biotech executive teams actually make pipeline decisions?

Hoppenot’s philosophy is elegantly simple: If the biology is right, you go.

• Prioritize Transformative Medicine: True validation doesn’t come from a market assessment; it comes from whether a drug does what it is biologically supposed to do and profoundly changes the lives of patients.
• Embrace the Uncertainty: Do not try to calibrate and over-optimize commercial projections from day one. As long as the indication isn’t completely absurd, advance the strong science and let the final financial scale reveal itself later.
• De-Risk with Pure Science: While you can never completely eliminate the “foggy area” of clinical development, anchoring your pipeline in exceptionally strong, unassailable biology is statistically your best tool to improve the probability of producing a massive commercial success.

Ultimately, biotech isn’t about mastering the spreadsheet. It’s about mastering the science. The companies that win are those that accept the inherent chaos of the market and focus entirely on creating medicines that patients genuinely cannot live without.

See the clip of this conversation: