Modeling the Volatility and Expected Value of pharmaceutical and biotechnology products, projects, and services.






Case Studies





Case Studies

  • Expected Value Analysis / Real Options Modeling

This expected value analysis case study [real world, sanitized model] is of a single oncology drug [product] targeted for multiple late-stage cancers.  The product is in different phases for each indication, therefore the probability of a positive outcome changes from one indication to another; obviously a Phase III trial has a greater likelihood of success, becoming a marketed product, than does a Phase II trial for the same drug.  In addition, decision tree modeling of expected value looks at the abandonment option; the option to abandon the project if performance in unsatisfactory [i.e. a clinical trial goes bad].  Other options are also modeled and include the option to switch inputs or outputs, option to delay, option to build, option to partner or option to grow.


Simple NPV weighting based on expected probability of positive outcome:

  • 'Expected probability of success' is determined by empirical data and expert opinion.

  • 'Non-weighted NPV' is what the product specific / indication specific model values the product at.

  • 'Weighted or expected NPV' is the adjusted NPV based on the 'expected probability of success'.



Expected prob.

of success

Non-weighted NPV [$000]

Weighted or expected NPV [$000]


Cancer 1






Cancer 2






Cancer 3











Expected value


Decision tree modeling:


Decision tree modeling allows for completely transparent and detailed visualization of the expected value analysis.  As you can see from the decision tree below, running probabilities and running expected NPVs are carried forward along all permutations of each decision branch.  The positive values are obvious and given in the matrix above, in the 'Non-weighted NPV' column.  The negative values [abandonment options] are derived within the product model itself and represent certain amounts of sunk costs if parts of the project were to fail along the way.  The total expected value for this project is $474,658 [000].  This value is 8.8% smaller than our expected value in the simple 'Weighted or expected NPV' analysis.  The difference can be explained in the fact that the decision tree model utilizes the potential losses whereas the matrix above does not.  In addition, the decision tree accounts for more variables and may be considered a more accurate analysis in light of the abandonment option at any node.


Expected value analysis and real options is based around the decision tree model.


The chart below is representative of expected values versus probabilities.  For instance, this project has a 51.60% probability of having an NPV of $397,500 [000] or greater.  This chart has an x-intercept of 92.55%, taken directly from the model.  Effectively, the project has a 92.55% probability of at least breaking even.


Expected value analysis is predicated on a good financial model along with a discounted cash flow model.


This expected value analysis is only a very small portion of an entire financial modeling system where a change in a seemingly unrelated part of the model will propagate throughout modeling system.  This is a very powerful attribute of the SG Systems' models.  Particularly when during the midst of an important presentation and a 'what if' question is asked.  You can simply make the change on-the-fly and have the model updated in seconds.


Expected value analysis can be used on single product, single application projects or on multi-dimensional products spanning multiple product lines and is not limited to pharmaceutical or biotechnology industries. Contact SG Systems for more information or to arrange a consultation.




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