Analytical Framework for Examining the Value of Antibacterial Products. 3.1 Expected Net Present Value (ENPV) Framework For Evaluating Private Returns


Drug development activities include early stage research and development (R&D), pre-clinical and clinical research as well as supply chain related efforts (such as sample preparation, process research development, manufacturing plant design) (see Figure 1 for a stylized depiction of the drug development process).  Each of these activities involves costs and failure risks.  Thus, a rational forward looking drug sponsor will evaluate these costs and risks against the potential returns before beginning development of a drug.

In this study, we model the drug developer’s evaluation in the form of a decision tree that looks at the decision process from the point of view of an expected-revenue-maximizing sponsor in the face of uncertainty (or risk).

Figure 1: Stylized Model of New Drug Development and Commercialization Activities

Figure 1: Stylized Model of New Drug Development and Commercialization Activities

Source: Blaue, Pekny, Varma, & Bunch, 2004


To illustrate our approach, we consider a highly simplified example adapted from Damodaran (2007) below - the analysis of a New Molecular Entity (NME) candidate for treating a hypothetical Indication X.  Assume that we are provided with the following hypothetical information:3


  • Pre-clinical research and development takes 5.5 years and costs around $21 million to identify a lead molecule.  There is a 31 percent likelihood that a lead molecule will be successfully identified.
  • Phase 1 trial is expected to cost $30 million and to require 100 participants to determine safety and dosage.  The trial is expected to last 1.5 years and there is a 54 percent likelihood that the drug will successfully complete the first phase.
  • Phase 2 involves testing the NME’s effectiveness in treating Indication X on 250 participants over a period of around 2.1 years.  This phase is expected to cost $45 million and the agent will need to show a statistically significant impact on a number of clinical endpoints to move on to the next phase.  There is only a 60 percent likelihood that the drug will prove successful in treating Indication X.
  • In Phase 3, the testing will be expanded to around 500 patients.  The phase will last 2.5 years and cost $210 million, and there is a 67 percent likelihood of success.
  • Upon completion of Phase 3, the sponsor will need to submit a New Drug Application (NDA) to the FDA paying a user fee of $2 million and there is an 85 percent likelihood of being approved.  The NDA/ Biologic License Application (BLA) submission decision will take 0.8 year.
  • Given the size of the patient population and average wholesale price for similar drugs, the net annual returns for the NME, if it is approved, are estimated at $793 million per year for 20 years (i.e., approximately $1.5 billion total).
  • The cost of capital for the sponsor is 11 percent.

We can now draw the decision tree for this NME by specifying the phases, the revenues at each phase, and the respective success and failure probabilities (see Figure 2).  The decision tree depicted shows the likelihood of success at each phase and the marginal returns associated with each step.  Because it takes time to go through the different phases of development, there is a time value effect that is built into the expected returns computation for each path.  The figure reflects this time value effect and computes the cumulative present value of returns from each path using the 11 percent cost of capital as the sponsor’s internal rate of discount.  When time-discounted costs of conducting trials are subtracted from the present value of the returns at the end nodes, we are left with the net present value (NPV) of each possible outcome.

In Figure 2, the yellow square is the root decision node of interest.  It is the point at which the revenue-maximizing sponsor is deciding whether or not to pursue development of the drug.  The green circles (event/chance nodes) represent the possibility of success or failure at each phase, with the probabilities associated with each possibility appearing to the left of each branch.  Finally, the red triangles are the end nodes.  To the right of each end node is the NPV of that outcome to the sponsor.  For example, if the drug completed all phases and successfully reached the market, the NPV of the cost and revenue streams would be $1.5 billion in this scenario.  By contrast, if the sponsor pushed forward with development but the drug failed at some point, the sponsor would incur the costs of the clinical trials without earning any revenues.  Therefore, the other outcome nodes represent negative NPVs.


Figure 2: Drug Development Decision Tree Depicting Expected Net Present Value (ENPV) of Private Returns (Values in $ Million) for a Hypothetical New Molecule X

Figure 2: Drug Development Decision Tree Depicting Expected Net Present Value (ENPV) of Private Returns (Values in $ Million) for a Hypothetical New Molecule X

The dollar values appearing in bold next to the green chance nodes are calculated from right to left across the tree by multiplying the NPVs associated with each outcome by the probabilities of that outcome occurring.  These dollar values thus represent the expected NPVs (ENPVs).  For example, the ENPV at the start of the NDA/BLA review phase is equal to ($1.5 billion × 85 percent) + (-$118 million × 15 percent), or $1.3 billion.  The $1.3 billion can then be used to do the same calculation for the chance node at Phase 3, and so forth until the value at the first chance node can be calculated.  This number, $62 million in this example, represents the ENPV to the sponsor of moving forward with the development project at the time when the decision is made to continue or abandon the new drug.  This value reflects all of the possibilities that can unfold over time clearly depicting the sub-optimal choices that a revenue-maximizing developer should reject.  The decision tree also characterizes the full range of outcomes, with the worst case scenario being failure in the NDA review stage to the best case scenario of FDA approval.


Postmarketing commitments, such as pediatric trials, and costs associated with supply chain activities, as described earlier, do not appear in Figure 2 as part of the decision tree because they do not play a role in determining which branch or outcome node a new drug ends up on in the same way that pre-clinical, Phase 1, 2, 3 trials, and NDA/BLA application process do.  However, these costs can easily be reflected in the values shown in the tree.4  The cost of these activities can then be discounted back to the start of the project (in the same way all of the other costs are) and included in the branch representing successful completion of applicable phases and approval of the new drug.

3 The figures provided are for demonstrative purposes only and do not represent a specific antibacterial NME.

4 For the purposes of this example, the costs of supply chain and post marketing activities are assumed to be zero.

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