Using @RISK for a Drug Development Decision: a Classroom Example

Using @RISK for a Drug Development Decision: a Classroom Example At Illinois State University, Associate Professor of Finance Domingo Joaquin uses @RISK to demonstrate how simulation modeling can be employed to support the R&D decision of a pharmaceutical firm, illustrating countless risk evaluation examples to students.

Dr. Joaquin uses the example of the fictitious company “Drugco”, which has just successfully completed Phase I and Phase II clinical trials for a new pharmaceutical, “Newdrug”. Drugco must decide if it should proceed with Phase II, which takes two years to complete and requires an investment of $200 million. At completion of Phase III, a filing is made with the FDA, which then takes a year to assess the efficacy of Newdrug in treating the targeted ailment with acceptable levels of side-effects.

If the FDA approves, Drugco can either sell the rights to the drug for a pre-launch exit value of $400 million, or it can launch production by investing $70 million in fixed assets and $30 million in net working capital.

Clearly there is a great deal of uncertainty facing this hypothetical company, making it a perfect problem for @RISK to analyze. Dr. Joaquin has his students include key inputs, including: drug efficacy; market size and growth; initial and subsequent market share; initial and subsequent cost of goods sold to sales ratio, and terminal EBITDA.

After running these inputs through @RISK, students get histograms that depict key outcomes, including the Net Present Value (NPV), Internal Rate of Return (IRR), as well as the most serious risk drivers and influential inputs, as depicted by a tornado chart.

Net Present Value (NPV)

Net Present Value (NPV)

Internal Rate of Return (IRR)

Internal Rate of Return (IRR)

Tornado chart showing ranked inputs and their effect on NPV.

Tornado chart showing ranked inputs and their effect on NPV.

Dr. Joaquin uses @RISK in his classes to teach examples like the one described above, as well as many others, preferring @RISK over other competing products due to its versatility and power.“It makes the process of simulation very easy to do, as opposed to having to start the simulation using Excel,” he says.

Read the detailed case study here.

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