OPIM101 - Spring 2012 - Lecture 6

# OPIM101 - Spring 2012 - Lecture 6 - Structured Decision...

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Slide 1 OPIM 101, Spring 12, Profs Cachon/Savin, Lecture #6 Structured Decision Making Lecture 6 February 21, 2012

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Slide 2 OPIM 101, Spring 12, Profs Cachon/Savin, Lecture #6 Complex decisions § Research and invest in a compound to treat malaria? § Develop a track of land in the Gulf of Mexico to produce oil and natural gas? § Hire an applicant for a consulting position? § Finance the development of a movie script? § Settle out of court or go to trial? § Perform a medical test or not?
Slide 3 OPIM 101, Spring 12, Profs Cachon/Savin, Lecture #6 Investing in a new compound to develop a new drug § Developing the drug will require additional investment: It will cost \$80 million to move the compound through clinical trials. § Developing the drug is risky: Clinical trials will judge the compound on two dimensions: u Efficacy – is it an effective treatment? u Toxicity – how harmful are the side effects? There is a 25% chance it will pass clinical trials. 25% is called a prior probability – your initial probability assessment. § Developing a drug is potentially profitable: § If it passes clinical trials, it will generate \$360 million in future profit, (not including the development cost) § If it fails, future profit is \$0.

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Slide 4 OPIM 101, Spring 12, Profs Cachon/Savin, Lecture #6 Some data on drug development Indication/disease Phase 1 Phase 2 Phase 3 Overall Alzheimer's disease 0.08 0.24 0.37 0.01 Anxiety disorder 0.01 0.07 0.17 0.00 Breast cancer 0.41 0.48 0.89 0.18 Congestive heart failure 0.27 0.47 0.64 0.08 Epilepsy 0.17 0.39 0.65 0.04 Erectile dysfunction 0.48 0.60 0.80 0.23 Hepatitis B 0.71 0.77 0.97 0.53 Migrane 0.27 0.45 0.72 0.09 Stroke 0.07 0.23 0.34 0.01 Historical probability of success at each clinical milestone for a sample of compounds
Slide 5 OPIM 101, Spring 12, Profs Cachon/Savin, Lecture #6 A simple decision tree Invest Abandon Fail (0.75) Pass (0.25) \$280 = \$360 - \$80 -\$80 \$0 = action or decision node = event node probability payoff outcomes Outcome description Action description

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Slide 6 OPIM 101, Spring 12, Profs Cachon/Savin, Lecture #6 A couple of rules about events and probabilities § Each event node must have an outbound arrow for all possible outcome of that event. § Each possible outcome for that event must have a probability associated with it. § The sum of the probabilities must equal 1.00: Pr(Pass) + Pr(Fail) = 1.00 0.25 + 0.75 = 1.00 Invest Abandon Fail (0.75) Pass (0.25) \$28 0 -\$80 \$0
Slide 7 OPIM 101, Spring 12, Profs Cachon/Savin, Lecture #6 What should we do? One option is Maximin § The maximin decision criterion: For each action evaluate the minimum payoff that could occur. Choose the action that yields the maximum minimum payoff. § In our example:

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OPIM101 - Spring 2012 - Lecture 6 - Structured Decision...

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