Add 'Concept paper 2022-02-09'
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# Goals
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I think I can get two, maybe three, papers out of this:
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- Estimate the joint probability of success and Plan Normalized duration.
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- Estimate a model similar to EK's model of market vs scientific failure.
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- Develop a structural model that includes a policy parameter relevant to a policy the CBO cares about (Not a high priority yet).
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## Questions:
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- How can one statistically describe the way drugs pass through the FDA development pipeline?
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- What is the effect of `policy` on phase completion and phase transition?
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# Models
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## Phase completion: Joint Probability Estimation (single paper?)
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Can probably use the data we have.
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This would include Plan Normalized duration, where we take the planned completion date and
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estimate the term: (Actual completion date - start date)/(Planned completion date - start date)
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By estimating P(end condition | data) and P(Plan normalized duration | end condition & data) I can get
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P(end condition and Plan normalized duration | data), the more useful joint probability describing phase completion.
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## Phase Transition: Probability Estimation (single paper?)
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Once I have the joint probability, I can begin estimateing a model similar to Ekaterina Khmelnitskaya's model of drug development,
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trying to separate out probability of scientific vs market drops.
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This would use the IND or similar data to build the list of phase transitions.
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### Design tradeoffs
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Some design tradeoffs include
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- Normalized or non-normalized transition paths? I'm particularly interested in inclucing mixed-phase paths.
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## Overall Model
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Overall this would allow me to construct a probabalistic description of passing through the d
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# Estimation Strategy
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Probably use a non-parametric bayesian approach to estimating the probability densities.
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## Identification Strategy
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