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