diff --git a/Concept-paper-2022-02-09.md b/Concept-paper-2022-02-09.md
index 3668bb1..ad552d2 100644
--- a/Concept-paper-2022-02-09.md
+++ b/Concept-paper-2022-02-09.md
@@ -27,7 +27,7 @@ Attempt to build a "cannonical" probabalistic model of the clinical trials proce
 A couple of general principles.
 
 - Describe the model in terms of conditional probability distributions (not expectations).
-- Model based on information known at the beginning of the trial. (benefit of the [data] in use)
+- Model based on information known at the beginning of the trial. (benefit of the [historical data](https://gitea.kgjk.icu/Research/ClinicalTrialsEstimation/wiki/Concept-paper-2022-02-09#data) we captured).
     - This might allow me to escape [[EK]]'s markov modeling approach for phase transitions.
 
 ## Phase completion: Joint Probability Estimation (single paper?)
@@ -63,6 +63,15 @@ The probabalistic model could then be used to answer various questions, includin
 It would also be straightforward to develop simulations from this approach, as the probabilities are right there.
 
 # Data
+## Phase Completion
+
+Use the API access given to CBO to get: 
+
+- Information at the beginning of the project.
+- Information after wrap-up of the project (completion status).
+
+This would allow estimation to be contingent on beliefs at the beginning of the trial.
+
 # Estimation Strategy
 Probably use a non-parametric (np-bayesian?) approach to estimating the probability densities.