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Developing new, effective pharmaceutical compounds is a fundamentally 
difficult task.
Starting with challenges identifying promising treatment targets and potential 
compounds to ensuring the drug can be properly delivered within the body, the 
scientific work that needs to succeede is massive.
The regulatory and market conditions in which they exist add to this difficulty. 
For example, regulations are designed to reduce the number of drugs released 
to market with significan issues, such as in the case of VIOXX 
\cite{krumholz_whathavewe_2007} 
or the Perdue Pharma scandal 
\cite{officepublicaffairsjusticedepartment_2020}.
These regulations, such as clinical trial standards 
\todo{add citation to clinical trials here}, 
increase the costs of developing new drugs, adding to the business concerns 
already present, including competitors already in the market or close to 
entering and the overall demand to address a given condition.

%begin discussing failures
%I am thinking I'll discuss marketing and operational failures
%I somehow need to step away from the drug development framing and soften it to ... what? drug investigation?
From these general challenges we can begin to classify failures in drug 
development into a hierarchy of causes.
\cite{khmelnitskaya_competitionattritiondrug_2021}
described two general causes for a drug to exit the drug-development pipline,
strategic exits and scientific failure.
\cite{hwang_failure_2016} 
described failues of Phase III trials in a similar way, 
ascribing drug development failures to issues with safety, 
efficacy, or other (buisness) concerns.

% The only one most ameniable to being targeted by policy 
% is those ``other concerns''.
Although decisions to continue drug development are driven 
by long term profit analyses,
pharmaceutical companies face short term operational challenges.
% As an example, while a drug may have few competitors and 
% strong evidence of safety, difficulties recruiting trial participants may 
% prevent the clinical trials process from being completed successfully.
For example, even with few competitors and strong safety evidence, recruitment difficulties can still derail a drug's clinical trial process.
\todo{Clean up that hypothetical, it doesn't seem clean}
Thus being able to isolate the effect of operational challenges from 
strategic decisions allows us to predict the intended or unintended effects
of a given policy on clinical trials.

In this work, I focus on separating the effects of enrollment and 
competing drugs on clinical trial completion, specifically Phase III trials.
To do this, I create a 
 dataset extracted from 
\url{ClinicalTrials.gov} 
that tracks individual clinical trials as they progress towards completion
as well as a novel causal model of individual clinical trial progression.
Unlike previous research which is focused on the drug development pipeline, I 
restrict my investigation to modelling individual clinical trials.
The goal of this restriction is to provide a way to predict the impact
of changes that affect enrollment independent of other confounding effects. 

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