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99 lines
4.0 KiB
TeX
99 lines
4.0 KiB
TeX
\documentclass[../Main.tex]{subfiles}
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\graphicspath{{\subfix{Assets/img/}}}
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\begin{document}
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% hook - what makes drugs expensive? Mention high failure rate
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% describe current research
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% - Examine mechanisms by which clinical trials fail.
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% - Mention data
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% - Results
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How to best address the high cost of pharmaceuticals is a crucial health
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and fiscal policy question that has been debated for
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decades.
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Due to the complicated legal and competitive landscape, unintended consequences
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are common
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\cite{vandergronde_addressingchallengehighpriced_2017}.
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One essential step to introduce a novel pharmaceutical - or even
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to begin selling a generic compound - is to establish that the drug as packaged and sold will
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have acceptable safety and efficacy profiles.
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When evaluating these compounds in a clinical trial, multiple outcomes are possible:
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\begin{enumerate}
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\item The compound demonstrates sufficient safety and efficacy, and proceeds in the appoval process.
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\label{Item:EndSuccess}
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\item The compound fails to demonstrate sufficient safety and efficacy, and the approval process halts.
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\label{Item:EndFail}
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\item The trial is terminated before it can acheive one of the first two
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outcomes, for reasons unrelated to safety and efficacy concerns.
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\label{Item:Terminate}
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\end{enumerate}
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\begin{table}
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\caption{Potential States of Knowledge from a clinical trial}\label{tab:StatesOfKnowledge}
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\begin{center}
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\begin{tabular}{p{0.15\textwidth} p{0.2\textwidth}||p{0.25\textwidth}|p{0.25\textwidth}|}
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\cline{3-4}
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\multicolumn{2}{c|}{Drug-Indication Match} & safe and efficacious & not safe or not efficatious \\
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\hline
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\hline
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\multirow{2}{0.15\textwidth}{Operations} & Success & Known good & Known bad \\
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\cline{2-4}
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& Failure & \multicolumn{2}{c|}{Unkown} \\
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\cline{2-4}
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\end{tabular}
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\end{center}
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\end{table}
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\begin{table}
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\caption{Clinical Trial end states}\label{tab:ClinicalTrialEndStates}
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\begin{center}
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\begin{tabular}{p{0.15\textwidth} p{0.2\textwidth}||p{0.25\textwidth}|p{0.25\textwidth}|}
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\cline{3-4}
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\multicolumn{2}{c|}{Drug-Indication Match} & safe and efficacious & not safe or not efficatious \\
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\hline
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\hline
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\multirow{2}{0.15\textwidth}{Operations} & Success & Completion & Completion or Termination \\
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\cline{2-4}
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& Failure & \multicolumn{2}{c|}{Termination} \\
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\cline{2-4}
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\end{tabular}
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\end{center}
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\end{table}
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While it is known that pharmaceutical companies withdraw some drugs from
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their development pipeline due to commercialization concerns
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(
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\cite{khmelnitskaya_competition_2021}
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and
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\cite{van_der_gronde_addressing_2017}
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), there are likely unseen
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effects that might affect the overall drug pipleline.
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One of these is the concern that when there are already approved therapies on
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the market, patients might be loath to enroll in clinical trials,
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causing the trial to fail for reasons unrelated to the scientific or
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commercial viability of the therapy.
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To adequately guide public policy it is crucial that robust, causally-identified
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statistical models are available to describe the interaction between
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various players within the space.
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This work endeavors to estimate the change in probability of successful completion
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of a clinical trial due to the existence of alternative drugs on the market.
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In particular, it seeks to establish whether such an impact is mediated
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by enrollment patterns or is caused more directly.
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The paper proceeds as follows: a brief literature review in \cref{SEC:LiteratureReview},
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a description of the caual model in \cref{SEC:CausalIdentification},
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followed by a description of the data (\cref{SEC:Data}) and the
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econometric model (\cref{SEC:EconometricModel}).
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Preliminary results are presented in \cref{SEC:Results} and a discussion
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of proposed improvements is included in \cref{SEC:Improvements}.
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\end{document}
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