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In 19xx the United States Food and Drug Administration (FDA) was created to "QUOTE".
As of Sept 2022 \todo{Check Date} they have approved 6,602 currently-marketed compounds with Structured Product Labels (SPL) 
and 10,983 previously-marketed SPLs. 
%from nsde table. Get number of unique application_nubmers_or_citations with most recent end date as null.
In 2007, they began requiring that drug developers register and publish clinical trials on \url{https://clinicaltrials.gov}.
This provides a public mechanism where clinical trial sponsors are responsible to explain
what they are trying to acheive and how it will be measured, as well as provide the public the ability to
search and find trials that they might enroll in.
Data such as this has become part of multiple datasets 
(e.g. the Cortellis Investigational Drugs dataset or the AACT dataset from the Clinical Trials Transformation Intiative) 
used to evaluate what drugs might be entering the market soon.
This brings up a question: can we use this public data on clinical trials to describe what effects their success or failure?
In this work, I use updates to records on \url{https://ClinicalTrials.gov} to disentangle 
the effect of participant enrollment and drugs on the market affect the success or failure of clinical trials.

%Describe how clinical trials fit into the drug development landscape and how they proceed
Clinical trials are a required part of drug development.
Not only does the FDA require that a series of clinical trials demonstrate sufficient safety and efficacy of
a novel pharmaceutical compound or device, producers of derivative medicines may be required to ensure that
their generic small molecule compound -- such as ibuprofen or levothyroxine -- matches the
performance of the originiator drug if delivery or dosage is changed.
For large molecule generics (termed biosimilars) such as Adalimumab
(Brand name Humira, with biosimilars Abrilada, Amjevita, Cyltezo, Hadlima, Hulio,
Hyrimoz, Idacio, Simlandi, Yuflyma, and Yusimry),
the biosimilars are required to prove they have similar efficacy and safety to the
reference drug.

When registering these clinical trials
% discuss how these are registered and what data is published.
% Include image and discuss stages
% Discuss challenges faced

% Introduce my work

In the world of drug development, these trials are classified into different 
phases of development.
\cite{FDADrugApprovalProcess_2022} 
provide an overview of this process
\cite{commissioner_DrugDevelopment_2020}
while describes the actual details.
Pre-clinical studies primarily establish toxicity and potential dosing levels 
\cite{commissioner_DrugDevelopment_2020}.
Phase I trials are the first attempt to evaluate safety and efficacy in humans. 
Participants typically are heathy individuals, and they measure how the drug 
affects healthy bodies, potential side effects, and adjust dosing levels. 
Sample sizes are often less than 100 participants. 
\cite{commissioner_DrugDevelopment_2020}.
Phase II trials typically involve a few hundred participants and is where 
investigators will dial in dosing, research methods, and safety.
\cite{commissioner_DrugDevelopment_2020}.
A Phase III trial is the final trial befor approval by the FDA, and is where 
the investigator must demonstrate safety and efficacy with a large number of 
participants, usually on the order of hundreds or thousands.
\cite{commissioner_DrugDevelopment_2020}.
Occassionally, a trial will be a multiphase trial, covering aspects of either
Phases I and II or Phases II and III. 


After a successful Phase III trial, the sponsor will decide whether or not 
to submit an application for approval from the FDA. 
Before filing this application, the developer must have completed 
"two large, controlled clinical trials."
\cite{commissioner_DrugDevelopment_2020}.
Phase IV trials are used after the drug has recieved marketing approval to 
validate safety and efficacy in the general populace.
Throughout this whole process, the FDA is available to assist in decisionmaking
regarding topics such as study design, document review, and whether or not
they should terminate the trial. 
The FDA also reserves the right to place a hold on the clinical trial for 
safety or other operational concerns, although this is rare. 
\cite{commissioner_DrugDevelopment_2020}.

In the economics literature, most of the focus has been on evaluating how 
drug candidates transition between different phases and their probability 
of final approval.
% Lead into lit review
% Abrantes-Metz, Adams, Metz (2004)
\cite{abrantes-metz_pharmaceutical_2004}, 
described the relationship between
various drug characteristics and how the drug progressed through clinical trials.
% This descriptive estimate was notable for using a 
% mixed state proportional hazard model and estimating the impact of 
% observed characteristics in each of the three phases.
They found that as Phase I and II trials last longer, 
the rate of failure increases. 
In contrast, Phase 3 trials generally have a higher rate of 
success than failure after 91 months.
This may be due to the fact that the purpose of Phases I and II are different
from the purpose of Phase III.

Continuing on this theme,
%DiMasi FeldmanSeckler Wilson 2009
\cite{dimasi_TrendsRisks_2010} examine the completion rate of clinical drug 
develompent and find that for the 50 largest drug producers, 
approximately 19\% of their drugs under development between 1993 and 2004
successfully moved from Phase I to recieving an New Drug Application (NDA) 
or Biologics License Application (BLA). 
They note a couple of changes in how drugs are developed over the years they 
study, most notably that
drugs began to fail earlier in their development cycle in the 
latter half of the time they studied. 
They note that this may reduce the cost of new drugs by eliminating late 
and costly failures in the development pipeline.

Earlier work by 
\authorcite{dimasi_ValueImproving_2002}
used data on 68 investigational drugs from 10 firms to simulate how reducing
time in development reduces the costs of developing drugs. 
He estimates that reducing Phase III of clinical trials by one year would 
reduce total costs by about 8.9\% and that moving 5\% of clinical trial failures
from phase III to Phase II would reduce out of pocket costs by 5.6\%. 

Like much of the work in this field, the focus of the the work by 
\citeauthor{dimasi_ValueImproving_2002}
and
\citeauthor{dimasi_TrendsRisks_2010}
tends to be on the drug development pipeline, i.e. the progression between 
phases and towards marketing approval. 
A key contribution to this drug development literature is the work by 
\authorcite{khmelnitskaya_CompetitionAttrition_2021}
on a causal identification strategy
to disentangle strategic exits from exits due to clinical failures 
in the drug development pipeline.
She found that overall 8.4\% of all pipeline exits are due to strategic 
terminations and that the rate of new drug production would be about 23\% 
higher if those strategic terminatations were elimintated.

The work that is closest to mine is the work by 
\authorcite{hwang_FailureInvestigational_2016}
who investigated causes for which late stage (Phase III)
clinical trials fail -- with a focus on trials in the USA, 
Europe, Japan, Canada, and Australia. 
They identified 640 novel therapies and then studied each therapy's 
development history, as outlined in commercial datasets.
They found that for late stage trials that did not go on to recieve approval,
57\% failed on efficacy grounds, 17\% failed on safety grounds, and 22\% failed
on commercial or other grounds.

% Begin Discussing what I do. Then introduce 
Unlike the majority of the literature, I focus on the progress of 
individual clinical trials, not on the drug development pipeline. 
In both 
\authorcite{khmelnitskaya_CompetitionAttrition_2021}
and
\authorcite{hwang_FailureInvestigational_2016}
the authors describe failures due to safety, efficacy, or strategic concerns.
There is another category of concerns that arise for individual clinical trials,
that of operational failures. 
Operational failures can arise when a trial struggles to recruit participants, 
the principle investigator or other key member leaves for another opportunity,
or other studies prove that the trial requires a protocol change. 

% In a personal review of 199 randomly selected clinical trials from the AACT
% database, the 
% \begin{table}
%     \caption{}\label{tab:}
%     \begin{center}
%         \begin{tabular}[c]{|l|l|}
%             \hline
%             Reason & Percentage Mentioned \\
%             \hline
%             Safety or Efficacy & 14.5\% \\
%             Funding Problems & 9.1\% \\
%             Enrollment Issues & 31\% \\
%             \hline
%         \end{tabular}
%     \end{center}
% \end{table}



This paper proposes the first model to separate the causal effects of 
market conditions (a strategic concern) from the effects of 
participant enrollment (an operational concern). 
This will allow me to answer the questions:
\begin{itemize}
    \item What is the marginal effect on trial completion of an additional 
        generic drug on the market?
    \item What is the marginal effect on trial completion of a delay in 
        closing enrollment?
\end{itemize}
To undderstand how I do this, we'll cover some background information on 
clinical trials in section \ref{SEC:ClinicalTrials}, 
explain the data in section \ref{SEC:DataSources}, 
and then examine causal identification and econometric model in sections 
\ref{SEC:CausalIdentificationAndModel}. 
Finally I'll review the results and conclusion in sections 
\ref{SEC:Results}
and
\ref{SEC:Conclusion}
respectively

% \subsection{Market incentives and drug development}
% %%%%%%%%% What do we know about drug development incentives?
%
% \cite{dranove_DoesConsumer_2022} use the implementation of Medicare part D 
% to examine whether the production of novel or follow up drugs increases during 
% the following 15 years. 
% They find that when Medicare part D was implemented -- increasing senior 
% citizens' ability to pay for drugs -- there was a (delayed) increase 
% in drug development, with effects concentrated among compounds that were least
% innovative according to their classification of innovations.
% They suggest that this is due to financial risk management, as novel 
% pharmaceuticals have a higher probability of failure compared to the less novel
% follow up development. 
% This is what leads risk-adverse companies to prefer follow up development.
%
%
% % Acemoglu and Linn
% % - Market size in innovation
% % - Exogenous demographic trends has a large impact on the entry of non-generic drugs and new molecular entitites.
% On the side of market analysis, 
% \citeauthor{acemoglu_market_2004} 
% (\citeyear{acemoglu_market_2004})
% used exogenous deomographics changes to show that the
% entry of novel compounds is highly driven by the underlying aged population.
% They estimate that a 1\% increase in applicable demographics increase the
% entry of new drugs by 6\%, mostly concentrated among generics.
% Among non-generics, a 1\% increase in potential market size 
% (as measured by demographic groups) leads to a 4\% increase in novel therapies.
%
% % Gupta
% % - Inperfect intellectual property rights in the pharmaceutical industry
% \cite{gupta_OneProduct_2020} discovered that uncertainty around which patents
% might apply to a novel drug causes a delay in the entry of generics after 
% the primary patent has expired. 
% She found that this delay in delivery is around 3 years. 
%
% % Agarwal and Gaule 2022
% % - Retrospective on impact from COVID-19 pandemic
% % Not in this version
%
% \subsection{Understanding Failures in Drug Development}
%
% % DISCUSS: Different types of failures
% There are myriad of reasons that a drug candidate may not make it to market, 
% regardless of it's novelty or known safety.
% In this work, I focus on the failure of individual clinical trials, but the 
% categories of failure apply to the individual trials as well as the entire
% drug development pipeline.
% They generally fall into one of the following categories:
% \begin{itemize}
%     \item Scientific  Failure: When there are issues regarding 
%         safety and efficacy that must be addressed. 
%         The preeminient question is: 
%         ``Will the drug work for patients?''
%         %E.Khm, Gupta, etc.
%     \item Strategic Failure: When the sponsors stop development because of 
%         profitability
%         %Whether or not the drug will be profitiable, or align with
%         %the drug developer's future Research \& Development directions i.e.
%         ``Will producing the drug be beneficial to the 
%         company in the long term?''
%         %E.Khm, Gupta, GLP-1s, etc.
%     \item Operational concerns are answers to: 
%         %Whether or not the developer can successfully conduct
%         %operations to meet scientific or strategic goals, i.e. 
%         ``What has prevented the the company from being able to 
%         finance, develop, produce, and market the drug?''
% \end{itemize}
% It is likely that a drug fails to complete the development cycle due to some
% combination of these factors. 
%
%
% %USE MetaBio/CalBio GLP-1 story to illuistrate these different factors.
% \cite{flier_DrugDevelopment_2024} documents the case of MetaBio, a company
% he was involved in founding that was in the first stages of
% developing a GLP-1 based drug for diabetes or obesety before being shut down
% in . 
% MetaBio was a wholy owned subsidiary of CalBio, a metabolic drug development 
% firm, that recieved a \$30 million -- 5 year investment from Pfizer to 
% persue development of GLP-1 based therapies. 
% At the time it was shut down, it faced a few challenges:
% \begin{itemize}
%     \item The compound had a short half life and they were seeking methods to 
%         improve it's effectiveness; a scientific failure.
%     \item Pfizer imposed a requirement that it be delivered though a route
%         other than injection (the known delivery mechanism); a strategic failure. 
%     \item When Pfizer pulled the plug, CalBio closed MetaBio because they 
%         could not find other funding sources; an operational failure.
% \end{itemize}
%
% The author states in his conclusion:
% \begin{displayquote}
%     Despite every possibility of success, 
%     MetaBio went down because there were mistaken ideas about what was 
%     possible and what was not in the realm of metabolic therapeutics, and 
%     because proper corporate structure and adequate capital are always 
%     issues when attempting to survive predictable setbacks.
% \end{displayquote} 
%
% From this we see that there was a cascade of issues leading to the failure to 
% develop this novel drug. 
%
%
% % I don't think I need to include modelling enrollment here. 
% % If it is applicable, it can show up in those sections later.
%
%

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