JobMarketPaper/Paper/sections/12_clinical_trial_background.tex

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% Clinical Trials Background Outline
% - ClinicalTrials.gov
% - Clincial trial progression
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To understand why clinical trials succeed or fail requires understanding how 
they operate and how their progress is documented. 
The primary source of this operational data is ClinicalTrials.gov, where 
investigators record key information about their trials' status and progression. 
To understand how my administrative data captures trial progression, we'll 
examine how investigators document their trials' states and transitions.
Figure \ref{Fig:Stages} is a flowchart of definitions of the different states 
that a trial can take and the decisions leading to each. 
It also describes the knowledge obtained by the study operator
and how that influences further decisions.
The states are standardized and defined by the National Library of Medicine
\cite{usnlm_protocolregistrationdata_2024-06-17}.
During the prior to a study, the trial investigators will design the trial, 
choose primary and secondary objectives,  and decide on how many participants
they need to enroll. 
 Once they have decided on these details, they post the trial to
\url{ClinicalTrials.com} and decide on a date to begin enrolling trial
participants. 
% If the investigators decide to not continue with the trial before enrolling any
% participants, the trial is marked as ``Withdrawn''. 
% If they begin enrolling participants, there are two methods to do so.
% The first is to enter an "Enrollment by invitation only" state where the 
% trial operators extend invitations through their own connections to doctors 
% and patients they are working with.
% The second is to enter a general ``Recruiting'' state, where participants apply 
% to join the trial, and the sponsoring organization may extend invitations as 
% before.
After a trial has enrolled enough participants, the sponsor will  move to an 
"Active, not recruiting" state to inform potential participants that they have
recruiting. 
During this time, the trial operators continue monitoring participants for 
adverse events and tracking their disease severity and compliance with treatment. 
Finally, when the investigators have obtained enough data to achieve their primary
objective, the clinical trial will be closed and marked as ``Completed'' in
\url{ClinicalTrials.gov}
If the trial is closed before achieving the primary objective, the trial is 
marked as ``Terminated'' on
\url{ClinicalTrials.gov}.
Trials can be terminated because safety or efficacy evidence suggested it was 
not worth continuing, enrollment rates were too low to achieve the primary
objective within time and budget contstraints.

\begin{figure}%[H] %use [H] to fix the figure here.
    \includegraphics[width=\textwidth]{../assets/img/ClinicalTrialStagesAndStatuses}
    \par \small 
        Diamonds represent decision points while
	Squares represent states of the clinical trial and Rhombuses represent data obtained by the trial.
    \caption[Clinical Trial Stages and Progression]{Clinical Trial Stages and Progression}
    \label{Fig:Stages}
\end{figure}

% Note the information we obtain about the trial from the final status: 
% ``Withdrawn'', ``Terminated'', or ``Completed''.
As a trial goes through the different stages of recruitment, the investigators
update the records on ClinicalTrials.gov. 
Even though there are only a few times that investigators are required 
to update this information, it tends to be updated somewhat regularly during 
enrollment as it is a way to communicate with potential enrollees. 
When a trial is first posted, it includes information
such as planned enrollment, 
planned end dates, 
the sites at which it is being conducted, 
the diseases that it is investigating, 
the drugs or other treatments that will be used,
and who is sponsoring the trial.
As enrollment is opened and closed and sites are added or removed, 
investigators will update the status and information
to help doctors and potential participants understand whether they should apply. 

When a trial ends, it can end in one of three ways.
The most desirable outcome is completion, where the trial achieves its 
primary objective by gathering sufficient data about safety and efficacy.
However, trials may also end early either through withdrawal 
(as mentioned previously) 
or termination. 
Termination occurs after enrollment has begun but before achieving the 
primary objective.

Understanding why trials terminate early is the key goal of this work, but
is not straightforward.
Terminated trials typically record a 
description of \textit{a single} reason for the clinical trial termination. 
This doesn't necessarily list all the reasons contributing to the trial 
termination and may not exist for a given trial.
As an example, if a Principal Investigator leaves for another institution 
(terminating the trial), this decision may be affected by things such as
a safety or efficacy concern, 
a new competitor on the market, 
difficulties recruiting participants,
or a lack of financial support from the study sponsor.
In this way, the stated reason may mask the underlying challenges that 
led to the termination, leaving us to 
use another way to infer the relative impact of operational difficulties.


To better descrobe termination causes, I suggest classifying them into 
three broad categories. 
The first category, Safety or Efficacy concerns, occurs when data suggests 
the treatment is unsafe or unlikely to achieve its therapeutic goals. 
While Khmelnitskaya 
\cite{khmelnitskaya_competitionattritiondrug_2021}
describes these as scientific failures, I contend that they represent successful 
knowledge gathering - the clinical trial process working as intended to 
identify ineffective treatments. 
The second category, Strategic concerns, encompasses business and 
market-driven decisions such as changes in company priorities or 
competitive landscape. 
The final category, Operational concerns, includes practical challenges 
like insufficient enrollment rates or loss of key personnel. 
These latter two categories represent true failures of the trial process, 
as they prevent us from learning whether the treatment would have 
been safe and effective.

\subsection{Data Summary}
%% Describe data here
Since Sep 27th, 2007 those who conduct clinical trials of FDA controlled 
drugs or devices on human subjects must register 
their trial at \url{ClinicalTrials.gov}
(\cite{anderson_fdadrugapproval_2022}).
This involves submitting information on the expected enrollment and duration of
trials, drugs or devices that will be used, treatment protocols and study arms, 
as well as contact information the trial sponsor and treatment sites.

When starting a new trial, the required information must be submitted 
``\dots not later than 21 calendar days after enrolling the first human subject\dots''.
After the initial submission, the data is briefly reviewed for quality and 
then the trial record is published and the trial is assigned a 
National Clinical Trial (NCT) identifier.
(\cite{anderson_fdadrugapproval_2022}).

Each trial's record is updated periodically, including a final update that must occur 
within a year of completing the primary objective, although exceptions are
available for trials related to drug approvals or for trials with secondary
objectives that require further observation\footnote{This rule came into effect in 2017}
(\cite{anderson_fdadrugapproval_2022}).
Other than the requirements for the first and last submissions, all other
updates occur at the discresion of the trial sponsor.
Because the ClinicalTrials.gov website serves as a central point of information
on which trials are active or recruting for a given condition or drug,
most trials are updated multiple times during their progression.

There are two primary ways to access data about clinical trials.
The first is to search individual trials on ClinicalTrials.gov with a web browser.
This web portal shows the current information about the trial and provides 
access to snapshots of previously submitted information.
Together, these features fulfill most of the needs of those seeking 
to join a clinical trial.
For this project I've been able to scrape these historical records to establish
snapshots of the records provided.
%include screenshots?
The second way to access the data is through a normalized database setup by
the 
\href{https://aact.ctti-clinicaltrials.org/}{Clinical Trials Transformation Initiative}
called AACT. %TODO: Get CITATION
The AACT database is available as a PostgreSQL database dump or set of 
flat-files. 
These dumps match a near-current version of the ClinicalTrials.gov database.
This format is ameniable to large scale analysis, but does not contain 
information about the past state of trials.
I combined these two sources, using the AACT dataset to select 
trials of interest and then scraping \url{ClinicalTrials.gov} to get 
a timeline of each trial.

%%%%%%%%%%%%%%%%%%%%%%%% Model Outline

The way I use this data is to predict the final status of the trial 
from the snapshots that were taken, in effect asking:
``how does the probability of a termination change from the current state 
of the trial if X changes?''
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