Added small updates

Latex/Paper/sections/01_introduction.tex

@@ -22,41 +22,53 @@ 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?
+%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.
+Similarly
 \cite{hwang_failure_2016} 
-described failues of Phase III trials in a similar way, 
+ascribe failues of Phase III trials to issues with safety, 
-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.
+pharmaceutical companies face short term operational challenges
+which can impede the development process. 
+Some operational reasons given for why a trial was stopped include: 
+\begin{itemize}
+    \item Organizational challenges (Principle Investigator left institution, 
+        changes in research focus, staff shortages)
+    \item Troubles with recruitment, (accural to slow/low, difficulty locating 
+        qualified participants, etc).
+    \item Changes in standards of care.
+    \item Sponsor withdraws support or provides insufficient financial support,
+        e.g Funding runs out.
+    \item Beginning or end of a pandemic.
+\end{itemize}
 % 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.
+Thus being able to isolate the effect of specific operational challenges from 
-\todo{Clean up that hypothetical, it doesn't seem clean}
+strategic decisions allows us to more accurately predict the intended or 
-Thus being able to isolate the effect of operational challenges from 
+unintended effects of a given policy on clinical trials.
-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 
+To do this, I create a dataset extracted from 
- dataset extracted from 
 \url{ClinicalTrials.gov} 
-that tracks individual clinical trials as they progress towards completion
+that tracks individual clinical trials as they progress towards completion. 
-as well as a novel causal model of individual clinical trial progression.
+I also introduce a novel causal model of individual clinical trial progression.
-Unlike previous research which is focused on the drug development pipeline, I 
+Unlike previous research which generally focuses on the drug development 
-restrict my investigation to modelling individual clinical trials.
+pipeline through multiple phases, I restrict my investigation to modelling 
-The goal of this restriction is to provide a way to predict the impact
+individual clinical trials.
-of changes that affect enrollment independent of other confounding effects. 
+This restriction provides a way to separate the impact of different operational
+changes, specifically enrollment troubles and changes in the market.
 
 \end{document}

Latex/Paper/sections/05_LitReview.tex

@@ -8,6 +8,7 @@
 
 Most studies of clinical trials attempt to model only those trials 
 which are involved in the drug approval process. 
+For example, 
 
 % Hwang, Carpenter, Lauffenburger, et al (2016)
 % - Why do investigational new drugs fail during late stage trials?
@@ -34,19 +35,16 @@ success than failure after 91 months.
 
 \cite{hay_ClinicalDevelopment_2014} tracks clinical trials based on 
 the number of indications studied. 
-They find that 10.4\% of all novel drug development paths for an indication, 
+They find that, for given indication, only 10.4\% of all novel drug development paths
-studied in a phase I trial, are ultimately approved by the FDA.
+studied in a phase I trial are ultimately approved by the FDA.
 
 \cite{wong_EstimationClinical_2019} 
-constructed a model where they estimated each, which they used to estimate the 
+estimate the probability of completing a given phase, conditional on starting a previous phase.
-probability of completing a given phase, conditional on starting a previous phase.
 In doing so, they found that 13.8\% of all drug development programs 
-completed successfully, which is higher than the approximately 10\% rate
+completed successfully. % slightly higherothers have found\cite{hay_ClinicalDevelopment_2014}.
-others have found\cite{hay_ClinicalDevelopment_2014}.
 One cause of this may be that they considered that a single drug might 
-be used tested for multiple indications.
+be tested for multiple indications.
-% Large dataset. 
+
-% they found lower estimates than previous work.
 
 % Ekaterina Khmelnitskaya (2021)
 % - separates scientific from market failure of the clinical drug pipeline
@@ -66,29 +64,32 @@ higher if those strategic terminatations were elimintated.
 %%%%%%%%% What do we know about drug development incentives?
 \subsection{What do we know about drug development incentives?}
 % Introduce section
-% key points
+% -  Dranov et al 2022 - demand pull seems to bias follow up drug development.
-% - multiple types of drugs (generic and brand named)
-% - These respond differently
-%   -  Dranov et al 2022 - demand pull seems to bias follow up drug development.
 %      - increasing demand doesn't necessarily result in new compounds (check this). Risks.
+\cite{dranove_DoesConsumer_2022} examined whether increased demand for drugs 
+will increase the development of novel drugs. 
+Using measures of the scientific novelty of drug compounds after the creation
+of Medicare part D, they found that most development occurred in the least
+novel categories of drugs, in spite of a relatively constant growth in novel 
+compounds. 
+
+
+
 %   -  acemoglu and linn 2004 - population size matters.
-% - Note then that separating effects is difficult at the drug development level.
 %   - Population ties into the number of drugs available, and operational (recruitment) concerns
 %   - In general, there are going to be many confounding variables.
 % - 
-% 
+% - Exogenous demographic trends has a large impact on the entry of non-generic drugs and new molecular entitites.
-
+On the side of market analysis, %TODO:remove when other sections are written up.
-% van der grong et al 2017 Addressing the challenge of high-price prescription drugs
+\citeauthor{acemoglu_market_2004} 
-% Massive number of policies used to try to reduce costs. These will affect production decisions. 
+(\citeyear{acemoglu_market_2004})
-% Some of the unintended consequences of that (in terms of reduced development incentives) include
+used exogenous deomographics changes to show that the
-% - reducing development costs - side effect of lower quality evidence
+entry of novel compounds is highly driven by the underlying aged population.
-% - Preference policy (e.g. policies about using generics first etc) - side effect of shorter life cycle for patented (novel) drugs.
+They estimate that a 1\% increase in applicable demographics increase the
-% - these are focused on reducing expenditures, i.e. they reduce profit. Some of them feed back into the development process.
+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.
 
-% Dranov, Garthwaite, and Hermosilla (2022)
-% - does the demand-pull theory of R&D explain novel compound development?
-% - no, when demand increased (creation of medicare part-D), investement in previously approved drugs grew the most.
 
 % Cerda 2007 - Endogenous innovations in the pharmaceutical industry
 % from abstract %TODO: Read better
@@ -98,45 +99,80 @@ higher if those strategic terminatations were elimintated.
 % - more drugs -> better survivability -> larger market 
 % Applicable because: Need to separate population and market effects.
 % Does this mess with my results? I don't think so because of the relatively short time in trials. Not enough time to effect population back, but it might have another effect.
+\cite{cerda_EndogenousInnovations_2007} 
+suggests a two-way, long term relationship between market size and drug 
+development.
+They suggest that a large population with a condition implies a (relatively) 
+larger market, which improves the profitabilty and thus number of drugs with that
+condition. 
+Then the drugs improve mortality, increasing the relative population.
+They do find evidence of the impact of both population and market size
+on the creation of new drugs. 
+
+
+% van der gronde et al 2017 Addressing the challenge of high-price prescription drugs
+% Massive number of policies used to try to reduce costs. These will affect production decisions. 
+% Some of the unintended consequences of that (in terms of reduced development incentives) include
+% - reducing development costs - side effect of lower quality evidence
+% - Preference policy (e.g. policies about using generics first etc) - side effect of shorter life cycle for patented (novel) drugs.
+% - these are focused on reducing expenditures, i.e. they reduce profit. Some of them feed back into the development process.
+
+\cite{vandergronde_AddressingChallenge_2017}
+documents many of the things driving drug development choices. 
+\begin{itemize}
+    \item Policies that encourage low cost generics shorten the life cycle of
+        patented/novel drugs.
+    \item Some diseases have lower safety and efficacy standards applied to them 
+        compared to similar diseases. These tend to have higher R\&D due to the 
+        lower costs involved.
+    \item As much of the "low hanging fruit" in drug development has been developed,
+        R\&D expenses have been increasing.
+\end{itemize}
 
 
 % Dubois et al 2015 - Market Size and pharmaceutical innovation
-% from abstract %TODO: Read better
 % estimate the relationship between marekt size and the innovation in pharmaceuticals
 % elasticity of innovation w.r.t. expected market size of 0.23, thus $2.5 billion in 
 % market size required to get a new chemical entity.
-
+\cite{dubois_MarketSize_2015}
-% Acemoglu and Linn
+examined the ``elasticity of innovation'', i.e. the ``additional revenue required
-% - Market size in innovation
+to support the invention of a new chemical entity.''
-% - Exogenous demographic trends has a large impact on the entry of non-generic drugs and new molecular entitites.
+They found that a marginal drug will require approximately a \$2.5 billon increase
-On the side of market analysis, %TODO:remove when other sections are written up.
+in expected revenue.
-\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} 
-\todo{Sumarize how intellectual property rights affect things}
+describes the impact that imperfect intellectual property rights have in the 
-% - link to difference between novel and generics from acemoglu and linn
+the market for pharmaceuticals. 
+She describes how overlapping and ambiguous patent rights increase the time 
+to entry of generic drugs by about 3 years.
 
-% Agarwal and Gaule 2022
-% - Retrospective on impact from COVID-19 pandemic
-% Not in this version
 
-\subsection{What do we know about how Clinical Trials proceed?}
+\subsection{What do we know about how Clinical Trials operations?}
 %interview with Adam George
 % - clinical trials are often handled by contractors
 % - they plan sites, start times, etc from beginning.
 % - Running late is normal.
+In a personal interview with someone who works for a company that runs clinical
+trials, I learned about how clinical trials will typically proceed. 
+\todo{Figure out best way to cite this}
+\begin{itemize}
+    \item Quote a job (one side of company): N, timeline, etc
+    \item Allocate resources (sites, doctors, etc) to try to accomplish
+    \item Sales vs Operations conflict, leading to lateness/issues delivering, etc.
+\end{itemize}
+
+% Bess Stillman - look at difficulties joining oncology trials
+
+% Random sample of Clinicaltrials.gov - how many closed due to operational problems?
+% TODO: random sample 171, about 30% mentioned recruitment issues
 
 % Results on enrollment projection
 % - nothing really good exists.
+% - Multiple models, no comparison.
 % - no cross validation, only tested on  a few trials.
 
+% Thus we should look at the effects that operational concerns have.
+
 \end{document}