From 0b34657c7df67d4b1055ee77dc037fb1f505e39e Mon Sep 17 00:00:00 2001 From: will king Date: Mon, 7 Oct 2024 11:27:57 -0700 Subject: [PATCH] Added small updates --- Latex/Paper/sections/01_introduction.tex | 46 +++++--- Latex/Paper/sections/05_LitReview.tex | 128 +++++++++++++++-------- 2 files changed, 111 insertions(+), 63 deletions(-) diff --git a/Latex/Paper/sections/01_introduction.tex b/Latex/Paper/sections/01_introduction.tex index 4b8fda1..f96f6ae 100644 --- a/Latex/Paper/sections/01_introduction.tex +++ b/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, -ascribing drug development failures to issues with safety, +ascribe failues of Phase III trials 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. -\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. +Thus being able to isolate the effect of specific operational challenges from +strategic decisions allows us to more accurately 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 +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. +that tracks individual clinical trials as they progress towards completion. +I also introduce a novel causal model of individual clinical trial progression. +Unlike previous research which generally focuses on the drug development +pipeline through multiple phases, I restrict my investigation to modelling +individual clinical trials. +This restriction provides a way to separate the impact of different operational +changes, specifically enrollment troubles and changes in the market. \end{document} diff --git a/Latex/Paper/sections/05_LitReview.tex b/Latex/Paper/sections/05_LitReview.tex index 81d27fd..d381a26 100644 --- a/Latex/Paper/sections/05_LitReview.tex +++ b/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, -studied in a phase I trial, are ultimately approved by the FDA. +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. \cite{wong_EstimationClinical_2019} -constructed a model where they estimated each, which they used to estimate the -probability of completing a given phase, conditional on starting a previous phase. +estimate the 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 -others have found\cite{hay_ClinicalDevelopment_2014}. +completed successfully. % slightly higherothers 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. -% Large dataset. -% they found lower estimates than previous work. +be tested for multiple indications. + % 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 -% - multiple types of drugs (generic and brand named) -% - These respond differently -% - Dranov et al 2022 - demand pull seems to bias follow up drug development. +% - 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. % - -% - -% van der grong 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. -% - +% - 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. +\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. -% 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. - -% 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, %TODO:remove when other sections are written up. -\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. +\cite{dubois_MarketSize_2015} +examined the ``elasticity of innovation'', i.e. the ``additional revenue required +to support the invention of a new chemical entity.'' +They found that a marginal drug will require approximately a \$2.5 billon increase +in expected revenue. % Gupta % - Inperfect intellectual property rights in the pharmaceutical industry \cite{gupta_OneProduct_2020} -\todo{Sumarize how intellectual property rights affect things} -% - link to difference between novel and generics from acemoglu and linn +describes the impact that imperfect intellectual property rights have in the +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}