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@ -6,11 +6,11 @@
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In 1938 President Franklin D Rosevelt signed the Food, Drug, and Cosmetic Act,
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granting the Food and Drug Administration (FDA) authority to require
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pre-market approval of pharmaceuticals.
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\cite{commissioner_MilestonesUS_2023}.
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\cite{commissioner_milestonesusfood_2023}
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As of Sept 2022 \todo{Check Date} they have approved 6,602 currently-marketed
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compounds with Structured Product Labels (SPLs)
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and 10,983 previously-marketed SPLs
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\cite{commissioner_NSDE_2024}.
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\cite{commissioner_nsde_2024},
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%from nsde table. Get number of unique application_nubmers_or_citations with most recent end date as null.
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In 1999, they began requiring that drug developers register and
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publish clinical trials on \url{https://clinicaltrials.gov}.
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@ -42,7 +42,8 @@ Hyrimoz, Idacio, Simlandi, Yuflyma, and Yusimry),
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the biosimilars are required to prove they have similar efficacy and safety to the
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reference drug.
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When registering these clinical trials
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%TODO? Decide whether to include this or not
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%When registering these clinical trials
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% discuss how these are registered and what data is published.
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% Include image and discuss stages
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% Discuss challenges faced
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@ -51,24 +52,25 @@ When registering these clinical trials
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In the world of drug development, these trials are classified into different
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phases of development.
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\cite{FDADrugApprovalProcess_2022}
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\cite{anderson_fdadrugapproval_2022}
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provide an overview of this process
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\cite{commissioner_DrugDevelopment_2020}
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while describes the actual details.
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while
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\cite{commissioner_drugdevelopmentprocess_2020}
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describes the actual details.
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Pre-clinical studies primarily establish toxicity and potential dosing levels
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\cite{commissioner_DrugDevelopment_2020}.
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\cite{commissioner_drugdevelopmentprocess_2020}.
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Phase I trials are the first attempt to evaluate safety and efficacy in humans.
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Participants typically are heathy individuals, and they measure how the drug
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affects healthy bodies, potential side effects, and adjust dosing levels.
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Sample sizes are often less than 100 participants.
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\cite{commissioner_DrugDevelopment_2020}.
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\cite{commissioner_drugdevelopmentprocess_2020}.
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Phase II trials typically involve a few hundred participants and is where
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investigators will dial in dosing, research methods, and safety.
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\cite{commissioner_DrugDevelopment_2020}.
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\cite{commissioner_drugdevelopmentprocess_2020}.
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A Phase III trial is the final trial befor approval by the FDA, and is where
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the investigator must demonstrate safety and efficacy with a large number of
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participants, usually on the order of hundreds or thousands.
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\cite{commissioner_DrugDevelopment_2020}.
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\cite{commissioner_drugdevelopmentprocess_2020}.
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Occassionally, a trial will be a multiphase trial, covering aspects of either
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Phases I and II or Phases II and III.
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@ -77,7 +79,7 @@ After a successful Phase III trial, the sponsor will decide whether or not
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to submit an application for approval from the FDA.
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Before filing this application, the developer must have completed
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"two large, controlled clinical trials."
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\cite{commissioner_DrugDevelopment_2020}.
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\cite{commissioner_drugdevelopmentprocess_2020}.
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Phase IV trials are used after the drug has recieved marketing approval to
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validate safety and efficacy in the general populace.
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Throughout this whole process, the FDA is available to assist in decisionmaking
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@ -85,14 +87,14 @@ regarding topics such as study design, document review, and whether or not
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they should terminate the trial.
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The FDA also reserves the right to place a hold on the clinical trial for
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safety or other operational concerns, although this is rare.
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\cite{commissioner_DrugDevelopment_2020}.
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\cite{commissioner_drugdevelopmentprocess_2020}.
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In the economics literature, most of the focus has been on evaluating how
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drug candidates transition between different phases and their probability
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of final approval.
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% Lead into lit review
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% Abrantes-Metz, Adams, Metz (2004)
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\cite{abrantes-metz_pharmaceutical_2004},
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\authorcite{abrantes-metz_pharmaceuticaldevelopmentphases_2004}
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described the relationship between
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various drug characteristics and how the drug progressed through clinical trials.
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% This descriptive estimate was notable for using a
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@ -107,7 +109,8 @@ from the purpose of Phase III.
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Continuing on this theme,
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%DiMasi FeldmanSeckler Wilson 2009
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\cite{dimasi_TrendsRisks_2010} examine the completion rate of clinical drug
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\authorcite{dimasi_trendsrisksassociated_2010}
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examine the completion rate of clinical drug
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develompent and find that for the 50 largest drug producers,
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approximately 19\% of their drugs under development between 1993 and 2004
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successfully moved from Phase I to recieving an New Drug Application (NDA)
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@ -120,7 +123,7 @@ They note that this may reduce the cost of new drugs by eliminating late
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and costly failures in the development pipeline.
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Earlier work by
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\authorcite{dimasi_ValueImproving_2002}
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\authorcite{dimasi_valueimprovingproductivity_2002}
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used data on 68 investigational drugs from 10 firms to simulate how reducing
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time in development reduces the costs of developing drugs.
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He estimates that reducing Phase III of clinical trials by one year would
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@ -128,13 +131,13 @@ reduce total costs by about 8.9\% and that moving 5\% of clinical trial failures
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from phase III to Phase II would reduce out of pocket costs by 5.6\%.
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Like much of the work in this field, the focus of the the work by
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\citeauthor{dimasi_ValueImproving_2002}
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\authorcite{dimasi_valueimprovingproductivity_2002}
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and
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\citeauthor{dimasi_TrendsRisks_2010}
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\authorcite{dimasi_trendsrisksassociated_2010}
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tends to be on the drug development pipeline, i.e. the progression between
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phases and towards marketing approval.
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A key contribution to this drug development literature is the work by
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\authorcite{khmelnitskaya_CompetitionAttrition_2021}
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\authorcite{khmelnitskaya_competitionattritiondrug_2021}
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on a causal identification strategy
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to disentangle strategic exits from exits due to clinical failures
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in the drug development pipeline.
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@ -143,7 +146,7 @@ terminations and that the rate of new drug production would be about 23\%
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higher if those strategic terminatations were elimintated.
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The work that is closest to mine is the work by
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\authorcite{hwang_FailureInvestigational_2016}
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\authorcite{hwang_failureinvestigationaldrugs_2016}
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who investigated causes for which late stage (Phase III)
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clinical trials fail -- with a focus on trials in the USA,
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Europe, Japan, Canada, and Australia.
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@ -157,14 +160,14 @@ on commercial or other grounds.
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Unlike the majority of the literature, I focus on the progress of
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individual clinical trials, not on the drug development pipeline.
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In both
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\authorcite{khmelnitskaya_CompetitionAttrition_2021}
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\authorcite{khmelnitskaya_competitionattritiondrug_2021}
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and
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\authorcite{hwang_FailureInvestigational_2016}
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\authorcite{hwang_failureinvestigationaldrugs_2016}
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the authors describe failures due to safety, efficacy, or strategic concerns.
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There is another category of concerns that arise for individual clinical trials,
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that of operational failures.
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Operational failures can arise when a trial struggles to recruit participants,
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the principle investigator or other key member leaves for another opportunity,
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the principal investigator or other key member leaves for another opportunity,
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or other studies prove that the trial requires a protocol change.
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% In a personal review of 199 randomly selected clinical trials from the AACT
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@ -189,23 +192,27 @@ or other studies prove that the trial requires a protocol change.
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This paper proposes the first model to separate the causal effects of
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market conditions (a strategic concern) from the effects of
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participant enrollment (an operational concern) on Phase III Clinical trials.
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This will allow me to answer the questions:
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\begin{itemize}
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\item What is the marginal effect on trial completion of an additional
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generic drug on the market?
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\item What is the marginal effect on trial completion of a delay in
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closing enrollment?
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\end{itemize}
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To undderstand how I do this, we'll cover some background information on
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clinical trials in section \ref{SEC:ClinicalTrials},
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explain the data in section \ref{SEC:DataSources},
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and then examine causal identification and econometric model in sections
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\ref{SEC:CausalIdentificationAndModel}.
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Finally I'll review the results and conclusion in sections
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\ref{SEC:Results}
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and
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\ref{SEC:Conclusion}
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respectively.
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This allows me to answer the question
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\textit{
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``How does the probability of trial termination change
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when the enrollment period is extended?''
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}
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using administrative data.
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To understand how I do this, we'll cover some background information on
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clinical trials and the administrative data I collected in section
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\ref{SEC:ClinicalTrials},
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explain the approach to causal identification strategy and the required data in section
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\ref{SEC:Data},
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and describe how the data used matches these requirements in section
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\ref{SEC:}.
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Then we'll cover the econometric model
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(section \ref{SEC:EconometricModel})
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and results (section
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\ref{SEC:Results}).
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Finally, we acknowledge deficiencies in the analysis and potential improvements
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in section
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\ref{SEC:Improvements},
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then summarize everything in the conclusion \ref{SEC:Conclusion}
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% \subsection{Market incentives and drug development}
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% %%%%%%%%% What do we know about drug development incentives?
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Will King
1 year ago