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@ -3,20 +3,32 @@
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\begin{document}
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In 19xx the United States Food and Drug Administration (FDA) was created to "QUOTE".
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As of Sept 2022 \todo{Check Date} they have approved 6,602 currently-marketed compounds with Structured Product Labels (SPL)
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and 10,983 previously-marketed SPLs.
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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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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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%from nsde table. Get number of unique application_nubmers_or_citations with most recent end date as null.
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In 2007, they began requiring that drug developers register and publish clinical trials on \url{https://clinicaltrials.gov}.
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This provides a public mechanism where clinical trial sponsors are responsible to explain
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what they are trying to acheive and how it will be measured, as well as provide the public the ability to
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search and find trials that they might enroll in.
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Data such as this has become part of multiple datasets
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(e.g. the Cortellis Investigational Drugs dataset or the AACT dataset from the Clinical Trials Transformation Intiative)
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used to evaluate what drugs might be entering the market soon.
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This brings up a question: can we use this public data on clinical trials to describe what effects their success or failure?
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In this work, I use updates to records on \url{https://ClinicalTrials.gov} to disentangle
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the effect of participant enrollment and drugs on the market affect the success or failure of clinical trials.
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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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This provides a public mechanism where clinical trial sponsors are
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responsible to explain what they are trying to acheive and how it will be
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measured, as well as provide the public the ability to search and find trials
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that they might enroll in.
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Multiple derived datasets such as the Cortellis Investigational Drugs dataset
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or the AACT dataset from the Clinical Trials Transformation Intiative
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integrate these data.
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This brings up a question:
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Can we use this public data on clinical trials to identify what effects the
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success or failure of trials?
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In this work, I use updates to records on
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\url{https://ClinicalTrials.gov}
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to do exactly that, disentangle the effect of participant enrollment
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and competing drugs on the market affect the success or failure of
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clinical trials.
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%Describe how clinical trials fit into the drug development landscape and how they proceed
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Clinical trials are a required part of drug development.
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