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156 lines
6.9 KiB
TeX
156 lines
6.9 KiB
TeX
\documentclass[../Main.tex]{subfiles}
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\graphicspath{{\subfix{Assets/img/}}}
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\begin{document}
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% TODO:
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%Need to distinguish that this isn't about drug development specifically, but
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% more around clinical trials progress.
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% Thoughts:
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% - What types of failures do clinical trials have an why do clinical trials fail?
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% - What is cited in termination reasons?
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% - Discussion on different types of failures:
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% 1. Failure to find safe and effective drug
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% 2. Failure to collect enough information to determine 1
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% - recruiting
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% - New information (other studies, changes in standards of care, etc)
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% 3. Failure due to other operational/strategic concern.
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% - Issues with PI/Sponsors
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% - profitability expectations
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% - Financial support
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% - Discuss how most studies are about clinical trials as part of the drug development pipeline.
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% - Review what we know about causes for failure.
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% - Things that correlate with failures. (adams)
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% - Causes for failure (khmelnitskaya & hwang)
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% - Then talk about studies on clinical trials themselves.
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% - Interview with Adam George
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% - Poor studies of enrollment prediction.
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% -
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% - Then talk about what drives approvals/clinical trial activity for drugs
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% - Elasticity of innovation
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% - No demand pull for novel drugs, but yes for derivatives
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% - Population and Market size interact & drive development (jointly determined)
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% - This doesn't apply to single trials though
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% -
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% - Sumarize
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% - Thus when trying to study what affects clinical trials we must separate
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% - Market & competition effects
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% - Population effects
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% - Multiple trial failure modes (safety & efficacy, Operational etc)
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% -
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% -
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% Abrantes-Metz, Adams, Metz (2004)
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% - What correlates with successfully passing clinical trials and FDA review?
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% -
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In \citeyear{abrantes-metz_pharmaceutical_2004},
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\citeauthor{abrantes-metz_pharmaceutical_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 non-causal estimate was notable for using a
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mixed state proportional hazard model and estimating the impact of
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observed characteristics in each of the three phases.
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They found that as trials last longer, the rate of failure increases for
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Phase I \& II trials, while Phase 3 trials generally have a higher rate of
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success than failure after 91 months.
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%%%%%%%%%%%%%%%% What do we know about clinical trials?
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\subsection{Understanding Failure Modes}
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% Hwang, Carpenter, Lauffenburger, et al (2016)
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% - Why do investigational new drugs fail during late stage trials?
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\citeauthor{hwang_failure_2016} (\citeyear{hwang_failure_2016})
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investigated causes for which late stage (Phase III)
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clinical trials fail across the USA, Europe, Japan, Canada, and Australia.
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They found that for late stage trials that did not go on to recieve approval,
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57\% failed on efficacy grounds, 17\% failed on safety grounds, and 22\% failed
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on commercial or other grounds.
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% Ekaterina Khmelnitskaya (2021)
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% - separates scientific from market failure of the clinical drug pipeline
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In her doctoral dissertation, Ekaterina Khmelnitskaya studied the transition of
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drug candidates between clinical trial phases.
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Her key contribution was to find ways to disentangle strategic exits from the
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development pipeline and exits due to clinical failures.
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She found that overall 8.4\% of all pipeline exits are due to strategic
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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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(\cite{khmelnitskaya_competition_2021}).
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% causal separation of strategic exits etc.
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% Waring, Arrosmith, Leach, et al (2015)
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% - Atrition of drug candidates from four major pharma companies
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% - Looked at how phisicochemical properties affected clinical failure due to safety issues
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% Possibly Applicable in this version
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\subsection{What about incentives?}
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%%%%%%%%% What do we know about drug development incentives?
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% Dranov, Garthwaite, and Hermosilla (2022)
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% - does the demand-pull theory of R&D explain novel compound development?
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% - no, it is biased towards follow-on drug R&D.
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% TODO
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\cite{dranove_DoesConsumer_2022} use the implementation of Medicare part D
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to examine whether the production of novel or follow up drugs increases during
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the following 15 years.
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They find that when Medicare part D was implemented -- increasing senior
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citizens' ability to pay for drugs -- there was a (delayed) increase
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in drug development, with effects concentrated among compounds that were least
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innovative according to their classification of innovations.
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They suggest that this is due to financial risk management, as novel
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pharmaceuticals have a higher probability of failure compared to the less novel
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follow up development.
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This is what leads risk-adverse companies to prefer follow up development.
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% Acemoglu and Linn
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% - Market size in innovation
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% - Exogenous demographic trends has a large impact on the entry of non-generic drugs and new molecular entitites.
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On the side of market analysis,
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\citeauthor{acemoglu_market_2004}
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(\citeyear{acemoglu_market_2004})
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used exogenous deomographics changes to show that the
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entry of novel compounds is highly driven by the underlying aged population.
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They estimate that a 1\% increase in applicable demographics increase the
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entry of new drugs by 6\%, mostly concentrated among generics.
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Among non-generics, a 1\% increase in potential market size
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(as measured by demographic groups) leads to a 4\% increase in novel therapies.
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% Gupta
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% - Inperfect intellectual property rights in the pharmaceutical industry
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\cite{gupta_OneProduct_2020} discovered that uncertainty around which patents
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might apply to a novel drug causes a delay in the entry of generics after
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the primary patent has expired.
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She found that this delay in delivery is around 3 years.
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% Agarwal and Gaule 2022
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% - Retrospective on impact from COVID-19 pandemic
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% Not in this version
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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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develompent and find that for the 50 largest drug producers,
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approximately X\% of their drugs under developm
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successfully completed the process.
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They note a couple of changes in how drugs are developed over the years they
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study (clinical development started between 1993 and 2004).
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This included that drugs began to fail earlier in their development cycle in the
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latter half of the time they studied.
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This may be an operational change to reduce the cost of new drugs.
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\cite{dimasi_ValueImproving_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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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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\end{document}
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