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@book{pearl_causality_2000,
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location = {Cambridge, U.K. ; New York},
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title = {Causality: models, reasoning, and inference},
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isbn = {978-0-521-89560-6 978-0-521-77362-1},
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shorttitle = {Causality},
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pagetotal = {384},
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publisher = {Cambridge University Press},
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author = {Pearl, Judea},
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date = {2000},
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langid = {english},
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keywords = {Causation, Probabilities},
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file = {Pearl - 2000 - Causality models, reasoning, and inference.pdf:/home/dad/Nextcloud/Zotero_data/storage/8GZJS832/Pearl - 2000 - Causality models, reasoning, and inference.pdf:application/pdf},
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}
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@thesis{khmelnitskaya_competition_2021,
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title = {Competition and Attrition in Drug Development},
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abstract = {With fewer than 10\% of new drugs reaching the market, the drug development process is notorious for its high attrition rate. However, we rarely observe the reason for a drug’s discontinuation. It is known that pharmaceutical firms withdraw drugs after clinical failures, such as when trial results do not demonstrate adequate safety or efficacy according to {FDA} standards. At the same time, surveys suggest that firms also withdraw drugs for strategic reasons, such as when competition makes it unprofitable to continue development. Disentangling these two sources of attrition is necessary in order to predict the effects a government policy would have on the number of drugs that reach consumers. In this paper, I propose an empirical framework to separately identify the two components of attrition for each disease. To this end, I build a continuous-time dynamic model of the drug development process. In the model, firms take competitors’ R\&D choices into account when they make exit decisions at different stages of the innovation process. To estimate the model, I use rich data on the development histories of experimental drugs, clinical trial outcomes, and disease-specific epidemiological characteristics. I find that, on average, strategic terminations account for 8.4\% of all attrition, and as much as 35\% for some diseases. Using these estimates in counterfactual simulations, I show that without strategic withdrawals, the rate at which new drugs reach consumers would be on average 23\% higher. Large subsidies for clinical trials help realize some of that gain, with better results found for diseases that have a higher share of strategic attrition. However, the overall effect of subsidies on the rate of new drug launches is small. Alternatively, the same effect can be achieved through any minor regulatory adjustment that marginally helps lower the probability of late-stage clinical failures.},
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pagetotal = {55},
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institution = {University of Virginia},
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type = {phdthesis},
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author = {Khmelnitskaya, Ekaterina},
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urldate = {2023-04-10},
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date = {2021-05},
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langid = {english},
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file = {1_Khmelnitskaya_Ekaterina_2021_PHD.pdf:/home/dad/Nextcloud/Zotero_data/storage/CSRFCIDB/1_Khmelnitskaya_Ekaterina_2021_PHD.pdf:application/pdf;Khmelnitskaya - Competition and Attrition in Drug Development.pdf:/home/dad/Nextcloud/Zotero_data/storage/QBXQ4ZLR/Khmelnitskaya - Competition and Attrition in Drug Development.pdf:application/pdf},
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}
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@article{ursu_drugcentral_2017,
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title = {{DrugCentral}: online drug compendium},
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volume = {45},
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issn = {0305-1048, 1362-4962},
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url = {https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw993},
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doi = {10.1093/nar/gkw993},
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shorttitle = {{DrugCentral}},
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pages = {D932--D939},
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issue = {D1},
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journaltitle = {Nucleic Acids Research},
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shortjournal = {Nucleic Acids Res},
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author = {Ursu, Oleg and Holmes, Jayme and Knockel, Jeffrey and Bologa, Cristian G. and Yang, Jeremy J. and Mathias, Stephen L. and Nelson, Stuart J. and Oprea, Tudor I.},
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urldate = {2023-04-10},
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date = {2017-01-04},
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langid = {english},
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file = {Full Text:/home/dad/Nextcloud/Zotero_data/storage/7W6THRK6/Ursu et al. - 2017 - DrugCentral online drug compendium.pdf:application/pdf},
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}
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