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In this thesis we investigate whether the inclusion of an exogenous variable in the form of patentapproval can improve the ARIMA model's predictions for the pharmaceutical companyAstrazeneca. A point of departure for the study is the questioning of the efficient markethypothesis. When comparing data on patent date approval with stock exchange data for threepharmaceutical companies, it could be observed that share prices increased on the date ofapproval in 65 percent of the cases. This observed correlation combined with the fact that severalpapers have established that the stock market may not be efficient make it interesting to studywhether the value of a patent has been included in the stock price prior to approval date.To investigate this, an ARIMA and an ARIMAX model was estimated. The exogenous variable,which controls for patent approvals, was created by retrieving data from the EPO's databasePATSTAT. The retrieved data was then formatted into a dummy variable. The purpose ofincluding an exogenous variable is to investigate whether the market reacts to patent information.If the addition of the exogenous variable proves significant, the result is in conflict with theefficient market hypothesis.During the model selection, it was found that an ARIMA (4,1,2) was the superior model. Themodel was then compared with the corresponding ARIMAX model. When comparing themodels, it was found that the predictions of the ARIMAX model follow the observed datasomewhat better, but a t-test concluded that the improvement was not statistically significant.This implies that the value of the patent has already been included in stock prices prior to patentapproval and indicates that the price increase is random. This results thus lends support for theefficient market hypothesis. To investigate this further, the stock market data was compared witha random walk and by conducting a t-test it could be concluded that it was not possible to rejectthe hypothesis that share prices follow a random walk, thus the result further supports theefficient market hypothesis.

Globalization in clinical research and development has increased since the 1990s. Products approved in the United States (U.S.) and European Union (EU) include increasing numbers of research participants from low- and middle-income countries. The purposes of this quantitative correlational study were to investigate the lag time, or drug lag, between U.S. approval and the approval of selected drugs in all countries that hosted their pivotal clinical trials. The study population was limited to products approved first in the U.S. between 2006 and 2015. The health capability model and research for health justice framework were the theoretical frameworks for the study. Data were collected from public reports and websites of the U.S. Food and Drug Administration (FDA), European Medicines Agency, National Institutes of Health, local ministries of health, National Association of Securities Dealers Automated Quotations, New York Stock Exchange, the World Bank, and a subscription-based report from Springer Publications. Data were analyzed descriptively, with inferential statistics performed via Wilcoxon and chi-square tests. Independent variables were FDA approval year, drug indication, FDA review type, orphan indication, host country World Bank income category, sponsor market capitalization, and sponsor headquarters country. The dependent variable was drug lag, in months. The U.S. to EU drug lag was significantly shorter than U.S. to last host country drug lag. Lower host country income was also associated with longer drug lag. Reducing drug lag may create justice for research participants, improve health outcomes, and yield positive social changes.

Breast cancer is the most common cancer in women worldwide and the solid tumor type for which the highest number of drugs have been approved to date. This study examines new drug approvals for breast cancer by the United States Food and Drug Administration (FDA) and the European Medicines Agency (EMA), based on an analysis of regulatory documents from both agencies for the period from 1995 to 2018. Of the 29 breast cancer drugs approved over this time span, 17 received positive decisions from both the FDA and EMA, including all drugs licensed after 2008. Nineteen of the 25 FDA-approved drugs, but none of the EMA approvals, benefited from special regulatory pathways (such as fast track, breakthrough therapy, or priority review). In the U.S.A., four accelerated approvals were granted (of which one, for bevacizumab, was later revoked), while only two drugs received provisional approvals following EMA review. New breast cancer drugs were approved approximately twelve months earlier in the United States than in Europe. These results suggest that a broader use of special regulatory pathways by EMA could help to accelerate access to novel drugs for European breast cancer patients.

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