Dissertation/Thesis Abstract

The author has requested that access to this graduate work be delayed until 2020-08-01. After this date, this graduate work will be available on an open access basis.
Identifying Areas of Competitive Advantage: Developing a Predictive Tool to Determine New Drug Approval Success
by Annan, Seth, D.Engr., The George Washington University, 2018, 105; 10846932
Abstract (Summary)

Healthcare costs are at an all-time high and there is no sign of ever relinquishing its upward trend or being controlled at the current level. The high cost of healthcare is partly attributed to the high cost of medicine. Research and development (R&D) costs have been identified as a contributor to the high cost of medicine. Prior to the enactment of the Hatch-Waxman Act in 1984, brand drugs, which are the first innovative drugs on the market, was dominating the market and was difficult for generic drugs to compete with. The Hatch-Waxman Act was passed to ensure a flat level playground for both brand drugs and generics drugs. Currently, generic drugs have outperformed brand drugs in areas including high approval, and low prices. Given that the generic drug business is more lucrative now than brand drugs, many of the drug manufacturing companies who concentrated on drug discovery of innovative drugs are now producing generic drugs. This has resulted in low drug discovery and low return on investment for brand drugs. In recent years, research and development costs have skyrocketed, and it takes many years (up to 15) for new drugs to reach the approval stage which, in turn, results in a high delay time for other unmet medical needs to be on the radar for research activities to begin.

This praxis aims to identify areas of competitive advantages for brand drugs and develop a predictive model to determine drug approval success during the clinical trial phase. First, areas of competitive advantages are identified through literature review and validated through drug utilization data. The prediction method was developed through statistical analysis tools including sample t-test, Wilcoxon test, and logistic regression analysis. Independent variables found to be statistically significant was used to develop a probability predictive tool for individual drugs to predict drug approval success. The model was validated using clinical trial data to demonstrate the application of results obtained. The proposed methods can provide information for the pharmaceutical industry to predict drug approval status early in the development process in order to make a risk based decision on a new drug candidate’s path forward.

Indexing (document details)
Advisor: Etemadi, Amir H., Malalla, Ebrahim
Commitee: Agbenyikey, Wilfred, Etemadi, Amir H., Malalla, Ebrahim
School: The George Washington University
Department: Engineering Management
School Location: United States -- District of Columbia
Source: DAI-B 79/12(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Health sciences
Keywords: Approval success, Areas of, Competive advantage, Develop, Identify, Predictive tool
Publication Number: 10846932
ISBN: 9780438270534
Copyright © 2019 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy
ProQuest