This article originally appeared on the BeyeNETWORK.
This article is the first in a series intended to share insight and provide guidance for the pharmaceutical industry, through a proven set of best practices and case studies within the strategic consulting, business intelligence, data warehousing and data management disciplines. The series will focus on drug discovery and development and how to increase operational efficiencies, reduce costs, accelerate decision-making processes and, most important, improve top- and bottom-line results.
Fierce competition, evaporating profit margins, patent expirations, generic drugs, intense scrutiny by regulatory agencies and merger and acquisition activity have placed the pharmaceutical industry in its most challenging position in well over a decade. The next three to five years will be an extremely critical time period requiring vision, thought-leadership and innovativeness, as the pressure for bringing new drugs, safer drugs and the right drugs to the market—in a cost-efficient, effective and timely manner—has never been greater.
Drug Discovery and Development
Drug discovery and development is the lifeline of the pharmaceutical industry. It is the process, by which a drug is discovered to treat a disease, is guided through development in the form of studies, registered with regulatory authorities for approval and finally launched in the marketplace.
Straightforward and simple, right? On the contrary, drug discovery and development is one of the most sophisticated, cross-functional processes in an operational environment, taking nearly seven to 10 years to complete and costing upwards of $750 million. These staggering costs have escalated almost tenfold every 20 years since the late 1950s when research and development costs were approximately $1.5 million and into the 1980s where costs rose to approximately $70 million. An important point is that these statistics are for the drugs that made it to the market! The fact is that thousands of drugs are screened, tested and fail to meet the defined criteria before “the right drug” is selected.
But seven to 10 years for one drug? Can this be real? Believe it or not, it is! Not only are numerous studies conducted on an individual drug within this timeframe to ensure safety and effectiveness, but some of these studies can last even longer. For example, lifetime carcinogenicity studies—which are designed to determine if a drug shows any sign of tumor development—can take as long as three years to complete. Two of those years cover dosing, while the other is for in-depth analysis and report writing.
Could the pharmaceutical industry be dragging their feet in getting a drug to the market?Not a chance! Statistics have shown that for every day the launch of a “marketable” drug is delayed, a million dollars is lost in revenue opportunity. Furthermore, in the late 1990s, the pharmaceutical industry took proactive steps to accelerate the Investigational New Drug Application process by having the Food and Drug Administration (FDA) accept the application electronically rather than in paper format. Before then, it was not unusual for an Investigational New Drug Application to be significantly greater than 100,000 pages in length and for the mandatory copies to weigh half a ton or more!
Business Intelligence Discipline
The disciplines of strategic consulting, business intelligence, data warehousing, data management and information quality, when practically applied, can advance the strategies and objectives of any business. And, in the case of the pharmaceutical industry, these disciplines can serve as the conduit for reengineering the drug discovery and development process.
Within the context of this opening article, we will begin to demonstrate the value of these disciplines with business intelligence. Business Intelligence is more than just the installation of leading-edge software; it’s about empowering companies with insight on what drives their business, as well as how to change it. An area of practical application gaining momentum in the corporate boardroom is clinical dashboards and their ability to assess the performance of investigators for their role in evaluating investigational new drugs within subjects and patients. Selecting the correct investigator criteria may seem to be a simple step in the overall process; but a mistake can set the course for ultimate disaster in terms of time and cost before a study is even completed! As a result, rich, robust screening processes—with supporting analytical views that provide insight on investigator qualifications, the qualifications of the investigator’s staff, patient/subject population, physical facilities, time commitments to studies and actual budgets vs. forecasted budgets—are now being used to determine whether an investigator and their facility can meet the objectives and criteria of the pharmaceutical company, good clinical practices (GCP) and regulatory agencies. Furthermore, experience has shown, it is more important to select an investigator with a proven track record in performing clinical drug research, rather than just selecting an expert in the targeted disease area. As a result, investigator performance is now being assessed and measured through dashboards using key performance indicators that provide selection guidance based on past subject/patient recruitment, screening, enrollment, withdrawal and completion; protocol adherence rate; data collection completeness and consistency; inquiry response; and study start-up.
Our next article will identify further opportunities to practically apply the business intelligencediscipline, and will introduce the inherent value and importance of data warehousing. In most pharmaceutical companies today, research, pre-clinical, clinical development, safety, operational and scientific data is stored in numerous source systems, in different physical formats and in various DBMS/storage technologies. The nature of the cross-functional drug discovery and development process requires access to this data, but in a consistent, consolidated and platform-independent format. The need for data warehousing is absolutely compelling!
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