Getting on the Fast Track: How Electronic Data Management Can Facilitate Drug Discovery, Expedite Time-to-Market and Increase Capacity
By Nicole Gray
One of the prevailing truths recognized by those in the pharmaceutical industry is that anything of value can be distilled down to its quantitative essence--from the cost of developing and commercializing drugs to the length and quality of human life. In many ways, drug discovery and development represent the convergence of the physical and the meta-physical, particularly in the post-genomic discovery climate. Yet, despite the lofty ideals that underscore drug development, time, money and resources are the most important variables that determine success. Several interrelated factors have put pressure on these variables: the immutability of time, the advent of genomic and protein-based development, decreased capacity and increased organizational complexity.
Figures released by the Pharmaceutical Research and Manufacturers of America (PhRMA) highlight the success of the pharmaceutical industry in 2001. With 32 new treatments in key therapeutic categories, pharmaceutical companies are fulfilling an important component of their mission: producing new life-enhancing treatments that contribute to reduced healthcare costs. To that end, pharmaceutical companies are now re-investing 20.1% of sales revenue in research and development, up from 11.9% in 1980. In 2001, PhRMA member companies invested $30.3 billion. According to the Tufts Center for the Study of Drug Development, the average cost of developing a new drug in 2001 was $802 million.
The concept of the "blockbuster" drug is part of a dying paradigm. Blockbuster drugs, which are traditionally defined as the 10% of drugs that yield revenues in excess of $500 million a year, are the cornerstone of profitability as they offset high drug-development costs, including the costs of the other 90% of drugs which usually yield less than $180 million a year in revenues. As long as this economic model was feasible, the slow adaptation of informatics into the pharmaceutical enterprise was acceptable. Now, however, the exponential increase in discovery targets has resulted in increasing reliance on informatics. From 1950 to 2000, researchers focused on roughly 500 potential targets. There are now literally hundreds of thousands of potential targets. This fact alone is largely responsible for decreasing capacity and inefficiency at the discovery phase.
Clearly, increasing competition and pressure to maintain margins require expedited discovery. Yet, several major factors influence the constraints on R&D: limited capacity, increasing complexity and the fragmentation that accompanies increased globalization and outsourcing. In the 1990's, globalization and increased reliance on CROs were effective strategies, however, given the complexity of managing communication, financial overhead and organizational complexities, pharmaceutical companies are looking for ways to increase control, compress the R&D timeline, reduce development costs and, ultimately, realize more profit in a shorter timeframe.
Using the Internet as the portal to accomplishing these multiple, yet interrelated, goals, pharmaceutical companies can realistically anticipate enhanced research initiatives and more innovative solutions within established timeframes. The implementation of informatics-based solutions, including using various types of application service providers (ASPs), enterprise resource planning systems (ERPs), clinical trials management systems (CTMs), process management systems (PMSs), and document management systems (DMSs) is the foundation for harnessing the full power of Internet-based services tailored specifically to the unique needs of the pharmaceutical industry.
In other industries, notably the automotive industry and telecommunications, information technology is an established component of competitiveness, yet research and development investment is lower when compared with the pharmaceutical industry (4.1% and 5.1% vs. 20.1%). The Pharmaceutical Research and Manufacturers of America estimates that 22% of R&D, or roughly $1.3 billion, is allotted to computer hardware and software, data centers, networks and staff. The key to leveraging these technologies is implementing a knowledge-based system. This assumes an understanding of organizational complexity, including how people, processes and technology function across the enterprise. Ultimately, compressing development time and decreasing time-to-market is a function of enterprise-wide data management. Fortunately, there are numerous solutions available to companies seeking a customized rational approach to harnessing the power of informatics.
The combined impact of genomics and new technology has radically altered the drug discovery paradigm. Scientifically, the shift from a largely biochemical approach to a development system dependent on protein-based molecular biology and informatics has been accepted industrywide. Nonetheless, the prevailing profit model is anachronistic and incompatible with success in the post-genomic era. Moreover, despite the confluence of various bio-, chemo- and clinical informatics, combinatorial chemistry, high-throughput screening (HTS) and pharmacogenomics, research productivity is down.
Informatics
A full 60% of the 15-year development-to-commercialiization timeline is devoted to the preclinical phase. The ratios are daunting, because many potential drug candidates fail as a result of poor absorption, distribution, metabolism, excretion and toxicity (ADME/T) results. Only one of every 5,000 to 15,000 compounds tested in the laboratory ever becomes an approved agent. Clinical trials are becoming increasingly complex, with more patients, more multicenter studies and varied protocols. Consequently, regulatory oversight and the focus on ethics and safety are only increasing the trend towards greater complexity. Ideally, an integrated informatics system can facilitate error detection at earlier stages of discovery. Specifically, researchers can access chemical libraries, expedite testing with automated systems that allow parallel testing and store data sets in a shared enterprise-wide database.
There is no singular informatics-based solution. Each enterprise requires a customized solution compatible with its particular organizational structure. By developing and integrating informatics systems in core competencies including drug substance characterization, product formulation, process development, regulatory management, manufacturing, packaging and logistical services, the pharmaceutical companies can increase profits and productivity. To a certain extent, much of this innovation has already taken place. Unfortunately, the demands of the post-genomic discovery environment have outpaced the effectiveness of solutions. Still, profit margins are threatened, the discovery phase of development is protracted and errors are legion.
Capacity
High-throughput systems and laboratory automation are designed to increase discovery capacity. Computational modeling and the advent of "in silico" bio-informatics will continue to make target prioritization easier. The intellectual capital is already there, as is the willingness to use new technologies; however, capacity is compromised, because researchers are bound by strict quality assurance (QA) guidelines and still rely on paper-based conventions in their efforts to be compliant and avoid FDA audits. The coexistence of automated workstations and hard-copy notebooks and control sheets is not a relic of the past---not yet at least. Though electronic submission and manufacturing practices have become increasingly sophisticated, the discovery phase of pharmaceutical development is still mired in paper-based conventions.
Chief amongst the concerns of pharmaceutical executives faced with the challenge of expanding time-to-market capacity is maintaining control while continuing to outsource and comply with regulatory changes. Additional pressure to maintain margins has driven decision-makers towards informatics-based solutions. Moving from the blockbuster paradigm to a knowledge-based system necessitates a thorough understanding of how to cope with complexity. The key issues involved are:1) recognizing and defining organizational complexity; 2) aligning people, processes and technology in accordance with organizational structure and 3) deploying technology.
Complexity
Organizational complexity has evolved in tandem with the more profound understanding of bio-complexity and that accompanied the genomic revolution. Just as bio-complexity is continuing to evolve as an organic force in the discovery process, organizational structures are dynamic and intrinsically linked with information technology. In the early 1990's, the concept that "knowledge is power" became an important catchphrase in corporate culture. In reality, that phrase was referring to information, as in "access to information is power." While that is an obvious point, information per se is not valuable, but structured information is highly valuable. In the pharmaceutical arena, the ability to structure information enterprisewide results in tremendous competitive advantage.
What is the most reliable way to give data order and structure? There is no fixed answer, because information and the technologies designed to leverage it are not static. Information classification systems are in a constant state of flux. New methods of characterizing information and supporting resource discovery can transform unstructured data into highly structured information made available to researchers, managers and regulators through standardized interfaces. The trend in informatics-based solutions is based on meta-data applications and intelligent engines. With the proper organizational context, capturing, organizing, visualizing and exploiting data becomes easier and more effective. The two most popular approaches to developing an informatics solution are utilization of ASPs and FSPs.
- Application Service Providers (ASPs) install, configure and maintain hardware and software infrastructure. Key features of this service include development of a central secure data center and a fully integrated and secure wide area network (WAN). A variety of applications ranging from analysis tools to high-end data management packages can be delivered via portals over a shared architecture or through a hosting service.
- Full Service Providers deliver several applications in a hosted environment including consulting and on-site service. Research has shown that a good FSP can set up, integrate and deploy systems within 12 weeks. In fact, by using an FSP versus one or several ASPs, companies can save up to 50% on the full cost of ownership (FCO) within the first year and 35% over a three-year period.
A good FSP should have a profound understanding of bio-informatics and information technology as well as a great deal of experience in the pharmaceutical industry. The ability to exploit current data management capabilities lies in understanding how organizations function and how complexity should be managed. Size should not be a barrier to achieving high-capacity development or flexibility. Instead, informatics is slowly changing the concept of scalability in the industry. Instead of relying on size and the ability to create scale, companies are increasingly focused on scope in their research efforts. In November 2001, Cockburn and Henderson reported in the Journal of Health Economics that successful drug discovery and development is more closely correlated with scope than scale. After conducting an analysis of development outcomes at ten pharmaceutical companies, they concluded that though larger companies are more successful, that success is largely attributable to undertaking a broad scope of research initiatives. In reality, scope is feasible only when research efforts and resources are highly coordinated.
Informatics as a tool is indispensable. Application of informatics-based solutions should be systematic and purposeful. The paperless pharmaceutical enterprise is still somewhere in the future, but much closer than we ever could have imagined. The complexities involved in a wholesale paradigm shift can be intimidating, but such a shift can realistically shorten the discovery and development stage by orders of magnitude.