Adoption may be lagging at the enterprise level, but there's a stalwart group of biopharmas making EDC happen. Here's how they're doing it
By Paul Bleicher
March 17, 2004
| Based on informal surveys, speeches at conferences, and word of mouth, many in the drug industry have concluded that electronic data capture (EDC) adoption has fallen short of great expectations. Bankruptcies and the financial troubles of smaller EDC companies have added to the uncertainty. Was EDC overhyped?
The commitment of companies such as Schering-Plough, Novartis, Bayer, Pfizer, and Procter & Gamble to a complete EDC-based clinical data process is evidence that the benefits of EDC are real. So why haven't more
pharmas and biotechs jumped on the bandwagon?
Part of the answer is found in a sharp division of attitudes. In one camp are the biopharmas that have embraced EDC wholeheartedly. In the other camp are companies resistant to trying EDC, that are stalled in pilot mode, or that tried EDC and abandoned it. What accounts for this split?
I've had the opportunity (and motivation) to study and learn from the dozen or so major companies that have made or are making the transition to a fully EDC-based clinical trial process. Each firm has taken a somewhat different path, but they share several common strategies:
· Committing the company
· Investing in resources
· Developing best practices
· Moving beyond pilots
Committing the company. All companies implementing large-scale EDC have an organizational commitment to the project. While some companies commit via a senior-management edict, others take a grassroots approach, often championed by a single, determined individual. The shared element is that this commitment is not just for a pilot program.
|Measuring EDC's Real Value
|Vendors, desperate to reach critical market share, overpromised on the possibilities of EDC.
Long-term commitment is key because EDC is a disruptive technology. It requires incremental effort to implement, and can threaten the position and responsibilities of some employees. Invariably, some staff members will support the effort half-heartedly and rejoice in signs of failure. Clear signals from senior management that the effort must succeed provide additional motivation to figure out how to ensure success.
Companies with successful EDC implementations have recognized the value of the technology; have developed detailed, realistic, and long-range plans for implementation; and don't expect immediate return on investment (ROI) based on short-term metrics and costs in the first one or two trials. Commitment is necessary, but not sufficient.
Investing in resources. After commitment, successful companies know that EDC requires an upfront investment in resources and time — sometimes more than first anticipated. Asking a team to introduce new technology while handling its normal responsibilities is often problematic. People are the most important resource of any organization, and they are also the most valuable resource for EDC implementations.
Biopharmas implementing EDC must be willing to provide the right expertise and attitude from across all disciplines — not only IT but also data management, clinical operations, statistics, regulatory, and elsewhere.
In addition, the project requires initial expenditures in technology at sites to provide adequate hardware, and for appropriate Internet service providers or corporate bandwidth and architecture. New technologies often require process changes, and committed companies must invest in mapping and changing process flows.
Developing best practices. Indeed, the major benefits of EDC are achieved through the development of, and adherence to, best practices. To date, the industry has collectively developed much experience with EDC. Some key implementers of the technology have developed best practices based on this experience. These firms have chosen a variety of approaches, from Six Sigma to classic business-process re-engineering, but all have involved detailed process mapping, baseline benchmarks, clear and relevant metrics, and a commitment to root-cause analysis and diagnosis. The process is necessarily iterative.
These best practices can be applied in all areas of EDC implementation — from the software development life cycle and validation, to the process of trial design and rollout, to the use models for the end-user.
Successful enterprise implementations of EDC often start with a detailed process map derived through systems analysis, and a tabula rasa approach to the EDC process. Forcing EDC to work atop a paper process generally leads to frustration and failure. By understanding the capabilities of the EDC software being employed, creative project teams are able to rewrite the data-collection process to better utilize the benefits of EDC, chief among them being data immediacy.
Moving beyond pilots. Pilot projects for various forms of remote data entry have been around for roughly 20 years. In most of these projects, remote data-capture technology was piloted to determine whether it would scale up. Unfortunately, many projects failed to lead to full-scale implementation.
Some of these transition failures were related to technological immaturity and vendor instability. Early issues with EDC involved vendor inexperience, lack of global support and global connectivity, and misjudgment of required resources. Also, many biopharmas conducted pilots with no intention of widespread or lasting adoption; they simply wanted to keep up with the technology by trying it out every few years.
However, EDC technology often doesn't progress beyond the pilot stage for business reasons — either failure to prove ROI or failure to convince other teams within the company of the benefits. Unfortunately, many biopharmas still don't understand the true costs of clinical research.
EDC teams have often set out to prove ROI, but found that the metrics they chose were flawed, or that unexpected support costs outweighed ROI benefits. Sometimes, a very tightly controlled pilot would show unbelievable cost and timing, so much so that the entire exercise was dismissed as being "artificial" and not applicable to real-world clinical trials.
The best practices of companies deploying enterprisewide EDC require a significant amount of confidence and patience. Through past pilots, industry discussions, and common sense, these companies can see the potential benefits of higher-quality data, more visibility, and cost/time savings with EDC. But they also recognize that these savings can develop only with experience and reasonably broad process re-engineering. These companies have set metrics and ROI measurements that extend over a three- to five-year period, and involve both tangible and intangible ROI benefits.
EDC adoption is brisk among a subset of companies in the biotechnology and pharmaceutical arena. Those companies engaged in significant numbers of EDC-based clinical trials are integrating the technology with their other enterprise solutions. The reported "delays" in adoption describe more the majority of companies that haven't quite gotten to enterprise implementation.
Granted, adoption hasn't been enough to nourish all 50 or more companies that have identified themselves as EDC vendors — but that's not the whole picture. In this environment, many vendors have disappeared, but two or three have emerged as financially strong, profitable, and viable for the long term.
The implementation question then becomes, "If not now, when?"
Paul Bleicher is chairman of Phase Forward, a provider of clinical solutions for drug development. E-mail: firstname.lastname@example.org.
PHOTO BY MARK A. GABRENYA