Current Drug Discovery
September 2002 - For every company developing pharmaceutical products, from the largest multinational to the smallest biotech, one of the most formidable challenges is improving the efficiency of the development process. Only those who fully leverage the opportunities of new technologies are likely to succeed.
Technology promises to dramatically alter how drugs are developed and, along with it, the notion of what a pharmaceutical company is. Most fundamentally, technology removes many of the financial barriers that have traditionally limited competition. It used to be that only large companies with formidable resources could field the army of researchers and support equipment necessary to discover drug candidates. Now, however, a modest investment can purchase of a room full of gene sequencers and allows nimble, innovative companies of any size to compete. The effective application of technology can similarly reduce development time and expense by approximately 30% over current benchmarks, a reduction of some $240 million and 3.6 years.
Although the application of technology thus presents a formidable opportunity, the industry has so far merely scratched the surface of its potential. Few in the industry appreciate the complimentary processes that must be in place to allow technology to be fully leveraged. Companies that recognize and can implement these changes stand to dominate the industry tomorrow, while those who are slow to change will inevitably wither.
What’s the problem?
Development centers on a predictable, structured process of gathering data that are used for decision making. Although the process differs between early development (first-in-man, to proof-of-concept [PoC], phases I-II) and pivotal (phase III) studies, much of the difficulty in either case arises from the need to collect vast amounts of data, quickly analyze it, and use it as a basis for increasing the knowledge about the product and making rapid decisions about progressing or failing the candidate.
While early development involves comparatively sparse data, it demands a high degree of judgment. Strategic decisions include issues such as reliability of surrogate endpoints, dosing that balances efficacy with toxicity, and size and number of studies needed to provide a clear indication of issues such as adequate PoC. In contrast, pivotal studies involve copious amounts of data and focus on efficient study conduction, with a relatively well defined path. Issues such as maximizing enrollment, minimizing queries, and rapid data cleaning to allow rapid database lock, become paramount considerations.
Throughout, development represents the challenge of quickly collecting data, and effectively transforming it to information, then to knowledge to facilitate decision making. These tasks must be executed quickly and shared among a technically and often geographically diverse group of individuals. The central goal is the ability to manage studies well, to collect data quickly and share that information widely, with different perspectives available for different job tasks (the lead CRA will want to look at different issues than the VP R&D, for example).
The role of technology
Although technology, primarily electronic data capture (EDC), has greatly speeded data collection, it has by itself largely failed to impact drug development timelines. The reason is that EDC represents just one of several necessary components that together can change timelines, but like a chain, each link is required. Without them, the rate-limiting step becomes the tradi-tional means of dealing with data once it is collected. The goal is not to collect data quickly; it is to shorten development timelines.
Achieving faster development timelines requires the ability to seamlessly collect, manage, summarize, analyze, and share information ranging from single data points to data summaries to broad conclusions. Just as early computers utilized word processing programs that required various add-ons to perform functions such as, spell checking and numbers, could not be shared between a spreadsheet and word processor, streamlining development will not occur until well-orchestrated, fluidly usable tools are in place.
The second major consideration is the processes around the use of technology. The most substantial contribution technology can make is to replace traditional paper-and-pencil processes that are slow and inefficient by today’s standards with new, streamlined processes that leverage technology’s capabilities. The biggest bot-tleneck is usually that internal processes that are not built around the need for data to be handled quickly, to be shared widely, and decisions to be made quickly. Ultimately, it is a combination of technology, processes, and people that will make possible great improvements in how products are developed.
Changing decision making
The near real-time availability of information based on both technology and processes that optimize it changes the way we think about doing studies. Traditional studies, including most that utilize EDC, collect data but await study completion before data are analyzed and shared. In contrast, data that are shared as they are collected means that knowledge increases with each day the study progresses.
Several important advantages are gained by being able to look at data as they are collected. First, we get an indication of the result early on that gains assurance with passing time -in effect, tightening confidence intervals. Second, we may get an answer before the planned end of the study. Since many clinical studies, especially in early development, reflect knowedgeable guesswork rather than hard science, the answer may be apparent earlier than the planned completion. In this case, it can stopped and we can move more quickly to following studies. Third, we may complete the study only to find that the results do not indicate an answer with the clarity desired, necessitating additional observation. The current study can then be extended rather than having to repeat the work with a new, longer study. Finally, if the study runs its expected course, the early indication of results allows subsequent work built on these results to be planned much earlier, even while the current study is going on, and initiated that much more quickly following its completion. All this follows from faster decision making based on the availability of more data of better quality earlier in the process than is otherwise possible.
An example of the use of a fully-integrated system to substantially improve time-lines comes from rising dose tolerance studies. Traditionally, a dose is given to subjects, safety information is compiled, and a decision is made about progressing to the next higher dose. This process generally takes several weeks and can stretch out to several months. Use of technology and redefined processes now allows data to be collected in real time, permitting statisticians to analyze data the same day. Data, summaries, and recommendations are posted to a secure and dedicated web site, and decision makers are then able to review the data wherever in the world they are, conference by telephone if necessary, and make decisions the same day about proceeding to the next higher dose. This carefully orchestrated approach allows redosing the following day.
A second example of the successes of this technology-processes-people approach comes from a large global evaluation of a product for Alzheimer’s disease. This pivotal study involved 107 sites in six countries and more than 1500 patients followed for 1 year, and succeeded in shaving 1.6 years off the 5-year timeline and saved $32 million in direct study costs. This study involved a machine-readable paper data entry (because sites find paper easier to work with and less disruptive to normal workflow) and the utilization of an electronic clinical trial management system that enabled data to be quickly collected and disseminated, and decisions implemented earlier and faster.
Key elements of this approach include:
- Data collection, by several options, includ-ing machine-readable paper forms, SmartPaper™ (a hybrid system where answers are recorded on paper and simulta¬neously recorded in an electronic database), and EDC
- A centralized data management system that validates data and a web-based data query management and resolution
- Reporting, linked in real-time to project databases
- Project management and monitoring
- Regulatory submissions
The most notable feature of this approach is the focus on getting data in quickly and sharing it widely, for both strategic and tactical purposes. The most impotant single issue is allowing different individuals access to validated and processed data essentially as they are collected. Nearly all current EDC systems collect data quickly, but are not able to effectively validate, summarize, and share it. Whether data collection takes an hour, a day, or even a week is not as critical as the need to share this information effectively. Much of this rests on recognizing that the processes that guide what happens to the data once collected are critical links in the chain. It is the combination of technology-processes-people that together will help to ensure an improvement in the product development process.
A common but naive expectation of EDC adopters is that its use will reduce timelines. The appeal of a quick fix, especially with a technology emphasis, has been overestimated: after an unsuccessful effort to improve Chrysler’s efficiency to the level of Toyota that lead to the company’s merger with Daimler-Benz, a senior executive said, “We adopted the same tools as Toyota, but what I failed to realize was that the way people think is far more important than the tools they use.”
Although technology’s ability to change the way drugs are developed has only been superficially explored in this industry, there is little question that the effective application will profoundly change the industry and, along with it, who emerges as domi-nant and even successful companies. Despite the attention technology has received, its promises remain unfilled because of the fact that it has been applied incrementally, rather than allowing new processes that leverage technology to be implemented. In the end, however, it is the combination of technology, processes, and people that will allow promise of reducing development timelines to be fulfilled.
Reprinted from Current Drug Discovery, September 2002