Applied Clinical Trials - August 2010 - (Page 44)
ity. In addition, an automated unit with this increased level of safety and lower financial cost base starts to differentiate companies from their competitors, enhancing the firm’s reputation and delivering a financial impact of its own.
first look at efficacy and stakeholders’ desire to share data rapidly. Meanwhile, the units aim to take on larger numbers of studies. All of these factors are leading to the simple conclusion that paper processes are no longer practical.
Where to prioritize
To inform and drive an implementation plan, it is important to identify and document those benefits that are sought, or if easier, the challenges that the clinical unit seek to overcome. These targets can then drive the selection of solutions and, as importantly, help identify the order in which they are implemented. For the purposes of this article we will look at automated solutions that aid the information flow that drives operational processes and those that facilitate the capture and processing of clinical data. The challenges that fall under this broad definition include: Recruiting volunteers . Trials generally require processing six to 12 volunteers as a group. The failure to recruit full subject groups can delay a trial but, more importantly for the clinical unit, have a significant adverse effect on the financial side as all activities are repeated for those volunteers required to complete the group. Complex workflow. In Phase I, data is collected at a rapid pace and in a highly structured manner, however, each trial is different. Time is of the essence, and the highly mobile staffers are typically multitasking within the unit, as they are usually handling more than one study. Scheduling studies . Key to accommodating a new trial is the availability of beds and staff to conduct the trial. In fact, the similarities with a hotel are marked, with the exception that you cannot move volunteers to a neighboring establishment if you overbook. Once started, trials often stop and restart, and trial designs change. This complex picture requires solutions that can model this flexibility and the ability to make real-time changes. Sample integrity. In the maelstrom of activity that typifies a Phase I unit, it’s important that clinical samples (such as blood) be processed accurately. If these samples are mixed up or improperly stored, or if collection times are missed, the volunteer’s data cannot be used and his or her participation in the study can be invalidated. Evidence of processes. While a strong set of standard operating procedures integrated with evidence of training can support claims of good practice, the ability to present an auditor with contemporaneous data—of freezer temperatures, for example—can provide the definitive picture that attracts both sponsors and regulatory bodies. Accurate data capture. Missing or erroneous data can invalidate results and necessitate a partial or complete repetition. Historically, these challenges have been addressed with increasingly intricate paper processes. These studies are, however, becoming more complex. The unit must accommodate the requirement that early phase trials deliver a
The idea of pushing operational data directly via device and onto a remote database via wireless network is easily accepted by most.
Once the priorities for automation are identified, the team can select appropriate solutions to meet those challenges. Early in the days of Phase I clinic automation, organizations attempted to modify solutions originally developed for later phases for use in Phase I. Today, however, there are many new solutions available built around Phase I requirements. The mobile behavior of staff and wide variety of clinical settings requires portable solutions. These have become possible as the variety of hardware available has increased—touch screen tablet PCs, bacteria and drop resistant laptops, and smaller devices like the PDA and mobile phones—ensuring a tailored solution can be available at the required location. Importantly, in parallel with these advances has come the acceptance of processing operational data directly in electronic format. Many homes now have their own wireless networks, and Internet use consumes a large part of the working and recreational day. Historical problems with network speeds are being overcome as high-level broadband becomes widely available. In areas where it is not as available, network accelerator companies provide the required boost. In short, the idea of pushing operational data directly via device and onto a remote database via wireless network is easily accepted by most. A natural extension sees the collection of clinical data directly into electronic format. To do this topic justice would require a paper in its own right. Positively, regulatory and industry bodies are starting to provide some guidelines toward such use of eSource, and issues previously seen as barriers are now seen as clearable hurdles. 3,4,5 Key areas where solutions have been developed to support the operational and process management challenges highlighted earlier include:6 Electronic schedule to drive operations. To fully automate a Phase I trial, it is important to codify the trial design framework. How many subjects, time of dosing, what clinical samples and data will be collected, and at what time relative to dosing? While the protocol and related documents typically convey this information, it can be captured electronically in just a few hours. This electronic schedule can then drive key operations. The schedule can be sent to
APPLIED CLINICAL TRIALS
Table of Contents for the Digital Edition of Applied Clinical Trials - August 2010
Applied Clinical Trials - August 2010
From the Editor
Letters to the Editor
View from Washington
View from Brussels
Considerations for Medical Device Trials
Automate Phase I Trials
Business and People Update
Calendar of Events
A Closing Thought
Applied Clinical Trials - August 2010