Workflow-based technology coupled with executive authoritative power encourages process optimization in the clinical trial continuum, helping to break down silos, enhance operational performance and ensure quality in the electronic trial master file.
Over the past decade the focus on technology as a driver of performance improvement in clinical trials has been intense. And particularly so for study startup, a widely recognized bottleneck, encompassing the activities associated with site identification, feasibility assessment, selection and activation, required before the first patient can be enrolled in a study.
Practices intended to streamline study startup timelines include the use of technology investments to expedite the collection of clinical data and to help sponsors/contract research organizations (CROs) better monitor clinical trial performance, but despite many attempts at improvement within organizations, gains in end-to-end cycle time have not been made.
A recent comprehensive survey conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD), Start-up Time And Readiness Tracking (START) II, determined that a mere 8% of sponsors and 14% of CROs are extremely satisfied with their study startup processes. By comparison, approximately 40% are either somewhat or completely unsatisfied with those processes. Respondents reporting that they are extremely satisfied have cycle times 57.5% shorter than those claiming to be completely unsatisfied.
Not surprisingly, CROs investment in technology is outpacing that of sponsors, as the outsourcing of clinical trials continues to gain steam. Overall, 80% of organizations which have invested in technology report time savings, with respondents reporting 30% shorter cycle times over those with inadequate technologies.
But despite technology remaining critical, as emphasis shifts to process optimization it may be only part of the solution. Stakeholders have learned that point solutions can hinder the flow of data across the continuum, causing already entrenched silos to dig in further. The need to focus on the overall process – instead of marginal improvements – should resonate with stakeholders responsible for study startup management.
Fortunately, technology provides more than just an opportunity to automate processes but an opportunity to rethink the inefficiencies of silos. Some stakeholders want to move away from vertical silos and "think horizontally." This method uses automation and workflows to integrate operational data across all functions, making it easier to extract meaningful insights from those data, and more importantly to offer significant reductions in overall study cycle times.
An end-to-end solution with workflows that aggregates data from disparate sources can draft documents in the correct format from the start and release them downstream into the electronic trial master file (eTMF). This approach can break down silos that have long performed in isolation with little understanding of what the next department needs to fulfill its regulatory obligations and achieve targets measured by performance metrics.
The importance of this change being driven by upper management cannot be overstated. Executive buy-in provides the critical impetus and strategic insight to align with the organizations goals for development of better therapies more quickly. Without this direction, efforts to jump-start overall performance optimization tend to flounder as departments retreat to their silos.
In short, tools although essential, don't create a master craftsman. That comes from combining experience with the authority and talent to influence how studies are conducted from an operational perspective. Research suggests that organizational issues become strategic and of interest to upper management once they believe it has relevance to performance.
Specifically, purpose-built workflow-based study startup solutions can identify the documents needed to conform to downstream regulatory requirements and can also signal bottlenecks or breakdowns in study execution. Using this approach helps to avoid rework, delays, and cost overruns, improves cycle times, and facilitates audit-readiness.
A seminal report from the Institute of Medicine (IOM) confronted the need to improve the clinical trial process head on by encouraging process transformation through quality improvement efforts, stating that process change rooted in technology should be embraced through the following suggestions:
- Undertake "creative destruction" of old clinical trial business models in favor of newer business models that complement advances in technology.
- Apply technologies, such as web-based clinical trials and smartphones, in place of outmoded mechanisms.
- Engage in more strategic planning and consider new organizational structures for entities conducting clinical trials.
Since this report, process improvement has emerged as a hot button issue as evidenced by the expanding volume of literature. For example, some articles confirm the widely acknowledged challenges linked to contract and budget negotiations as a particularly rate-limiting step in study startup. Martinez et al found those tasks to be the most time-consuming part of the study activation process and to be widely variable in duration due to lack of standardized processes. Using a simulation model, they determined that increasing the efficiency of contract and budget development would reduce activation time by 28%. Other articles describe the need for an organized Six Sigma approach to better study startup processes, whereby steps are carefully defined and continuous improvement becomes standard practice.
While the industry is trying to actively implement processes that improve study startup quality, regulatory efforts may be the driving force.
The recent ICH-GCP E6(R2) guideline, the first new Good Clinical Practice guideline (GCP) in twenty years, includes a new section focused exclusively on risk-based Quality Management. It states that the sponsor should implement a system to manage quality from the start, and throughout all stages of the trial process. This section addresses topics such as critical process and data identification followed by sub-sections focused on risk factors, namely risk identification, risk evaluation and risk control.
In essence, the guideline acknowledges that technology has advanced to the point that it can support processes and generate data that provide actionable insights into risks and study bottlenecks. One example is the use of an application program interface (API), which makes it possible to integrate cloud-based solutions, such as electronic data capture (EDC) and the clinical trial management system (CTMS), optimizing the flow of data across the clinical trial continuum, eventually releasing them into the eTMF. Unfortunately, entrenched siloes have long stymied these efforts, resulting in various stakeholders having minimal understanding of what is needed downstream, resulting in an inefficient assembly-line process from one department to the next.
This awkward management style is one of the root causes of problems with the eTMF. Typically, information about the standardized taxonomy and metadata provided in the TMF Reference Model is not shared with study startup team members, so they are frequently unaware of which documents are needed or the required format for release into the eTMF. Later on, this creates challenges for the regulatory group tasked with mapping documents to the eTMF, as well as indexing the metadata, as startup generates almost half of the TMF artifacts.
Fortunately, with the help of technology, the opportunity to re-think the inefficiencies of siloes is garnering attention. This refers to using automation and workflows to integrate operational data across all functions, making it easier to extract meaningful insights from those data. Also, some believe that bringing interdependent functions together with the help of technology and critical teams will help navigate the highly complicated global regulatory maze.
Optimizing study conduct starts with embracing a workflow-based process that defines the documents needed for study startup. This method boosts quality by preparing documents that are accurate, complete, and conform to the eTMF format established by a sponsor's or CRO's regulatory team, enhancing audit readiness.
The START II study on study startup process highlights how sponsors and CROs profess a strong need for improvement. Both had lengthy site start-up cycle times, in the range of four months for CROs for repeat investigative sites as compared to five months for sponsors. Times were even longer for new sites.
Numerous factors can adversely impact study startup and its efficiency, in an industry plagued by rising development costs and increasing complexities. Complex protocols (leading to increased difficulty in finding patients who meet the inclusion/exclusion criteria), protocol amendments, competition for sites, contract and budget negotiations, regulatory changes and compliance for global studies, IRB approvals, PI and CRA turnover, and others, contribute to significant trial delays.
Given these statistics and inherent bottlenecks, a workflow-based tool that facilitates quality efforts is a sensible option. The tool's integrated data from several eClinical solutions provides an end-to-end continuum that allows properly formatted documents and structured artifacts to flow into the eTMF. Moreover, with the help of this tool, documents eventually needed for the eTMF can be defined upfront, during study startup. This is a major advantage because within those documents, there are often more than 400 draft and supporting artifacts that can be structured, resulting in a final set of approximated 60 artifacts that will ultimately be released into the eTMF.
As clinical trial stakeholders ramp up efforts to optimize the study startup process and begin the arduous task of dismantling siloes, there is a growing recognition that technology is a critical component. Without it, sponsors and CROs will continue to experience the measurable ramifications of poor quality, namely delays, cost overruns, poor communication among study teams, and lack of preparedness for audits. These problems can be avoided with the expanded use of workflow-based tools and performance metrics. For example, despite the presence of many point solutions, eight months remains the average timeframe for moving from pre-visit to site initiation.
With proactive planning supported by integration of information from disparate data sources, issues will be identified earlier, rather than waiting until they reach the eTMF. Currently, regulatory metrics derived from documents arriving in the eTMF are developed too late to provide proactive insight and allow for timely interventions in study execution. In contrast, with a real-time workflow tool, insight from performance metrics can offer the transparency needed to take action in real-time. By embracing this approach, complemented by support from key decision makers, it is possible to move the needle on process change and increase the likelihood of more predictable cycle times, better adherence to study budgets, and audit readiness.
Article published in Clinical Leader, August 2018