Revolutionizing clinical trials with workflow automation

Revolutionizing clinical trials with workflow automation

The pressure is on. Life-science companies seek to market innovative treatment faster, but clinical trials become more challenging and require running and coordinating complex processes involving stakeholders from all over the world. The complexity stems from the need to comply with extensive and consistently evolving regulations, the increasing costs to conduct clinical trials, and the effort and nuances of governing clinical trials. As a consequence, the clinical trial industry turned to technology in the hope of alleviating some of these increasing burdens. Still, the return on investment failed to reach an acceptable level. Current technology hasn’t been able to keep pace with these increasing challenges, despite being the industry that invests the most in R&D. The enormous increase of data generated by clinical development is outstripping the ability for legacy software to efficiently and quickly manage the competing need for data sharing, patient privacy, and data integrity. Ultimately, clinical trials take more time and increase in cost.

This article will outline the main issues related to clinical trial management. It will describe the landscape of technology available today, its main limitation, and the consequences on time and cost. Finally, it will introduce a novel technology developed by Zapclinica: workflow automation for clinical trial operation. This technology aims to revolutionize clinical trial management by replacing manual processes with an intelligent and autonomous engine that enables the clinical team to focus on higher-value work instead of repetitive tasks.

Why have clinical trials increased in cost? Why do they take more time?

As discussed in the introduction, clinical trials have increased in complexity, face a more stringent regulatory environment, and require a vast workforce that must be adequately managed. These aspects have had a considerable impact on today’s clinical trials. Let explore them in detail.

First, clinical trials have increased in complexity. Based on multiple studies conducted by the Tufts Center for the Study of Drug Development ( CSDD ) over the past 15 years, protocols have more endpoints, procedures, inclusion/exclusion criteria, amendments, sites, and case report forms. This situation increases the burden of execution on clinical trial coordinators and health providers to ensure strict compliance with protocols. It increases costs and performance and the overall risk of errors, as well as lengthens the amount of time necessary to train the clinical team. Some of the reasons for the increase in complexity include a focus on chronic illnesses that requires additional data to measure more difficult clinical endpoints, a need for more data to differentiate products based on efficacy or safety differences, requests for additional data from regulatory agencies, purchasers and payers to address concerns about drug safety and comparative effectiveness, and a shift of post-approval studies from observational to robustly controlled.

As the complexity of clinical trials increases, complying with regulations also becomes more difficult. The landscape of clinical trials has changed considerably over the past decade. With stricter regulations and increased complexity in the protocol, clinical trials have produced much more than before. Numerous resources are needed to ensure all the processes are compliant. Maintaining visibility into the compliance program requires communication across the organization. However, a traditional compliance workflow often becomes burdensome on an organizational scale. Emails and calendar notifications become lost in the day-to-day clutter of operations and meetings. During a clinical trial, multiple stakeholders can share overlapping compliance responsibilities, but someone also needs to set tasks and assign responsibilities. That person then needs to ensure that tasks are completed on time. This outdated process can lead to confusion and missed deadlines, which overwhelm the team involved in the clinical trial.

On top of that, managing all the stakeholders involved in a clinical trial is challenging and time-consuming. Hiring and training highly knowledgeable and effective staff for clinical trial management takes time and resources. In the current environment, it has become hard to manage staff efficiently without causing unnecessary issues and delays in the clinical trial’s success.

High turnover in the industry interferes with the consistency of processes, reduces the quality of data, and increases the risk of errors. There is no strategy in place to transfer knowledge. Alleviating the issue by relying on outsourced trial management does not result in the expected outcome; outsourcing without proper support from the sponsor to identify and prioritize essential tasks results in opacity and wasted time. Consequently, consultants tend to focus their efforts on non-important study risks. Managers end up without a holistic understanding of the project. Important information is not formalized and tends to be held only by a small group of people. Finally, time pressure on personnel increases the number of people who are unable to take the time to understand the data — reduce to source data verification in detriment of risk management.

With these challenges, one would ask about technology currently used in the industry. Technology was supposed to bring clinical development into a new age of ease and compliance and enable faster delivery of information. But it has become part of the problem by promoting isolated databases from a multitude of different vendors. Users need to log in to various applications with different credentials and user IDs. Data are often transferred from one system to another manually, thus incurring a high probability of errors in the process. Without a standardized process, every data transfer needs special treatment, which becomes even more intricate when you involve third-party vendors. This adds a risk of data discrepancy, threatening the safety and reliability of the study. In the age when data have become an asset, it is unacceptable. Data are a crucial business asset from which we can extract value and gain a competitive advantage. Those who use data well will be the success stories of the future. More and more pharmaceutical companies understand the importance of data in those competitive markets and treat them as a corporate asset.

As a consequence, clinical trials cost more and take more time. It takes an average of $2.6 billion, including the cost of failures, and 10–15 years to discover, develop, and get approval for a new drug. Additionally, only one of every 10 drugs that start trials ends up being approved by the FDA; 80% of clinical trials fail to meet their expected milestones and lose between $600K and $8M each day a drug is delayed from the market.

Clearly, a breakthrough technology needs to be created to solve these issues.

Say hello to workflow automation for clinical trials.

Zapclinica developed a new technology that removes repetitive manual tasks with automated processes operated by an intelligent system. By leveraging self-operating processes that perform manual tasks, workflow automation will save time and money, diminish errors, and boost productivity in your clinical operation. In order to understand the potential of the technology, let’s showcase the benefits of workflow automation with a use-case scenario.

Let’s automate the process of IRB approval of the study post-site selection. As mentioned earlier, clinical trials are comprised of processes that are manual. When an investigator agrees to participate in a clinical trial, the sponsor and the investigator work together to seek IRB approval for a site to start enrolling participants in the study. This process is usually called IRB approval of the study’s post-site selection and includes tasks like collecting essential documents, delegating responsibilities, and training. On average, it takes six months to complete. This process is intense and requires time and patience. The study project manager, study monitor, or CRO representative usually manages this process by phone or email. Failing to follow up with an activity results in delays and non-compliance, which might trigger a concern from regulatory authorities during the audit. Transforming this manual workflow into an automated one is easy and yields huge benefits. Below is a simplified version of this process, after being automated through an automation assistant:

The workflow is straightforward:

1. The first step is a trigger. An automation trigger is an initial input that kicks off the activation of an automated workflow. In a sense, an automation trigger is, quite literally, the first step in automation. In this case, the trigger happens when a new site is added to the EDC. The workflow is automatically initiated and executes the first action.

2. The second step is action. An action is an event a workflow performs after it is triggered and can leverage any application or tool of your choice. In this case, we leverage the Tasks application and create a new task assigned to the principal investigator. The task requests document review of the protocol, brochures, recruitment materials, informed consent template, and CRFs template.

3. When step 2 is complete, request the principal investigator to send all of these documents to IRB.

4. When step 3 is complete, request the principal investigator to upload the IRB approval.

5. When step 4 is complete, automatically store the IRB approval directly in the expected location in the ETMF.

Below an example of ongoing automated workflow

On March 10th, a new site, Sutter Health, was added to the EDC. This trigger automatically generated a task assigned to Hellen Doe, principal investigator at Sutter Health, who was required to review the protocol. As the automated workflow unfolds, a new step will be added until the full completion of the process according to the requirements.

Conclusion

The benefits of this system are obvious and immediate. By automating the flow of actions and precisely configuring the steps in adherence to the protocol, we have effectively let the system take care of all the burden that would otherwise be on the shoulders of the sponsor clinical team. The automation process now eliminates any human error, delay, or opacity to the process. This novel approach completely changes the rules of the game. Let’s review the main advantages of this new technology.

First, workflow automation reduces the complexity of managing clinical trials. With fewer papers, fewer emails, and less time-wasting when managing or requesting statuses, the clinical trial becomes easier to manage.

Secondly, it improves governance and oversight. All users can see what they need to do. When they are done, the system validates their actions and passes to the next person. So, it’s no longer necessary to run after people to request relevant information or get things acknowledged.

Moreover, we can enable a few experts to create well-designed, automated workflows at scale as well as to measure, in real-time, the value of human and automated work across a clinical trial. We can learn from past decisions, simulations, or real-time data to improve workflow accuracy. When changes to logistical rules are required, users can quickly update them, providing the agility and speed needed to meet changing demands.

Third, it improves compliance with regulations. Streamlining the process with workflow automation makes documenting part of the system. Audits rely on documenting policies, processes, and procedures rather than manual tasks. Auditors can verify the audit trail just by looking at the workflow history.

This novel technology has been developed over the past three years and is patented. We hope to bring it to the market so clinical trials won’t be as hard as they were in the past.