Both sponsors and research sites can benefit by increasing the use of digitalization and data enablement in clinical trials. According to Martin Lim, Managing Consultant and Clinical Lead at NNIT, streamlined patient recruitment, better data capture and reduced investigator burnout are just some of the advantages.
The life sciences industry has been using digital technologies like electronic data capture (EDC) systems and electronic trial master files (eTMF) to enable clinical trials for over two decades. Yet, many clinical research sites around the world still use paper to collect clinical trial data, which is then manually entered into EDC systems. With the advent of tools such as ChatGPT, not only can the data be collected digitally, but can also be analyzed through the use of AI to draw conclusions and provide insights.
It is something of a paradox that the life sciences industry is both one of the most innovative industries and one of the most conservative, especially when it comes to the use of new digital technologies for clinical trials.
As clinical trials often represent multimillion-dollar investments, many pharma companies are understandably reluctant to risk the outcome on new and unproven technologies. In addition, many biotechnology companies are under financial pressure to save on costs while making progress on their drug development pipeline, so adopting new technologies is not always a top priority.
– In recent years there have been extraordinary advances in novel treatments, advanced therapies and digital innovations for clinical research. On the other hand, many sponsor organizations are slower to introduce new technologies in their clinical trials, says Martin Lim, Managing Consultant and Clinical Lead for the APAC Region at NNIT.
The result is that organizations choose traditional paper and manual processes or incorporate less innovative, lower-cost technologies. But upgrading to fit-for-purpose platforms such as eTMF, incorporating digital technologies to expand reach and compliance in a clinical trial, and using AI tools for data enablement can significantly improve clinical research in numerous ways. Ultimately, this can lead to faster, more cost-effective clinical trials and better outcomes for patients. In this article, we explore several of these opportunities further.
Make patient recruitment and enrollment easier
Identifying, recruiting and retaining a sufficient number of participants is a major challenge for most clinical studies. If the number of participants is too low, the sponsor organization may be forced to open additional research sites and broaden the search for suitable candidates, which is both costly and time-consuming.
– To help mitigate these risk, pharma companies can use digital marketing campaigns and patient-engagement platforms to reach a wider pool of potential study participants, increase awareness of clinical trials, and improve patient engagement and retention. At hospitals and health centers, healthcare professionals can use artificial intelligence (AI) to comb through electronic medical record (EMR) data and identify suitable patients, based on relevant criteria, says Martin Lim and continues:
– Once a participant is recruited into the study, eConsent technologies can make the informed consent process easier and more understandable. For some sponsors, eConsent is the first entry into decentralization of their clinical trials. Although seemingly straightforward from the surface, sponsors and sites use a wide variety of eConsent platforms, significantly increasing complexity.
Gather clinical data from a variety of digital sources
Once a participant is enrolled, a host of technologies enable clinical trials behind the scenes. From eTMF managing non-clinical data, to interactive response technology (IRT) systems managing participant randomization and supply levels, to the EDC systems that collect the clinical data and prepare it for analysis, all of these technologies are orchestrated to bring a clinical trial to fruition.
All of these digital tools can help to collect and manage data more efficiently and accurately. Ideally, a unified platform, built on a single technology stack that encompasses all the clinical operations technology needs, is the best solution. However, in practice, sometimes “best in breed” solutions are necessary. In this situation, interoperability is required for business continuity.
Furthermore, digital technologies such as electronic patient-reported outcomes (ePRO) platforms, wearables and mobile health apps can be used to monitor patients in real-time, providing researchers with more accurate and detailed data on patient health and behavior. But the introduction of these new tools in clinical trials requires careful attention to protocol design and factors that can impact the data quality, such as smartphone ownership and digital literacy among the trial participants. Done right, such digital technologies can reduce the burden on participants, increase retention rates and speed up overall completion of clinical trials.
Once the clinical data has been collected, all of these various sources will eventually need to be integrated back to the main EDC system of the clinical trial sponsor for analysis.
Integrate and learn from clinical operations data
As sponsor organizations advance their drug development portfolios, they accumulate a wealth of clinical operations data, which can be used to improve the quality of future trials.
In addition, AI and machine learning (ML) algorithms can be used to consolidate and analyze large volumes of data, identify patterns in study progress, site performance, data quality, and resource allocation, and make predictions about patient outcomes.
– Sponsors should aim to extract as many insights as possible from their clinical operations data. How long did the startup and enrollment phase take? What was the dropout rate? Why did some sites perform better than others? Did our investigators and site staff have the right training? Answering these questions can help researchers to identify potential safety issues, reduce errors and optimize study protocols, says Martin Lim.
Prevent investigator burnout
Digital collaboration tools can be used to improve communication and collaboration between researchers, study sites, and sponsors. This can help to streamline processes, reduce errors, and ensure that everyone is working towards the same goals. Digital collaboration tools can also significantly reduce the burden for clinical research sites and investigators. For example, a clinical site might have one familiar platform for gathering and compiling EMR and other source data, which can integrate with whichever EDC system the sponsor prefers.
– In the clinical research community, the term “one-and-done” alludes to the fact that, of all the physician investigators who participate in clinical research, over 50 percent only participate in one clinical trial over the course of their career. The main reason for this is the tremendous workload that a trial places on investigators. The consequences are significant in terms of knowledge drain and the added cost of finding new investigators, says Martin Lim and concludes:
– There is a huge potential for enabling clinical research sites with new technologies to reduce the burden on investigators and their supporting staff, especially in less developed countries. This presents opportunity for new technologies and business models to emerge, and the need for integration and interoperability will not only persist but continue to grow as the number of technologies coming online increases.
