AI, ML, and Me – Oh My! – How AI/ML can Elevate the Clinical Data Manager’s Role

There are moments in time, huge defining moments and smaller (but just as important) ones that shift what it means to be a human on this planet. The big discoveries (e.g., fire, the wheel, and electricity); the huge leaps in technology (e.g., the airplane, the space program, and the internet); and the smaller steps, like the move from paper maps to GPS, these are things that led to complete transformations in how people live and work. For clinical research data professionals, moments like these that evolve how we work can feel like going to sleep at a comfortable Kansas farm, only to wake up (after what may be a bumpy ride) in the land of Oz, surrounded by unfamiliar faces and loads of questions. Remember, though – Dorothy discovered that Oz, for all its uncertainty, also offered new friends and new ideas about how to move forward.

Everything is About to Change – For Good

Today, Artificial Intelligence (AI) and Machine Learning (ML) are about to change everything. For clinical data management, the timing is perfect as clinical trials become more complex. Data volumes are growing to vast proportions as more, and more diverse sources of data are added to study designs. But this revolution is not merely about adopting new tools, rather it signifies a fundamental change in how clinical data is managed, analyzed, and utilized. Unlike other technological advances, AI/ML are less solutions to leverage and more collaborative partners as we seek to enhance efficiency, accuracy, and insights. Returning to Oz, we should not think of AI as the Wizard, but as the Scarecrow, Lion, and Tin Man – Dorothy’s essential collaborators. Thinking of it this way requires an open mindset about the need to evolve our roles as data managers to embrace the broader scope of clinical data science.

The Brain: Reducing the Labor Burden for Clinical Data Managers

The labor-intensive nature of traditional clinical data management is well-known. The meticulous process of data review, anomaly detection, and query management demands considerable time and effort, often leading to delays and increased costs. However, the integration of AI/ML technologies promises to change things dramatically. Just as GPS technology revolutionized navigation by offering real-time updates and efficient route planning, AI/ML is transforming clinical data management by automating routine tasks, enhancing accuracy, and providing faster insights.

Predictive analytics and anomaly detection, two AI-powered tools, are two good examples of this transformation. This is the extended intelligence – the “Brain” the Scarecrow so desperately sought – necessary to performing effective and efficient data tasks in modern trials. These tools analyze vast datasets, identify patterns, and predict future data trends, enabling data managers to proactively address issues and make informed decisions. By reducing manual labor through automation, AI/ML frees up data managers to focus on more complex and strategic aspects of their roles, effectively reducing the labor burden and increasing the value of their contributions to clinical trials.

The Heart: The Indispensable Role of Human Expertise

A common worry often heard regarding AI/ML is that it will replace the human data manager. First, regulatory considerations would preclude this, but there are many other reasons why the human element remains irreplaceable. The journey toward technological advancement in clinical data management echoes the quest of Oz’s Tin Man for a heart. It underscores the essence of humanity—emotion, compassion, and intuition—in the realm of clinical trials. AI/ML can extend our capabilities, but it is the human touch that interprets data nuances, understands the context, and makes ethically sound decisions. This collaboration between technology and human expertise ensures that clinical trials are not only efficient but also empathetic and patient centric.

The integration of AI/ML doesn’t sideline human expertise; instead, it transforms and elevates the role of data managers. By handling routine tasks, AI allows data managers to engage more deeply with data analysis, interpretation, and strategic decision-making. This synergy ensures that clinical trials are conducted with a high degree of accuracy and ethical consideration, ultimately benefiting patients through the development and delivery of life-saving drugs.

Courage: The Evolution Toward Clinical Data Science

The integration of AI/ML into workflows stands to transform the role of clinical data managers. It can be, understandably, a little nerve-wracking for data pros to witness the potential for such rapid change. But, if we face our fears like Dorothy’s friend the Lion, we can embrace a future where data managers are even more valuable to study success. Part of this evolution is the transition from traditional data management approaches to broader thinking around clinical data science. Here, the focus shifts from mere data collection and management to comprehensive data analysis and interpretation. With AI/ML able to enhance the efficiency and accuracy of data management processes, data managers are open to new ways to explore data and generate insights.

The Change is Already Happening

This shift is happening now. As noted in our 2024 Industry Outlook, a significant majority of the clinical data leaders we spoke with at a recent industry event are currently exploring ways to integrate AI/ML technologies into their workflows. A smaller, but growing, number of early adopters are already demonstrating practical outcomes from AI/ML integrations. The challenges of trial complexity, data volume, and speed of data acquisition reinforce the necessity for this transformation, driving the evolution of data managers into data scientists who leverage AI/ML to ensure the integrity, quality, and insightful analysis of clinical trial data.

New Partners for Modern Research

The integration of AI/ML into our work points to a future where data management is smarter, more efficient, and more insightful. Returning to “The Wizard of Oz,” moving forward will require intelligence, heart, and courage. Intelligence to harness the power of AI/ML, heart to maintain the human compassion and empathy that underpin clinical trials, and courage to embrace the evolving role of clinical data managers toward clinical data scientists. The collaboration between AI and humans, far from being adversarial, is a partnership that unlocks new possibilities, driving innovation and efficiency in clinical trials for the betterment of patient care and medical advancements.

For more insights into clinical data management trends based on insights from industry professionals, check out our 2024 Industry Outlook survey. For more information on how eClinical Solutions Biometrics Services can help you develop plans that combine the power of People, Process, and Technology, and to learn how elluminate® can help you establish a foundation for AI/ML-powered process and workflow strategies that fit your organization, visit eclinicalsol.com.