Discover how AI technology is transforming clinical data analytics and driving innovation in the healthcare industry.
Tim, kindly brief us about yourself and your journey as the VP of Clinical Data Analytics at IQVIA Technologies.
I have delivered data management, analytics, and business intelligence solutions in leadership and consulting roles for more than 20 years. I have been part of IQVIA Technologies for almost nine years now, and I currently lead the Clinical Data Analytics Suite (CDAS) of products. These software-as-a-service solutions are utilized by CROs and sold directly to customers. I am also responsible for overseeing the complete lifecycle delivery of other AI and ML-powered solutions such as Risk-Based Quality Management (RBQM), Planning and Monitoring, R&D data and analytics solutions for clinical operations, clinical data management, and intelligent applications.
Previously, I worked at an electronic medical record company where I developed a centralized warehouse to support population health reporting for physicians. Prior to that, I was with one of the largest US health insurance companies, where my role was to provide insights into member demographics and disease trends to assist in forecasting insurance costs.
My diverse experiences have enabled me to gain a broad perspective on data and analytics across the provider, payer, and life sciences spaces. I find it rewarding to witness how data from these distinct areas have come together to enhance clinical trials and ultimately, patient outcomes.
Please share your source of inspiration for exploring various facets of technology and life sciences.
As I mentioned, I’ve had the opportunity to lead data and analytics across the payer, provider, and life sciences industries. Despite the inherent differences across these spaces, the common thread has always been a strong focus on the patient, through providing technologies or services to improve patient care.
At IQVIA Technologies, we continuously innovate and bring more technology and insights – through AI/ML – to clinical trials. This means we can make a faster, more informed decision to enhance patient safety, while also streamlining and automating processes to complete trials more quickly. Having the chance to be at the leading edge of solutions that drive better outcomes for patients is the cornerstone of IQVIA Technologies’ mission and pushes my continued passion for technology in life sciences.
Kindly give us a brief overview of IQVIA Technologies’ products and offerings.
At IQVIA Technologies, we provide a broad range of technology products that execute clinical trials more quickly for our important stakeholders, including pharmaceutical organizations, investigator sites (hospitals, medical groups, etc.), and, most importantly, patients.
As clinical research creates more data than ever before, humans are not able to sift through the volume and variety of data being generated. We provide technology using AI/ML to help our customers get more value from their data.
What are the core values on which the organization is built, and what is the mission of the organization?
Our purpose is to be a catalyst for innovation in healthcare, to drive healthcare forward every day, and to make the extraordinary possible for patients.
At IQVIA Technologies, we do this by speeding up drug development, ensuring product quality and safety, improving commercial effectiveness, getting the right treatments to patients, and improving access to and delivery of healthcare – ultimately driving better health outcomes.
We are passionate about helping customers and partners improve results and patient outcomes. Everything we do contributes to this vision of creating a healthier world.
Being a thought leader, how do you strategize to further IQVIA’s mission and vision?
We understand that today’s clinical trial leaders face unprecedented challenges. Whether navigating complex protocols or facing pressure to move faster, our customers must drive their trials forward to deliver life-changing therapies, all while keeping subjects and patients safe.
So how does IQVIA help? Connected Intelligence™, is focused on connecting people, data, analytics, and technology with our extensive trial expertise to optimize clinical trials so our customers can meet challenges head-on. The results are connected, coherent and efficient ecosystems that help life sciences organizations make faster decisions, drive more innovation and reduce risk throughout the lifecycle of a trial.
In the world of clinical trials, how does IQVIA Technologies leverage AI to improve data integrity, identify any potential issues and improve and accelerate trial outcomes?
AI/ML is at the core of how IQVIA Technologies helps our customers drive trial outcomes. Something that truly sets us apart is our focus not only on AI development but also on insight deployment: ensuring AI-driven insights are automatically and seamlessly introduced into the clinical trial workflow to provide value. We focus on deploying insights to the right person at the right time to drive the right decision. To do this, we maintain a few key priorities when developing technology solutions.
First, we focus on digitizing the process. To ensure clinical trials are successful and future-proofed, we help our customers focus their AI/ML implementation in areas where their processes are already digitalized. The digital process itself allows for the generation of data with which future recommendations can be made.
We also prioritize capturing and incorporating feedback. Our technology solutions allow a user to override a recommendation and capture feedback. As an example, if an algorithm recommends a certain investigator for a trial but that investigator is no longer practicing, that piece of critical information is captured to ensure the investigator is not recommended in the future.
Finally, it is critical that insights are managed centrally. To ensure that algorithms are not tied too closely to a particular application, which would prevent the ability to re-use those insights in other solutions, we developed technologies to enable centrally-managed insights – deployed via APIs to digital workflows. This offers better visibility into the data and insights collected.
Please tell our audience about the emerging trends in clinical trials and how you plan to fulfill the dynamic needs in the pharmaceutical space.
There are many important trends emerging, including ensuring subject diversity in trials, increasing pressures around data security, and focusing on site enablement – to name only a few. However, I’d like to focus on the trend we’re seeing most: reducing patient burden by increasing the amount of activity that can be done remotely. This trend is interesting because reducing patient burden in this way will effectively increase the different types of data processed in a trial. Data will come from the traditional EDC solution along with connected devices, patient-reported surveys, and novel data sources. As more data streams are enabled, more oversight is required.
This shift will require more robust monitoring solutions to ensure the right activities are executed by the right stakeholder, at the right time in order to make the right decision. Due to the complexity involved, it requires AI algorithms to identify where issues may exist and for digital workflows to resolve issues once identified. IQVIA Technologies continues to enhance our tools to meet this challenge on an ongoing basis.
As a specific example, let’s discuss our RBQM technology. In this solution, AI/ML is used to streamline the data review process. AI algorithms coupled with workflow automation result in more proactive risk management. When a risk is identified, the platform can automatically assign the appropriate actions and send a Key Risk Indicator (KRI) trigger with an associated action item to the right team – freeing the monitors and site staff to focus on solutions rather than reviewing all the data and then deciding whether a risk warrants an action or not. Each issue receives the necessary level of scrutiny, resulting in optimal corrective and preventive actions to ensure the identified issue is mitigated and a similar issue does not repeat.
Having the tides of clinical trials changed by the unprecedented pandemic, how has the Covid crisis increased the adoption of AI in clinical trials?
The onset of the pandemic pressured the industry to go further and faster in trial execution – bringing innovations that many thought impossible in pre-pandemic times. When this began, we needed to find more investigators to enroll more patients to collect more primary and secondary endpoints than ever before, through a variety of newly connected devices. This required accelerated improvements in the entire ecosystem, particularly in tools to monitor clinical trials, which needed to handle data volumes many times larger than a typical study. In addition, these tools needed augmentation to help users provide oversight. That augmentation was often in the form of AI and data science-based solutions.
Examples of such tools fast-tracked by the pandemic include algorithms to identify and predict what sites have issues with enrollment, protocol deviations, etc. Other examples include algorithms to automatically spot issues in the data based on past trial data. Additionally, finding novel ways to connect data generated from a clinical trial with other data to augment the view of the patient became increasingly important.
Can you mention a few challenges that clinical trial sponsors are having in adopting AI into their clinical trials? What are your suggestions to address these challenges?
While many have become quite proficient in their adoption of AI, we have seen where there can be significant challenges to be overcome when adopting AI into trials. Interestingly, many of these challenges stem not from the algorithms or technology but rather from finding ways to make efficient and effective use of the insights and predictions that come from the algorithms and technology. In fact, just ensuring that an AI-generated insight or prediction gets to the right decision-maker at the right time is a significant hurdle many sponsors face. However, a strong understanding of, and focus on, workflows and the decision-maker experience will go a long way toward solving this issue.
Additionally, access to data is a significant challenge when implementing AI during a clinical trial. Substantial data is created during trials, but it can be difficult to access due to availability, complexity, and organizational silos. Organizations do not always have the resources, or the infrastructure required to easily store, aggregate, and access data across teams. In addition, change management, and initiatives specifically designed to ensure access to data, will become a key priority in addressing this challenge.
What would be your valuable words of advice for sponsors looking to run a clinical trial today?
While many components make up a successful clinical trial, it is becoming especially important to think through your monitoring strategy upfront with a combined lens across your site monitoring strategy, your data management plan, your central management plan, etc. Predicting risk, and the ability to proactively address risk is key, for this reason, it’s important to ensure tools used for monitoring provide views of the data at least daily and are complemented with the latest AI/ML features to automatically identify issues. By doing this, you’ll be able to identify and resolve issues more quickly and increase the likelihood of success for your trial.
Tim Riely,
Vice President of Data Analytics at IQVIA Technologies
Tim has 20 years of experience delivering business intelligence, data management, and analytical solutions in both leadership and consulting roles. Tim currently leads the IQIVA Clinical Data Analytics Suite (CDAS), providing both SaaS solutions for the market as well as IQVIA’s internal CRO needs. Tim is also responsible for overseeing the complete lifecycle delivery of other AI and ML-powered solutions such as Risk-Based Quality Management (RBQM), Planning and Monitoring, and R&D data and analytics solutions for clinical operations, clinical data management, and intelligent applications. Tim’s background includes a unique combination of payer, provider, and clinical research technology experience.
