INDUSTRY OUTLOOK
2024
Driving Tomorrow’s Breakthroughs with Clinical Data Transformation
TABLE OF CONTENTS
About the Authors ......................................................................................................................................1 Executive Summary .................................................................................................................................2 About the Survey .......................................................................................................................................3 Predicting Industry Impact – Eyes on AI ..................................................................................4 Empowering People and Enhancing Processes ...................................................................7 Data Challenges – Moving Beyond EDC ....................................................................................9 Overcoming Cycle Time Challenges .............................................................................................11 Conclusion .....................................................................................................................................................13
ABOUT THE AUTHORS
Katrina Rice Chief Delivery Officer, Biometrics Services, eClinical Solutions
Katrina Rice is an accomplished and recognized clinical research industry leader with a career spanning more than 25 years. With a strong history of leading business transformations and managing global portfolios, she is as much at home scaling operations as she is in developing data strategies that enable growth for trial sponsors. At eClinical Solutions, Katrina leads our thriving biometrics services group, delivering high-quality data management, biostatistics, and biostatistical programming outsourcing solutions that enable pharmaceutical sponsors to maximize the value of their clinical data, through people, process, and technology.
Diane Lacroix VP Clinical Data Management, eClinical Solutions
Diane Lacroix is a data management professional and leader with over 20 years in the pharmaceutical/CRO industry. As VP, Clinical Data Management at eClinical Solutions, Diane is responsible for leading the data management function including building effective process and implementation strategies to ensure that clients receive maximum value and quality from the elluminate-driven biometrics services that Diane’s team delivers. Diane’s data management career includes numerous leadership roles both at service providers and on the sponsor side. Diane has deep expertise in the oncology and rare disease therapeutic areas and in technologies including EDC (Electronic Data Capture) systems and integration and analytics technology platforms like elluminate.
Sandy Ng, Ph.D. VP Data Science, eClinical Solutions
Sandy Ng is the VP of Data Science at eClinical Solutions. Her team collaborates closely with internal and external stakeholders to bring humans-in-the-loop AI/ ML solutions to life science problems. She holds a doctorate in engineering and is experienced with building data science products for cardiovascular and neurological applications at startup and midsized medical device companies as well as academic medical centers. For the past five years, she has been focused on AI/ML applications for healthcare payer and provider data and clinical trials data.
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EXECUTIVE SUMMARY
The Industry Outlook 2024 reveals a substantial increase in interest in artificial intelligence and machine learning (AI/ML). This surge is attributed to the continued growth in complexity of trials and challenges handling the volume and diversity of data types. While most respondents are still in the early stages of AI/ML integration, 2024 promises a significant shift toward these advanced technologies. At the same time, survey respondents point to a mix of traditional and tech-driven approaches to managing data complexity, for example, respondents expressed keen interest in adapting processes, developing skills, and incorporating advanced analytics tools. Interestingly, the 2024 Outlook indicates a potential stagnation in the growth of external data sources. This is likely due to the slower than expected adoption of DCT approaches, though it may also reflect survey demographics. The results show a higher preference for data from sources that deliver more specific data points, such as central and local labs, Interactive Response Technology (IRT), biomarkers, and imaging over wearables and Real-World Data (RWD). Finally, cycle times remain a significant challenge in the industry, so taking a practical approach with incremental innovation that can accelerate timelines and enhance efficiency is critical. Technologies such as AI/ML represent clear opportunities to increase productivity across the clinical trial life cycle while equipping sponsors to drive new breakthroughs against the backdrop of greater complexity.
Key Takeaways :
•
Over 50% of respondents believe AI/ML will have the greatest impact on efficiency and outcomes in 2024
•
Interest in external data sources is varied, but use of Decentralized Clinical Trial (DCT) technologies and wearables in particular, lag far behind more specific sources of data (labs, biomarkers, etc.)
•
Cycle times remain a significant challenge for respondents
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Methodology and approach: This survey was created to gain illustrative insights and a ‘pulse check‘ of the most pressing concerns for industry colleagues and help inform our biometrics services and elluminate approaches. We received responses from 77 professionals working across clinical operations, data management, statistical programming, and biometrics functions within over 50 organizations. The survey was shared at various industry events between September and November 2023, including at eClinical Solutions’ annual ENGAGE
ABOUT T H E
S U R V E Y
conference. It is important to note the shift in demographics between the Industry Outlook 2024 and the previous year’s report. While the Industry Outlook 2023 primarily incorporated responses from eClinical Solutions’ clients, the survey responses this year reflect a wider cohort.
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PR E D I CT I N G I N DU STRY I M PACT –
EYES ON AI Interest in artificial intelligence and machine learning (AI/ML) in comparison to last year’s Industry Outlook has grown significantly (11% of respondents selected AI/ML as their top trend last year, versus 53% this year), surpassing automation, last year’s highest priority. This shift is driven by the continued increasing complexity of trials and the volume and diversity of data types. As a result, there is a heightened need for advanced analytics, along with the transformation of processes and roles towards a clinical data science framework. The strong interest in AI/ML among respondents may also reflect the hype around the topic over recent months both within the life science industry, and beyond, particularly around the prevalence of generative AI tools such as Chat GPT.
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There is clear enthusiasm among the respondents to embrace innovative technologies and approaches that support this rapid evolution. The results point to a broad interest in a wide variety of AI applications, such as study design, real-time monitoring and anomaly detection, predictive modeling for recruitment, risk assessment, and data transformation. However, it is observed that the vast majority of respondents are still in the exploratory phase of integrating AI into their systems.
Which AI/ML approaches are being used or explored within your organization?
Optimizing Trial Design
There is a gap for the industry to bridge between exploring potential uses of AI/ML and realizing the value, yet there is an expectation from survey respondents that these technologies will have a significant impact inside the next 12 months. The barriers to further integration are diverse, including access to data, concerns about the impact on job security and roles, and uncertainty about the ability to demonstrate return on investment. Clearly, a collaborative industry-wide effort will be needed to overcome these barriers and realize meaningful results within this timeline.
Real-time Data Monitoring and Anomaly Detection
Predictive Modelling for Patient Recruitment
Which life science industry trends do you believe will have the greatest impact on efficiency and outcomes over the next 12 months? Decentralized Clinical Trials (DCTs)
Risk Prediction and Management Risk Based Strategies
13%
Data Transformation
13%
Identifying Safety Concerns
21%
Biomarker Identification using AI/ML
53% Automation
Others
Artificial Intelligence (AI) and Machine Learning (ML)
Data Redundancy
Patient Stratification Driving Tomorrow’s Breakthroughs with Clinical Data Transformation
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“
“Our focus is to stay ahead of the clinical trials evolution, and we innovate in a practical way through a phased approach. The addition of AI and ML to the toolkit is a power boost in the transformation to a modernized data management approach and journey towards clinical data science.” -Diane Lacroix, VP Clinical Data Management, eClinical Solutions
To what extent has your organization integrated AI/ML approaches into clinical data workflows?
80%
are in the exploratory stage or are planning to implement AI/ML
7%
have integrated AI/ML across one or multiple applications
13%
have no current plans to implement AI/ML
With a scalable, interoperable clinical data infrastructure that includes embedded AI and other cutting-edge capabilities, eClinical Solutions emerges as a pivotal player, wellpositioned to assist sponsors embarking on, or accelerating, their AI journey. The team has initially prioritized use cases around clinical data review and is already moving into data transformation and other applications.
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EMPOWERING PEOPLE AND
ENHANCING PROCESSES Respondents expressed strong interest in adapting processes and workflows, developing skills and training, and incorporating more advanced analytics tools. This aligns with the industry’s focus on evolving from a traditional clinical data management model towards a more holistic clinical data science framework. Clinical data science not only considers the data itself, but also risk, and the journey necessary to consistently produce high quality data. Effective transformations must address all aspects of the data cycle, including skills, workflow efficiencies, available technologies, and necessary partnerships to ensure all bases are covered. They require complete assessments of an organization’s current models and available resources, liabilities, reliance on technology, and much more.
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eClinical is prepared with the necessary experts to assist clients in integrating various technologies and solutions essential for facilitating modern trials. This approach focuses on blending people and technology to create solutions that are greater than the sum of their parts, ensuring a seamless integration of innovative practices even as approaches evolve, and new technologies continue to emerge. When working with clients, eClinical Solutions brings a holistic focus on adaptive processes, reducing handoffs and redundancies within workflows, maximizing the benefit of existing technologies, and supporting the introduction of new ones.
Which are the top 3 most effective strategies your organization is using to handle greater trial and data complexity?
Adapted processes and workflows Implemented skills development and training programs
Leveraged specialized partnerships
Adopted AI/ML technologies
“The modern data manager looks at the whole picture the data tells across all data sources, connecting it to their knowledge of the data strategy for the trial.” -Katrina Rice, Chief Delivery Officer, eClinical Solutions
Increased resource allocation
Others
Incorporated advanced analytics tools
“
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DATA CHALLENGES –
MOVING BEYOND EDC This year’s survey revealed a slight stagnation in the reported number of external data sources being used compared to last year. This can be partly attributed to slower-than-anticipated adoption of decentralized clinical trial (DCT) approaches, though may, as previously mentioned, be a feature of respondent demographics. Nevertheless, volume and variety of data clearly remain key issues, reflected in both the reported usage, and in discussions during eClinical Solutions’ ENGAGE event. According to survey results, the types of external data sources being used vary widely. Despite buzz around wearable devices, actual use lags. This is in line with the less-than-expected uptake of decentralized clinical trials across the board. Realworld data use is also less prevalent. In contrast, there is high interest in collecting data directly from central labs, local labs, Interactive Response Technology (IRT), biomarkers, and imaging. It can be inferred that external data sources that deliver more direct and specific measurements are currently much more likely to be utilized. One barrier to adoption of hybrid and fully decentralized trials may be the complexity of navigating the vendor ecosystem and operationalizing with new partners, particularly in the context of data security and data privacy concerns.
“
How many external data sources (outside of EDC) are you routinely incorporating at your company?
“We’re seeing a lot of external data sources that are bringing in data in so many ways. We’re trying to house that data externally from EDC, which is a good thing, but the question becomes, “How do you bring all of this data in and make it useful for reporting purposes?”” -Emily Pereira, Director of Clinical Data Management at bluebird bio
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“ “A key task for the future is incorporating and integrating all these data sources to get a more holistic picture of the patient.”
In addition, despite decentralization, there is often a burden placed on sites to manage the technologies or technology distribution, which needs to be overcome. In a traditional, regulatoryconstrained industry, the limited number of use cases and success stories for sponsors to refer to about DCT approaches in practice may also be an inhibitor.
best practices to maximize the value of external data is critical, as is building a dedicated infrastructure across people, workflows, and technology to examine, process, reconcile, and standardize diverse data. To this end, eClinical Solutions has established a Center of Excellence for External Data which promotes best practices across its Biometrics Services group.
As the industry grapples to understand how best to leverage these approaches effectively, sponsors are increasingly turning to partners to help navigate the inherent challenges around the adoption of DCT approaches, including wearables. Many sponsors are seeking practical guidance on data acquisition approaches for specific study needs, as well as future-proof technologies to handle the collection and monitoring of expanding data volume. Further, they need partners that can support them now and in the future as more data sources emerge. Embedding
Regardless of the slower than anticipated growth in the use of some external data sources, the industry overall is more comfortable pulling data directly from the source. Whether clients require a hybrid approach that includes external data and EDC data or are operating studies that rely entirely on external data, eClinical Solutions provides a platform that can do either while simultaneously bridging the gap between the different strategies.
What types of external data sources are you routinely using within your clinical trials?
-Sandy Ng, VP Data Science, eClinical Solutions
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“ OVERCOMING
CYCLE TIME CHALLENGES Survey results highlight that cycle times remain a significant and ongoing challenge, intrinsically
“More than ever, clinical development and data management professionals are challenged to increase operational efficiency and reduce trial cycle times. Sponsors and service providers alike are grappling with the question – how do we compress the time it takes us to reach key milestones while maintaining quality?” -Katrina Rice, Chief Delivery Officer, eClinical Solutions
connected to the increased complexity of the overall clinical trial landscape. As discussed by thought leaders during eClinical Solutions ENGAGE conference, progress towards acceleration has been lackluster, and is of significant concern in the context of return on R&D (research & development) investment, patient enrollment challenges, and overall industry headwinds.
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Understanding that these macro pressures
Collaboration and process optimization
eClinical Solutions demonstrates significant
are top of mind for the industry, eClinical
also play a crucial role in driving resource
improvements in various cycle time areas. This
Solutions employs a combination of
efficiency and productivity, offering another
is most notable in accelerating the time from
innovative technologies and expert services
avenue for timeline acceleration. Given that
last-patient-last-visit (LPLV) to database lock,
to streamline processes and accelerate
cycle times within the data management
where cycle times of 2-4 weeks are typically
timelines and include AI-enabled data
process are co-owned between the
achieved, compared with the industry average
review capabilities, and Electronic Data
sponsor, data service provider, and involve
of over 6 weeks. These improvements have
Capture (EDC) build automation and LPLV
multiple stakeholders, developing close
been delivered through technology, along
to database lock timelines. Automated data
outsourcing partnerships and committing
with people and process initiatives such as the
standardization is another tool facilitating
to transparent communication can help
Center of Excellence for External Data which
quicker data access and providing insights
optimize review cycles and unlock efficiencies.
delivers a reconciliation timeline of under 5
within six weeks of EDC go-live.
Through knowledge of sponsors’ processes,
days.
standards, and communication preferences,
What is the average timeline from kick off meeting to database live?
What is the average timeline from Last Patient Last Visit (LPLV) to database lock?
What is the average timeline from DBL to final TLFs (Tables, Listings, Figures)?
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CONCLUSION
The 2024 Industry Outlook reveals several key themes. It is clear that growing data volumes and complexity are causing many to look proactively to technology for solutions. Interest in AI/ML is high, with the vast majority of respondents already exploring how to implement these approches. Still, there is uncertainty in how to go about implementing leading edge technologies. eClinical Solutions is well-positioned with its future-ready clinical data and analytics infrastructure, and innovation-led services to give researchers the confidence to take the next steps in conducting modern clinical trials. Working together, we can reduce cycle times, discover and implement new and more efficient processes, build a foundation ready to handle the challenges of the future, and drive tomorrow’s breakthroughs.
To learn more about how eClinical Solutions’ technology and biometrics services are helping life sciences organizations navigate the challenges and opportunities of clinical data transformation, schedule a meeting with a subject matter expert. Click here
“ “I am an optimist, and I believe the next few years are going to be quite different from what we have seen in the industry over the last two decades. Compared to the years it took for adoption of EDC, I genuinely believe it’s going to be significantly different in terms of the adoption of modern technologies.” -Raj Indupuri, CEO eClinical Solutions (Engage 2023)
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ABOUT eCLINICAL SOLUTIONS eClinical Solutions’ industry-leading data & analytics platform and biometrics services experts help biopharma researchers at large, mid-size, and emerging life sciences organizations manage trial complexity in less time and with fewer resources. Clients get accurate and timely data insights for better decisionmaking – enabling them to reduce cycle times, improve productivity, easily scale, and develop tomorrow’s breakthroughs with today’s resources.
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