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Senior Director, Clinical Data Strategy and Operations, AbbVie

Using an AI + Human in the Loop (HITL) approach can be utilized for Study Data Tabulation Model (SDTM) transformation, potentially alleviating current challenges

The Future of SDTM Transformation: AI and HITL

Even with exciting advancements, stakeholders must remain diligent in choosing data platforms.

Modern Technology is Shaping the Face of COA

Advarra has published results from its 2024 Site-Sponsor-CRO Collaboration Survey. Results include responses from over 200 stakeholders within sites, sponsors, and CROs. The full report highlights three distinct barriers that prevent greater collaboration, ultimately delaying clinical trial execution.

Survey respondents agreed on the importance of communication. However, over half of the respondents from sites and 43% from sponsors/CROs ranked the need for improved communication as important or very important. Additionally, results showed a much higher percentage of sites are initiating daily/weekly communication compared to sponsors/CROs.

"Sites, sponsors, and CROs have good intentions, but they often work in siloes, isolated from the daily concerns of one another, which—over time—creates friction and slows trials," Christine Senn, vice president of site-sponsor innovation, Advarra, said in a press release. "With strong relationships across stakeholders, Advarra is uniquely positioned to create common ground to drive innovation and advance clinical research."

Responses indicated staffing issues as an area needing improvement. In particular, respondents from sites indicated they are seeking better education and training for inexperienced clinical research associates.

In terms of technology and its role in enabling collaboration, about half of the site and sponsor/CRO respondents expressed that better technology would improve their relationships with each other. Despite this, only 29% of site respondents agreed or strongly agreed that sponsor/CRO technology solutions deliver their promised value.

Based on the results of the survey, Advarra identified key actions that can be taken to improve stakeholder relationships. These action items include:

Optimize reporting, visibility, and feedback

Earlier in October, Senn authored an article about site-sponsor collaboration on 

. In the article she wrote, “It may not be easy, but the path forward must start with improving processes, communication, and technology to reduce the time and effort required for study startup. We are better together than apart. Only by committing to be part of our theoretical village, can the industry productively collaborate and come together to accelerate study activation and improve the overall efficiency of clinical research.”

The full report from Advarra can be downloaded 

1. Advarra Publishes 2024 Site-Sponsor-CRO Collaboration Survey Results to Improve Clinical Research. News release. Advarra. November 12, 2024. Accessed November 13, 2024. 

https://www.prnewswire.com/news-releases/advarra-publishes-2024-site-sponsor-cro-collaboration-survey-results-to-improve-clinical-research-302302070.html

2. Senn C. From Isolation to Integration: Improving Site-Sponsor Collaboration in Clinical Trial Startup. 

 October 24, 2024. Accessed November 13, 2024. 

https://www.appliedclinicaltrialsonline.com/view/integration-improving-site-sponsor-collaboration-clinical-trial-startup

Over 200 stakeholders highlighted challenges such as communication, training, and improving technology.

Advarra Publishes Latest Site-Sponsor-CRO Collaboration Survey Results

In the first part of this roundtable discussion, a panel of experts introduce themselves and highlight the challenges industry is seeing with underrepresentation of racial and ethnic groups in clinical trials.

Peer Exchange: The Importance of Improving DE&I in Clinical Trials (Episode 1)

In this roundtable discussion, industry experts gathered to address the state of achieving greater diversity in clinical research. The group highlighted a variety of topics including current challenges they are seeing, the use of technology, and more.

Moderated by Otis Johnson, PhD, MPA Co-Founder & Principal Consultant, Trial Equity, the panel featured key insights from Sophia McLeod, Sr. Director, Government Relations, ACRO; Erin Stern, PharmD, Research Support Pharmacist, Mayo Clinic; and Caitlin Brown, PharmD, Neurocritical Care and Emergency Medicine Clinical Pharmacist, Mayo Clinic.

Brown highlighted the progress in women's representation, but also noted challenges with racial and ethnic groups due to historical mistrust, access, eligibility criteria, and language barriers. McLeod emphasized the importance of early diversity planning in protocol design and community engagement. Stern discussed the logistical challenges of decentralized trials and the need for better technology integration. The panel agreed on the necessity of consistent funding, community involvement, and ethical artificial intelligence use to enhance DE&I in clinical research.

Peer Exchange: The Importance of Improving DE&I in Clinical Trials

Get the initial IRB submission right the first time.

Initial IRB Submission: 7 Fundamentals of Success

Join us for an insightful webinar on antimicrobial resistance (AMR), tailored for experts in clinical development.

https://www.appliedclinicaltrialsonline.com/act_w/future-of-amr

Join us for an insightful webinar on antimicrobial resistance (AMR), tailored for experts in clinical development. We’ll kick off with an introduction to AMR, setting the stage for a deeper understanding of this critical issue. Following this, a summary of key highlights from the September 26 high-level meeting at the United Nations on AMR will be provided, offering a sneak peek into the latest developments and discussions in the field.

The session will culminate in a dynamic panel discussion, featuring leading voices from scientific and regulatory backgrounds. Experts will delve into the challenges faced in clinical research and explore innovative ways to advance AMR. Don’t miss this opportunity to engage with thought leaders and gain valuable insights into the future of AMR solutions.




Latest developments: Learn about the most recent advancements and discussions from the AMR meeting at the United Nations, providing insights into global efforts and strategies to combat AMR.


Innovative approaches: Delve into innovative approaches and breakthroughs to advance scientific understanding.


Future directions: Explore the challenges and opportunities in clinical research for AMR therapeutics, with expert perspectives on overcoming regulatory hurdles and ensuring compliance to drive progress.


Principal – Antimicrobial Resistance, Global Public Health

is an infectious disease epidemiologist by training with over 15 years of experience working in the field of antimicrobial resistance (AMR). She has held positions across several sectors, including health care, academia, public health, and industry. Freeman is passionate about incorporating data into solutions designed to tackle AMR and has spent the majority of her career implementing surveillance systems and optimizing data collection. Freeman is leading IQVIA’s AMR strategy, including the development of innovative solutions and offerings that integrate real-world data into decision-making. She is an advocate for the need for cross-sectoral and transdisciplinary work in addressing the threat posed by AMR and is leading engagements with national bodies and the life sciences industry in support of generating valuable data assets that may be used to provide powerful insights.




Senior Therapeutic Strategy Director, Infectious Diseases and Vaccines

is a senior director of therapeutic strategy in infectious diseases and vaccines, with over 29 years of industry experience spanning both clinical research and R&D formulations. She has a deep focus on respiratory infectious diseases, specifically on community-acquired and ventilator-acquired pneumonias, as well as studies involving antimicrobial resistance and invasive fungal infections in vulnerable HSCT and immunocompromised populations. She has over a decade of experience managing clinical trials and developing therapeutic strategies around VABP/HABP/CABP and VRE/CRE-related infection protocols.


Webinar Date/Time: Tuesday, November 12th, 2024 at 10am EST | 7am PST | 3pm GMT | 4pm CET     

Webcasts: Regulatory, Other

Webcast: Therapeutic Areas

Webcasts: Risk-Based Monitoring

Webcasts: Data Management

Navigating the Future of AMR: Insights and Innovations in Clinical Development

IQVIA is transforming clinical trials through patient- and site-focused solutions that enhance site capabilities and improve outcomes throughout the trial process. This session will delve into cutting-edge strategies and technologies aimed at boosting recruitment, providing targeted support to address enrollment and retention challenges in a competitive landscape, and delivering tangible improvements in strategic scenarios and solution recommendations tailored to meet customer needs.

https://www.appliedclinicaltrialsonline.com/act_w/novel-support

Join us for an insightful webinar where we will delve into how IQVIA is transforming clinical trials with patient- and site-centric solutions. This session will highlight the innovative strategies and technologies that empower sites throughout the trial journey, ensuring delivery as promised to the sponsor. Discover how our structured approach enhances recruitment, mitigates risks, and reduces site burden, ultimately leading to successful clinical trials.



Innovative strategies and technologies: 

Explore the latest tools and methods we use to enhance clinical trial processes.


Learn how our solutions help attract and retain participants effectively.


Understand how we mitigate risks and ensure smooth trial operations.


See how our strategies deliver tangible results tailored to your needs.


is a highly accomplished leader with over 30 years of experience in the clinical research industry. She joined IMA in 2023, bringing her knowledge from senior-level roles in global clinical operations, project management, and strategic partnerships at industry-leading organizations. Throughout her career, she has excelled in building and scaling high-performance teams, optimizing processes, and developing strategic alliances that deliver measurable results.

Senior Vice President Patient and Site Centric Solutions 


- With a career spanning over 20 years in the healthcare and life sciences industry, she excels in overseeing large global teams, P&L management, revenue growth, and C-Suite Relationship Management. Alison's expertise extends to Digital & Change Transformation projects in the data and patient space within the Life Science industry. Passionate about creating efficient ways of working and utilizing technology to drive outcomes, she has held executive positions at ICON plc. and Accenture contributing significantly to their patient, site, and data strategy implementation that helped aide in accelerating drug delivery.

Webinar Date/Time: Thursday, November 21st, 2024 at 11am EST | 8am PST | 4pm GMT | 5pm CET    

Webcasts: CRO/Sponsor

Webcasts: Patient Participation

Webcasts: Clinical Operations

Webcasts: Protocol Design

Webcasts: Trial Design

Novel Support for Sites: Ensuring Clinical Trial Delivery and Sponsor Confidence

In an interview with Nico Saraceno at DPHARM 2024, Munther Baara, VP strategy and innovation, EDETEK touches on the features an effective AI/ML model can provide and how they benefit data management in trials.

DPHARM 2024: Developing AI/ML Models for Clinical Trials

ACT: You have an upcoming session on “Transforming Clinical Trials: From Reactive to Predictive.” What are some of the main points that will be discussed during the session?

 I'll be talking about the metaphor of travelers. Back in the days—it depends how old you are—you might remember when people used to travel, they'll have a map with them. There'll be a passenger next to them with the highlighter trying to map their route, and if they miss an exit, it will probably take them another hour to come back and then we progressed to the MapQuest, where we printed the map, and then we end up with the GPS, and then we end up with a smartphone, and then became a gamification with ways and now we're getting into the predictive analytics to basically predict how you get to do your next day and probably telling you what you should be doing, etc. I see this like in our clinical trials, there's some companies that are still using the paper, navigating with the highlighter, there's people at the GPS, and once a new study with different endpoints, it becomes harder and harder for them, basically, to navigate and be able to see the big picture.

What I'm going to talk about is very simple concept. We call it the four Cs—connect, collect, conform, and consume. What we've done, we’ve built this whole architecture to allow you to connect to the different data providers at the site level or at the study level, so that gives you the ultimate flexibility. You could use different ADC vendors, central labs, ePRO, new digital endpoints, genomics, data, etc., it doesn't matter. The idea behind it is those data providers will immediately be basically pushing data into what we call our digital data pipeline. Then, once the data starts flowing in, you'll see the data coming in and then conforming to the standard of your liking, whether it's for submission or for data review, and then provide you the final piece, which is what we call the consume piece. That's what's so powerful, because now you have to think about it like, you come to a building, you expect light, electricity, and water, right? You don't think about it. Once we do these hooks into the building, into your clinical trial, into our digital data pipeline, things start flowing, and now you're seeing everything in one place, one version of the truth. There are no delays because typically study managers tell me my study was great—green for six, nine months, the first DMC data monitoring committee meeting, I need to do the cleanup or interim analysis—that's when things start basically going south. It went immediately from yellow to red, and I see I have the wrong patients in the study, etc. We solve this problem from day one. That's the key. Study starts. Data starts flowing in. You're seeing whether you are enrolling the right patients into the study or not.

ACT: From a technological standpoint, what’s required for the development of more accurate AI/ML models?

 That's a good question. I struggle a lot of the time when people talk about AI and machine learning, and I feel like they have not done the foundational pieces that's needed in place. Of course, you need AI and modeling and machine learning, but you’ve got to think about: you need to be able to curate the data, aggregate the data, and you need to make sure the data is validated with high quality, so not only curate, but cleansing of the data. The 4 Cs concept that I described does exactly that because we bring data in real time, we basically run all these validation checks, and we have what we call flexible validation rules that you can do through and point and click. Zero programming involved. It eliminates SAS coding, et cetera, especially when you cross data across different data providers. I can look, for example, like somebody says in the exposure data, we adjusted the treatment, and then I look in adverse events, there is no reason for adjustment, et cetera. I can basically cross reference a lot of data. I can cross reference lab collection with the actual lab results, the ePRO data, with how the patient reported safety versus SAE, so I can do that all in coding and then we can apply algorithms as well to monitor the quality of the data. As the data comes in, you immediately point out where there's weak points or what needs to be addressed and tackled, and you’re cleaning the data as you go. That gives you the foundation to have excellent AI and machine learning, basically models in place in order to respond to this. Without it, your model is going to be weak. You're going to be missing a lot of pieces, and not only that—which I forgot to talk about—is the metadata about the data. In order for machine learning and AI to increase the accuracy of it, you need to have the data about the data and that's what our platform has. We can take raw data, transform it to any target data, like from the EDC collection to the CDISC SDTM format that's ready for submission for the regulatory agencies, so that together is needed in order to be able really to get into the next level.

Sanjay Bhardwaj

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