ISPOR 2025
13-16 May 2025 | Montréal, QC, Canada | Booth #822
Embarking on your next research journey?
You can’t find the evidence you’re seeking without looking into the world’s largest ecosystem of real-world data.
TriNetX is thrilled to embark on a journey of discovery at ISPOR 2025, taking place May 13-16 in Montreal, Canada.
As pioneers in real-world evidence (RWE), we push boundaries to uncover insights that drive better healthcare decisions.
This year’s conference theme, ‘Collaborating to Improve Healthcare Decision Making for All: Expanding HEOR Horizons’, aligns with our mission to equip researchers with the tools, support, and data to navigate health economics outcomes research (HEOR) complexities.
From uncovering real-world insights to guiding regulatory pathways, our solutions help healthcare leaders turn data into action. Join us at ISPOR 2025 to advance evidence generation and reshape the future of patient outcomes together.
Why visit TriNetX at ISPOR 2025?
- Live Demos: See our analytics platform, TriNetX LIVE™, in action
- Expert Discussions: Connect with our team of real-world evidence specialists
- Exclusive Content: Get access to our latest research and insights
- Networking Opportunities: Join thought leaders shaping the future of healthcare
- TriNetX Prize Draw: Enter at our booth for a chance to win an Apple Watch Series 10!
Only the best real-world evidence…
Meet with our RWE consulting team at Booth #822 to explore how we can support your research goals, ensuring every step of your evidence generation process is optimized and purpose-driven for success.
Our expert team, with decades of clinical, epidemiological, and regulatory experience, provides tailored strategies across the entire product lifecycle—from early discovery to post-market analysis.
Let TriNetX RWD guide your RWE journey to uncover ground-breaking insights that improve decision-making, targeting, and health outcome evaluations.


…is generated with the best real-world data
Are you frequently faced with data challenges, such as harmonization, access, and depth, that can quickly complicate research and decision-making processes? TriNetX provides fit-for-purpose, real-world data (RWD) solutions backed by a dedicated team of data scientists and researchers, offering rich, harmonized datasets that account for the evolving global data standards.
To ensure your teams are emboldened to deliver next-generation evidence, they’ll be equipped with extensive training and support to help effectively navigate and leverage these datasets for your research needs.
Leverage real-world data across a broad range of therapeutic areas
Patient Counts by Disease Indication
Pulmonology
(J00-J99)
Patients
Endocrine, Nutritional, and Metabolic
(E00-E89)
Patients
Cardiology
(I00-I99)
Patients
Pre-Book Meetings with TriNetX
Let’s meet at ISPOR to explore the possibilities in your next RWE project.
Visit the TriNetX Booth
Booth #822
Exhibit Hall Hours:
Wednesday, 14 May: 9:30AM – 7:00PM ET
Thursday, 15 May: 9:30AM – 7:00PM ET
Friday, 16 May: 8:30AM – 11:30AM ET

TriNetX Poster Presentations at ISPOR 2025

RWD70: Barriers to Genetic Risk Factor Molecular Testing in CLL: An Analysis of Real-World Practice and Alignment with 2023 Guidelines in Germany
Presenter: Zuzana Dostalova, Data Scientist, TriNetX
Research objective: Despite the 2023 German CLL guidelines emphasizing TP53 aberrant and IGHV unmutated status testing for treatment decisions, many patients remain untested. This research examines molecular testing frequency in clinical practice in Germany and explores physician-reported barriers to implementation.
Where to find us: Poster Session 2
Date: Wednesday, 14 May
Time: 4:00PM – 7:00PM
Discussion period: 6:00PM – 7:00PM
MSR81: Imputing Breast Cancer Stage in a Large EHR Dataset: Light Gradient Boosting Machine Algorithm and Explainable Artificial Intelligence
Presenter: Marley Boyd, Senior Director of Analytics, TriNetX
Research objective: Electronic health records (EHR) data are often missing cancer staging. Advanced machine learning builds accurate but uninterpretable models; Explainable AI deciphers the logic behind these models. In this study, Light Gradient Boosting Machine (LightGBM) imputed breast cancer stage at initial diagnosis, and SHAP (SHapley Additive Explanations) explored feature importance of the underlying model.
Where to find us: Poster Session 3
Date: Thursday, 15 May
Time: 10:30AM – 1:30PM
Discussion period: 12:30PM – 1:30PM
MSR130: Using Real-World Data and Machine Learning to Identify Patients at Highest Risk for Hospitalization Following Respiratory Syncytial Virus Infection
Presenter: Zuzanna Drebert, Data Scientist, TriNetX
Research objective: Respiratory syncytial virus (RSV) infection is a common cause of respiratory illness in adults, posing a greater risk to patients with chronic medical conditions than to healthy individuals. In 2023, the U.S. Food and Drug Administration (FDA) approved two RSV vaccines for older adults and The Centers for Disease Control and Prevention (CDC) recommends vaccination for adults aged 75 years and older and adults aged 60-74 years with chronic medical conditions. This work aimed to leverage machine learning (ML) to explore how variables derived from electronic health records (EHR) influence the risk of RSV-related hospitalization. We used Explainable AI to understand how these clinical and healthcare utilization characteristics contribute to this risk.
Where to find us: Poster Session 4
Date: Thursday, 15 May
Time: 4:00PM – 7:00PM
Discussion period: 6:00PM – 7:00PM
RWD105: Benchmarking Disease Prevalence in a Large Scale Electronic Health Record Data Network: An Assessment of Chronic and Rare Disease in the United States in 2023
Presenter: Amanda Moore, Principal Research Scientist, TriNetX
Research objective: The representativeness of real-world data sources can vary when comparing the observed population to the broader target population. The study objective was to benchmark the 2023 prevalences of common chronic conditions and selected rare diseases, comparing the TriNetX Dataworks-USA network to the US healthcare-seeking population.
Where to find us: Poster Session 4
Date: Thursday, 15 May
Time: 4:00PM – 7:00PM
Discussion period: 6:00PM – 7:00PM
EPH165: Race, Social Determinants of Health (SDoH), and Stage at Breast Cancer Diagnosis in Electronic Health Records (EHR) Data
Presenters: Zuzanna Drebert, Data Scientist, TriNetX and Katie White, Director, Project Management, TriNetX
Research objective: Early diagnosis of breast cancer is associated with improved outcomes. Black women are generally more likely than White women to be diagnosed at a later stage. Some studies have found that racial disparities in diagnostic timing persist despite adjustment for SDoH and other factors. We aim to explore the associations between race, SDoH, and stage at diagnosis using EHR data.
Where to find us: Poster Session 5
Date: Friday, 16 May
Time: 9:00AM – 11:30AM
Discussion period: 9:00AM – 10:00AM
Our World-Renowned Experts

Jeff Brown
Chief Scientific Officer

Jeff Graham
Vice President, Data Solutions

K. Arnold Chan, MD, ScD, FISPE
Senior Vice-President, CSO Office

E. Susan Amirian, PhD
Senior Director, Research

Andreas Weber
Senior Vice-President, Oncology

Markus Rückert, PhD
Medical Director

Zuzana Dostalova
Data Scientist

Julia O’Rourke, PhD, MS, MMSc
Principal Data Scientist, Research

Zuzanna Drebert
Data Scientist

Marley Boyd, MS
Senior Director, Analytics, Research & Data Solutions
Exploring TriNetX Solutions for HEOR and Beyond
Explore Data Sets & Analytics Solutions
Downloadable, curated, or linked data sets to power analysis. Plus, non-US, regulatory grade oncology registries to support market access and regulatory submissions.
Discover What’s Next in Insights & Evidence Generation
Partner with our world-class analysts, epidemiologists, and evidence strategists to uncover solutions to your research challenges.
Revealing the Patient Journey with Linked Claims & EHR
When it comes to patient journeys, EHRs and claims tell only half the story. Make sure you draw your insights from data that integrates the richest versions of both.
The Growing Influence of Real-World Data and Evidence
The importance of high-quality, transparent, and secure RWD to generate reliable RWEand how they drive impactful outcomes for patients and healthcare systems globally.
Our Mission is Our Promise
At TriNetX, our mission is to operate the world’s broadest federated network of real-world data in partnership with healthcare providers and apply intelligence that accelerates innovation across the healthcare ecosystem.
Access and Analyze Rich, Secure, Real-Time Data
TriNetX is a global network of healthcare organizations and life science companies, driving real-world research to accelerate the development of life-saving therapies.
From trial operations to evidence generation, we put you at the forefront of discovery.
Clinical Trial Design & Optimization
Datasets & Analytics
Non-US Oncology
Real-World Evidence Generation
Pharmacovigilance & Drug Safety
Events with TriNetX
Please complete the form below to request a meeting with the TriNetX team, and learn how you could become part of the connections improving human health across the world.
Jeffrey Brown
Chief Scientific Officer
Jeffrey Brown, PhD is an internationally recognized expert in the use of real-world data to support the evidentiary needs of regulatory agencies and medical product sponsors and an expert in the assessment of data quality of real-world data resources. Dr. Brown has more than 25 years of experience in research using real-world data, most recently as an Associate Professor in the Department of Population Medicine at Harvard Medical School and as a trusted consultant to numerous research groups and pharma companies. Dr. Brown holds a master’s degree in Economics from Tufts University and a PhD in Social Policy from Brandeis University.

Jeff Graham
Vice President, Data Solutions
Jeff Graham is a recognized expert in real-world data (RWD) strategy, product development, and healthcare analytics. With over 16 years of experience, he has led the creation of scalable data solutions that support regulatory-grade research and commercial insights across the life sciences industry.
Mr. Graham is currently Vice President of Data Solutions at TriNetX, where he leads the development of linked data products and AI/ML-enabled research tools. Previously, he led the Data Innovation department at a Fortune 15 healthcare company, driving enterprise data strategy and innovation.

K. Arnold Chan, MD, ScD, FISPE
Senior Vice-President, CSO Office
K. Arnold Chan, MD, ScD, FISPE, is an internationally recognized epidemiologist with more than 30 years of global research experience in academia and the private sector, primarily in the post-marketing evaluation of pharmaceutical agents and vaccines. He has served on the Harvard School of Public Health and National Taiwan University faculty and was Chief Scientist of the epidemiology unit of a Fortune 10 company. Dr. Chan has authored or co-authored more than 150 peer-reviewed articles on pharmacoepidemiology and clinical epidemiology and co-edited a textbook on pharmacoepidemiology and therapeutic risk management.

E. Susan Amirian, PhD
Senior Director, Research
A seasoned MD Anderson-trained epidemiologist with over 15 years of observational research experience, Dr. Amirian has previously led teams on sponsored real-world research projects at small startups and a Fortune 10 company, where she drove impactful insights from real-world data. She also led the Public Health Portfolio at the Texas Policy Lab, Rice University, focusing on innovative public health initiatives. Before this, she was an Assistant Professor in the Division of Hematology-Oncology at Baylor College of Medicine and was the Associate Director of Data Quality at the Population Sciences Biorepository. Her expertise spans epidemiology, oncology, and data quality management, contributing significantly to advancing medical research and healthcare practices.

Andreas Weber
Senior Vice-President, Oncology
Andreas brings a wealth of experience to the TriNetX team, following a distinguished 30-year career in the life sciences industry. Most recently, he served as the CEO of EvidentIQ, a leading provider of technology and data science solutions for clinical research. His career includes senior management roles at ERT/BioClinica and Oracle Health Sciences, where he built a 17-year sales and business development legacy.
As a senior executive with a proven track record in management and leadership, Andreas is known for his deep understanding of life sciences, spanning the entire industry continuum. His expertise encompasses pharmacovigilance, drug safety, regulatory affairs, and end-to-end eClinical processes, with a strong focus on business process optimization, outsourcing, and information technology.
Andreas’s career reflects a commitment to advancing the life sciences industry through strategic innovation and effective leadership, making him a valuable asset to TriNetX and a respected figure in European oncology research.

Markus Rückert, PhD
Medical Director
Markus is a seasoned biopharmaceutical expert specializing in oncology and rare diseases, boasting over 20 years of extensive experience in leadership positions across renowned organizations such as Ipsen Pharma, CSL Vifor, MorphoSys, among others. Proficient in clinical development and Medical Affairs, experimental and real-world evidence generation, Markus has successfully navigated various stages of drug development—from discovery to market launch—with a keen focus on advancing oncological and rare disease therapies for tangible patient benefits. Having achieved significant milestones in oncology and rare disease therapeutics, Markus now channels his diverse expertise towards broader pursuits in epidemiology, health service research, and the real-world impact of oncological treatments. Holding a PhD in biochemistry and pharmacology, Markus has contributed academically to esteemed institutions such as the University of Würzburg, Germany and the Karolinska Institutet, Stockholm, Sweden.

Zuzana Dostalova
Data Scientist
Zuzana is a Data Scientist at Trinetx Oncology, a wholly owned subsidiary of TriNetX, specializing in real-world data oncology research. She focuses on innovation and data quality to transform raw data into meaningful insights that support cancer research and patient care.
By leveraging data science, Zuzana addresses challenges in oncology, ensuring high standards of data accuracy and reliability. She collaborates closely with researchers, clinicians, and other data analysts to produce scientifically robust and clinically applicable findings.
Passionate about continuous learning and professional growth, Zuzana’s work aims to enhance the understanding of cancer and improve patient outcomes through informed and personalized treatments. Her efforts bridge the gap between data science and clinical practice, driving advancements in cancer research and patient care.

Julia O’Rourke, PhD, MS, MMSc
Principal Data Scientist, Research
Dr. O’Rourke has completed an NIH post-doctoral fellowship in biomedical informatics at Massachusetts General Hospital. She has served as a faculty member at Harvard Medical School, a principal investigator at the Lurie Center for Autism, and has authored and co-authored over a dozen publications on various topics. During her five-year tenure at TriNetX, Dr. O’Rourke has held roles on the engineering, data science, and research teams, most recently focusing on leading and co-leading client research projects and publishing her research utilizing TriNetX’s real-world data. Her research interests focus on using machine learning with real-world data to address various questions in oncology research.

Zuzanna Drebert
Data Scientist
Zuzanna Drebert is a data specialist with over seven years of experience working with real-world medical data. With a PhD in Experimental Cancer Research from Ghent University in Belgium, she combines her biomedical expertise with technical skills to help solve problems and drive advancements in healthcare and research.
As a Data Scientist at TriNetX, Zuzanna supports both internal and external research projects by leveraging her experience in data analysis, machine learning, data visualization, and domain knowledge. She also contributes to experiments exploring various methods for extracting data from free-text clinical notes.
Zuzanna is passionate about learning, experimenting with new ideas and techniques, and continuously improving her work to achieve meaningful outcomes.

Marley Boyd, MS
Senior Director, Analytics, Research & Data Solutions
Marley Boyd, Senior Director of Analytics at TriNetX, is a statistician with extensive experience in real-world research and expertise in multiple therapeutic areas, including oncology and chronic kidney disease. After training at Sam Houston State University, Mr. Boyd has spent ten years developing and leading analytic teams working on sponsored real-world research studies at a mid-size contract research organization and a Fortune 10 company. Mr. Boyd has authored or co-authored over 25 scientific publications. A list of his publications can be found here.
His expertise spans biostatistics, oncology, and automation of analytics, contributing extensively to advancing medical research and healthcare practices.
