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TriNetX Summit Recordings

TriNetX’s end user conference took place on October 17-19, 2022 at the InterContinental hotel in Boston. The two-day, invitation-only event brought the global community of TriNetX members together to network, share best practices, participate in training, highlight research discoveries and guide the company’s product roadmap including design, enhancements and development timelines.

Watch sessions and experience the innovation and excitement of the 2022 TriNetX Summit.

Real-World Evidence Generation: A Model Process

When it comes to bringing better treatments to patients, speed matters. Real-world evidence generation needs to keep pace. Historically, it hasn’t. Data sourcing, licensing, integration, staging, and analysis have remained fragmented processes prone to delay.

Recently, we hosted a webinar diagnosing the problems with real-world evidence generation as it’s conducted today. Featuring TriNetX Chief Scientific Officer and FDA Sentinel System co-architect Jeff Brown, PhD, the webinar shows how LUCID connects the industry’s largest federated network of EHR and claims data to a high-performance data science environment.

Going Beyond the Limits of Legacy Pharmacovigilance with Real-World Data

The revolution in drug safety data is underway. The advent of RWD, together with technologies to aggregate, standardize, and analyze it, have turned Pharmacovigilance (PV) specialists into evidence generation leaders.

Join us on September 13 to see how TriNetX is supporting the forefront of pharmacovigilance with an unmatched, panoramic view of real-word, global patient data. Starting from our GVP-IX compliant platform for automated signal detection and management, we’ll follow a path from simple adverse event disproportionality to the evidence for drug attributability. Along the way, we’ll show you the tools and data that speed the time to resolution while enriching the possibilities for analysis, thus unlocking the full power of drug safety data from both internal and disparate data sources.

Don’t wait for the future of pharmacovigilance, be a part of it.

Follow the Patient: Prospective Monitoring with Real-World Data

What if you could combine the richness and volume of real-world data with the objectivity of prospective monitoring? Now you can. By tagging a cohort in TriNetX for active surveillance, you can “enroll” de-identified patients from around the world into a virtual study – in days, if not immediately – then monitor new data for those patients as it arrives. Follow the Patient lets you:

  • conduct your own prospective cohort study, at a bare fraction of the cost and operational burden,
  • add a prospective support arm to your interventional trial, with no patient consent required,
  • capture outcomes from the experimental and control arms of your trial well beyond the last visit, by tagging study participants who consent to long-term monitoring.

Spend an hour with real-world data experts from TriNetX on April 12 and learn how Follow the Patient can help you generate better evidence for decision-making, publication, and regulatory submission.

Demanding Depth from Your Global Real-World Cancer Data

No two cancers are completely alike. Differences in primary site, histology, stage, biomarkers, and more all factor into treatment planning. This understanding drives today’s cancer care, bench research, and trials. Are we demanding the same level of depth from our real-world data?

Join us on April 5 to learn how to better evaluate your potential sources of real-world oncology data. Our experts will discuss the importance of data elements that span cancer type, patient biomarkers and history, treatment, and outcome. You’ll learn why U.S. data alone is not always enough, why it’s critical to draw on cancer registries at both academic and community hospitals, and how getting a clear picture of medical history before and after the cancer diagnosis is essential to moving personalized care forward. Finally, we’ll present our solutions for delivering both structured and curated, unstructured data through datasets  and a 100+ hospital network you can query on demand.

From Detection to Action: Applying Your Model to Real World Data from TriNetX

From simple scoring formulas to regressions trained with machine learning, data models help us detect patients who may benefit from close monitoring, or who might qualify for a clinical trial. See the solutions we’ve developed to help researchers move from “detection to action” more efficiently over our global research networks.

Improving Access to Clinical Trials for Underrepresented Patient Populations Using Real-World Data and TriNetX’s Diversity Lens

Evaluate the impact of eligibility criteria on your trial’s enrollment of underrepresented patient populations. With these results, study teams can better adjust criteria and seek out partner organizations caring for the patients who qualify for their study.

Publishing with TriNetX: Guidelines, Best Practices, and a Real-World Example

Spend time with two experienced members of the TriNetX team and a recent author from Penn State College of Medicine to learn how to maximize your chances for successful publication at every step along the journey, from query design to corresponding with journal editors.

Closing Gaps in Patient Diversity Within Clinical Trials Using Real-World Data

Learn how to use real-world data on the TriNetX platform to explore patient diversity, identify gaps, and attain guidance to recommend and improve diversity in clinical trials and investigator-initiated studies.

Tokenizing and integrating patient data

Revealing the Patient Journey with Linked Claims and EHR

When it comes to patient journeys, EHR and claims each tell only half the story. Make sure you draw your insights from data that integrates the richest versions of each.

Introducing the Japan Claims Network

Trials that include patients in Japan have an advantage when it comes to regulatory approval in that country. But approval requires promising results from a well-executed study. Start the process the right way by understanding Japan’s patient population, designing a feasible study, and selecting the right trial sites.