The AI Revolution in Clinical Research: Next-Gen Precision Patient Matching

Life Sciences, Clinical Trials, Patient Recruitment & Retention,
  • Thursday, March 14, 2024

The convergence of artificial intelligence (AI) and electronic medical record (EMR) data has brought unprecedented precision and speed to finding patients for clinical trials, real-world evidence studies and even treatments in a clinical setting. In this webinar, the featured speakers will explore innovative ways in which life sciences companies are using AI to find patients more precisely, prioritize patients for research based on therapy-specific criteria and collaborate with sites to quickly access EMR data.

Traditionally, finding the right patients for a trial or research project is done by searching EMRs for structured codes or performing keyword lookups. Unfortunately, the results are imprecise and the process is time-consuming, requiring manual chart review and validation. Finding patients that match criteria without an associated code or with inconsistent documentation adds further complexity (e.g., ‘triple negative breast cancer’ can appear in the text as TNBC, triple negative BC, breast tumor – TN, and so on). Additionally, it can take over a year for life science companies to get access to EMR data to develop novel patient-matching algorithms for their research. Using AI to mine deep, real-time EMR data, including structured and unstructured information, such as clinician notes, omics, labs and pathology reports, can quickly and precisely find all clinically eligible patients for a clinical trial or research study.

In this webinar, the speakers will share their experience leveraging AI to identify patients with chronic obstructive pulmonary disease (COPD) exacerbations in the clinical setting, as well as how they identified and prioritized patients for a heart device clinical trial.

Register for this webinar today to gain insights into the benefits of AI-driven patient matching as well as mining of deep, real-time EMR data.

Speakers

Kristin Wrobleski, PhD, Senior Director, GSK

Dr. Kristin Kahle Wrobleski is the therapeutic area lead for the anti-infectives and respiratory portfolio at GSK in the Value Evidence and Outcomes organization. She leads a team of scientists accountable for the strategic design and execution of value-focused evidence generation plans focused on the US market. Kristin previously worked at Eli Lilly and AbbVie in global value evidence roles and is committed to finding new and innovative ways to improve patient outcomes. While in a prior role at ConvergeHEALTH by Deloitte, she lent her RWE and clinical trial expertise to the development and deployment of a suite of life sciences-focused software products.

Kristin holds a PhD in clinical psychology from the University of Kansas. She completed her clinical internship at the West Los Angeles VA hospital and her post-doctoral fellowship at the Institute for Brain Aging and Dementia, University of California – Irvine.

Message Presenter
Daniel Fort, Ochsner Health

Daniel Fort, PhD, MPH, Assoc Professor and Manager Clinical Informatics, Ochsner Center for Outcomes Research, Ochsner Health

Dan Fort operates as the Biomedical Research Informatics Specialist for the Center for Applied Health Services Research and the Ochsner Health System. His PhD was in Biomedical Informatics, specializing in clinical research informatics, particularly data modeling, clinical phenotyping algorithms and biases within electronic clinical data. He also has degrees in Health Systems Management and Biochemistry. Dan joined Ochsner after three years at Northwestern University working within their clinical and translational science unit.

Message Presenter
Dan Housman, Graticule

Dan Housman, Chief Technology Officer, Graticule

Dan Housman is a thought leader and industry veteran in the areas of real-world data, interoperability and clinical analytics. Dan is a co-founder and CTO of Graticule, an on-demand, advanced real-world data and advisory provider serving life science companies and health systems. Throughout his career in clinical informatics, Dan has championed scalable open systems, including the distribution of the i2b2 cohort selection system, the creation of the tranSMART bioinformatics framework and the adoption of OMOP and FHIR. Previously, Dan founded Recombinant Data, a clinical data warehousing company serving health systems and pharmaceutical companies, which was acquired by Deloitte in 2012. While at Deloitte, Dan served as CTO of their healthcare analytics business, leading strategy for the ConvergeHEALTH portfolio of products. He also consulted with senior leaders at life sciences companies on innovation regarding AI in R&D and migration of patient data systems to cloud infrastructure such as Amazon Web Services.

Message Presenter
Wout Brusselaers, Deep 6 AI

(Moderator) Wout Brusselaers, CEO, Deep 6 AI

Wout Brusselaers is the founder and CEO of Deep 6 AI, a precision research company that empowers healthcare organizations and life sciences companies to de-risk and accelerate clinical research. Wout founded Deep 6 AI in 2016 to improve clinical trial outcomes through AI-driven software that mines electronic medical record (EMR) data to precision match patients to trials. Wout leverages his entrepreneurial experience and deep operational expertise to help address the industry’s patient recruitment and retention challenges. Wout holds a Masters in International Economics from the University College Dublin, an MFA in Film Production from Chapman University, and a Licentiate degree in Economics from Vrije Universiteit Brussel.

Message Presenter

Who Should Attend?

This webinar will appeal to sponsors and CROs working within:

  • Clinical operations
  • Trial management
  • Site engagement
  • Data and analytics
  • Innovation
  • TA leads
  • HEOR
  • RWE
  • RWD

What You Will Learn

In this webinar, the attendees will learn how to:

  • Accelerate turnaround times for accessing EMR data from the traditional nine to 18 months to under two months
  • Precisely find patients meeting criteria for which there are no specific codes and inconsistent documentation
  • Prioritize patients for a study using project-specific criteria

Xtalks Partner

Deep 6 AI

Deep 6 AI is the leading precision research platform, enabling healthcare organizations and life sciences companies to improve study design, accelerate recruitment, and generate real-world evidence with unprecedented speed and precision. Its AI-powered software mines structured and unstructured electronic medical record data to precisely match patients to clinical trials in real time across its ecosystem of 1K+ research sites. Visit deep6.ai to learn more.

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