Predicting Non-Adherence and Dropout Risks: Enhance Clinical Trial Efficiency and Support Patient Engagement

Life Sciences, Patient Recruitment & Retention, Patient Safety,
  • Wednesday, June 21, 2023

Poor patient adherence in clinical research and medical practice continues to be a widespread challenge that impacts drug development and healthcare costs but more importantly, introduces risk for patient safety and long-term well-being.

In clinical research, the objective is to assess the safety and efficacy of a new treatment under investigation. The lack of medication adherence (or over-estimation of adherence) might have broad consequences on both of these objectives, leading to inaccurate risk/benefit ratios. In addition, it has been common practice to compensate for patient dropouts by recruiting extra sites and patients, and depending on the therapeutic focus, this may result in 20-30 percent more patients and costs.

Encouraging patient adherence and retention throughout the clinical trial and offering strategies to proactively manage adherence based on patient profiles will help personalize the patient’s trial journey and improve the quality and effectiveness of the clinical trial conduct.

In this webinar, the featured speakers will present a newly released solution, Compl-AI. Compl-AI predicts the risk of lack of patient adherence to treatment/dropout from the study. It captures patients’ psychology and specific characteristics to provide access to a, so far, unreached set of information. This intuitive, easy-to-use interface may personalize patient engagement strategies deployed by sponsors and CROs as well as adherence management solutions.

Register to learn how this innovative prediction may improve patient’s journey and clinical study conduct to complement and significantly enhance current patient adherence, patient retention and engagement strategies.


Dominique Demolle, Cognivia

Dominique Demolle, PhD, CEO, Cognivia

Dr. Dominique Demolle is the Chief Executive Officer at Cognivia. Dominique holds a PhD in biochemistry from the University of Brussels. She has held various leadership positions at Eli Lilly and Company and has extensive knowledge in global early phase drug development. Dominique consulted with pharmas and biotechs before founding Cognivia. Dominique has contributed to the clinical development of dozens of drugs and several launches. Most recently, she has been recognized as one of the 2022’s Most Inspiring People in the life sciences for the annual PharmaVoice 100 awards.

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Chantal Gossuin, Cognivia

Chantal Gossuin, COO, Cognivia

Chantal Gossuin has worked as the Chief Operating Officer at Cognivia since its inception in 2013. Ms. Gossuin holds a master’s degree in industrial pharmacy from the University of Brussels. Ms. Gossuin began her industrial career in the Quality Control Department at Eli Lilly and Company, Fegersheim. Thereafter, she held positions with increasing responsibility at Lilly in the Clinical Trial Material Department. She then moved to UCB as Project Manager in the Drug Product Management and Industrialization Department. In 2008 she joined Aepodia, a consultancy clinical research organization.

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Who Should Attend?

Companies and organizations interested in patient engagement strategies, including adherence to treatment:

  • Pharmaceutical/Biotechnology companies, CROs
  • Tech Companies/Service Providers
  • Health Insurers
  • CEO, CSO, CMO, CDO, COO VP, SVP, EVP, Sr. Director, Director, etc. of: Clinical Development; Clinical Science; Clinical Operations; Regulatory; Clinical Project Management; Business Development; Clinical Scientists
  • Companies working in patient adherence and engagement management

What You Will Learn

Attendees will gain insights into:

  • How accounting for individual patient psychology, perceptions and beliefs can mitigate the risk of non-adherence to treatment and dropout
  • The advantages of integrating this approach into overall patient engagement strategies

Xtalks Partner


Cognivia is the first and only company to combine quantification of patient psychology with artificial intelligence (AI)/machine learning (ML) to improve measurement of therapeutic efficacy in clinical trials – and beyond. Cognivia technologies predict patient behavior and treatment response in clinical trials using predictive ML powered algorithms based on a quantitative understanding of patient psychological traits, expectations and beliefs collected via our own and specific questionnaires developed toward that objective. Cognivia aims at harnessing “the power of the mind” and quantifying this unique phenomenon to improve clinical trial success rates, de-risk drug development and ultimately improve healthcare.

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