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.
TORONTO (PRWEB)
June 07, 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.
Join experts from Cognivia, Dominique Demolle, PhD, CEO; and Chantal Gossuin, COO, for the live webinar on Wednesday, June 21, 2023, at 10am EDT (4pm CEST/EU-Central).
For more information, or to register for this event, visit Predicting Non-Adherence and Dropout Risks: Enhance Clinical Trial Efficiency and Support Patient Engagement.
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Contact:
Vera Kovacevic
Tel: +1 (416) 977-6555 x371
Email: vkovacevic@xtalks.com
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