Advanced Analytics Using RWD Can Mitigate Risks in AD Drug Development, Reimbursement and Utilization

Alzheimer’s Disease (AD) is a progressive degenerative brain disease causing behavioral disturbances as well as irreversible impairment in cognitive abilities and daily functioning eventually leading to institutionalization and death. Traditionally, the stages of AD included Mild Cognitive Impairment (MCI) and dementia. In the last decade, new research criteria have also distinguished a pre-clinical phase in which people with AD pathology or risk factors do not experience any (or only very minor) symptoms. All drug development efforts these days target these early AD stages, which raises specific requirements and challenges for drug development, reimbursement, and clinical utilization.

This webinar will start with a short overview of these challenges based on the recent literature findings and the ongoing discussion in the field. We will explain how these challenges can be addressed using advanced analytics. Special focus will be on the statistical modeling of AD progression and treatment effects using real-world data. Then, we will present a recently published case study where we developed a longitudinal joint model which used decline in cognition to predict future MCI or dementia due to AD in cognitively normal people. We will also reflect on the current availability and usability of RWD for modeling. The presentation will finish with an overview of the ethical considerations and social implications connected with using advanced analytics in AD research, drug development, payers/health technology assessment (HTA) evaluations, and clinical practice.

Speaker(s): Billy Amzal, Zuzanna Angehrn, Luyuan Qi
Date: Thursday, June 6, 2019
Time: 11:00 am ET
Duration: 1 hour

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