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Advanced Analytics Using RWD Mitigates Risks in AD Drug Development & Reimbursement
Thu, June 06th
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 started with a short overview of these challenges based on the recent literature findings and the ongoing discussion in the field. We explained how these challenges can be addressed using advanced analytics. Special focus was on the statistical modeling of AD progression and treatment effects using real-world data. Then, we presented 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 also reflected on the current availability and usability of RWD for modeling. The presentation finished 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.


Billy Amzal

Billy Amzal graduated from Ecole Polytechnique, from AgroParisTech, and holds a PhD in Decision Mathematics from Paris-Dauphine University, which was awarded by the International Society of Bayesian Analysis and by the International Biometrics Society. Over the past 20+ years, Billy has developed quantitative methodologies to inform and support strategic decision making in healthcare. Prior to joining Certara, Billy led the model-based drug development initiative at Novartis Pharma. Subsequently, he developed the methodology department at the European Food Safety Authority. Billy was also Head of the Data Center at the NIH-sponsored Program for HIV Prevention and Treatment in Thailand. Billy is now Senior VP at Certara, acts as statistical expert for public Health Authorities (EFSA, ANSES, WHO), and teaches pharmacoeconomics at CNAM university in Paris.

Zuzanna Angehrn

Zuzanna is a consultant with several years of hands-on experience in data analytical work and statistical modeling. Her current focus is on disease progression modeling and bridging between RCT efficacy and RW effectiveness, as well as on precision dosing initiatives. Zuzanna holds a PhD in Sociology and Public Health from the Jagiellonian University in Poland as well as a BS in Computer Science and Econometrics from the University of Economy in Cracow, Poland. She was a Visiting Fellow at the School of Public Health at the University of Washington, Seattle, USA and in The Swiss Tropical and Public Health Institute, Basel, Switzerland.

Luyuan Qi

Luyuan is an applied mathematician with 5+ years of experience in diverse modeling projects in Asia, America, and Europe. Her skills cover mathematical modeling, statistical modeling, multi-agent system modeling, machine learning, and optimization / control design. She holds a PhD in applied mathematics from Northwestern Polytechnical University, and was a research assistant in Royal Institute of Technology (KTH) in Sweden. Before joining Certara as a modeler, Luyuan led a European project on data-driven modeling of infectious disease in the French National Institute of Agricultural Research (INRA).

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