speaker-info

Telba Irony

Deputy Director, Office of Biostatistics and Epidemiology

Telba Irony is Deputy Director of the Office of Biostatistics and Epidemiology at the Center for Biologics at the FDA. She works on the Science of Patient Input that includes patient preference information and patient reported outcomes. She also works on Bayesian innovative trial designs, decision analysis, and benefit-risk assessments.

Previously, Telba worked at the Center for Devices at FDA (CDRH) and was instrumental in writing several guidance documents including “Use of Bayesian Statistics in Medical Device Clinical Trials,” “Factors to Consider when Making Benefit – Risk Determinations for Medical Devices,” and “Submission of Patient Preference Information for Benefit-Risk determinations.” She was the leader of the Decision Analysis initiative at CDRH, that involved Bayesian statistics, benefit-risk determinations and patient preference studies.

In 2014, Telba received the FDA Excellence in Analytical Science Achievement Award for spearheading innovative regulatory science studies culminating in the release of novel guidance documents, supporting complex policy decision making and changing the submission review paradigm.
Telba received her PhD from the University of California, Berkeley and joined the FDA to implement the use of Bayesian statistics in medical device clinical trials. She is a fellow of the American Statistical Association and an elected member of the International Statistical Institute.

My Sessions

Life Sciences Panel: Decision Analysis and Medical Benefit-Risk Decision Making with the FDA

Grays Peak

Pharmaceutical industry and regulators use decision analysis within their organizations to support complex benefit risk decision-making.  Systematic use of quantitative benefit risk assessment is possible in future interactions between these stakeholders.  Regulators are exploring ways in which quantitative decision analysis approaches, methods and tools can be used to inform benefit risk assessment and decision making […]

Life Sciences
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