BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Telerik Inc.//Sitefinity CMS 13.3//EN BEGIN:VTIMEZONE TZID:GMT Standard Time BEGIN:STANDARD DTSTART:20251002T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=2;BYMINUTE=0;BYMONTH=10 TZNAME:GMT Standard Time TZOFFSETFROM:+0100 TZOFFSETTO:+0000 END:STANDARD BEGIN:DAYLIGHT DTSTART:20250301T010000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=1;BYMINUTE=0;BYMONTH=3 TZNAME:GMT Daylight Time TZOFFSETFROM:+0000 TZOFFSETTO:+0100 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION: \;\n\n \n \n U.S. regulatory consider ations and case studies for rare diseases\n In this talk\, I wi ll present an overview of the U.S. Food and Drug Administration&rsquo\;s p olicies and practices for encouraging development of products for rare dis eases and of evaluating clinical evidence for the safety and effectiveness of such products. I&rsquo\;ll discuss study designs that may be particula rly appropriate for rare disease product development\, and address some of their statistical implications. Finally\, I&rsquo\;ll present case studie s of products that were approved for rare diseases using unusual or innova tive study designs and/or regulatory pathways.\n \n \n \n \n  \;\n  \;John Scott i s Deputy Director of the Division of Biostatistics in the FDA's Center for Biologics Evaluation and Research\, where he has also served as a statist ical reviewer for blood products and for cellular\, tissue and gene therap ies. Prior to joining the FDA in 2008\, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital\, Harvar d Medical School. He has authored or co-authored numerous articles in area s including Bayesian and adaptive clinical trial design and analysis\, dru g and vaccine safety\, data and text mining\, and benefit-risk assessment. He holds a Ph.D. in Biostatistics from the University of Pittsburgh and a n M.A. in Mathematics from Washington University in St. Louis\, and is an associate editor of the journal\, Pharmaceutical Statistics.\n \n \n\n\n\n\n \n \n Bayesian methods for the design an d interpretation of clinical trials in rare diseases\n For stud ies in rare diseases\, the sample size needed to meet a conventional frequ entist power requirement can be daunting\, even if patients are to be recr uited over several years. Rather\, the expectation of any such trial has t o be limited to the generation of an improved understanding of treatment o ptions. We propose Bayesian approaches for the conduct of rare disease tri als comparing an experimental treatment with a control when the primary en dpoint is binary or normally distributed. We describe processes which can be used to systematically elicit from clinicians opinions on treatment eff icacy in order to establish Bayesian priors for unknown model parameters. The proposed approaches are illustrated by describing applications to two Bayesian randomised controlled trials\, namely a study in childhood polyar teritis nodosa and a study in chronic recurrent multifocal osteomyelitis. Once prior distributions have been established\, consideration of the exte nt to which opinion can be changed\, even by the best feasible design\, ca n help to determine whether a small trial is worthwhile.\n &nbs p\;\n \n \n \n \n  \;\n  \;Lisa Hampson is a Lecturer in Statistics at Lancaster U niversity. Her research interests are in clinical trials\, including group sequential tests and Bayesian methods for trials in rare diseases and dos e-escalation. Her recent research has focused on developing methods for cl inical trials of new medicines for children. She holds a PhD in Statistics from the University of Bath. \;\n \n \n\n\nTo access the re cording\, please visit the Video-on-Demand Library. DTEND:20161116T153000Z DTSTAMP:20260310T005156Z DTSTART:20161116T140000Z LOCATION: SEQUENCE:0 SUMMARY:PSI Scientific Committee Webinar: Rare Diseases: Regulatory and Stu dy Design Considerations UID:RFCALITEM639087007165655293 X-ALT-DESC;FMTTYPE=text/html:

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U.S. regulatory considerations and case studies for rar e diseases
\n In this talk\, I will present an ov erview of the U.S. Food and Drug Administration&rsquo\;s policies and prac tices for encouraging development of products for rare diseases and of eva luating clinical evidence for the safety and effectiveness of such product s. I&rsquo\;ll discuss study designs that may be particularly appropriate for rare disease product development\, and address some of their statistic al implications. Finally\, I&rsquo\;ll present case studies of products th at were approved for rare diseases using unusual or innovative study desig ns and/or regulatory pathways.
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< span data-sfref="[images|OpenAccessDataProvider]eb54b7ff-3ad6-65b3-a176-ff 00001f6b97" class="sfImageWrapper">John Scott \;&nbs p\;John Scott is Deputy Director of the Division of Biostatistics in the F DA's Center for Biologics Evaluation and Research\, where he has also serv ed as a statistical reviewer for blood products and for cellular\, tissue and gene therapies. Prior to joining the FDA in 2008\, he worked in psychi atric clinical trials at the University of Pittsburgh Medical Center and d id neuroimaging research with the Neurostatistics Laboratory at McClean Ho spital\, Harvard Medical School. He has authored or co-authored numerous a rticles in areas including Bayesian and adaptive clinical trial design and analysis\, drug and vaccine safety\, data and text mining\, and benefit-r isk assessment. He holds a Ph.D. in Biostatistics from the University of P ittsburgh and an M.A. in Mathematics from Washington University in St. Lou is\, and is an associate editor of the journal\, Pharmaceutical Statistics .
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Bayesian methods for the design and interpretation of clin ical trials in rare diseases
\n For studies in ra re diseases\, the sample size needed to meet a conventional frequentist po wer requirement can be daunting\, even if patients are to be recruited ove r several years. Rather\, the expectation of any such trial has to be limi ted to the generation of an improved understanding of treatment options. W e propose Bayesian approaches for the conduct of rare disease trials compa ring an experimental treatment with a control when the primary endpoint is binary or normally distributed. We describe processes which can be used t o systematically elicit from clinicians opinions on treatment efficacy in order to establish Bayesian priors for unknown model parameters. The propo sed approaches are illustrated by describing applications to two Bayesian randomised controlled trials\, namely a study in childhood polyarteritis n odosa and a study in chronic recurrent multifocal osteomyelitis. Once prio r distributions have been established\, consideration of the extent to whi ch opinion can be changed\, even by the best feasible design\, can help to determine whether a small trial is worthwhile.
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 \;Lisa Hampson< /td>\n  \;Lisa Ha mpson is a Lecturer in Statistics at Lancaster University. Her research in terests are in clinical trials\, including group sequential tests and Baye sian methods for trials in rare diseases and dose-escalation. Her recent r esearch has focused on developing methods for clinical trials of new medic ines for children. She holds a PhD in Statistics from the University of Ba th. \;
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\nTo access the recording\, please visit the Video-on-Demand Library.
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