Medical statistics

Bayesian Statistics at the FDA: The Pioneering Experience with Medical Devices

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• published: 21 Jun 2016
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Don't hesitate to comment below if you have any questions or additional phrases Bayesian Statistics at the FDA: The Pioneering Experience with Medical Devices Greg Campbell, Ph.D. Director, Division of Biostatistics Center for Devices and Radiological Health Food and Drug Administration Florida State University Dept. of Statistics 50th Anniv. April 17, 2009 ,Outline What are devices? The nature of medical devices and their regulation Bayesian statistics in medical device trials Adaptive trials ,Center for Drug Eval. & Research Center for Biologic Eval. & Research Center for Devices & Rad. Health Food and Drug Administration Center for Food Safety & Nuitrition Center for Veterinary Medicine Nat’l Center for Toxicol. Research ,What are Medical Devices? Definition by exclusion: any medical item for use in humans that is not a drug nor a biological product PRK lasers pacemakers defibrillators spinal fixation devices glucometers artificial heartshearing aids latex gloves artificial skinsoftware, etc intraocular lenses MRI machines breast implants surgical instruments thermometers (drug-coated) stents home kit for AIDS diagnostic test kits bone densitometers artificial hips ,What is a Drug-Eluting Stent? Example:Cordis’ Cypher™ Sirolimus-Eluting Coronary Stent Components Stent Platform & Delivery System Carrier(s) Drug ,Meet Yorick ,Devices Not Drugs -- The Differences Different Alphabet SoupIDE -- Investigational Device ExemptionPMA -- PreMarket Approval510(k) -- Substantial Equivalence---not bioequivalence A Single Confirmatory Trial (not 2). A ‘Sham’ Control Trial may not be possible Masking (blinding) may be impossible for patients, health care professionals, investigators Usually don’t use Phase I, IIA, IIB, III, IV ,Devices Not Drugs -- The Differences (Cont.) Bench/Mechanical Testing not PK/PD Mechanism of Action often well understood Effect tends to be localized rather than systemic, physical not pharmacokinetic Pre-clinical Animal Studies (not for toxicity) Number & Size of Device Companies About 15,000 registered firms Median device company size--under 50 employees (Many are new start-up companies.) Implants (skill dependent; learning curve) ,The Nature of Medical Device Studies Whereas drugs are discovered, devices evolve; they are constantly being “improved”; life length of a device is 1-2 years. Rapidly changing technology ,Why Did CDRH Launch the Bayesian Effort? Devices often have a great deal of prior information. The mechanism of action is physical (not pharmacokinetic or pharmacodynamic) and local (not systemic) Devices usually evolve in small steps whereas drugs are discovered. Computationally feasible due to the gigantic progress in computing hardware and algorithms The possibility of bringing good technology to the market in a timely manner by arriving at the same decision sooner or with less current data was of great appeal to the device industry. ,Early Decisions We Made Restrict to data-based prior information. A subjective approach is fraught with danger. Companies need access to good prior information to make it worth their risk. FDA needs to work with the companies to reach an agreement on the validity of any prior information. Need to bring the industry and FDA review staff up to speed New decision-rules for clinical study success ,Important Lessons Learned Early Bayesian trials need to be prospectively designed. (It is almost never a good idea to switch from frequentist to Bayesian or vice versa.) Companies need to meet early and often with CDRH. The prior information needs to be identified in advance as well as be agreed upon and legal. The control group cannot be used a source of prior information for the new device, especially if the objective is to show the new device is non-inferior. ,Important Lessons Learned Early (cont.) Both the label and the Summary of Safety and Effectiveness (SS&E) of the device need to change. A successful company gen