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© Guidant 2004 Medical Device versus Drug Similarities and Differences Jeng Mah, David Breiter Guidant Corporation FDA Industry Workshop September 16, 2005
© Guidant 2004 Workshop 2005 2 Device vs. Drug - physical DeviceDrug
© Guidant 2004 Workshop 2005 3 Device vs. Drug - functional Device Actions Mechanical Physical Dynamic Adaptive User dependent Device Effects Local Direct/immediate Measurable Reversible Drug Actions Chemical Physiological Fixed Not adaptive Simple Drug Effects Systemic Indirect/deferred Difficult to measure irreversible
© Guidant 2004 Workshop 2005 4 Device vs. Drug - statistical Device Studies May perform multiple adaptive functions (bundled features) Extensive & informative bench and acute tests Non-blinded, non- placebo pivotal studies Automation & decision making Subject specific optimal programming User interface/skill affects/determines out- comes Real time data collection generates lots of data Drug Studies One drug one desired effect (usually), or deal with drug interactions Phase I, II studies serve different purposes Active control, blinded pivotal studies Subjects receive identi- cal, fixed treatments Data collection focuses on final, pragmatic outcomes
© Guidant 2004 Workshop 2005 5 Device vs. Drug - statistical Device Studies Difficult to administer FDA requirement: single pivotal trial Reliability and quality control issues Drug Studies Easy to administer FDA requirement: two pivotal trials Reliability and quality control issues are less prominent
© Guidant 2004 Workshop 2005 6 To test an intelligent device with a new feature: the new feature include one programmable parameter; physician needs to find the optimal setting of each patient based on the responses of an acute test. This parameter can be modified anytime. Questions: how do we model a true device effect adjusted for the physician, parameter, and patient? What is the treatment we are interested in? Feature? Parameter? Programmability? Utility? What is the experimental unit? When do we need to do new studies? An Example
Workshop C – Evaluation Rod Taylor Complex Interventions Research Framework Masterclass 2010.
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天 津 医 科 大 学天 津 医 科 大 学 Clinical trail. 天 津 医 科 大 学天 津 医 科 大 学 1.Historical Background 1537: Treatment of battle wounds: 1741: Treatment of Scurvy 1948:
Clinical Trials Importance in future therapies. What are the Requirements to Produce New Drugs? Drug must work significantly better than a control treatment.
Clinical Trials Medical Interventions
Impact of Dose Selection Strategies on the Probability of Success in the Phase III Zoran Antonijevic Senior Director Strategic Development, Biostatistics.
Statistics between Inductive Logic and Empirical Science Jan Sprenger University of Bonn Tilburg Center for Logic and Philosophy of Science 3 rd PROGIC.
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