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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
Clinical Trials Medical Interventions
Introduction to Biostatistics, Harvard Extension School, Fall, 2005 © Scott Evans, Ph.D.1 Sample Size and Power Considerations.
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Gatekeeping Testing Strategies in Clinical Trials Alex Dmitrienko, Ph.D. Eli Lilly and Company FDA/Industry Statistics Workshop September 2004.
Experiments Part 3. The purpose of the design is to rule out these alternative causes, leaving only the actual factor that is the real cause.
EVIDENCE BASED MEDICINE Health economics Ross Lawrenson.
Green Tea and Cancer. Methotrexate is known to slow cancer growth in some patients Many useful drugs come from plant sources Epidemiological studies.
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Levels of Evidence Dr Chetan Khatri Steering Committee, STARSurg.
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Impact of Dose Selection Strategies on the Probability of Success in the Phase III Zoran Antonijevic Senior Director Strategic Development, Biostatistics.
A Simple Method for Evaluating the Clinical Literature “PP-ICONS” approach Based on Robert J. Flaherty - Family Practice Management – 5/2004.
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1 FDA Industry Workshop Statistics in the FDA & Industry The Future David L DeMets, PhD Department of Biostatistics & Medical Informatics University of.
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.
What is a Clinical Trial (alpha version) John M. Harris Jr., MD President Medical Directions, Inc.
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Investigational Drugs in the hospital. + What is Investigational Drug? Investigational or experimental drugs are new drugs that have not yet been approved.
Purpose of Clinical Trials Assess safety and efficacy of Experimental treatments New combinations of drugs New approaches to surgery or radiation therapies.
PRAGMATIC Study Designs: Elderly Cancer Trials
Federal Institute for Drugs and Medical Devices The BfArM is a Federal Institute within the portfolio of the Federal Ministry of Health (BMG) The use of.
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Analysis by design Statistics is involved in the analysis of data generated from an experiment. It is essential to spend time and effort in advance to.
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