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Jurisdictional Decision Support Tool Mark Hamblin Carnegie Mellon University.

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Presentation on theme: "Jurisdictional Decision Support Tool Mark Hamblin Carnegie Mellon University."— Presentation transcript:

1 Jurisdictional Decision Support Tool Mark Hamblin Carnegie Mellon University

2 Public Policy Project Course Tissue Engineering Navigating the FDA approval process Social and ethical issues Financial and marketing issues Jurisdictional determination Review of current process Review of inter-center agreements Creation of web-based decision support tool

3 Current Jurisdiction Process Intercenter Agreements provide rules for classifying combination products, but are too focused in scope Only cover existing technologies Intercenter Agreements may not apply to new technologies Jurisdiction determination is then based only on the “primary mode of action”, of which no clear definition exists Some subjectivity is necessary to reach a decision, yielding a lack of consistency, predictability, and transparency

4 Purpose of Decision Support Tool Create a rule based system that classifies medical products based on product characteristics Incorporate previously established jurisdiction rules from Intercenter Agreements Add additional criteria for determining jurisdiction to fill in the gaps Allow for easy adaptability and variability to accommodate current FDA regulatory requirements and trends Make the tool widely available (web-based) to allow for greater transparency and predictability in jurisdiction determination process

5 Details of Decision Support Tool Each product has 3 “pools of points”, one each for each of the three FDA regulatory centers List of 88 yes/no questions pertaining to product characteristics If “yes” for a question, X points go to pool 1, Y points go to pool 2, Z points go to pool 3 Each question has a weight from 0 to 1 based on how important that question is in the overall classification scheme Points for each pool get scaled based on the weight for that question Product gets classified into the respective center based on the “pool” that has the most points Easy to change classification scheme by changing respective weights of questions and point distributions

6 Creating Model Inputs Extracted 67 questions from the rules in the Intercenter Agreements Conducted a survey of tissue engineering experts Sent to 205 members of the Pittsburgh Tissue Engineering Initiative Proposed 21 different product characteristics Surveyed how the experts thought the presence of these characteristics should affect classification Created 21 questions for the model based on these product characteristics Assigned points for the model based on the survey responses Also gathered responses regarding experiences and opinions of FDA jurisdictional decision process and approval process

7 How It Helps Intercenter Agreements form a precedent based decision model by looking only at specific characteristics of previously developed products Precedent based decision models typically are not optimal for classifying new types of products Too subjective Proposed decision support tool is a rule based model that looks at a product’s general characteristics More applicable to future products and technology Widely accessible rule based decision model will provide a consistent, predictable, and transparent method for classification problems

8 Analysis of the FDA Approval Process Conducted in-depth analysis of the approval process Created detailed flow diagrams of the process Surveyed and interviewed several firms on their perspective Developed web-based tool through analysis of the process and interview feedback and developed the following guidelines Firms would benefit from graphical view of entire process Easier quick access to FDA contact information Online form submission to the FDA is highly requested to expedite approval steps More details on these interviews and the web tool available in the final project report

9 Final Presentation and Report Final presentation to be given in Washington DC on Wed. December 4, 2002 Members of review panel include senior management from FDA, academic and industry researchers, other stakeholders Publication of written report expected in January 2003 Contact for details on final presentation or written

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