Development of an ISO 13485 AND FDA QSR Compliant Quality System for an Academic R&D Group: From Concept to Certification
Bibliographic record
Abstract
The British Columbia Institute of Technology’s (BCIT) Health Technology Research Group (HTRG) is a team of multidisciplinary researchers that provides medical device development and evaluation services to clients from medical device companies, health care organizations, and academia. Researchers include biomedical engineers, biomechanics and anthropology scientists, plastics, mechanical, electrical, robotics/automation technologists, trades researchers, and industrial designers. In 2000 the HTRG embarked on the development of a quality system that complied with the design and risk management requirements of the U.S. Food and Drug Administration (FDA) Design Controls, Health Canada’s Canadian Medical Device Conformity Assessment System (CMDCAS), and the ISO 13485 Medical devices—Quality management systems—Requirements for regulatory purposes (ISO 13485). An initial system was developed and launched in 2002. In 2005 we further developed the system to be fully compliant with all requirements of ISO 13485 and obtained certification of the system in 2007. The BCIT HTRG is currently the only ISO 13485 certified academic medical device research group in Canada. The benefits of the quality system for industry clients, students, and the academic research team are discussed as well as the challenges faced in implementing a quality system in an academic research setting. The HTRG has worked with a number of multinational and international companies and would not have been able to attract these clients without operating under a certified system. Our research team is able to shorten the development time from concept to commercialization as prototypes that are developed under a certified quality system can be evaluated in surgical settings. The research staff has been able to access new research funding in part due to the quality system. The major benefit to BCIT’s biomedical and other engineering students is hands-on experience with a working quality system prior to graduation. The challenges associated with introduction and acceptance of a quality system in an academic setting are also discussed along with strategies to increase acceptance of the system. Challenges include overcoming resistance from researchers that perceive quality systems as a constraint on their creativity and as a new administrative burden, managing the costs associated with developing and maintaining a certified quality system, and interfacing with outside departments in an academic environment. Strategies for overcoming these challenges include involving all researchers in the initial development of a system and creating an efficient electronic system that is easily accessed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.073 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".