Pharmaceutical
Here you can find some of the research conducted around Pharmaceuticals. Some of these topics include: pharmacovigilance, A.D.R.s, and more.
Medical Device
Here you can find some of the research that has been conducted during one of the courses we offer around Medical Device Technology.
Digital Transformation
Explore research on Digital Transformation from across Innopharma.
Featured Research
“Staying Ahead in Patient Safety and Compliance: Assessing the awareness of Regulatory Requirements in an Irish Medical Devices Distributor” by Cathy Tyndall
Safety is paramount in the medical device industry. This study examined the awareness and perception of Medical Device Regulation (MDR) within an Irish medical distributor, aiming to improve patient safety. Using a mixed-method approach, it included 74 surveys and four interviews with managers and employees. The findings revealed significant awareness and understanding of MDR, particularly regarding adverse event reporting and CE marking. However, the perceived importance of MDR varied across roles, indicating a need for tailored training and communication. Both employees and management viewed MDR positively, recognizing its commercial benefits. Recommendations for future research include comparative studies on non-managerial roles, longitudinal studies on training effectiveness, and assessments of MDR awareness in the manufacturing sector and among healthcare professionals. Cathy’s research underscores the importance of positive organizational culture and customized training for regulatory compliance and patient safety
“The Impact of AI (Machine Learning and Automation) on Biopharmaceutical Manufacturing Industry” by Ruchi Sayal
This study investigates the transformative impact of artificial intelligence (AI), machine learning (ML), and automation on the biopharmaceutical manufacturing industry. By analyzing extensive literature and survey data, the research highlights how these technologies tackle challenges like data quality and complex biological systems, improve regulatory compliance, and enhance manufacturing efficiency. It identifies trends driving AI adoption, such as the need for process optimization, advancements in drug discovery, and better quality control. The study shows AI’s disruption of traditional manufacturing models through real-time issue identification, enhanced quality control, and productivity boosts. Innovations like personalized medication, AI-powered robotics, and AI-assisted drug discovery underscore AI’s transformative potential. The research concludes that AI adoption is rapidly advancing, driven by its ability to enhance efficiency, innovation, and competitiveness, and offers valuable insights for strategic decision-making and responsible integration of AI in biopharmaceutical manufacturing.
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