Improving patient outcomes with regenerative medicine: How the Regenerative Medicine Manufacturing Society plans to move the needle forward in cell manufacturing, standards, 3D bioprinting, artificial intelligence-enabled automation, education, and training

Hunsberger, Joshua; Simon, Carl G.; Zylberberg, Claudia; Ramamoorthy, Preveen; Tubon, Thomas C.; Bedi, Robinder P.; Gielen, Kurt; Hansen, Caitlin E.; Fischer, Lynn; Johnson, Jed; Baraniak, Priya R.; Mahdavi, Behzad; Pereira, Taciana; Hadjisavas, Michael; Eaker, Shannon; Miller, Cameron

doi:10.1002/sctm.19-0389

Cited by 16 publications

(6 citation statements)

References 22 publications

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“…Related scholars have proposed that the application of artificial intelligence in the field of education will have an impact on teachers' teaching skills, educational thoughts, educational strategies and teaching methods, and professional qualities and affect the professional development of teachers [15]. Researchers analyzed the opportunities for teachers' professional development in the era of artificial intelligence and proposed a new mentorship education model; precision education teaching methods and ubiquitous learning teaching methods all provide new opportunities for teachers' professional development [16]. Relevant scholars have proposed that the application of artificial intelligence in teaching can liberate teachers and truly teach students in accordance with their aptitude [17].…”

Section: Related Workmentioning

confidence: 99%

Educational Information System Optimization for Artificial Intelligence Teaching Strategies

2021

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Under the background of the information age, scientific research and engineering practice have developed vigorously, resulting in many complex optimization problems that are difficult to solve. How to design more effective optimization methods has become the focus of urgent solutions in many academic fields. Under the guidance of such demand, intelligent optimization algorithms have emerged. This article analyzes and optimizes the modern artificial intelligence teaching information system in detail. On the basis of determining the network architecture, a detailed demand analysis was carried out, and the overall structure optimization of the network was given; the business process and data flow of the main modules of the website (resource center module and collaborative learning module) were optimized. In order to further enhance the local search ability of the algorithm, a multiclass interactive optimization algorithm is proposed in combination with the Euclidean distance-based clustering method, which changes the teaching mode from “one-person teaching” to “multiperson teaching.” This clustering method has lower complexity and is beneficial to enhance the utilization of neighborhood information. At the same time, in order to enhance the diversity of the population and strengthen the connection between the subgroups, after the teaching phase, the worst students in each subgroup are allowed to learn from the best teachers of the population, and after the learning phase, individuals in a random subgroup are allowed to learn from other subgroups. The algorithm was tested in the experimental environment of unconstrained, constrained, and an engineering problem. From the test results, it can be seen that the algorithm is not easy to fall into the local optimum. Compared with other algorithms, the solution accuracy is higher and the stability is better. And it performed well in engineering optimization problems, thus verifying the effectiveness of the strategy.

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Section: Related Workmentioning

confidence: 99%

Educational Information System Optimization for Artificial Intelligence Teaching Strategies

2021

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“…Reactors housing organs or vessels require calibrated perfusion [38][39][40]. Scale-up and product transport remain challenges for tissue engineered products [41][42][43]. The hours of labor, the facilities, and the supplies needed to grow the EHBD required to test a statistically significant number of stents is, at this time, cost prohibitive for biliary stent product development applications [44,45].…”

Section: Discussionmentioning

confidence: 99%

3D Printed Model of Extrahepatic Biliary Ducts for Biliary Stent Testing

et al. 2020

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Several inflammatory conditions of the bile ducts cause strictures that prevent the drainage of bile into the gastrointestinal tract. Non-pharmacological treatments to re-establish bile flow include plastic or self-expanding metal stents (SEMs) that are inserted in the bile ducts during endoscopic retrograde cholangiopancreatography (ERCP) procedures. The focus of this study was to 3D print an anatomically accurate model of the extrahepatic bile ducts (EHBDs) with tissue-like mechanical properties to improve in vitro testing of stent prototypes. Following generation of an EHBD model via computer aided design (CAD), we tested the ability of Formlabs SLA 3D printers to precisely print the model with polymers selected based on the desired mechanical properties. We found the printers were reliable in printing the dimensionally accurate EHBD model with candidate polymers. Next, we evaluated the mechanical properties of Formlabs Elastic (FE), Flexible (FF), and Durable (FD) resins pre- and post-exposure to water, saline, or bile acid solution at 37 °C for up to one week. FE possessed the most bile duct-like mechanical properties based on its elastic moduli, percent elongations at break, and changes in mass under all liquid exposure conditions. EHBD models printed in FE sustained no functional damage during biliary stent deployment or when tube connectors were inserted, and provided a high level of visualization of deployed stents. These results demonstrate that our 3D printed EHBD model facilitates more realistic pre-clinical in vitro testing of biliary stent prototypes.

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“…Technology advances (developmental and cell biology, material sciences, tissue engineering, nanomedicine, etc.) have created a 'biopotentiated' healthcare ecosystem, enabling targeted disease repair and organ restoration strategies [6]. Accordingly, the preparedness of healthcare professionals must evolve to match growing opportunities.…”

Section: Regenerative Education Readinessmentioning

confidence: 99%

Emerging Workforce Readiness in Regenerative Healthcare

et al. 2021

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The biology of regenerative medicine has steadily matured, providing the foundation for randomized clinical trials and translation into validated applications. Today, the growing regenerative armamentarium is poised to impact disease management, yet a gap in training next-generation healthcare providers, equipped to adopt and deliver regenerative options, has been exposed. This special report highlights a multiyear experience in developing and deploying a comprehensive regenerative curriculum for medical trainees. For academicians and institutions invested in establishing a formalized regenerative medicine syllabus, the Regenerative Medicine and Surgery course provides a patient-focused prototype for next-generation learners, offering a dedicated educational experience that encompasses discovery, development and delivery of regenerative solutions. Built with the vision of an evolving regenerative care model, this transdisciplinary endeavor could serve as an adoptable education portal to advance the readiness of the emergent regenerative healthcare workforce globally.

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Improving patient outcomes with regenerative medicine: How the Regenerative Medicine Manufacturing Society plans to move the needle forward in cell manufacturing, standards, 3D bioprinting, artificial intelligence-enabled automation, education, and training

Cited by 16 publications

References 22 publications

Educational Information System Optimization for Artificial Intelligence Teaching Strategies

Educational Information System Optimization for Artificial Intelligence Teaching Strategies

3D Printed Model of Extrahepatic Biliary Ducts for Biliary Stent Testing

Emerging Workforce Readiness in Regenerative Healthcare

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