Transformative Technologies for Bioengineering and Regenerative Medicine

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Regenerative Engineering".

Deadline for manuscript submissions: 10 January 2026 | Viewed by 1600

Special Issue Editors


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Guest Editor
College of Engineering, North Carolina A & T State University, Greensboro, NC 27411, USA
Interests: hybrid nano-/micro- and biomanufacturing; regenerative tissue engineering and drug delivery; multiscale and multiphysics modeling; combinatorial additive manufacturing; digital smart manufacturing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. RegenMed Development Organization (ReMDO), Winston-Salem, NC, USA
2. Regenerative Medicine Manufacturing Society (RMMS), Winston-Salem, NC, USA
Interests: stem cells; regenerative medicine; additive manufacturing; 3D bioprinting; in space biomanufacturing; artificial intelligence; machine learning

Special Issue Information

Dear Colleagues,

This Special Issue aims to explore the intersection of bioengineering, artificial intelligence (AI), digital twin technology, IIoTs, and smart manufacturing. It will highlight cutting-edge research, innovative methodologies, comprehensive reviews, and case studies that demonstrate how these technologies can revolutionize biomanufacturing processes for next-generation regenerative medicine applications. Key topics include industrial-internet of things (IIoTs) sensors, organ-on-chip technologies, AI- and machine learning-based diagnostics, bioprinting, privacy and cybersecurity issues, and the digital twinning of biomedical devices and processes. This Special Issue will also cover emerging technologies at the intersection of bioengineering, AI, and smart manufacturing in both terrestrial and space environments. Topics of interest for this Special Issue include, but are not limited to, the following:

  1. AI-driven optimization of bioengineering processes and outcomes.
  2. Machine learning models for predicting the behavior of biological systems and medical devices.
  3. Digital twins and their applications in bioengineering.
  4. Smart manufacturing integrating automation and robotics in bioengineering and biomanufacturing processes.
  5. Role of IoT-enabled devices for monitoring biomanufacturing processes.
  6. Privacy and cybersecurity issues in biomanufacturing and tissue engineering. 

Dr. Salil Desai
Dr. Joshua Hunsberger
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • regenerative medicine
  • tissue engineering
  • artificial intelligence
  • digital twins
  • IIoTs
  • biomaterials
  • biomanufacturing
  • cybersecurity

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Published Papers (1 paper)

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27 pages, 2250 KB  
Perspective
A Collaborative Data Sharing Platform to Accelerate Translation of Biomedical Innovations
by Zohreh Izadifar, Greg Storm, Amol M. Joshi, Anna Hochberg, Michael Hadjisavas, Gary Rodrigue, Steven R. Bauer, James B. Schmidt, Sita Somara, Anthony Atala, Izabele Heyward, Salil Desai and Joshua Hunsberger
Bioengineering 2025, 12(9), 938; https://doi.org/10.3390/bioengineering12090938 - 30 Aug 2025
Cited by 1 | Viewed by 1269
Abstract
This perspective article presents an innovative concept for a biomanufacturing Knowledge Hub (KH), designed as a data-driven learning platform supporting the entire lifecycle of biomedical products. By integrating advanced data sharing and processing technologies, the KH aspires to connect patients, bioengineers, clinicians, regulators, [...] Read more.
This perspective article presents an innovative concept for a biomanufacturing Knowledge Hub (KH), designed as a data-driven learning platform supporting the entire lifecycle of biomedical products. By integrating advanced data sharing and processing technologies, the KH aspires to connect patients, bioengineers, clinicians, regulators, companies, and investors to accelerate product development, reduce redundancies, and ultimately fast-track the delivery of biomedical innovations to patients. We discuss current challenges in accessing and sharing data within biomanufacturing and outline novel approaches for building an ecosystem that links data stores, integrates digital twins, and leverages advanced analytics. The KH offers transformative capabilities, enabling the development of new products at a substantial increased speed. It is built as a secure, quantum-resistant platform that encrypts data and allows access through advanced algorithms, creating an intelligent, collaborative environment. Users can harness collective knowledge to enhance products, launch innovations, integrate technologies, and unlock revenue opportunities based on data quality and usage. This KH aims to revolutionize biomanufacturing, offering unprecedented opportunities for innovation, better patient outcomes, and commercialization with far reaching applications beyond biomanufacturing in the future. Full article
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