AI-Driven Biofabrication: Accelerating Design, Optimization, and Translation
A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "B2: Biofabrication and Tissue Engineering".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 7
Special Issue Editor
Interests: tissue engineering; bio-hybrid robotics; regenerative medicine; magnetic systems; magnetic nanoparticles; iron oxide nanoparticles; SPIO; theranostics; tissue regeneration; stem cells; soft robotics; biohybrid robotics; micromachines; remote control; drug delivery; microrobots; neuromodulation
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Special Issue Information
Dear Colleagues,
Biofabrication is redefining how we engineer living and bio-hybrid systems from biomaterials and cells by applying advanced fabrication techniques to produce complex, functional structures. As this field evolves, artificial intelligence (AI) is emerging as a powerful catalyst to address longstanding challenges, particularly the inefficiencies, trial-and-error nature, and resource-intensive protocols that often limit reproducibility and scalability. This Special Issue focuses on the transformative potential of AI in optimizing biofabrication workflows, from material design and construct geometry to cell behavior prediction and functional integration.
The convergence of machine learning, high-throughput experimentation, and simulation-based design enables a shift toward the predictive, sustainable, and more autonomous manufacturing of engineered biological systems. By guiding material selection, enhancing process control, and enabling real-time feedback during fabrication, AI can dramatically accelerate development cycles while minimizing waste and energy consumption. The implications span from regenerative medicine and soft robotics to ecological interventions and sustainable engineering.
This Special Issue welcomes a variety of submission types, including original research articles, comprehensive reviews, and perspectives. We invite contributions that investigate AI-driven strategies in design automation, the optimization of fabrication parameters, the computational modeling of tissue dynamics, and validation methods for bioengineered constructs. In addition to these core areas of AI and biofabrication, we encourage submissions from related disciplines such as data science, computational biology, and materials science. Together, these interdisciplinary advances are shaping a new era of smart biofabrication, where digital intelligence empowers biological processes to achieve scalable, precise, and environmentally sustainable production.
I look forward to receiving your contributions.
Dr. Miriam Filippi
Guest Editor
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. Micromachines 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 2100 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
- biofabrication
- machine learning
- artificial intelligence
- predictive modeling
- high-throughput experimentation
- simulation-based design
- process optimization
- scalability
- sustainable engineering
- material design
- cell behavior prediction
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