Speaker
Description
Bioprinting is facing several scientific and technological challenges toward having a clear clinical impact. Together with the complexity of multimaterial and multiscale features required for the fabrication of functional and effective bioprinted constructs, it is necessary to consider the compelling request of a consistent high quality, including inter-batch variability, and safety (e.g., meeting specific standards) of the final products.
In this perspective, Artificial Intelligence (AI) can have a transformative impact on the bioprinting field. A comprehensive view of current advancements and prospects in incorporating AI into bioprinting practices will be provided, from the development of new designs and the optimization of bioprinting protocols, to the enhanced quality control on the fabrication process and on the bioprinted construct.
For example, AI can automatically extract valuable insights from vast literature on bioprinting and Tissue Engineering, fostering innovation in materials and fabrication techniques. Such advancements could mitigate the lengthy trial-and-error approaches and suggest novel material-technology combinations based on scientific literature insights. On the other hand, several AI-based strategies have been described for quality control throughout the bioprinting process, including pre-process quality checks (such as optimizing printing parameters), in-process monitoring (detecting real-time defects), and post-process evaluations (assessing shape fidelity and functionality). Successful applications of ML techniques for each phase of the bioprinting process will be illustrated with a specific focus: the real-time monitoring of extrusion-based bioprinting utilizing a Deep Learning (DL) model to identify printing errors from video streams; and the automatic optimization of printing parameters by leveraging DL evaluations to enhance print quality dynamically. Indeed, AI can make bioprinting more accurate and reliable, facilitating compliance with regulations. In this forward-looking perspective talk, addressing technological obstacles and navigating regulatory frameworks, it is fundamental to consider that AI is in a continuous and accelerated evolution. As such, AI-enhanced solutions for bioprinting come with great potential but also important open questions related to intellectual property, safety, and liability, which need to be taken into account in a holistic view.
