Abstract

The EU Horizon 2020 project »JointPromise« implies the conception and implementation of an end-to-end automated production platform for three-dimensional joint implants, paving the way for tissue-engineered implants able to regenerate deep osteochondral defects. Spheroid-based implants provide a novel approach in tissue engineering by aggregating progenitor cells into potent microtissues. After the differentiation of cartilaginous microtissues, functional joint implants are assembled via 3D bioprinting to match the complex structural organization of native cartilage tissue. As the automation approach of the project aims to overcome bottlenecks in manual production such as product variability, lack of scalability and high personnel costs, a high-throughput quality control system is crucial for the production of reliable Advanced Therapy Medicinal Products (ATMPs).By establishing not only a technical solution for the full digitization of the cell culture plates but also an intelligent image processing algorithm for the detection of the cell spheroids, relevant process parameters like size distribution and growth curves can be detected. Critical thresholds in spheroid growth are evaluated to minimize risks of carcinogenic tissue formation in vivo as well as to define harvest criteria to prevent inhomogeneous bioprinting results. In order to calculate the required throughput and elaborate optimization potentials of the automated spheroid production, voids in the cultivation vessel or disrupted aggregates due to media changes or transportation are detected. Ultimately, the highspeed-microscopy complies with the requirements of a high-throughput automated cell production platform to meet the rising demand for alternative therapeutic approaches in regenerative medicine.

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