Review and proposition for model-based multivariable-multiobjective optimisation of extrusion-based bioprinting

Emebu, Samuel; Ogunleye, Raphael Olabanji; Achbergerová, Eva; Vítková, Lenka; Ponížil, Petr; Martinez, Clara Mendoza

doi:10.1016/j.apmt.2023.101914

Cited by 4 publications

(2 citation statements)

References 127 publications

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“…This pseudoplastic behavior not only facilitates the smooth and easy extrusion of bioinks through the nozzle but also mitigates the impact of high shear stress on encapsulated cells, thus improving cell viability. 46 In this study, we investigated the shear-thinning behavior of the prepared hydrogel over a range of shear rates, from 0.01 to 1000 s −1 . As shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Development of novel iron(iii) crosslinked bioinks comprising carboxymethyl cellulose, xanthan gum, and hyaluronic acid for soft tissue engineering applications

Le,

Hassan,

Ramezanpour

et al. 2024

J. Mater. Chem. B

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Section: Resultsmentioning

confidence: 99%

Development of novel iron(iii) crosslinked bioinks comprising carboxymethyl cellulose, xanthan gum, and hyaluronic acid for soft tissue engineering applications

Le,

Hassan,

Ramezanpour

et al. 2024

J. Mater. Chem. B

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“…Bioinks are usually modelled as shear-thinning fluids, which enables to deduce the equation of the flow through the extrusion needle and thus estimate the size of the printed filament, as for example, in the Ostwald-de Waele model [7]. These models have been proven precise within bounded operating limits but may struggle to properly predict results in atypical operating conditions (for instance, with high pressures) [26]. In addition, as these models only predict flow through the extrusion needle, they do not provide information about the shape of the filament once extruded as it is affected by gravity.…”

Section: Physical Modelsmentioning

confidence: 99%

Open-Loop Control System for High Precision Extrusion-Based Bioprinting Through Machine Learning Modeling

Arduengo,

Hascoet,

Chinesta

et al. 2024

Journal of Machine Engineering

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Bioprinting is a process that uses 3D printing techniques to combine cells, growth factors, and biomaterials to create biomedical components, often with the aim of imitating natural tissue characteristics. Typically, 3D bioprinting adopts a layer-by-layer method, using materials known as bio-inks to build structures resembling tissues. This study introduces an open-loop control system designed to improve the accuracy of extrusion-based bioprinting techniques, which is composed of a specific experimental setup and a series of algorithms and models. Firstly, a method employing Logistic Regression is used to select the tests that will serve to train and test the following model. Then, using a Machine Learning Algorithm, a model that allows the optimization of printing parameters and enables process control through an open-loop system was developed. Through rigorous experimentation and validation, it is shown that the model exhibits a high degree of accuracy in independent tests. Thus, the control system offers predictability and adaptability capabilities to ensure the consistent production of high-quality bioprinted structures. Experimental results confirm the efficacy of this machine learning model and the open-loop control system in achieving optimal bioprinting outcomes.

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Recent advances in the 3D skin bioprinting for regenerative medicine: Cells, biomaterials, and methods

Carvalho,

Peres,

Alonso-Goulart

et al. 2024

J Biomater Appl

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The skin is a tissue constantly exposed to the risk of damage, such as cuts, burns, and genetic disorders. The standard treatment is autograft, but it can cause pain to the patient being extremely complex in patients suffering from burns on large body surfaces. Considering that there is a need to develop technologies for the repair of skin tissue like 3D bioprinting. Skin is a tissue that is approximately 1/16 of the total body weight and has three main layers: epidermis, dermis, and hypodermis. Therefore, there are several studies using cells, biomaterials, and bioprinting for skin regeneration. Here, we provide an overview of the structure and function of the epidermis, dermis, and hypodermis, and showed in the recent research in skin regeneration, the main cells used, biomaterials studied that provide initial support for these cells, allowing the growth and formation of the neotissue and general characteristics, advantages and disadvantages of each methodology and the landmarks in recent research in the 3D skin bioprinting.

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Review and proposition for model-based multivariable-multiobjective optimisation of extrusion-based bioprinting

Cited by 4 publications

References 127 publications

Development of novel iron(iii) crosslinked bioinks comprising carboxymethyl cellulose, xanthan gum, and hyaluronic acid for soft tissue engineering applications

Development of novel iron(iii) crosslinked bioinks comprising carboxymethyl cellulose, xanthan gum, and hyaluronic acid for soft tissue engineering applications

Open-Loop Control System for High Precision Extrusion-Based Bioprinting Through Machine Learning Modeling

Recent advances in the 3D skin bioprinting for regenerative medicine: Cells, biomaterials, and methods

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