Improving the Rate of Translation of Tissue Engineering Products

Deep Learning for Predicting Spheroid Viability: Novel Convolutional Neural Network Model for Automating Quality Control for Three-Dimensional Bioprinting

Spheroids serve as the building blocks for three-dimensional (3D) bioprinted tissue patches. When larger than 500 μm, the desired size for 3D bioprinting, they tend to have a hypoxic core with necrotic cells. Therefore, it is critical to assess the viability of spheroids in order to ensure the successful fabrication of high-viability patches. However, current viability assays are time-consuming, labor-intensive, require specialized training, or are subject to human bias. In this study, we build a convolutional neural network (CNN) model to efficiently and accurately predict spheroid viability, using a phase-contrast image of a spheroid as its input. A comprehensive dataset of mouse mesenchymal stem cell (mMSC) spheroids of varying sizes with corresponding viability percentages, which was obtained through CCK-8 assays, was established and used to train and validate the model. The model was trained to automatically classify spheroids into one of four distinct categories based on their predicted viability: 0-20%, 20-40%, 40-70%, and 70-100%. The model achieved an average accuracy of 92%, with a consistent loss below 0.2. This deep-learning model offers a non-invasive, efficient, and accurate method to streamline the assessment of spheroid quality, thereby accelerating the development of bioengineered cardiac tissue patches for cardiovascular disease therapies.

Recent advances in artificial intelligent strategies for tissue engineering and regenerative medicine

BACKGROUND

Tissue engineering and regenerative medicine (TERM) aim to repair or replace damaged or lost tissues or organs due to accidents, diseases, or aging, by applying different sciences. For this purpose, an essential part of TERM is the designing, manufacturing, and evaluating of scaffolds, cells, tissues, and organs. Artificial intelligence (AI) or the intelligence of machines or software can be effective in all areas where computers play a role.

METHODS

The "artificial intelligence," "machine learning," "tissue engineering," "clinical evaluation," and "scaffold" keywords used for searching in various databases and articles published from 2000 to 2024 were evaluated.

RESULTS

The combination of tissue engineering and AI has created a new generation of technological advancement in the biomedical industry. Experience in TERM has been refined using advanced design and manufacturing techniques. Advances in AI, particularly deep learning, offer an opportunity to improve scientific understanding and clinical outcomes in TERM.

CONCLUSION

The findings of this research show the high potential of AI, machine learning, and robots in the selection, design, and fabrication of scaffolds, cells, tissues, or organs, and their analysis, characterization, and evaluation after their implantation. AI can be a tool to accelerate the introduction of tissue engineering products to the bedside.

HIGHLIGHTS

The capabilities of artificial intelligence (AI) can be used in different ways in all the different stages of TERM and not only solve the existing limitations, but also accelerate the processes, increase efficiency and precision, reduce costs, and complications after transplantation. ML predicts which technologies have the most efficient and easiest path to enter the market and clinic. The use of AI along with these imaging techniques can lead to the improvement of diagnostic information, the reduction of operator errors when reading images, and the improvement of image analysis (such as classification, localization, regression, and segmentation).

A perioperative layered autologous tissue expansion graft for hollow organ repair

Tissue engineering has not been widely adopted in clinical settings for several reasons, including technical challenges, high costs, and regulatory complexity. Here, we introduce the Perioperative Layered Autologous Tissue Expansion graft (PLATE graft), a composite biomaterial and collagen-reinforced construct with autologous epithelium on one side and smooth muscle tissue on the other. Designed to mimic the structure and function of natural hollow organs, the PLATE graft is unique in that it can be produced in a standard operating theatre and is cost-effective. In this proof-of-principle study, we test its regenerative performance in eight different organs, present biomechanical and permeability tests, and finally explore its in vivo performance in live rabbits.

The cell-assembled extracellular matrix: A focus on the storage stability and terminal sterilization of this human "bio" material

The Cell-Assembled extracellular Matrix (CAM) is an attractive biomaterial because it provided the backbone of vascular grafts that were successfully implanted in patients, and because it can now be assembled in "human textiles". For future clinical development, it is important to consider key manufacturing questions. In this study, the impact of various storage conditions and sterilization methods were evaluated. After 1 year of dry frozen storage, no change in mechanical nor physicochemical properties were detected. However, storage at 4 °C and room temperature resulted in some mechanical changes, especially for dry CAM, but physicochemical changes were minor. Sterilization modified CAM mechanical and physicochemical properties marginally except for hydrated gamma treatment. All sterilized CAM supported cell proliferation. CAM ribbons were implanted subcutaneously in immunodeficient rats to assess the impact of sterilization on the innate immune response. Sterilization accelerated strength loss but no significant difference could be shown at 10 months. Very mild and transient inflammatory responses were observed. Supercritical CO2 sterilization had the least effect. In conclusion, the CAM is a promising biomaterial since it is unaffected by long-term storage in conditions available in hospitals (hydrated at 4 °C), and can be sterilized terminally (scCO2) without compromising in vitro nor in vivo performance. STATEMENT OF SIGNIFICANCE: In the field of tissue engineering, the use of extracellular matrix (ECM) proteins as a scaffolding biomaterial has become very popular. Recently, many investigators have focused on ECM produced by cells in vitro to produce unprocessed biological scaffolds. As this new kind of "biomaterial" becomes more and more relevant, it is critical to consider key manufacturing questions to facilitate future transition to the clinic. This article presents an extensive evaluation of long-term storage stability and terminal sterilization effects on an extracellular matrix assembled by cells in vitro. We believe that this article will be of great interest to help tissue engineers involved in so-called scaffold-free approaches to better prepare the translation from benchtop to bedside.

Biocompatibility Study of Hydrogel Biopolymer Scaffold with Encapsulated Mesenchymal Stem Cells

One of the key and actively developing areas of regenerative medicine is tissue-engineering. There is no doubt that the use of tissue-engineering products can have a significant impact on the efficiency of repair of damaged tissues and organs. However, before being used in clinical practice, tissue-engineering products require thorough preclinical studies to confirm their safety and efficacy, both with in vitro models and in experimental animals. This paper presents preclinical studies of a tissue-engineered construct, based on a hydrogel biopolymer scaffold carrier (consisting of blood plasma cryoprecipitate and collagen) with encapsulated mesenchymal stem cells, to evaluate its biocompatibility in vivo. The results were analyzed using histomorphology and transmission electron microscopy. It was shown that when implanted into animal (rat) tissues, the implants were completely replaced by connective tissue components. We also confirmed that no acute inflammation occurred in response to the scaffold implantation. The observed processes of cell recruitment to the scaffold from the surrounding tissues, the active formation of collagen fibers and the absence of acute inflammation testified that the regeneration process was ongoing in the implantation area. Thus, the presented tissue-engineered construct shows promise for becoming an effective tool for regenerative medicine in the future and may be used, in particular, to repair soft tissues.

Recent progress in the manipulation of biochemical and biophysical cues for engineering functional tissues

Tissue engineering (TE) is currently considered a cutting-edge discipline that offers the potential for developing treatments for health conditions that negatively affect the quality of life. This interdisciplinary field typically involves the combination of cells, scaffolds, and appropriate induction factors for the regeneration and repair of damaged tissue. Cell fate decisions, such as survival, proliferation, or differentiation, critically depend on various biochemical and biophysical factors provided by the extracellular environment during developmental, physiological, and pathological processes. Therefore, understanding the mechanisms of action of these factors is critical to accurately mimic the complex architecture of the extracellular environment of living tissues and improve the efficiency of TE approaches. In this review, we recapitulate the effects that biochemical and biophysical induction factors have on various aspects of cell fate. While the role of biochemical factors, such as growth factors, small molecules, extracellular matrix (ECM) components, and cytokines, has been extensively studied in the context of TE applications, it is only recently that we have begun to understand the effects of biophysical signals such as surface topography, mechanical, and electrical signals. These biophysical cues could provide a more robust set of stimuli to manipulate cell signaling pathways during the formation of the engineered tissue. Furthermore, the simultaneous application of different types of signals appears to elicit synergistic responses that are likely to improve functional outcomes, which could help translate results into successful clinical therapies in the future.

The Role of Machine Learning and Design of Experiments in the Advancement of Biomaterial and Tissue Engineering Research

Optimisation of tissue engineering (TE) processes requires models that can identify relationships between the parameters to be optimised and predict structural and performance outcomes from both physical and chemical processes. Currently, Design of Experiments (DoE) methods are commonly used for optimisation purposes in addition to playing an important role in statistical quality control and systematic randomisation for experiment planning. DoE is only used for the analysis and optimisation of quantitative data (i.e., number-based, countable or measurable), while it lacks the suitability for imaging and high dimensional data analysis. Machine learning (ML) offers considerable potential for data analysis, providing a greater flexibility in terms of data that can be used for optimisation and predictions. Its application within the fields of biomaterials and TE has recently been explored. This review presents the different types of DoE methodologies and the appropriate methods that have been used in TE applications. Next, ML algorithms that are widely used for optimisation and predictions are introduced and their advantages and disadvantages are presented. The use of different ML algorithms for TE applications is reviewed, with a particular focus on their use in optimising 3D bioprinting processes for tissue-engineered construct fabrication. Finally, the review discusses the future perspectives and presents the possibility of integrating DoE and ML in one system that would provide opportunities for researchers to achieve greater improvements in the TE field.

Highlights on Advancing Frontiers in Tissue Engineering

The field of tissue engineering continues to advance, sometimes in exponential leaps forward, but also sometimes at a rate that does not fulfill the promise that the field imagined a few decades ago. This review is in part a catalog of success in an effort to inform the process of innovation. Tissue engineering has recruited new technologies and developed new methods for engineering tissue constructs that can be used to mitigate or model disease states for study. Key to this antecedent statement is that the scientific effort must be anchored in the needs of a disease state and be working toward a functional product in regenerative medicine. It is this focus on the wildly important ideas coupled with partnered research efforts within both academia and industry that have shown most translational potential. The field continues to thrive and among the most important recent developments are the use of three-dimensional bioprinting, organ-on-a-chip, and induced pluripotent stem cell technologies that warrant special attention. Developments in the aforementioned areas as well as future directions are highlighted in this article. Although several early efforts have not come to fruition, there are good examples of commercial profitability that merit continued investment in tissue engineering. Impact statement Tissue engineering led to the development of new methods for regenerative medicine and disease models. Among the most important recent developments in tissue engineering are the use of three-dimensional bioprinting, organ-on-a-chip, and induced pluripotent stem cell technologies. These technologies and an understanding of them will have impact on the success of tissue engineering and its translation to regenerative medicine. Continued investment in tissue engineering will yield products and therapeutics, with both commercial importance and simultaneous disease mitigation.

Reproducibility, relevance and reliability as barriers to efficient and credible biomedical technology translation

Biomedical research accuracy and relevance for improving healthcare are increasingly identified as costly problems. Basic research data quality, reporting and methodology, and reproducibility are common factors implicated in this challenge. Preclinical models of disease and therapy, largely conducted in rodents, have known deficiencies in replicating most human conditions. Their translation to human results is acknowledged to be poor for decades. Clinical data quality and quantity is also recognized as deficient; gold standard randomized clinical trials are expensive. Few solid conclusions from clinical studies are replicable and many remain unpublished. The translational pathway from fundamental biomedical research through to innovative solutions handed to clinical practitioners is therefore highly inefficient and costly in terms of wasted resources, early claims from fundamental discoveries never witnessed in humans, and few new, improved solutions available clinically for myriad diseases. Improving this biomedical research strategy and resourcing for reliability, translational relevance, reproducibility and clinical impact requires careful analysis and consistent enforcement at both funding and peer review levels.

Neovascularization of engineered tissues for clinical translation: Where we are, where we should be?

One of the key challenges in engineering three-dimensional tissue constructs is the development of a mature microvascular network capable of supplying sufficient oxygen and nutrients to the tissue. Recent angiogenic therapeutic strategies have focused on vascularization of the constructed tissue, and its integration in vitro; these strategies typically combine regenerative cells, growth factors (GFs) with custom-designed biomaterials. However, the field needs to progress in the clinical translation of tissue engineering strategies. The article first presents a detailed description of the steps in neovascularization and the roles of extracellular matrix elements such as GFs in angiogenesis. It then delves into decellularization, cell, and GF-based strategies employed thus far for therapeutic angiogenesis, with a particularly detailed examination of different methods by which GFs are delivered in biomaterial scaffolds. Finally, interdisciplinary approaches involving advancement in biomaterials science and current state of technological development in fabrication techniques are critically evaluated, and a list of remaining challenges is presented that need to be solved for successful translation to the clinics.

Engineering skeletal muscle: Building complexity to achieve functionality

Volumetric muscle loss (VML) VML is defined as the loss of a critical mass of skeletal muscle that overwhelms the muscle's natural healing mechanisms, leaving patients with permanent functional deficits and deformity. The treatment of these defects is complex, as skeletal muscle is a composite structure that relies closely on the action of supporting tissues such as tendons, vasculature, nerves, and bone. The gold standard of treatment for VML injuries, an autologous muscle flap transfer, suffers from many shortcomings but nevertheless remains the best clinically available avenue to restore function. This review will consider the use of composite tissue engineered constructs, with multiple components that act together to replicate the function of an intact muscle, as an alternative to autologous muscle flaps. We will discuss recent advances in the field of tissue engineering that enable skeletal muscle constructs to more closely reproduce the functionality of an autologous muscle flap by incorporating vasculature, promoting innervation, and reconstructing the muscle-tendon boundary. Additionally, our understanding of the cellular composition of skeletal muscle has evolved to recognize the importance of a diverse variety of cell types in muscle regeneration, including fibro/adipogenic progenitors and immune cells like macrophages and regulatory T cells. We will address recent advances in our understanding of how these cell types interact with, and can be incorporated into, implanted tissue engineered constructs.

Acellular dense collagen-S53P4 bioactive glass hybrid gel scaffolds form more bone than stem cell delivered constructs

Dense collagen (DC) gels facilitate the osteoblastic differentiation of seeded dental pulp stem cells (DPSCs) and undergo rapid acellular mineralization when incorporated with bioactive glass particles, both in vitro and subcutaneously in vivo. However, the potential of DC-bioactive glass hybrid gels in delivering DPSCs for bone regeneration in an osseous site has not been investigated. In this study, the efficacies of both acellular and DPSC-seeded DC-S53P4 bioactive glass [(53)SiO₂-(23)Na₂O-(20)CaO-(4)P₂O₅, wt%] hybrid gels were investigated in a critical-sized murine calvarial defect. The incorporation of S53P4, an osteostimulative bioactive glass, into DC gels led to its accelerated acellular mineralization in simulated body fluid (SBF), in vitro, where hydroxycarbonated apatite was detected within 1 day. By day 7 in SBF, micro-mechanical analysis demonstrated an 8-fold increase in the compressive modulus of the mineralized gels. The in-situ effect of the bioactive glass on human-DPSCs within DC-S53P4 was evident, by their osteogenic differentiation in the absence of osteogenic supplements. The production of alkaline phosphatase and collagen type I was further increased when cultured in osteogenic media. This osteostimulative effect of DC-S53P4 constructs was confirmed in vivo, where after 8 weeks implantation, both acellular scaffolds and DPSC-seeded DC-S53P4 constructs formed mineralized and vascularized bone matrices with osteoblastic and osteoclastic cell activity. Surprisingly, however, in vivo micro-CT analysis confirmed that the acellular scaffolds generated larger volumes of bone, already visible at week 3 and exhibiting superior trabecular architecture. The results of this study suggest that DC-S53P4 scaffolds negate the need for stem cell delivery for effective bone tissue regeneration and may expedite their path towards clinical applications.

Cells, Materials, and Fabrication Processes for Cardiac Tissue Engineering

Cardiovascular disease is the number one killer worldwide, with myocardial infarction (MI) responsible for approximately 1 in 6 deaths. The lack of endogenous regenerative capacity, added to the deleterious remodelling programme set into motion by myocardial necrosis, turns MI into a progressively debilitating disease, which current pharmacological therapy cannot halt. The advent of Regenerative Therapies over 2 decades ago kick-started a whole new scientific field whose aim was to prevent or even reverse the pathological processes of MI. As a highly dynamic organ, the heart displays a tight association between 3D structure and function, with the non-cellular components, mainly the cardiac extracellular matrix (ECM), playing both fundamental active and passive roles. Tissue engineering aims to reproduce this tissue architecture and function in order to fabricate replicas able to mimic or even substitute damaged organs. Recent advances in cell reprogramming and refinement of methods for additive manufacturing have played a critical role in the development of clinically relevant engineered cardiovascular tissues. This review focuses on the generation of human cardiac tissues for therapy, paying special attention to human pluripotent stem cells and their derivatives. We provide a perspective on progress in regenerative medicine from the early stages of cell therapy to the present day, as well as an overview of cellular processes, materials and fabrication strategies currently under investigation. Finally, we summarise current clinical applications and reflect on the most urgent needs and gaps to be filled for efficient translation to the clinical arena.

Engineering Tissue Fabrication With Machine Intelligence: Generating a Blueprint for Regeneration

Regenerating lost or damaged tissue is the primary goal of Tissue Engineering. 3D bioprinting technologies have been widely applied in many research areas of tissue regeneration and disease modeling with unprecedented spatial resolution and tissue-like complexity. However, the extraction of tissue architecture and the generation of high-resolution blueprints are challenging tasks for tissue regeneration. Traditionally, such spatial information is obtained from a collection of microscopic images and then combined together to visualize regions of interest. To fabricate such engineered tissues, rendered microscopic images are transformed to code to inform a 3D bioprinting process. If this process is augmented with data-driven approaches and streamlined with machine intelligence, identification of an optimal blueprint can become an achievable task for functional tissue regeneration. In this review, our perspective is guided by an emerging paradigm to generate a blueprint for regeneration with machine intelligence. First, we reviewed recent articles with respect to our perspective for machine intelligence-driven information retrieval and fabrication. After briefly introducing recent trends in information retrieval methods from publicly available data, our discussion is focused on recent works that use machine intelligence to discover tissue architectures from imaging and spectral data. Then, our focus is on utilizing optimization approaches to increase print fidelity and enhance biomimicry with machine learning (ML) strategies to acquire a blueprint ready for 3D bioprinting.