Automation, Monitoring, and Standardization of Cell Product Manufacturing

An integrated perspective on measuring cytokines to inform CAR-T bioprocessing

Chimeric antigen receptor (CAR)-T cells are emerging as a generation-defining therapeutic however their manufacture remains a major barrier to meeting increased market demand. Monitoring critical quality attributes (CQAs) and critical process parameters (CPPs) during manufacture would vastly enrich acquired information related to the process and product, providing feedback to enable real-time decision making. Here we identify specific CAR-T cytokines as value-adding analytes and discuss their roles as plausible CPPs and CQAs. High sensitivity sensing technologies which can be easily integrated into manufacture workflows are essential to implement real-time monitoring of these cytokines. We therefore present biosensors as enabling technologies and evaluate recent advancements in cytokine detection in cell cultures, offering promising translatability to CAR-T biomanufacture. Finally, we outline emerging sensing technologies with future promise, and provide an overall outlook on existing gaps to implementation and the optimal sensing platform to enable cytokine monitoring in CAR-T biomanufacture.

Automated CRISPR/Cas9-based genome editing of human pluripotent stem cells using the StemCellFactory

CRISPR/Cas9 genome editing is a rapidly advancing technology that has the potential to accelerate research and development in a variety of fields. However, manual genome editing processes suffer from limitations in scalability, efficiency, and standardization. The implementation of automated systems for genome editing addresses these challenges, allowing researchers to cover the increasing need and perform large-scale studies for disease modeling, drug development, and personalized medicine. In this study, we developed an automated CRISPR/Cas9-based genome editing process on the StemCellFactory platform. We implemented a 4D-Nucleofector with a 96-well shuttle device into the StemCellFactory, optimized several parameters for single cell culturing and established an automated workflow for CRISPR/Cas9-based genome editing. When validated with a variety of genetic backgrounds and target genes, the automated workflow showed genome editing efficiencies similar to manual methods, with indel rates of up to 98%. Monoclonal colony growth was achieved and monitored using the StemCellFactory-integrated CellCelector, which allowed the exclusion of colonies derived from multiple cells or growing too close to neighbouring colonies. In summary, we demonstrate the successful establishment of an automated CRISPR/Cas9-based genome editing process on the StemCellFactory platform. The development of such a standardized and scalable automated CRISPR/Cas9 system represents an exciting new tool in genome editing, enhancing our ability to address a wide range of scientific questions in disease modeling, drug development and personalized medicine.

Single-Cell RNA Sequencing Reveals Repair Features of Human Umbilical Cord Mesenchymal Stromal Cells

Rationale: The chronic lung disease bronchopulmonary dysplasia (BPD) is the most severe complication of extreme prematurity. BPD results in impaired lung alveolar and vascular development and long-term respiratory morbidity, for which only supportive therapies exist. Umbilical cord-derived mesenchymal stromal cells (UC-MSCs) improve lung structure and function in experimental BPD. Results of clinical trials with MSCs for many disorders do not yet match the promising preclinical studies. A lack of specific criteria to define functionally distinct MSCs persists. Objectives: To determine and correlate single-cell UC-MSC transcriptomic profiles with therapeutic potential. Methods: UC-MSCs from five term donors and human neonatal dermal fibroblasts (HNDFs; control cells of mesenchymal origin) transcriptomes were investigated using single-cell RNA sequencing (scRNA-seq) analysis. The lung-protective effect of UC-MSCs with a distinct transcriptome and control HNDFs was tested in vivo in hyperoxia-induced neonatal lung injury in rats. Measurements and Main Results: UC-MSCs showed limited transcriptomic heterogeneity but were different from HNDFs. Gene Ontology enrichment analysis revealed distinct (progenitor-like and fibroblast-like) UC-MSC subpopulations. Only treatment with progenitor-like UC-MSCs improved lung function and structure and attenuated pulmonary hypertension in hyperoxia-exposed rat pups. Moreover, scRNA-seq identified major histocompatibility complex class I as a molecular marker of nontherapeutic cells and associated with decreased lung retention. Conclusions: UC-MSCs with a progenitor-like transcriptome, but not with a fibroblast-like transcriptome, provide lung protection in experimental BPD. High expression of major histocompatibility complex class I is associated with reduced therapeutic benefit. scRNA-seq may be useful to identify subsets of MSCs with superior repair capacity for clinical application.

Achieving near-zero particle generation by simplicity of design-A compliant-mechanism-based gripper for clean-room environments

Lab Automation facilitates high-throughput processes and improves reproducibility and efficiency while removing human action, primary source of contaminating particles. Handling poses a risk of contamination due to close contact with the objects. We propose a novel gripper (CrocoGrip) relying on compliant mechanisms to reduce the amount of contaminating particles generated by the gripper rather than preventing their emission, the latter being the common approach in current grippers. Our novel gripper is actuated by linear solenoids and purely relies on deformation for its motion. As a result, abrasive behavior and, therefore, the generation of particles is reduced without the need for additional sealing. We experimentally proved that only particles smaller than 3.0µm are emitted by the gripper, with a large proportion of the particles being generated by the actuation. The CrocoGrip fulfills the demands of ISO14644 class 5. The gripping relies on the deformation energy of the compliant mechanism, making the gripping energy-efficient and safe. The maximum gripping force achieved by the CrocoGrip was 5.5N. Because the force transmitted to the handling object depends on the design of the gripping jaws, which are interchangeable, the force can be reduced for more sensible handling objects. Using three different sets of jaws, CrocoGrip was able to handle a microplate in SBS-standard, a 50mL Falcon tube, and a Ø60mm Petri dish using a robotic arm. Due to the monolithic design of the CrocoGrip and, as a result, the need for few components, we achieve a simplicity of design, making cleaning, sterilization and maintenance easy, even for nonexperts. The CrocoGrip exploits the advantages of compliant mechanisms, especially for applications requiring clean-room environments. This approach of compliant-mechanism-based grippers enables an increase in the cleanliness of handling processes without an increase in system complexity of the gripper to facilitate the lab automation of highly sensible processes, such as in tissue engineering.

Bioprocessing considerations for generation of iPSCs intended for clinical application: perspectives from the ISCT Emerging Regenerative Medicine Technology working group

Approval of induced pluripotent stem cells (iPSCs) for the manufacture of cell therapies to support clinical trials is now becoming realized after 20 years of research and development. In 2022 the International Society for Cell and Gene Therapy (ISCT) established a Working Group on Emerging Regenerative Medicine Technologies, an area in which iPSCs-derived technologies are expected to play a key role. In this article, the Working Group surveys the steps that an end user should consider when generating iPSCs that are stable, well-characterised, pluripotent, and suitable for making differentiated cell types for allogeneic or autologous cell therapies. The objective is to provide the reader with a holistic view of how to achieve high-quality iPSCs from selection of the starting material through to cell banking. Key considerations include: (i) intellectual property licenses; (ii) selection of the raw materials and cell sources for creating iPSC intermediates and master cell banks; (iii) regulatory considerations for reprogramming methods; (iv) options for expansion in 2D vs. 3D cultures; and (v) available technologies and equipment for harvesting, washing, concentration, filling, cryopreservation, and storage. Some key process limitations are highlighted to help drive further improvement and innovation, and includes recommendations to close and automate current open and manual processes.

Noninvasive total counting of cultured cells using a home-use scanner with a pattern sheet

The inherent variability in cell culture techniques hinders their reproducibility. To address this issue, we introduce a comprehensive cell observation device. This new approach enhances the features of existing home-use scanners by implementing a pattern sheet. Compared with fluorescent staining, our method over- or underestimated the cell count by a mere 5%. The proposed technique showcased a strong correlation with conventional methodologies, displaying R2 values of 0.91 and 0.99 compared with the standard chamber and fluorescence methods, respectively. Simulations of microscopic observations indicated the potential to estimate accurately the total cell count using just 20 fields of view. Our proposed cell-counting device offers a straightforward, noninvasive means of measuring the number of cultured cells. By harnessing the power of deep learning, this device ensures data integrity, thereby making it an attractive option for future cell culture research.

High-volume, label-free imaging for quantifying single-cell dynamics in induced pluripotent stem cell colonies

To facilitate the characterization of unlabeled induced pluripotent stem cells (iPSCs) during culture and expansion, we developed an AI pipeline for nuclear segmentation and mitosis detection from phase contrast images of individual cells within iPSC colonies. The analysis uses a 2D convolutional neural network (U-Net) plus a 3D U-Net applied on time lapse images to detect and segment nuclei, mitotic events, and daughter nuclei to enable tracking of large numbers of individual cells over long times in culture. The analysis uses fluorescence data to train models for segmenting nuclei in phase contrast images. The use of classical image processing routines to segment fluorescent nuclei precludes the need for manual annotation. We optimize and evaluate the accuracy of automated annotation to assure the reliability of the training. The model is generalizable in that it performs well on different datasets with an average F1 score of 0.94, on cells at different densities, and on cells from different pluripotent cell lines. The method allows us to assess, in a non-invasive manner, rates of mitosis and cell division which serve as indicators of cell state and cell health. We assess these parameters in up to hundreds of thousands of cells in culture for more than 36 hours, at different locations in the colonies, and as a function of excitation light exposure.

Physical Laboratory Automation in Synthetic Biology

Synthetic Biology has overcome many of the early challenges facing the field and is entering a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches. The need for automation and standardization to enable reproducible, scalable, and translatable research has become increasingly accepted in recent years, and many of the hardware and software tools needed to address these challenges are now in place or under development. However, the lack of connectivity between DBTL modules and barriers to access and adoption remain significant challenges to realizing the full potential of lab automation. In this review, we characterize and classify the state of automation in synthetic biology with a focus on the physical automation of experimental workflows. Though fully autonomous scientific discovery is likely a long way off, impressive progress has been made toward automating critical elements of experimentation by combining intelligent hardware and software tools. It is worth questioning whether total automation that removes humans entirely from the loop should be the ultimate goal, and considerations for appropriate automation versus total automation are discussed in this light while emphasizing areas where further development is needed in both contexts.

FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines

The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potential of automation will thus require the design of robust analysis pipelines that span the entire workflow in question. Here we present FocA, a deep learning tool that, in near real-time, identifies in-focus and out-of-focus images generated on a fully automated cell biology research platform, the NYSCF Global Stem Cell Array®. The tool is trained on small patches of downsampled images to maximize computational efficiency without compromising accuracy, and optimized to make sure no sub-quality images are stored and used in downstream analyses. The tool automatically generates balanced and maximally diverse training sets to avoid bias. The resulting model correctly identifies 100% of out-of-focus and 98% of in-focus images in under 4 s per 96-well plate, and achieves this result even in heavily downsampled data (∼30 times smaller than native resolution). Integrating the tool into automated workflows minimizes the need for human verification as well as the collection and usage of low-quality data. FocA thus offers a solution to ensure reliable image data hygiene and improve the efficiency of automated imaging workflows using minimal computational resources.

Screening Station, a novel laboratory automation system for physiologically relevant cell-based assays

Due to their physiological relevance, cell-based assays using human-induced pluripotent stem cell (iPSC)-derived cells are a promising in vitro pharmacological evaluation system for drug candidates. However, cell-based assays involve complex processes such as long-term culture, real-time and continuous observation of living cells, and detection of many cellular events. Automating multi-sample processing through these assays will enhance reproducibility by limiting human error and reduce researchers' valuable time spent conducting these experiments. Furthermore, this integration enables continuous tracking of morphological changes, which is not possible with the use of stand-alone devices. This report describes a new laboratory automation system called the Screening Station, which uses novel automation control and scheduling software called Green Button Go to integrate various devices. To integrate the above-mentioned processes, we established three workflows in Green Button Go: 1) For long-term cell culture, culture plates and medium containers are transported from the automatic CO2 incubator and cool incubator, respectively, and the cell culture medium in the microplates is exchanged daily using the Biomek i7 workstation; 2) For time-lapse live-cell imaging, culture plates are automatically transferred between the CQ1 confocal quantitative image cytometer and the SCALE48W automatic CO2 incubator; 3) For immunofluorescence imaging assays, in addition to the above-mentioned devices, the 405LS microplate washer allows for formalin-fixation and immunostaining of cells. By scheduling various combinations of the three workflows, we successfully automated the culture and medium exchange processes for iPSCs derived from patients with facioscapulohumeral muscular dystrophy, confirmation of their differentiation status by live-cell imaging, and confirmation of the presence of differentiation markers by immunostaining. In addition, deep learning analysis enabled us to quantify the degree of iPSC differentiation from live-cell imaging data. Further, the results of the fully automated experiments could be accessed via the intranet, enabling experiments and analysis to be conducted remotely once the necessary reagents and labware were prepared. We expect that the ability to perform clinically and physiologically relevant cell-based assays from remote locations using the Screening Station will facilitate global research collaboration and accelerate the discovery of new drug candidates.

Mini-review: Equipment evaluation for process scalability and readiness for current Good Manufacturing Practices in cell therapy workflows

Cell therapies present a promising treatment for a variety of diseases and are a rapidly growing market. This facilitates the need for robust biomanufacturing processes that can be implemented early during process establishment which enables scalable and reproducible manufacturing. Historically, cell therapy has used equipment originally repurposed from biologics, where the supernatant is harvested at the end of production and not the cells. Unlike biologics, cell therapy requires the preservation of cell phenotype and potency, as well as the functional recovery of the cells for the final formulation. These traditional equipment platforms have been widely adopted and, in many cases, successfully. However, given that cell therapy processes are complex, equipment specifically designed for the intended application will add immense value by producing products that are pure, potent and stable. New equipment better suited for cell therapy is being introduced to improve efficiency and product quality compared with current systems, fill key gaps that exist in current workflows or address an emerging need in new paradigms. Integration of these new instruments in laboratories using current Good Manufacturing Practices to produce cell-based drug products and drug substances requires a risk-based approach to evaluate features based on suitability and compliance with regulatory requirements. The speed at which new equipment is evaluated and implemented into new workflows is critical to match the speed of therapeutic product innovations and manufacturing capabilities. Here, we outline a framework to evaluate new equipment and de-risk implementation based on a series of features, namely, hardware, software, consumables, and workflow compatibility for the intended use. A hypothetical evaluation of three cell processing workflows is used as an example to inform equipment deployment for early process establishment and translational use for current Good Manufacturing Practices-destined workflows.

A computer vision based optical method for measuring fluid level in cell culture plates

For a transparent well with a known volume capacity, changes in fluid level result in predictable changes in magnification of an overhead light source. For a given well size and fluid, the relationship between volume and magnification can be calculated if the fluid's index of refraction is known or in a naive fashion with a calibration procedure. Light source magnification can be measured through a camera and processed using computer vision contour analysis with OpenCV. This principle was applied in the design of a 3D printable sensing device using a raspberry pi zero and a camera.

Artificial intelligence and improvement of stem cell delivery in healthcare

Artificial intelligence (AI) is critical for improving the quality of stem cell manufacturing and delivery. AI can assist in determining the viability, effectiveness, efficacy, and safety of stem cells. Furthermore, in stem cell and regenerative medicine, AI is utilized to streamline simulation and model-building processes and find connections between cellular activities and their microenvironments. However, thoughtful consideration is required to minimize unwanted implications of AI incorporation for stem cell-based treatment.

Bioprinting of Cardiac Tissue in Space: Where Are We?

Bioprinting in space is the next frontier in tissue engineering. In the absence of gravity, novel opportunities arise, as well as new challenges. The cardiovascular system needs particular attention in tissue engineering, not only to develop safe countermeasures for astronauts in future deep and long-term space missions, but also to bring solutions to organ transplantation shortage. In this perspective, the challenges encountered when using bioprinting techniques in space and current gaps that need to be overcome are discussed. The recent developments that have been made in the bioprinting of heart tissues in space and an outlook on potential future bioprinting opportunities in space are described.

Translation of biophysical environment in bone into dynamic cell culture under flow for bone tissue engineering

Bone is a dynamic environment where osteocytes, osteoblasts, and mesenchymal stem/progenitor cells perceive mechanical cues and regulate bone metabolism accordingly. In particular, interstitial fluid flow in bone and bone marrow serves as a primary biophysical stimulus, which regulates the growth and fate of the cellular components of bone. The processes of mechano-sensory and -transduction towards bone formation have been well studied mainly in vivo as well as in two-dimensional (2D) dynamic cell culture platforms, which elucidated mechanically induced osteogenesis starting with anabolic responses, such as production of nitrogen oxide and prostaglandins followed by the activation of canonical Wnt signaling, upon mechanosensation. The knowledge has been now translated into regenerative medicine, particularly into the field of bone tissue engineering, where multipotent stem cells are combined with three-dimensional (3D) scaffolding biomaterials to produce transplantable constructs for bone regeneration. In the presence of 3D scaffolds, the importance of suitable dynamic cell culture platforms increases further not only to improve mass transfer inside the scaffolds but to provide appropriate biophysical cues to guide cell fate. In principle, the concept of dynamic cell culture platforms is rooted to bone mechanobiology. Therefore, this review primarily focuses on biophysical environment in bone and its translation into dynamic cell culture platforms commonly used for 2D and 3D cell expansion, including their advancement, challenges, and future perspectives. Additionally, it provides the literature review of recent empirical studies using 2D and 3D flow-based dynamic cell culture systems for bone tissue engineering.

Implementation of transfer learning for the segmentation of human mesenchymal stem cells-A validation study

INTRODUCTION

Stem cell therapy has been gaining interest in the regeneration rather than repair of lost human tissues. However, the manual analysis of stem cells prior to implantation is a cumbersome task that can be automated to improve the efficiency and accuracy of this process.

OBJECTIVE

To develop a Deep Learning (DL) algorithm for segmentation of human mesenchymal stem cells (MSCs) on micrographic images and to validate its performance relative to the ground truth laid down via annotation.

METHODOLOGY

Pre-trained DeepLab algorithms were trained on annotated images of human MSCs obtained from the open-source EVICAN dataset. This dataset comprises of partially annotated images; a limitation that is overcome by blurring backgrounds of these images which consequently blurs the unannotated cells. Two algorithms were trained on the two different kinds of images from this dataset; with blurred and normal backgrounds, respectively. Algorithm 1 was trained on 139 images with blurred backgrounds and algorithm 2 was trained on 37 images from the same dataset with normal backgrounds to replicate real-life scenarios.

RESULTS

The performance metrics of algorithm 1 included accuracy of 99.22%, dice co-efficient of 99.66% and Intersection over Union (IoU) score of 0.84. Algorithm 2 was 96.34% accurate with dice co-efficient and IoU scores of 98.39% and 0.48, respectively.

CONCLUSION

Both algorithms showed adequate performance in the segmentation of human MSCs with performance metrics close to the ground truth. However, algorithm 2 has better clinical applicability, even with smaller dataset and relatively lower performance metrics.

Transformative Materials to Create 3D Functional Human Tissue Models In Vitro in a Reproducible Manner

Recreating human tissues and organs in the petri dish to establish models as tools in biomedical sciences has gained momentum. These models can provide insight into mechanisms of human physiology, disease onset, and progression, and improve drug target validation, as well as the development of new medical therapeutics. Transformative materials play an important role in this evolution, as they can be programmed to direct cell behavior and fate by controlling the activity of bioactive molecules and material properties. Using nature as an inspiration, scientists are creating materials that incorporate specific biological processes observed during human organogenesis and tissue regeneration. This article presents the reader with state-of-the-art developments in the field of in vitro tissue engineering and the challenges related to the design, production, and translation of these transformative materials. Advances regarding (stem) cell sources, expansion, and differentiation, and how novel responsive materials, automated and large-scale fabrication processes, culture conditions, in situ monitoring systems, and computer simulations are required to create functional human tissue models that are relevant and efficient for drug discovery, are described. This paper illustrates how these different technologies need to converge to generate in vitro life-like human tissue models that provide a platform to answer health-based scientific questions.

Stem cell sources and characterization in the development of cell-based products for treating retinal disease: An NEI Town Hall report

National Eye Institute recently issued a new Strategic Plan outlining priority research areas for the next 5 years. Starting cell source for deriving stem cell lines is as an area with gaps and opportunities for making progress in regenerative medicine, a key area of emphasis within the NEI Strategic Plan. There is a critical need to understand how starting cell source affects the cell therapy product and what specific manufacturing capabilities and quality control standards are required for autologous vs allogeneic stem cell sources. With the goal of addressing some of these questions, in discussion with the community-at-large, NEI hosted a Town Hall at the Association for Research in Vision and Ophthalmology annual meeting in May 2022. This session leveraged recent clinical advances in autologous and allogeneic RPE replacement strategies to develop guidance for upcoming cell therapies for photoreceptors, retinal ganglion cells, and other ocular cell types. Our focus on stem cell-based therapies for RPE underscores the relatively advanced stage of RPE cell therapies to patients with several ongoing clinical trials. Thus, this workshop encouraged lessons learned from the RPE field to help accelerate progress in developing stem cell-based therapies in other ocular tissues. This report provides a synthesis of the key points discussed at the Town Hall and highlights needs and opportunities in ocular regenerative medicine.

Cross-contamination risk and decontamination during changeover after cell-product processing

Introduction

During changeover in cell-product processing, it is essential to minimize cross-contamination risks. These risks differ depending on the patient from whom the cells were derived. Human error during manual cell-product processing increases the contamination risk in biosafety cabinets. Here, we evaluate the risk of cross-contamination during manual cell-processing to develop an evidence-based changeover method for biosafety cabinets.

Methods

Contaminant coverage was analyzed during simulated medium preparation, cell seeding, and waste liquid decanting by seven operators, classified by skill. Environmental bacteria were surveyed at four participating facilities. Finally, we assessed the effect of conventional UV irradiation in biosafety cabinets on bacteria and fungi that pose a cross-contamination risk.

Results

Under simulated conditions, scattered contamination occurred via droplets falling onto the surface from heights of 30 cm, and from bubbles rupturing at this height. Visible traces of contaminants were distributed up to 50 cm from the point of droplet impact, or from the location of the pipette tip when the bubble ruptured. In several facilities, we detected Bacillus subtilis, of which the associated endospores are highly resistant to disinfection. Irradiation at 50 mJ/cm² effectively eliminated Bacillus subtilis vegetative cells and Aspergillus brasiliensis, which is highly resistant to UV. Bacillus subtilis endospores were eliminated at 100 mJ/cm².

Conclusions

Under these simulated optimal conditions, UV irradiation successfully prevents cross-contamination. Therefore, following cell-product processing, monitoring the UV dose in the biosafety cabinet during cell changeover represents a promising method for reducing cross-contamination.

Translating musculoskeletal bioengineering into tissue regeneration therapies

Musculoskeletal injuries and disorders are the leading cause of physical disability worldwide and a considerable socioeconomic burden. The lack of effective therapies has driven the development of novel bioengineering approaches that have recently started to gain clinical approvals. In this review, we first discuss the self-repair capacity of the musculoskeletal tissues and describe causes of musculoskeletal dysfunction. We then review the development of novel biomaterial, immunomodulatory, cellular, and gene therapies to treat musculoskeletal disorders. Last, we consider the recent regulatory changes and future areas of technological progress that can accelerate translation of these therapies to clinical practice.

Engineering bone-forming callus organoid implants in a xenogeneic-free differentiation medium

The field of tissue engineering aspires to provide clinically relevant solutions for patients through the integration of developmental engineering principles with a bottom-up manufacturing approach. However, the manufacturing of cell-based advanced therapy medicinal products is hampered by protocol complexity, lack of non-invasive critical quality controls, and dependency on animal-derived components for tissue differentiation. We investigate a serum-free, chemically defined, xeno- and lipid-free chondrogenic differentiation medium to generate bone-forming callus organoids. Our results show an increase in microtissue homogeneity during prolonged differentiation and the high quality of in vivo bone-forming organoids. The low protein content of the culture medium potentially allows for the monitoring of relevant secreted biomarkers as (critical) quality attributes. Together, we envisage that this xeno- and lipid-free chondrogenic medium is compatible with industrial scale-up and automation while facilitating the implementation of non-invasive imaging and the use of quality control parameters based on secreted biomarkers.

A pH Monitoring Algorithm for Orifice Plate Culture Medium

Recently, there has been renewed interest in cell therapy, which plays a key role in the clinical research of genetic diseases, advanced blood disease, and other diseases. It shows considerable clinical application value and is known as “the new pillar of future medicine”. Automatic cell culture and operation technology is the key to ensuring scale, standardization, and stability between batches of therapeutic cells. The pH of the cell culture medium is vital for cell growth. Most cells are suitable for growth at pH 7.2~7.4. A pH of cell culture medium lower than 6.8 or higher than 7.6 is harmful to cells, and cells will degenerate or even die. At present, the monitoring method of cell culture medium pH of automatic cell culture equipment is mainly a visual observation method, which can not accurately or quickly reflect changes in the cell culture medium. To address the issue of monitoring of cell culture fluid pH for automated cell culture equipment and the inability to employ invasive sensors to measure pH during well plate culture, a pH monitoring method for orifice plate culture medium algorithm based on HSV (hue, saturation, value) model is proposed by studying the changes of cell culture medium in the process of cell culture. The research presented here reveals the laws of cell culture fluid pH change and its color moment, and the intelligent monitoring of cell culture fluid pH was successfully achieved. The problem of non-destructive monitoring of the pH of cell culture fluids in well plates is also addressed.

3D Printed Solutions for Spheroid Engineering and Cancer Research

In multicellular organisms, cells are organized in a 3-dimensional framework and this is essential for organogenesis and tissue morphogenesis. Systems to recapitulate 3D cell growth are therefore vital for understanding development and cancer biology. Cells organized in 3D environments can evolve certain phenotypic traits valuable to physiologically relevant models that cannot be accessed in 2D culture. Cellular spheroids constitute an important aspect of in vitro tumor biology and they are usually prepared using the hanging drop method. Here a 3D printed approach is demonstrated to fabricate bespoke hanging drop devices for the culture of tumor cells. The design attributes of the hanging drop device take into account the need for high-throughput, high efficacy in spheroid formation, and automation. Specifically, in this study, custom-fit, modularized hanging drop devices comprising of inserts (Q-serts) were designed and fabricated using fused filament deposition (FFD). The utility of the Q-serts in the engineering of unicellular and multicellular spheroids-synthetic tumor microenvironment mimics (STEMs)—was established using human (cancer) cells. The culture of spheroids was automated using a pipetting robot and bioprinted using a custom bioink based on carboxylated agarose to simulate a tumor microenvironment (TME). The spheroids were characterized using light microscopy and histology. They showed good morphological and structural integrity and had high viability throughout the entire workflow. The systems and workflow presented here represent a user-focused 3D printing-driven spheroid culture platform which can be reliably reproduced in any research environment and scaled to- and on-demand. The standardization of spheroid preparation, handling, and culture should eliminate user-dependent variables, and have a positive impact on translational research to enable direct comparison of scientific findings.

Toward Rapid, Widely Available Autologous CAR-T Cell Therapy – Artificial Intelligence and Automation Enabling the Smart Manufacturing Hospital

CAR-T cell therapy is a promising treatment for acute leukemia and lymphoma. CAR-T cell therapies take a pioneering role in autologous gene therapy with three EMA-approved products. However, the chance of clinical success remains relatively low as the applicability of CAR-T cell therapy suffers from long, labor-intensive manufacturing and a lack of comprehensive insight into the bioprocess. This leads to high manufacturing costs and limited clinical success, preventing the widespread use of CAR-T cell therapies. New manufacturing approaches are needed to lower costs to improve manufacturing capacity and shorten provision times. Semi-automated devices such as the Miltenyi Prodigy® were developed to reduce hands-on production time. However, these devices are not equipped with the process analytical technology necessary to fully characterize and control the process. An automated AI-driven CAR-T cell manufacturing platform in smart manufacturing hospitals (SMH) is being developed to address these challenges. Automation will increase the cost-effectiveness and robustness of manufacturing. Using Artificial Intelligence (AI) to interpret the data collected on the platform will provide valuable process insights and drive decisions for process optimization. The smart integration of automated CAR-T cell manufacturing platforms into hospitals enables the independent manufacture of autologous CAR-T cell products. In this perspective, we will be discussing current challenges and opportunities of the patient-specific but highly automated, AI-enabled CAR-T cell manufacturing. A first automation concept will be shown, including a system architecture based on current Industry 4.0 approaches for AI integration.

Intelligent Detection of Steel Defects Based on Improved Split Attention Networks

The intelligent monitoring and diagnosis of steel defects plays an important role in improving steel quality, production efficiency, and associated smart manufacturing. The application of the bio-inspired algorithms to mechanical engineering problems is of great significance. The split attention network is an improvement of the residual network, and it is an improvement of the visual attention mechanism in the bionic algorithm. In this paper, based on the feature pyramid network and split attention network, the network is improved and optimised in terms of data enhancement, multi-scale feature fusion and network structure optimisation. The DF-ResNeSt50 network model is proposed, which introduces a simple modularized split attention block, which can improve the attention mechanism of cross-feature graph groups. Finally, experimental validation proves that the proposed network model has good performance and application prospects in the intelligent detection of steel defects.

Induced pluripotency in the context of stem cell expansion bioprocess development, optimization, and manufacturing: a roadmap to the clinic

The translation of laboratory-scale bioprocess protocols and technologies to industrial scales and the application of human induced pluripotent stem cell (hiPSC) derivatives in clinical trials globally presents optimism for the future of stem-cell products to impact healthcare. However, while many promising therapeutic approaches are being tested in pre-clinical studies, hiPSC-derived products currently account for a small fraction of active clinical trials. The complexity and volatility of hiPSCs present several bioprocessing challenges, where the goal is to generate a sufficiently large, high-quality, homogeneous population for downstream differentiation-the derivatives of which must retain functional efficacy and meet regulatory safety criteria in application. It is argued herein that one of the major challenges currently faced in improving the robustness of routine stem-cell biomanufacturing is in utilizing continuous, meaningful assessments of molecular and cellular characteristics from process to application. This includes integrating process data with biological characteristic and functional assessment data to model the interplay between variables in the search for global optimization strategies. Coupling complete datasets with relevant computational methods will contribute significantly to model development and automation in achieving process robustness. This overarching approach is thus crucially important in realizing the potential of hiPSC biomanufacturing for transformation of regenerative medicine and the healthcare industry.

Optimized Manufacture of Lyophilized Dermal Fibroblasts for Next-Generation Off-the-Shelf Progenitor Biological Bandages in Topical Post-Burn Regenerative Medicine

Cultured fibroblast progenitor cells (FPC) have been studied in Swiss translational regenerative medicine for over two decades, wherein clinical experience was gathered for safely managing burns and refractory cutaneous ulcers. Inherent FPC advantages include high robustness, optimal adaptability to industrial manufacture, and potential for effective repair stimulation of wounded tissues. Major technical bottlenecks in cell therapy development comprise sustainability, stability, and logistics of biological material sources. Herein, we report stringently optimized and up-scaled processing (i.e., cell biobanking and stabilization by lyophilization) of dermal FPCs, with the objective of addressing potential cell source sustainability and stability issues with regard to active substance manufacturing in cutaneous regenerative medicine. Firstly, multi-tiered FPC banking was optimized in terms of overall quality and efficiency by benchmarking key reagents (e.g., medium supplement source, dissociation reagent), consumables (e.g., culture vessels), and technical specifications. Therein, fetal bovine serum batch identity and culture vessel surface were confirmed, among other parameters, to largely impact harvest cell yields. Secondly, FPC stabilization by lyophilization was undertaken and shown to maintain critical functions for devitalized cells in vitro, potentially enabling high logistical gains. Overall, this study provides the technical basis for the elaboration of next-generation off-the-shelf topical regenerative medicine therapeutic products for wound healing and post-burn care.

Effects of Surface Chemistry Interaction on Primary Neural Stem Cell Neurosphere Responses

The characteristics of a material's surface are extremely important when considering their interactions with biological species. Despite surface chemistry playing a critical role in mediating the responses of cells, there remains no single rule which dictates absolute performance; this is particularly challenging when considering the response of differing cell types to a range of materials. Here, we highlight the functional behavior of neural stem cells presented as neurospheres, with respect to a range of alkane-based self-assembled monolayers presenting different functional groups: OH, CO₂H, NH₂, phenyl, CH₃, SH, and laminin. The influence of chemical cues was examined in terms of neurosphere spreading on each of these defined surfaces (cell adhesion and migration capacity) and neuronal versus glial marker expression. Measurements were made over a time series of 3, 5, and 7 days, showing a dynamic nature to the initial responses observed after seeding. While OH surfaces presented an excellent platform for glial migration, larger proportions of cells expressing neuronal β₃-tubulin were found on SH- and laminin-coated surfaces. Axonal elongation was found to be initially similar on all surfaces with neurite lengths having a wider spread predominantly on NH₂- and laminin-presenting surfaces. A generalized trend could not be found to correlate cellular responses with surface wettability, lipophilicity (log P), or charge/ionizability (pK _a). These results highlight the potential for chemical cues to direct primary neural stem cell responses in contact with the defined materials. New biomaterials which control specific cell culture characteristics in vitro will streamline the up-scale manufacture of cellular therapies, with the enrichment of the required populations resulting from a defined material interaction.

SpheroidPicker for automated 3D cell culture manipulation using deep learning

Recent statistics report that more than 3.7 million new cases of cancer occur in Europe yearly, and the disease accounts for approximately 20% of all deaths. High-throughput screening of cancer cell cultures has dominated the search for novel, effective anticancer therapies in the past decades. Recently, functional assays with patient-derived ex vivo 3D cell culture have gained importance for drug discovery and precision medicine. We recently evaluated the major advancements and needs for the 3D cell culture screening, and concluded that strictly standardized and robust sample preparation is the most desired development. Here we propose an artificial intelligence-guided low-cost 3D cell culture delivery system. It consists of a light microscope, a micromanipulator, a syringe pump, and a controller computer. The system performs morphology-based feature analysis on spheroids and can select uniform sized or shaped spheroids to transfer them between various sample holders. It can select the samples from standard sample holders, including Petri dishes and microwell plates, and then transfer them to a variety of holders up to 384 well plates. The device performs reliable semi- and fully automated spheroid transfer. This results in highly controlled experimental conditions and eliminates non-trivial side effects of sample variability that is a key aspect towards next-generation precision medicine.

Scaffold-free cell-based tissue engineering therapies: advances, shortfalls and forecast

Cell-based scaffold-free therapies seek to develop in vitro organotypic three-dimensional (3D) tissue-like surrogates, capitalising upon the inherent capacity of cells to create tissues with efficiency and sophistication that is still unparalleled by human-made devices. Although automation systems have been realised and (some) success stories have been witnessed over the years in clinical and commercial arenas, in vitro organogenesis is far from becoming a standard way of care. This limited technology transfer is largely attributed to scalability-associated costs, considering that the development of a borderline 3D implantable device requires very high number of functional cells and prolonged ex vivo culture periods. Herein, we critically discuss advancements and shortfalls of scaffold-free cell-based tissue engineering strategies, along with pioneering concepts that have the potential to transform regenerative and reparative medicine.

Regenerative medicine clinical readiness

Regenerative medicine, poised to transform 21st century healthcare, has aspired to enrich care options by bringing cures to patients in need. Science-driven responsible and regulated translation of innovative technology has enabled the launch of previously unimaginable care pathways adopted prudently for select serious diseases and disabilities. The collective resolve to advance the design, manufacture and validity of affordable regenerative solutions aims to democratize such health benefits for all. The objective of this Review is to outline the framework and prerequisites that underpin clinical readiness of regenerative care. Integrated research and development, specialized workforce education and accessible evidence-based practice implementation are at the core of realizing an equitable regenerative medicine vision.

Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status

Human induced pluripotent stem cells (hiPSCs) are capable of differentiating into a variety of human tissue cells. They offer new opportunities for personalized medicine and drug screening. This requires large quantities of high quality hiPSCs, obtainable only via automated cultivation. One of the major requirements of an automated cultivation is a regular, non-invasive analysis of the cell condition, e.g. by whole-well microscopy. However, despite the urgency of this requirement, there are currently no automatic, image-processing-based solutions for multi-class routine quantification of this nature. This paper describes a method to fully automate the cell state recognition based on phase contrast microscopy and deep-learning. This approach can be used for in process control during an automated hiPSC cultivation. The U-Net based algorithm is capable of segmenting important parameters of hiPSC colony formation and can discriminate between the classes hiPSC colony, single cells, differentiated cells and dead cells. The model achieves more accurate results for the classes hiPSC colonies, differentiated cells, single hiPSCs and dead cells than visual estimation by a skilled expert. Furthermore, parameters for each hiPSC colony are derived directly from the classification result such as roundness, size, center of gravity and inclusions of other cells. These parameters provide localized information about the cell state and enable well based treatment of the cell culture in automated processes. Thus, the model can be exploited for routine, non-invasive image analysis during an automated hiPSC cultivation. This facilitates the generation of high quality hiPSC derived products for biomedical purposes.

Automation in the Life Science Research Laboratory

Protocols in the academic life science laboratory are heavily reliant on the manual manipulation of tools, reagents and instruments by a host of research staff and students. In contrast to industrial and clinical laboratory environments, the usage of automation to augment or replace manual tasks is limited. Causes of this 'automation gap' are unique to academic research, with rigid short-term funding structures, high levels of protocol variability and a benevolent culture of investment in people over equipment. Automation, however, can bestow multiple benefits through improvements in reproducibility, researcher efficiency, clinical translation, and safety. Less immediately obvious are the accompanying limitations, including obsolescence and an inhibitory effect on the freedom to innovate. Growing the range of automation options suitable for research laboratories will require more flexible, modular and cheaper designs. Academic and commercial developers of automation will increasingly need to design with an environmental awareness and an understanding that large high-tech robotic solutions may not be appropriate for laboratories with constrained financial and spatial resources. To fully exploit the potential of laboratory automation, future generations of scientists will require both engineering and biology skills. Automation in the research laboratory is likely to be an increasingly critical component of future research programs and will continue the trend of combining engineering and science expertise together to answer novel research questions.

Development of a bio-inkjet printed LAMP test kit for detecting human African trypanosomiasis

Human African trypanosomiasis (HAT) is one of the neglected tropical diseases in sub-Saharan Africa. Early diagnosis and treatment prior to disease progression are crucial for the survival of HAT patients. We had previously established a loop-mediated isothermal amplification (LAMP) method for HAT diagnosis in which the reagents were dried for field-use purposes. In this study, we used a semi-automated process to produce the test tubes using a bio-inkjet printer to achieve an accurate production. The performance of the inkjet printer-produced dried LAMP test (CZC-LAMP) was found to be stable after storage for up to 180 days at 30 °C. The diagnostic accuracy of CZC-LAMP HAT was evaluated using DNA samples that were extracted from 116 Trypanosoma brucei gambiense patients and 66 T. b. rhodesiense patients. The sensitivity was 72% for T. b. gambiense (95%CI: 63%-80%) and 80% for T. b. rhodesiense (95%CI: 69%-89%). The specificity determined using DNA from 116 endemic control DNA samples was 95% (95%CI: 89%-98%). The performance of the CZC-LAMP HAT and CZC-LAMP rHAT were also evaluated using 14 crude blood lysate samples obtained from T. b. rhodesiense patients and endemic control samples collected from Rumphi District in Malawi. The sensitivity and specificity were both 100% (95%CI: 77%-100%). As the developed CZC-LAMP test does not require a cold chain or a sophisticated laboratory, it holds promise for use as a routine simple molecular tool for point-of-care HAT diagnosis in endemic areas.