The StemCellFactory: A Modular System Integration for Automated Generation and Expansion of Human Induced Pluripotent Stem Cells

Advancements in kidney organoids and tubuloids to study (dys)function

The rising prevalence of kidney diseases urges the need for novel therapies. Kidney organoids and tubuloids are advanced in vitro models and have recently been described as promising tools to study kidney (patho)physiology. Recent developments have shown their application in disease modeling, drug screening, and nephrotoxicity. These applications rely on their ability to mimic (dys)function in vitro including endocrine activity and drug, electrolyte, and water transport. This review provides an overview of these emerging kidney models and focuses on the most recent developments that utilize their functional capabilities. In addition, we cover current limitations and provide future perspectives for this rapidly evolving field, including what these functional properties mean for translational and personalized medicine now and in the future.

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.

Automated human induced pluripotent stem cell colony segmentation for use in cell culture automation applications

Human induced pluripotent stem cells (hiPSCs) have demonstrated great promise for a variety of applications that include cell therapy and regenerative medicine. Production of clinical grade hiPSCs requires reproducible manufacturing methods with stringent quality-controls such as those provided by image-controlled robotic processing systems. In this paper we present an automated image analysis method for identifying and picking hiPSC colonies for clonal expansion using the CellXTM robotic cell processing system. This method couples a light weight deep learning segmentation approach based on the U-Net architecture to automatically segment the hiPSC colonies in full field of view (FOV) high resolution phase contrast images with a standardized approach for suggesting pick locations. The utility of this method is demonstrated using images and data obtained from the CellXTM system where clinical grade hiPSCs were reprogrammed, clonally expanded, and differentiated into retinal organoids for use in treatment of patients with inherited retinal degenerative blindness.

Overcoming the Variability of iPSCs in the Manufacturing of Cell-Based Therapies

Various factors are known to contribute to the diversity of human induced pluripotent stem cells (hiPSCs). Among these are the donor's genetic background and family history, the somatic cell source, the iPSC reprogramming method, and the culture system of choice. Moreover, variability is seen even in iPSC clones, generated in a single reprogramming event, where the donor, somatic cell type, and reprogramming platform are the same. The diversity seen in iPSC lines often translates to epigenetic differences, as well as to differences in the expansion rate, iPSC line culture robustness, and their ability to differentiate into specific cell types. As such, the diversity of iPSCs presents a hurdle to standardizing iPSC-based cell therapy manufacturing. In this review, we will expand on the various factors that impact iPSC diversity and the strategies and tools that could be taken by the industry to overcome the differences amongst various iPSC lines, therefore enabling robust and reproducible iPSC-based cell therapy manufacturing processes.

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.

Application-Oriented Bulk Cryopreservation of Human iPSCs in Cryo Bags Followed by Direct Inoculation in Scalable Suspension Bioreactors for Expansion and Neural Differentiation

Stem cell-based therapies are promising tools for regenerative medicine and require bulk numbers of high-quality cells. Currently, cells are produced on demand and have a limited shelf-life as conventional cryopreservation is primarily designed for stock keeping. We present a study on bulk cryopreservation of the human iPSC lines UKKi011-A and BIONi010-C-41. By increasing cell concentration and volume, compared to conventional cryopreservation routines in cryo vials, one billion cells were frozen in 50 mL cryo bags. Upon thawing, the cells were immediately seeded in scalable suspension-based bioreactors for expansion to assess the stemness maintenance and for neural differentiation to assess their differentiation potential on the gene and protein levels. Both the conventional and bulk cryo approach show comparative results regarding viability and aggregation upon thawing and bioreactor inoculation. Reduced performance compared to the non-frozen control was compensated within 3 days regarding biomass yield. Stemness was maintained upon thawing in expansion. In neural differentiation, a delay of the neural marker expression on day 4 was compensated at day 9. We conclude that cryopreservation in cryo bags, using high cell concentrations and volumes, does not alter the cells' fate and is a suitable technology to avoid pre-cultivation and enable time- and cost-efficient therapeutic approaches with bulk cell numbers.

Engineering considerations of iPSC-based personalized medicine

Personalized medicine aims to provide tailored medical treatment that considers the clinical, genetic, and environmental characteristics of patients. iPSCs have attracted considerable attention in the field of personalized medicine; however, the inherent limitations of iPSCs prevent their widespread use in clinical applications. That is, it would be important to develop notable engineering strategies to overcome the current limitations of iPSCs. Such engineering approaches could lead to significant advances in iPSC-based personalized therapy by offering innovative solutions to existing challenges, from iPSC preparation to clinical applications. In this review, we summarize how engineering strategies have been used to advance iPSC-based personalized medicine by categorizing the development process into three distinctive steps: 1) the production of therapeutic iPSCs; 2) engineering of therapeutic iPSCs; and 3) clinical applications of engineered iPSCs. Specifically, we focus on engineering strategies and their implications for each step in the development of iPSC-based personalized medicine.

Propensity of Patient-Derived iPSCs for Retinal Differentiation: Implications for Autologous Cell Replacement

Prior to use, newly generated induced pluripotent stem cells (iPSC) should be thoroughly validated. While excellent validation and release testing assays designed to evaluate potency, genetic integrity, and sterility exist, they do not have the ability to predict cell type-specific differentiation capacity. Selection of iPSC lines that have limited capacity to produce high-quality transplantable cells, places significant strain on valuable clinical manufacturing resources. The purpose of this study was to determine the degree and root cause of variability in retinal differentiation capacity between cGMP-derived patient iPSC lines. In turn, our goal was to develop a release testing assay that could be used to augment the widely used ScoreCard panel. IPSCs were generated from 15 patients (14-76 years old), differentiated into retinal organoids, and scored based on their retinal differentiation capacity. Despite significant differences in retinal differentiation propensity, RNA-sequencing revealed remarkable similarity between patient-derived iPSC lines prior to differentiation. At 7 days of differentiation, significant differences in gene expression could be detected. Ingenuity pathway analysis revealed perturbations in pathways associated with pluripotency and early cell fate commitment. For example, good and poor producers had noticeably different expressions of OCT4 and SOX2 effector genes. QPCR assays targeting genes identified via RNA sequencing were developed and validated in a masked fashion using iPSCs from 8 independent patients. A subset of 14 genes, which include the retinal cell fate markers RAX, LHX2, VSX2, and SIX6 (all elevated in the good producers), were found to be predictive of retinal differentiation propensity.

Automating iPSC generation to enable autologous photoreceptor cell replacement therapy

BACKGROUND

Inherited retinal degeneration is a leading cause of incurable vision loss in the developed world. While autologous iPSC mediated photoreceptor cell replacement is theoretically possible, the lack of commercially available technologies designed to enable high throughput parallel production of patient specific therapeutics has hindered clinical translation.

METHODS

In this study, we describe the use of the Cell X precision robotic cell culture platform to enable parallel production of clinical grade patient specific iPSCs. The Cell X is housed within an ISO Class 5 cGMP compliant closed aseptic isolator (Biospherix XVivo X2), where all procedures from fibroblast culture to iPSC generation, clonal expansion and retinal differentiation were performed.

RESULTS

Patient iPSCs generated using the Cell X platform were determined to be pluripotent via score card analysis and genetically stable via karyotyping. As determined via immunostaining and confocal microscopy, iPSCs generated using the Cell X platform gave rise to retinal organoids that were indistinguishable from organoids derived from manually generated iPSCs. In addition, at 120 days post-differentiation, single-cell RNA sequencing analysis revealed that cells generated using the Cell X platform were comparable to those generated under manual conditions in a separate laboratory.

CONCLUSION

We have successfully developed a robotic iPSC generation platform and standard operating procedures for production of high-quality photoreceptor precursor cells that are compatible with current good manufacturing practices. This system will enable clinical grade production of iPSCs for autologous retinal cell replacement.

Stem cell programming - prospects for perinatal medicine

Recreating human cell and organ systems in vitro has tremendous potential for disease modeling, drug discovery and regenerative medicine. The aim of this short overview is to recapitulate the impressive progress that has been made in the fast-developing field of cell programming during the past years, to illuminate the advantages and limitations of the various cell programming technologies for addressing nervous system disorders and to gauge their impact for perinatal medicine.

Emergence of nociceptive functionality and opioid signaling in human induced pluripotent stem cell-derived sensory neurons

ABSTRACT

Induced pluripotent stem cells (iPSCs) have enabled the generation of various difficult-to-access cell types such as human nociceptors. A key challenge associated with human iPSC-derived nociceptors (hiPSCdNs) is their prolonged functional maturation. While numerous studies have addressed the expression of classic neuronal markers and ion channels in hiPSCdNs, the temporal development of key signaling cascades regulating nociceptor activity has remained largely unexplored. In this study, we used an immunocytochemical high-content imaging approach alongside electrophysiological staging to assess metabotropic and ionotropic signaling of large scale-generated hiPSCdNs across 70 days of in vitro differentiation. During this period, the resting membrane potential became more hyperpolarized, while rheobase, action potential peak amplitude, and membrane capacitance increased. After 70 days, hiPSCdNs exhibited robust physiological responses induced by GABA, pH shift, ATP, and capsaicin. Direct activation of protein kinase A type II (PKA-II) through adenylyl cyclase stimulation with forskolin resulted in PKA-II activation at all time points. Depolarization-induced activation of PKA-II emerged after 35 days of differentiation. However, effective inhibition of forskolin-induced PKA-II activation by opioid receptor agonists required 70 days of in vitro differentiation. Our results identify a pronounced time difference between early expression of functionally important ion channels and emergence of regulatory metabotropic sensitizing and desensitizing signaling only at advanced stages of in vitro cultivation, suggesting an independent regulation of ionotropic and metabotropic signaling. These data are relevant for devising future studies into the development and regulation of human nociceptor function and for defining time windows suitable for hiPSCdN-based drug discovery.

Bringing to light the physiological and pathological firing patterns of human induced pluripotent stem cell-derived neurons using optical recordings

Human induced pluripotent stem cells (hiPSCs) are a promising approach to study neurological and neuropsychiatric diseases. Most methods to record the activity of these cells have major drawbacks as they are invasive or they do not allow single cell resolution. Genetically encoded voltage indicators (GEVIs) open the path to high throughput visualization of undisturbed neuronal activity. However, conventional GEVIs perturb membrane integrity through inserting multiple copies of transmembrane domains into the plasma membrane. To circumvent large add-ons to the plasma membrane, we used a minimally invasive novel hybrid dark quencher GEVI to record the physiological and pathological firing patterns of hiPSCs-derived sensory neurons from patients with inherited erythromelalgia, a chronic pain condition associated with recurrent attacks of redness and swelling in the distal extremities. We observed considerable differences in action potential firing patterns between patient and control neurons that were previously overlooked with other recording methods. Our system also performed well in hiPSC-derived forebrain neurons where it detected spontaneous synchronous bursting behavior, thus opening the path to future applications in other cell types and disease models including Parkinson's disease, Alzheimer's disease, epilepsy, and schizophrenia, conditions associated with disturbances of neuronal activity and synchrony.

Quality Control of Human Pluripotent Stem Cell Colonies by Computational Image Analysis Using Convolutional Neural Networks

Human pluripotent stem cells are promising for a wide range of research and therapeutic purposes. Their maintenance in culture requires the deep control of their pluripotent and clonal status. A non-invasive method for such control involves day-to-day observation of the morphological changes, along with imaging colonies, with the subsequent automatic assessment of colony phenotype using image analysis by machine learning methods. We developed a classifier using a convolutional neural network and applied it to discriminate between images of human embryonic stem cell (hESC) colonies with "good" and "bad" morphological phenotypes associated with a high and low potential for pluripotency and clonality maintenance, respectively. The training dataset included the phase-contrast images of hESC line H9, in which the morphological phenotype of each colony was assessed through visual analysis. The classifier showed a high level of accuracy (89%) in phenotype prediction. By training the classifier on cropped images of various sizes, we showed that the spatial scale of ~144 μm was the most informative in terms of classification quality, which was an intermediate size between the characteristic diameters of a single cell (~15 μm) and the entire colony (~540 μm). We additionally performed a proteomic analysis of several H9 cell samples used in the computational analysis and showed that cells of different phenotypes differentiated at the molecular level. Our results indicated that the proposed approach could be used as an effective method of non-invasive automated analysis to identify undesirable developmental anomalies during the propagation of pluripotent stem cells.

Dendritic cells generated from induced pluripotent stem cells and by direct reprogramming of somatic cells

Novel and exciting avenues allow generating dendritic cells (DC) by reprogramming of somatic cells. DC are obtained from induced pluripotent stem cells (iPS cells), referred to as ipDC, and by direct reprogramming of cells toward DC, referred to as induced DC (iDC). iPS cells represent pluripotent stem cells generated by reprogramming of somatic cells and can differentiate into all cell types of the body, including DC. This makes iPS cells and ipDC derived thereof useful for studying various DC subsets, acquiring high cell numbers for research and clinical use, or applying genome editing to generate DC with wanted properties. Thereby, ipDC overcome limitations in specific DC subsets, which are only found in low abundance in blood or lymphoid organs. iDC are generated by direct reprogramming of somatic cells with a specific set of transcription factors and offer an avenue to obtain DC without a pluripotent cell intermediate. ipDC and iDC retain patient and disease-specific mutations and this opens new perspectives for studying DC in disease. This review summarizes the current techniques used to generate ipDC and iDC, and the types and functionality of the DC generated.

Additively Manufactured Robot Gripper Blades for Automated Cell Production Processes

The automation of cell production processes demands strict requirements with regard to sterility, reliability, and flexibility. Robots work in such environments as transporting devices for a huge variety of disposables, e.g., cell plates, tubes, cassettes, and other objects. Therefore, the blades of their grippers must be designed to hold all of these different materials in a stable, gentle manner, and in defined positions, which means that the blades require complex geometries. Furthermore, they should have as few edges as possible, so as to be easy to clean. In this report, we demonstrate how these requirements can be met by producing stainless steel robot grippers by additive manufacturing.

Cell Cluster Sorting in Automated Differentiation of Patient-specific Induced Pluripotent Stem Cells Towards Blood Cells

Induced pluripotent stem cells (iPS cells) represent a particularly versatile stem cell type for a large array of applications in biology and medicine. Taking full advantage of iPS cell technology requires high throughput and automated iPS cell culture and differentiation. We present an automated platform for efficient and robust iPS cell culture and differentiation into blood cells. We implemented cell cluster sorting for analysis and sorting of iPS cell clusters in order to establish clonal iPS cell lines with high reproducibility and efficacy. Patient-specific iPS cells were induced to differentiate towards hematopoietic cells via embryoid body (EB) formation. EB size impacts on iPS cell differentiation and we applied cell cluster sorting to obtain EB of defined size for efficient blood cell differentiation. In summary, implementing cell cluster sorting into the workflow of iPS cell cloning, growth and differentiation represent a valuable add-on for standard and automated iPS cell handling.

Advances in hPSC expansion towards therapeutic entities: A review

For use in regenerative medicine, large‐scale manufacturing of human pluripotent stem cells (hPSCs) under current good manufacturing practice (cGMPs) is required. Much progress has been made since culturing under static two‐dimensional (2D) conditions on feeders, including feeder‐free cultures, conditioned and xeno‐free media, and three‐dimensional (3D) dynamic suspension expansion. With the advent of horizontal‐blade and vertical‐wheel bioreactors, scale‐out for large‐scale production of differentiated hPSCs became possible; control of aggregate size, shear stress, fluid hydrodynamics, batch‐feeding strategies, and other process parameters became a reality. Moving from substantially manipulated processes (i.e., 2D) to more automated ones allows easer compliance to current good manufacturing practices (cGMPs), and thus easier regulatory approval. Here, we review the current advances in the field of hPSC culturing, advantages, and challenges in bioreactor use, and regulatory areas of concern with respect to these advances. Manufacturing trends to reduce risk and streamline large‐scale manufacturing will bring about easier, faster regulatory approval for clinical applications.

Testing Mitochondrial-Targeted Drugs in iPSC-RPE from Patients with Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. No universally effective treatments exist for atrophic or “dry” AMD, which results from loss of the retinal pigment epithelium (RPE) and photoreceptors and accounts for ≈80% of all AMD patients. Prior studies provide evidence for the involvement of mitochondrial dysfunction in AMD pathology. This study used induced pluripotent stem cell (iPSC) RPE derived from five AMD patients to test the efficacy of three drugs (AICAR (5-Aminoimidazole-4-carboxamide ribonucleotide), Metformin, trehalose) that target key processes in maintaining optimal mitochondrial function. The patient iPSC-RPE lines were used in a proof-of-concept drug screen, utilizing an analysis of RPE mitochondrial function following acute and extended drug exposure. Results show considerable variability in drug response across patient cell lines, supporting the need for a personalized medicine approach for treating AMD. Furthermore, our results demonstrate the feasibility of using iPSC-RPE from AMD patients to develop a personalized drug treatment regime and provide a roadmap for the future clinical management of AMD.

Automating Laboratory Processes by Connecting Biotech and Robotic Devices—An Overview of the Current Challenges, Existing Solutions and Ongoing Developments

The constantly growing interest and range of applications of advanced cell, gene and regenerative therapies raise the need for efficient production of biological material and novel treatment technologies. Many of the production and manipulation processes of such materials are still manual and, therefore, need to be transferred to a fully automated execution. Developers of such systems face several challenges, one of which is mechanical and communication interfaces in biotechnological devices. In the present state, many devices are still designed for manual use and rarely provide a connection to external software for receiving commands and sending data. However, a trend towards automation on the device market is clearly visible, and the communication protocol, Open Platform Communications Data Access (OPC DA), seems to become established as a standard in biotech devices. A rising number of vendors offer software for device control and automated processing, some of which even allow the integration of devices from multiple manufacturers. The high, application-specific need in functionalities, flexibility and adaptivity makes it difficult to find the best solution and, in many cases, leads to the creation of new custom-designed software. This report shall give an overview of existing technologies, devices and software for laboratory automation of biotechnological processes. Furthermore, it presents an outlook for possible future developments and standardizations.

Fully Automated Cultivation of Adipose-Derived Stem Cells in the StemCellDiscovery—A Robotic Laboratory for Small-Scale, High-Throughput Cell Production Including Deep Learning-Based Confluence Estimation

Laboratory automation is a key driver in biotechnology and an enabler for powerful new technologies and applications. In particular, in the field of personalized therapies, automation in research and production is a prerequisite for achieving cost efficiency and broad availability of tailored treatments. For this reason, we present the StemCellDiscovery, a fully automated robotic laboratory for the cultivation of human mesenchymal stem cells (hMSCs) in small scale and in parallel. While the system can handle different kinds of adherent cells, here, we focus on the cultivation of adipose-derived hMSCs. The StemCellDiscovery provides an in-line visual quality control for automated confluence estimation, which is realized by combining high-speed microscopy with deep learning-based image processing. We demonstrate the feasibility of the algorithm to detect hMSCs in culture at different densities and calculate confluences based on the resulting image. Furthermore, we show that the StemCellDiscovery is capable of expanding adipose-derived hMSCs in a fully automated manner using the confluence estimation algorithm. In order to estimate the system capacity under high-throughput conditions, we modeled the production environment in a simulation software. The simulations of the production process indicate that the robotic laboratory is capable of handling more than 95 cell culture plates per day.

Techno-Economic Analysis of Automated iPSC Production

Induced pluripotent stem cells (iPSC) open up the unique perspective of manufacturing cell products for drug development and regenerative medicine in tissue-, disease- and patient-specific forms. iPSC can be multiplied almost without restriction and differentiated into cell types of all organs. The basis for clinical use of iPSC is a high number of cells (approximately 7 × 107 cells per treatment), which must be produced cost-effectively while maintaining reproducible and high quality. Compared to manual cell production, the automation of cell production offers a unique chance of reliable reproducibility of cells in addition to cost reduction and increased throughput. StemCellFactory is a prototype for a fully automated production of iPSC. However, in addition to the already tested functionality of the system, it must be shown that this automation brings necessary economic advantages. This paper presents that fully automated stem cell production offers economic advantages in addition to increased throughput and better quality. First, biological and technological basics for a fully automated production of iPSC are presented. Second, the basics for profitability calculation are presented. Third, profitability of both manual and automated production are calculated. Finally, different scenarios effecting the profitability of manual and automated production are compared.

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.