Robotic high-throughput biomanufacturing and functional differentiation of human pluripotent stem cells

Automated manufacturing of cell therapies

Advanced therapy medicinal products (ATMPs), particularly genetically engineered cell-based therapies, are a major class of drugs with several high-profile Food and Drug Administration (FDA) approvals in the past decade. However, the high cost and limited production capacity of these drugs remain a barrier to access. These costs are primarily due to the complex manufacturing processes (often a single batch for a single patient), which increases personnel and facility expenses, and the challenges associated with tech-transfer from research and development stages to clinical-stage production. In order to scale up and scale out in a cost-effective way, automated solutions capable of multi-step manufacturing have been developed in academia and industry. The aim of the present article is to summarize the design approaches and key features of current multi-step automated systems for cell therapy manufacturing. For each system described in the literature, we will discuss different aspects in detail such as cell specificity, modularity, processing models, manufacturing locations, and integrated quality control. Our analysis highlights that developers need to balance competing needs in an environment where the biological, business, and technological factors are constantly evolving. Thus, designing engineering solutions that align with the pharmaceutical end-user is essential. Adopting a risk-based approach grounded in published data is the most effective strategy to evaluate existing and emerging automated systems.

Scaling up pluripotent stem cell-based therapies - considerations, current challenges and emerging technologies: perspectives from the ISCT Emerging Regenerative Medicine Working Group

Approval of induced pluripotent stem cells (iPSCs) for the manufacture of cell therapies to support clinical trials is now becoming realized after more than 20 years of research and development. However, manufacturing these therapies at the scale required for patient treatment, as well as for key clinical trial enabling activities such as preclinical and stability studies, remains a challenge. In 2022 the International Society for Cell and Gene Therapy (ISCT) established a Working Group on Emerging Regenerative Medicine Technologies, an area in which iPSC-derived technologies are expected to play a key role. In this article, the Working Group provides an overview of the considerations and challenges facing stem cell therapy developers, including development-stage specific manufacturing processes, the decision on when to implement automation, the choice of technology and different requirements of expansion and differentiation aspects of the process, and the integration of automation for both manufacturing and analytics in an end-to-end manufacturing process. The role of scalable manufacturing technologies in the application of quality-by-design approaches to product development, and the use of design-of-experiment approaches for increased product characterization, is discussed. Finally, we provide an in-depth review of the different technologies that have been used for expansion and differentiation of iPSC-derived therapies to date, including compatibility with good manufacturing practice requirements and process analytical technologies. We hope that this overview will summarize the existing knowledge in the field and reduce the challenges that therapy developers face in translating their research into clinical and commercial scale manufacturing.

Advances in physiological and clinical relevance of hiPSC-derived brain models for precision medicine pipelines

Precision, or personalized, medicine aims to stratify patients based on variable pathogenic signatures to optimize the effectiveness of disease prevention and treatment. This approach is favorable in the context of brain disorders, which are often heterogeneous in their pathophysiological features, patterns of disease progression and treatment response, resulting in limited therapeutic standard-of-care. Here we highlight the transformative role that human induced pluripotent stem cell (hiPSC)-derived neural models are poised to play in advancing precision medicine for brain disorders, particularly emerging innovations that improve the relevance of hiPSC models to human physiology. hiPSCs derived from accessible patient somatic cells can produce various neural cell types and tissues; current efforts to increase the complexity of these models, incorporating region-specific neural tissues and non-neural cell types of the brain microenvironment, are providing increasingly relevant insights into human-specific neurobiology. Continued advances in tissue engineering combined with innovations in genomics, high-throughput screening and imaging strengthen the physiological relevance of hiPSC models and thus their ability to uncover disease mechanisms, therapeutic vulnerabilities, and tissue and fluid-based biomarkers that will have real impact on neurological disease treatment. True physiological understanding, however, necessitates integration of hiPSC-neural models with patient biophysical data, including quantitative neuroimaging representations. We discuss recent innovations in cellular neuroscience that can provide these direct connections through generative AI modeling. Our focus is to highlight the great potential of synergy between these emerging innovations to pave the way for personalized medicine becoming a viable option for patients suffering from neuropathologies, particularly rare epileptic and neurodegenerative disorders.

AI-Based solutions for current challenges in regenerative medicine

The emergence of Artificial Intelligence (AI) and its usage in regenerative medicine represents a significant opportunity that holds the promise of tackling critical challenges and improving therapeutic outcomes. This article examines the ways in which AI, including machine learning and data fusion techniques, can contribute to regenerative medicine, particularly in gene therapy, stem cell therapy, and tissue engineering. In gene therapy, AI tools can boost the accuracy and safety of treatments by analyzing extensive genomic datasets to target and modify genetic material in a precise manner. In cell therapy, AI improves the characterization and optimization of cell products like mesenchymal stem cells (MSCs) by predicting their function and potency. Additionally, AI enhances advanced microscopy techniques, enabling accurate, non-invasive and quantitative analyses of live cell cultures. AI enhances tissue engineering by optimizing biomaterial and scaffold designs, predicting interactions with tissues, and streamlining development. This leads to faster and more cost-effective innovations by decreasing trial and error. The convergence of AI and regenerative medicine holds great transformative potential, promising effective treatments and innovative therapeutic strategies. This review highlights the importance of interdisciplinary collaboration and the continued integration of AI-based technologies, such as data fusion methods, to overcome current challenges and advance regenerative medicine.

Embryonic Stem Cell Differentiation to Definitive Endoderm As a Model of Heterogeneity Onset During Germ Layer Specification

Embryonic stem cells (ESCs) hold great promise for regenerative medicine thanks to their ability to self-renew and differentiate into somatic cells and the germline. ESCs correspond to pluripotent epiblast - the tissue from which the following three germ layers originate during embryonic gastrulation: the ectoderm, mesoderm, and endoderm. Importantly, ESCs can be induced to differentiate toward various cell types by varying culture conditions, which can be exploited for in vitro modeling of developmental processes such as gastrulation. The classical model of gastrulation postulates that mesoderm and endoderm specification is made possible through the FGF-, BMP-, Wnt-, and Nodal-signaling gradients. Hence, it can be expected that one of these signals should direct ESC differentiation towards specific germ layers. However, ESC specification appears to be more complicated, and the same signal can be interpreted differently depending on the readout. In this research, using chemically defined culture conditions, homogeneous naïve ESCs as a starting cell population, and the Foxa2 gene-driven EGFP reporter tool, we established a robust model of definitive endoderm (DE) specification. This in vitro model features formative pluripotency as an intermediate state acquired by the epiblast in vivo shortly after implantation. Despite the initially homogeneous state of the cells in the model and high Activin concentration during endodermal specification, there remains a cell subpopulation that does not reach the endodermal state. This simple model developed by us can be used to study the origins of cellular heterogeneity during germ layer specification.

Scalable Hypothalamic Arcuate Neuron Differentiation from Human Pluripotent Stem Cells Suitable for Modeling Metabolic and Reproductive Disorders

The hypothalamus, composed of several nuclei, is essential for maintaining our body's homeostasis. The arcuate nucleus (ARC), located in the mediobasal hypothalamus, contains neuronal populations with eminent roles in energy and glucose homeostasis as well as reproduction. These neuronal populations are of great interest for translational research. To fulfill this promise, we used a robotic cell culture platform to provide a scalable and chemically defined approach for differentiating human pluripotent stem cells (hPSCs) into pro-opiomelanocortin (POMC), somatostatin (SST), tyrosine hydroxylase (TH) and gonadotropin-releasing hormone (GnRH) neuronal subpopulations with an ARC-like signature. This robust approach is reproducible across several distinct hPSC lines and exhibits a stepwise induction of key ventral diencephalon and ARC markers in transcriptomic profiling experiments. This is further corroborated by direct comparison to human fetal hypothalamus, and the enriched expression of genes implicated in obesity and type 2 diabetes (T2D). Genome-wide chromatin accessibility profiling by ATAC-seq identified accessible regulatory regions that can be utilized to predict candidate enhancers related to metabolic disorders and hypothalamic development. In depth molecular, cellular, and functional experiments unveiled the responsiveness of the hPSC-derived hypothalamic neurons to hormonal stimuli, such as insulin, neuropeptides including kisspeptin, and incretin mimetic drugs such as Exendin-4, highlighting their potential utility as physiologically relevant cellular models for disease studies. In addition, differential glucose and insulin treatments uncovered adaptability within the generated ARC neurons in the dynamic regulation of POMC and insulin receptors. In summary, the establishment of this model represents a novel, chemically defined, and scalable platform for manufacturing large numbers of hypothalamic arcuate neurons and serves as a valuable resource for modeling metabolic and reproductive disorders.

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.

hPSC-Derived Astrocytes at the Forefront of Translational Applications in Neurological Disorders

Astrocytes, the most abundant glial cell type in the brain, play crucial roles in maintaining homeostasis within the central nervous system (CNS). Impairment or abnormalities of typical astrocyte functions in the CNS serve as a causative or contributing factor in numerous neurodevelopmental, neurodegenerative, and neuropsychiatric disorders. Currently, disease-modeling and drug-screening approaches, primarily focused on human astrocytes, rely on human pluripotent stem cell (hPSC)-derived astrocytes. However, it is important to acknowledge that these hPSC-derived astrocytes exhibit notable differences across studies and when compared to their in vivo counterparts. These differences may potentially compromise translational outcomes if not carefully accounted for. This review aims to explore state-of-the-art in vitro models of human astrocyte development, focusing on the developmental processes, functional maturity, and technical aspects of various hPSC-derived astrocyte differentiation protocols. Additionally, it summarizes their successful application in modeling neurological disorders. The discussion extends to recent advancements in the large-scale production of human astrocytes and their application in developing high-throughput assays conducive to therapeutic drug discovery.

The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review

BACKGROUND

Stem cell research, particularly in the domain of induced pluripotent stem cell (iPSC) technology, has shown significant progress. The integration of artificial intelligence (AI), especially machine learning (ML) and deep learning (DL), has played a pivotal role in refining iPSC classification, monitoring cell functionality, and conducting genetic analysis. These enhancements are broadening the applications of iPSC technology in disease modelling, drug screening, and regenerative medicine. This review aims to explore the role of AI in the advancement of iPSC research.

METHODS

In December 2023, data were collected from three electronic databases (PubMed, Web of Science, and Science Direct) to investigate the application of AI technology in iPSC processing.

RESULTS

This systematic scoping review encompassed 79 studies that met the inclusion criteria. The number of research studies in this area has increased over time, with the United States emerging as a leading contributor in this field. AI technologies have been diversely applied in iPSC technology, encompassing the classification of cell types, assessment of disease-specific phenotypes in iPSC-derived cells, and the facilitation of drug screening using iPSC. The precision of AI methodologies has improved significantly in recent years, creating a foundation for future advancements in iPSC-based technologies.

CONCLUSIONS

Our review offers insights into the role of AI in regenerative and personalized medicine, highlighting both challenges and opportunities. Although still in its early stages, AI technologies show significant promise in advancing our understanding of disease progression and development, paving the way for future clinical applications.

Noninvasive Assessment of hiPSC Differentiation toward Cardiomyocytes Using Pretrained Convolutional Neural Networks and the Channel Pruning Algorithm

Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (hiPSC-CMs) offer versatile applications in tissue engineering and drug screening. To facilitate the monitoring of hiPSC cardiac differentiation, a noninvasive approach using convolutional neural networks (CNNs) was explored. HiPSCs were differentiated into cardiomyocytes and analyzed using the quantitative real-time polymerase chain reaction (qRT-PCR). The bright-field images of the cells at different time points were captured to create the dataset. Six pretrained models (AlexNet, GoogleNet, ResNet 18, ResNet 50, DenseNet 121, VGG 19-BN) were employed to identify different stages in differentiation. VGG 19-BN outperformed the other five CNNs and exhibited remarkable performance with 99.2% accuracy, recall, precision, and F1 score and 99.8% specificity. The pruning process was then applied to the optimal model, resulting in a significant reduction of model parameters while maintaining high accuracy. Finally, an automation application using the pruned VGG 19-BN model was developed, facilitating users in assessing the cell status during the myocardial differentiation of hiPSCs.

Strengthening cardiac therapy pipelines using human pluripotent stem cell-derived cardiomyocytes

Advances in hiPSC isolation and reprogramming and hPSC-CM differentiation have prompted their therapeutic application and utilization for evaluating potential cardiovascular safety liabilities. In this perspective, we showcase key efforts toward the large-scale production of hiPSC-CMs, implementation of hiPSC-CMs in industry settings, and recent clinical applications of this technology. The key observations are a need for traceable gender and ethnically diverse hiPSC lines, approaches to reduce cost of scale-up, accessible clinical trial datasets, and transparent guidelines surrounding the safety and efficacy of hiPSC-based therapies.

Rebaudioside B Attenuates Lung Ischemia-reperfusion Injury Associated Apoptosis and Inflammation

OBJECTIVE

At present, no proven effective treatment is available for Lung Ischemiareperfusion Injury (LIRI). Natural compounds offer promising prospects for developing new drugs to address various diseases. This study sought to explore the potential of Rebaudioside B (Reb B) as a treatment compound for LIRI, both in vivo and in vitro.

METHODS

This study involved utilizing the human pulmonary alveolar cell line A549, consisting of epithelial type II cells, subjected to Oxygen-glucose Deprivation/recovery (OGD/R) for highthroughput in vitro cell viability screening. The aim was to identify the most promising candidate compounds. Additionally, an in vivo rat model of lung ischemia-reperfusion was employed to evaluate the potential protective effects of Reb B.

RESULTS

Through high-throughput screening, Reb B emerged as the most promising natural compound among those tested. In the A549 OGD/R models, Reb B exhibited a capacity to enhance cell viability by mitigating apoptosis. In the in vivo LIRI model, pre-treatment with Reb B notably decreased apoptotic cells, perivascular edema, and neutrophil infiltration within lung tissues. Furthermore, Reb B demonstrated its ability to attenuate lung inflammation associated with LIRI primarily by elevating IL-10 levels while reducing levels of IL-6, IL-8, and TNF-α.

CONCLUSION

The comprehensive outcomes strongly suggest Reb B's potential as a protective agent against LIRI. This effect is attributed to its inhibition of the mitochondrial apoptotic pathway and its ability to mitigate the inflammatory response.

Drug Screening Using Normal Cell and Cancer Cell Mixture in an Automated 3D Cell Culture System

Three-dimensional (3D) cell culture creates a more physiologically relevant environment for enhanced drug screening capabilities using microcarriers. An automated 3D system that integrates robotic manipulators, liquid handling systems, sensors, and environment control systems has the capacity to handle multiple samples in parallel, perform repetitive tasks, and provide real-time monitoring and analysis. This chapter describes a potential 3D cell culture drug screening model by combining renal proximal tubule cells as a representative normal cell line with cancer cell lines. This combination is subjected to drug screening to evaluate the drug's efficacy in suppressing cancer cells while minimizing impact on normal cells with the added benefit of having the ability to separate the two cell types by magnetic isolation for high content screens including mass spectrometry-based proteomics. This study presents advancements in 3D cell culture techniques, emphasizing the importance of automation and the potential of microcarriers in drug screening and disease modeling.

Stress-free cell aggregation by using the CEPT cocktail enhances embryoid body and organoid fitness

Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models.

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.

Application of patient-derived induced pluripotent stem cells and organoids in inherited retinal diseases

Inherited retinal diseases (IRDs) can induce severe sight-threatening retinal degeneration and impose a considerable economic burden on patients and society, making efforts to cure blindness imperative. Transgenic animals mimicking human genetic diseases have long been used as a primary research tool to decipher the underlying pathogenesis, but there are still some obvious limitations. As an alternative strategy, patient-derived induced pluripotent stem cells (iPSCs), particularly three-dimensional (3D) organoid technology, are considered a promising platform for modeling different forms of IRDs, including retinitis pigmentosa, Leber congenital amaurosis, X-linked recessive retinoschisis, Batten disease, achromatopsia, and best vitelliform macular dystrophy. Here, this paper focuses on the status of patient-derived iPSCs and organoids in IRDs in recent years concerning disease modeling and therapeutic exploration, along with potential challenges for translating laboratory research to clinical application. Finally, the importance of human iPSCs and organoids in combination with emerging technologies such as multi-omics integration analysis, 3D bioprinting, or microfluidic chip platform are highlighted. Patient-derived retinal organoids may be a preferred choice for more accurately uncovering the mechanisms of human retinal diseases and will contribute to clinical practice.

Basic science methods for the characterization of variants of uncertain significance in hypertrophic cardiomyopathy

With the advent of next-generation whole genome sequencing, many variants of uncertain significance (VUS) have been identified in individuals suffering from inheritable hypertrophic cardiomyopathy (HCM). Unfortunately, this classification of a genetic variant results in ambiguity in interpretation, risk stratification, and clinical practice. Here, we aim to review some basic science methods to gain a more accurate characterization of VUS in HCM. Currently, many genomic data-based computational methods have been developed and validated against each other to provide a robust set of resources for researchers. With the continual improvement in computing speed and accuracy, in silico molecular dynamic simulations can also be applied in mutational studies and provide valuable mechanistic insights. In addition, high throughput in vitro screening can provide more biologically meaningful insights into the structural and functional effects of VUS. Lastly, multi-level mathematical modeling can predict how the mutations could cause clinically significant organ-level dysfunction. We discuss emerging technologies that will aid in better VUS characterization and offer a possible basic science workflow for exploring the pathogenicity of VUS in HCM. Although the focus of this mini review was on HCM, these basic science methods can be applied to research in dilated cardiomyopathy (DCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (ACM), or other genetic cardiomyopathies.

Assessing Tumorigenicity in Stem Cell-Derived Therapeutic Products: A Critical Step in Safeguarding Regenerative Medicine

Stem cells hold promise in regenerative medicine due to their ability to proliferate and differentiate into various cell types. However, their self-renewal and multipotency also raise concerns about their tumorigenicity during and post-therapy. Indeed, multiple studies have reported the presence of stem cell-derived tumors in animal models and clinical administrations. Therefore, the assessment of tumorigenicity is crucial in evaluating the safety of stem cell-derived therapeutic products. Ideally, the assessment needs to be performed rapidly, sensitively, cost-effectively, and scalable. This article reviews various approaches for assessing tumorigenicity, including animal models, soft agar culture, PCR, flow cytometry, and microfluidics. Each method has its advantages and limitations. The selection of the assay depends on the specific needs of the study and the stage of development of the stem cell-derived therapeutic product. Combining multiple assays may provide a more comprehensive evaluation of tumorigenicity. Future developments should focus on the optimization and standardization of microfluidics-based methods, as well as the integration of multiple assays into a single platform for efficient and comprehensive evaluation of tumorigenicity.

Scalable generation of sensory neurons from human pluripotent stem cells

Development of new non-addictive analgesics requires advanced strategies to differentiate human pluripotent stem cells (hPSCs) into relevant cell types. Following principles of developmental biology and translational applicability, here we developed an efficient stepwise differentiation method for peptidergic and non-peptidergic nociceptors. By modulating specific cell signaling pathways, hPSCs were first converted into SOX10+ neural crest, followed by differentiation into sensory neurons. Detailed characterization, including ultrastructural analysis, confirmed that the hPSC-derived nociceptors displayed cellular and molecular features comparable to native dorsal root ganglion (DRG) neurons, and expressed high-threshold primary sensory neuron markers, transcription factors, neuropeptides, and over 150 ion channels and receptors relevant for pain research and axonal growth/regeneration studies (e.g., TRPV1, NAV1.7, NAV1.8, TAC1, CALCA, GAP43, DPYSL2, NMNAT2). Moreover, after confirming robust functional activities and differential response to noxious stimuli and specific drugs, a robotic cell culture system was employed to produce large quantities of human sensory neurons, which can be used to develop nociceptor-selective analgesics.

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.

SEQUIN is an R/Shiny framework for rapid and reproducible analysis of RNA-seq data

SEQUIN is a web-based application (app) that allows fast and intuitive analysis of RNA sequencing data derived for model organisms, tissues, and single cells. Integrated app functions enable uploading datasets, quality control, gene set enrichment, data visualization, and differential gene expression analysis. We also developed the iPSC Profiler, a practical gene module scoring tool that helps measure and compare pluripotent and differentiated cell types. Benchmarking to other commercial and non-commercial products underscored several advantages of SEQUIN. Freely available to the public, SEQUIN empowers scientists using interdisciplinary methods to investigate and present transcriptome data firsthand with state-of-the-art statistical methods. Hence, SEQUIN helps democratize and increase the throughput of interrogating biological questions using next-generation sequencing data with single-cell resolution.

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.

Pharma's Bio-AI revolution

Drug development has become unbearably slow and expensive. A key underlying problem is the clinical prediction challenge: the inability to predict which drug candidates will be safe in the human body and for whom. Recently, a dramatic regulatory change has removed FDA's mandated reliance on antiquated, ineffective animal studies. A new frontier is an integration of several disruptive technologies [machine learning (ML), patient-on-chip, real-time sensing, and stem cells], which when integrated, have the potential to address this challenge, drastically cutting the time and cost of developing drugs, and tailoring them to individual patients.

Organoid factory: The recent role of the human induced pluripotent stem cells (hiPSCs) in precision medicine

During the last decades, hiPSC-derived organoids have been extensively studied and used as in vitro models for several applications among which research studies. They can be considered as organ and tissue prototypes, especially for those difficult to obtain. Moreover, several diseases can be accurately modeled and studied. Hence, patient-derived organoids (PDOs) can be used to predict individual drug responses, thus paving the way toward personalized medicine. Lastly, by applying tissue engineering and 3D printing techniques, organoids could be used in the future to replace or regenerate damaged tissue. In this review, we will focus on hiPSC-derived 3D cultures and their ability to model human diseases with an in-depth analysis of gene editing applications, as well as tumor models. Furthermore, we will highlight the state-of-the-art of organoid facilities that around the world offer know-how and services. This is an increasing trend that shed the light on the need of bridging the publicand the private sector. Hence, in the context of drug discovery, Organoid Factories can offer biobanks of validated 3D organoid models that can be used in collaboration with pharmaceutical companies to speed up the drug screening process. Finally, we will discuss the limitations and the future development that will lead hiPSC-derived technology from bench to bedside, toward personalized medicine, such as maturity, organoid interconnections, costs, reproducibility and standardization, and ethics. hiPSC-derived organoid technology is now passing from a proof-of-principle to real applications in the clinic, also thanks to the applicability of techniques, such as CRISPR/Cas9 genome editing system, material engineering for the scaffolds, or microfluidic systems. The benefits will have a crucial role in the advance of both basic biological and translational research, particularly in the pharmacological field and drug development. In fact, in the near future, 3D organoids will guide the clinical decision-making process, having validated patient-specific drug screening platforms. This is particularly important in the context of rare genetic diseases or when testing cancer treatments that could in principle have severe side effects. Therefore, this technology has enabled the advancement of personalized medicine in a way never seen before.

Efficient and safe single-cell cloning of human pluripotent stem cells using the CEPT cocktail

Human pluripotent stem cells (hPSCs) are inherently sensitive cells. Single-cell dissociation and the establishment of clonal cell lines have been long-standing challenges. This inefficiency of cell cloning represents a major obstacle for the standardization and streamlining of gene editing in induced pluripotent stem cells for basic and translational research. Here we describe a chemically defined protocol for robust single-cell cloning using microfluidics-based cell sorting in combination with the CEPT small-molecule cocktail. This advanced strategy promotes the viability and cell fitness of self-renewing stem cells. The use of low-pressure microfluidic cell dispensing ensures gentle and rapid dispensing of single cells into 96- and 384-well plates, while the fast-acting CEPT cocktail minimizes cellular stress and maintains cell structure and function immediately after cell dissociation. The protocol also facilitates clone picking and produces genetically stable clonal cell lines from hPSCs in a safe and cost-efficient fashion. Depending on the proliferation rate of the clone derived from a single cell, this protocol can be completed in 7-14 d and requires experience with aseptic cell culture techniques. Altogether, the relative ease, scalability and robustness of this workflow should boost gene editing in hPSCs and leverage a wide range of applications, including cell line development (e.g., reporter and isogenic cell lines), disease modeling and applications in regenerative medicine.

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.

Cost-Effective Mechanical Aggregation of Cardiac Progenitors and Encapsulation in Matrigel Support Self-Organization in a Dynamic Culture Environment

Human iPSC-derived self-organized cardiac tissues can be valuable for the development of platforms for disease modeling and drug screening, enhancing test accuracy and reducing pharmaceutical industry financial burden. However, current differentiation systems still rely on static culture conditions and specialized commercial microwells for aggregation, which hinders the full potential of hiPSC-derived cardiac tissues. Herein, we integrate cost-effective and reproducible manual aggregation of hiPSC-derived cardiac progenitors with Matrigel encapsulation and a dynamic culture to support hiPSC cardiac differentiation and self-organization. Manual aggregation at day 7 of cardiac differentiation resulted in 97% of beating aggregates with 78% of cTnT-positive cells. Matrigel encapsulation conjugated with a dynamic culture promoted cell migration and the creation of organized structures, with observed cell polarization and the creation of lumens. In addition, encapsulation increased buoyancy and decreased coalescence of the hiPSC-derived cardiac aggregates. Moreover, VEGF supplementation increased over two-fold the percentage of CD31-positive cells resulting in the emergence of microvessel-like structures. Thus, this study shows that the explored culture parameters support the self-organization of hiPSC-derived cardiac microtissues containing multiple cardiac cell types. Additional stimuli (e.g., BMP) in long-term scalable and fully automatized cultures can further potentiate highly structured and mature hiPSC-derived cardiac models, contributing to the development of reliable platforms for high-throughput drug screening and disease modeling.

Compact automated culture machine for human induced pluripotent stem cell maintenance and differentiation

The technologies used to generate human induced pluripotent stem cell (iPSC) from somatic cells potentially enable the wide application of iPSC-derived differentiated cells in industrial research fields as a replacement for animals. However, as highly trained individuals are required to obtain reproducible results, this approach has limited social implementation. In the research field of iPSC, it is believed that documentable information is not enough for reproducing the quality of the differentiated cells. Therefore, automated culture machines for cell processing should make the starting of iPSC-using researches easier. We developed a programmable all-in-one automated culture machine, with dense and compact constitution that fits within a normal biosafety cabinet (200 mm wide, 233 mm height, and 110 mm depth). This instrument was fabricated using novel x-y-z-axes-rail-system, such as an overhead traveling crane, in a factory, which served as the main handling machinery. This machine enabled stable and efficient expansion of human iPSC under the feeder-free condition, without karyotype alterations, and simultaneously differentiated the cells into various cell types, including cardiomyocytes, hepatocytes, neural progenitors, and keratinocytes. Overall, this machine would facilitate the social implementation of human pluripotent stem cells and contribute to the accumulation of sharable knowledge for the standardization of the entire handling processes of iPSC in pharmaceutical, food, and cosmetic research.

Advancing translational science education

In this communication, the authors offer considerations for how the scientific community can capitalize on decades of translational science advances and experiential knowledge to develop new education opportunities for a diverse and highly skilled translational science workforce. Continued advancement of the field of translational science will require new education approaches that distill key concepts in translational science from past and ongoing research initiatives and teach this foundational knowledge to current and future translational scientists. These key concepts include generalizable scientific and operational principles to guide translational science, as well as evidence-informed practices. Inspired by this approach, the National Center for Advancing Translational Sciences (NCATS) has developed an initial set of guiding principles for translational science generated via case studies of multiple highly successful translational science initiatives, and is now teaching them via new education activities that aim to reach a broad scientific audience interested in translational science. Our goal with this review is to prompt continued conversation with the translational science community regarding capitalizing on our collective translational science knowledge to advance core content for translational science education and disseminating this content to a broad range of scientific audiences.

iPSCs in NK Cell Manufacturing and NKEV Development

Natural killer (NK) cell immunotherapies for cancer can complement existing T cell therapies while benefiting from advancements already made in the immunotherapy field. For NK cell manufacturing, induced pluripotent stem cells (iPSCs) offer advantages including eliminating donor variation and providing an ideal platform for genome engineering. At the same time, extracellular vesicles (EVs) have become a major research interest, and purified NK cell extracellular vesicles (NKEVs) have been shown to reproduce the key functions of their parent NK cells. NKEVs have the potential to be developed into a standalone therapeutic with reduced complexity and immunogenicity compared to cell therapies. This review explores the role iPSC technology can play in both NK cell manufacturing and NKEV development.

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.

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.

Induced Pluripotent Stem Cell-Based Drug Screening by Use of Artificial Intelligence

Induced pluripotent stem cells (iPSCs) are terminally differentiated somatic cells that differentiate into various cell types. iPSCs are expected to be used for disease modeling and for developing novel treatments because differentiated cells from iPSCs can recapitulate the cellular pathology of patients with genetic mutations. However, a barrier to using iPSCs for comprehensive drug screening is the difficulty of evaluating their pathophysiology. Recently, the accuracy of image analysis has dramatically improved with the development of artificial intelligence (AI) technology. In the field of cell biology, it has become possible to estimate cell types and states by examining cellular morphology obtained from simple microscopic images. AI can evaluate disease-specific phenotypes of iPS-derived cells from label-free microscopic images; thus, AI can be utilized for disease-specific drug screening using iPSCs. In addition to image analysis, various AI-based methods can be applied to drug development, including phenotype prediction by analyzing genomic data and virtual screening by analyzing structural formulas and protein-protein interactions of compounds. In the future, combining AI methods may rapidly accelerate drug discovery using iPSCs. In this review, we explain the details of AI technology and the application of AI for iPSC-based drug screening.

Decellularized Organ-Derived Scaffold Is a Promising Carrier for Human Induced Pluripotent Stem Cells-Derived Hepatocytes

Human induced pluripotent stem cells (hiPSCs) are a promising cell source for elucidating disease pathology and therapy. The mass supply of hiPSC-derived cells is technically feasible. Carriers that can contain a large number of hiPSC-derived cells and evaluate their functions in vivo-like environments will become increasingly important for understanding disease pathogenesis or treating end-stage organ failure. hiPSC-derived hepatocyte-like cells (hiPSC-HLCs; 5 × 10⁸) were seeded into decellularized organ-derived scaffolds under circumfusion culture. The scaffolds were implanted into immunodeficient microminiature pigs to examine their applicability in vivo. The seeded hiPSC-HLCs demonstrated increased albumin secretion and up-regulated cytochrome P450 activities compared with those in standard two-dimensional culture conditions. Moreover, they showed long-term survival accompanied by neovascularization in vivo. The decellularized organ-derived scaffold is a promising carrier for hiPSC-derived cells for ex vivo and in vivo use and is an essential platform for regenerative medicine and research.