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.

Elaborating the potential of Artificial Intelligence in automated CAR-T cell manufacturing.

This paper discusses the challenges of producing CAR-T cells for cancer treatment and the potential for Artificial Intelligence (AI) for its improvement. CAR-T cell therapy was approved in 2018 as the first Advanced Therapy Medicinal Product (ATMP) for treating acute leukemia and lymphoma. ATMPs are cell- and gene-based therapies that show great promise for treating various cancers and hereditary diseases.

Smart Sensor Control and Monitoring of an Automated Cell Expansion Process.

Immune therapy for cancer patients is a new and promising area that in the future may complement traditional chemotherapy. The cell expansion phase is a critical part of the process chain to produce a large number of high-quality, genetically modified immune cells from an initial sample from the patient. Smart sensors augment the ability of the control and monitoring system of the process to react in real-time to key control parameter variations, adapt to different patient profiles, and optimize the process.

Acquiring Process Knowledge in Extrusion-Based Additive Manufacturing via Interpretable Machine Learning.

Additive manufacturing (AM), especially the extrusion-based process, has many process parameters which influence the resulting part properties. Those parameters have complex interdependencies and are therefore difficult if not impossible to model analytically. Machine learning (ML) is a promising approach to find suitable combinations of process parameters for manufacturing a part with desired properties without having to analytically model the process in its entirety.

Young's Modulus-Independent Determination of Fibre Parameters for Rayleigh-Based Optical Frequency Domain Reflectometry from Cryogenic Temperatures up to 353 K.

The magnetic spectrometer AMS-100, which includes a superconducting coil, is designed to measure cosmic rays and detect cosmic antimatter in space. This extreme environment requires a suitable sensing solution to monitor critical changes in the structure such as the beginning of a quench in the superconducting coil. Rayleigh-scattering-based distributed optical fibre sensors (DOFS) fulfil the high requirements for these extreme conditions but require precise calibration of the temperature and strain coefficients of the optical fibre.

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.

Optical coherence tomography combined with convolutional neural networks can differentiate between intrahepatic cholangiocarcinoma and liver parenchyma ex vivo.

Purpose: Surgical resection with complete tumor excision (R0) provides the best chance of long-term survival for patients with intrahepatic cholangiocarcinoma (iCCA). A non-invasive imaging technology, which could provide quick intraoperative assessment of resection margins, as an adjunct to histological examination, is optical coherence tomography (OCT). In this study, we investigated the ability of OCT combined with convolutional neural networks (CNN), to differentiate iCCA from normal liver parenchyma ex vivo.

Adaptive phase contrast microscopy to compensate for the meniscus effect.

Phase contrast is one of the most important microscopic methods for making visible transparent, unstained cells. Cell cultures are often cultivated in microtiter plates, consisting of several cylindrical wells. The surface tension of the culture medium forms a liquid lens within the well, causing phase contrast conditions to fail in the more curved edge areas, preventing cell observation.

LIFTOSCOPE: development of an automated AI-based module for time-effective and contactless analysis and isolation of cells in microtiter plates.

Background: The cultivation, analysis, and isolation of single cells or cell cultures are fundamental to modern biological and medical processes. The novel LIFTOSCOPE technology aims to integrate analysis and isolation into one versatile, fully automated device.

Methods: LIFTOSCOPE's three core technologies are high-speed microscopy for rapid full-surface imaging of cell culture vessels, AI-based semantic segmentation of microscope images for localization and evaluation of cells, and laser-induced forward transfer (LIFT) for contact-free isolation of cells and cell clusters.

Needle to needle robot-assisted manufacture of cell therapy products.

Advanced therapeutic medicinal products (ATMPs) have emerged as novel therapies for untreatable diseases, generating the need for large volumes of high-quality, clinically-compliant GMP cells to replace costly, high-risk and limited scale manual expansion processes. We present the design of a fully automated, robot-assisted platform incorporating the use of multiliter stirred tank bioreactors for scalable production of adherent human stem cells. The design addresses a needle-to-needle closed process incorporating automated bone marrow collection, cell isolation, expansion, and collection into cryovials for patient delivery.

Optical coherence tomography and convolutional neural networks can differentiate colorectal liver metastases from liver parenchyma ex vivo.

Purpose: Optical coherence tomography (OCT) is an imaging technology based on low-coherence interferometry, which provides non-invasive, high-resolution cross-sectional images of biological tissues. A potential clinical application is the intraoperative examination of resection margins, as a real-time adjunct to histological examination. In this ex vivo study, we investigated the ability of OCT to differentiate colorectal liver metastases (CRLM) from healthy liver parenchyma, when combined with convolutional neural networks (CNN).

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.

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.

From Single Batch to Mass Production-Automated Platform Design Concept for a Phase II Clinical Trial Tissue Engineered Cartilage Product.

Advanced Therapy Medicinal Products (ATMP) provide promising treatment options particularly for unmet clinical needs, such as progressive and chronic diseases where currently no satisfying treatment exists. Especially from the ATMP subclass of Tissue Engineered Products (TEPs), only a few have yet been translated from an academic setting to clinic and beyond. A reason for low numbers of TEPs in current clinical trials and one main key hurdle for TEPs is the cost and labor-intensive manufacturing process.

Daratumumab therapy for post-HSCT immune-mediated cytopenia: experiences from two pediatric cases and review of literature.

Background: Immune-mediated cytopenias (AIC) are challenging complications following allogeneic hematopoietic stem cell transplantation (HSCT). While broad-acting immunosuppressive agents like corticosteroids are often standard of care, several novel therapies which target specific immunological pathways have recently been developed and provide hope for patients with steroid-refractory courses and may limit long-term toxicity. The successful off-label use of the plasma cell depleting anti-CD38 antibody daratumumab was published in several case reports, suggesting efficacy, i.

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.

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

While human induced pluripotent stem cells (hiPSCs) provide novel prospects for disease-modeling, the high phenotypic variability seen across different lines demands usage of large hiPSC cohorts to decipher the impact of individual genetic variants. Thus, a much higher grade of parallelization, and throughput in the production of hiPSCs is needed, which can only be achieved by implementing automated solutions for cell reprogramming, and hiPSC expansion. Here, we describe the StemCellFactory, an automated, modular platform covering the entire process of hiPSC production, ranging from adult human fibroblast expansion, Sendai virus-based reprogramming to automated isolation, and parallel expansion of hiPSC clones.

Automation, Monitoring, and Standardization of Cell Product Manufacturing.

Although regenerative medicine products are at the forefront of scientific research, technological innovation, and clinical translation, their reproducibility and large-scale production are compromised by automation, monitoring, and standardization issues. To overcome these limitations, new technologies at software (e.g.

Leveraging spatial uncertainty for online error compensation in EMT.

Purpose: Electromagnetic tracking (EMT) can potentially complement fluoroscopic navigation, reducing radiation exposure in a hybrid setting. Due to the susceptibility to external distortions, systematic error in EMT needs to be compensated algorithmically. Compensation algorithms for EMT in guidewire procedures are only practical in an online setting.

BabyLux device: a diffuse optical system integrating diffuse correlation spectroscopy and time-resolved near-infrared spectroscopy for the neuromonitoring of the premature newborn brain.

The BabyLux device is a hybrid diffuse optical neuromonitor that has been developed and built to be employed in neonatal intensive care unit for the noninvasive, cot-side monitoring of microvascular cerebral blood flow and blood oxygenation. It integrates time-resolved near-infrared and diffuse correlation spectroscopies in a user-friendly device as a prototype for a future medical grade device. We present a thorough characterization of the device performance using test measurements in laboratory settings.

High-precision evaluation of electromagnetic tracking.

Purpose: Navigation in high-precision minimally invasive surgery (HP-MIS) demands high tracking accuracy in the absence of line of sight (LOS). Currently, no tracking technology can satisfy this requirement. Electromagnetic tracking (EMT) is the best tracking paradigm in the absence of LOS despite limited accuracy and robustness.

Precise phase demodulation of single carrier-frequency interferogram by pixel-level Lissajous figure and ellipse fitting.

Phase demodulation from a single carrier-frequency fringe pattern is becoming increasingly important particularly in areas of optical metrology such as dynamic interferometry, deflectometry and profilometry. The Fourier transform (FT) method and the spatial-carrier phase-shifting technique (SCPS) are two popular and well-established approaches to demodulation. However FT has the drawback of significant edge errors because of the Gibbs effect, whilst detuning errors for the local phase shift occur when SCPS is applied.

Detection of magnetized quark-nuggets, a candidate for dark matter.

Quark nuggets are theoretical objects composed of approximately equal numbers of up, down, and strange quarks and are also called strangelets and nuclearites. They have been proposed as a candidate for dark matter, which constitutes ~85% of the universe's mass and which has been a mystery for decades. Previous efforts to detect quark nuggets assumed that the nuclear-density core interacts directly with the surrounding matter so the stopping power is minimal.

Clinical presentation and outcome in a series of 32 patients with 2-methylacetoacetyl-coenzyme A thiolase (MAT) deficiency.

2-methylacetoacetyl-coenzyme A thiolase (MAT) deficiency, also known as beta-ketothiolase deficiency, is an inborn error of ketone body utilization and isoleucine catabolism. It is caused by mutations in the ACAT1 gene and may present with metabolic ketoacidosis. In order to obtain a more comprehensive view on this disease, we have collected clinical and biochemical data as well as information on ACAT1 mutations of 32 patients from 12 metabolic centers in five countries.