SLAS 2024 Journey into the Lab of the Future

Journey into the Lab of the Future: Molecular Devices' Visionary Posters at SLAS 2024

Molecular Devices is honored to be designated as a “Lab of the Future Company.”

Exhibitors that received the SLAS2024 Lab of the Future designation have demonstrated their ability to provide solutions that go beyond automated instrumentation alone to push the boundaries of current technology and break new ground in achieving complete integration of automated workflows in the lab space.

Explore six posters that feature this groundbreaking innovation and unveil the latest advancements in laboratory research and technology. These posters delve into the world of AI-driven decision-making, automated cell culture, organoid research, and precision medicine, showcasing the potential for pioneering discoveries. Discover the future of cell culture and how automation is revolutionizing reproducibility and standardization while uncovering the promise of patient-derived organoids in improving therapeutic outcomes. We demonstrate a streamlined process for assessing drug effects on 3D cancer spheroid and then dive into the realm of neurospheres and their role in modeling Alzheimer's disease.

Take a step ‘back to the future’ and revisit us at SLAS 2024 - Lab of the Future, where science and technology converge to shape the future of medicine.

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CellXpress.ai Automated Cell Culture System: Automated workstation for reproducible organoid cultivation

Felix Spira, PhD
Hardware Engineering and Applications Manager

Within the past few years, many publications advocate the promise of organoids to improve clinical trial success and enable personalized medicine. However, organoid research is suffering from a lack of standardization and high organoid-to-organoid variability. These challenges, together with difficult cultivation techniques are impeding the wider adoption of organoid technologies. To overcome these limitations, we have developed the CellXpress.ai Automated Cell Culture System.
Felix Spira demonstrates the CellXpress.ai Automated Cell Culture System

The CellXpress.ai system is a highly integrated organoid generation and cultivation workstation that integrates cutting-edge hardware and software technologies with advanced biological science to automate and standardize the 2D and 3D cell culture process. From maintenance, monitoring, and incubation through imaging, analysis, and data processing, the CellXpress.ai cell culture system delivers consistent, unbiased, and biologically relevant results at scale. To support scientists at every level of their organoid research, the system guides the user to set up and execute iPSC, tumoroid, and adult stem cell-derived organoid workflows.

As proof of concept, Dr. Spira demonstrates the successful cultivation of iPSC and human intestinal organoid workflows over multiple passages. The workflows include cell/organoid seeding, feeding, and passaging, with in-line monitoring and machine-learning image analysis and classification.

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Scalable patient-derived 3D colorectal cancer organoids in high throughput applications

Angeline Lim, PhD
Sr. Applications Scientist

Despite promising data in vitro, many oncology drugs fail at the later stages of the drug development pipeline. The use of 3D cell models, such as patient-derived organoids (PDOs), offers a promising solution to this problem. Studies show that patients and their derived organoids respond similarly to drugs, suggesting the value of using PDOs to improve therapeutic outcomes. However, challenges such as assay reproducibility, scalability, and cost have limited the use of PDOs in mainstream drug discovery pipelines.
Angeline Lim describes an end-to-end automated workflow with patient-derived 3D colorectal cancer organoids

In this poster, Dr. Lim addresses the challenges associated with the use of PDOs and demonstrates their utility for high throughput applications. She describes an end-end, automated workflow starting with assay-ready colorectal cancer (CRC) organoids expanded in a bioreactor.

  1. Developed a semi-automated process for the controlled production of PDOs. The bioreactor maintains an environment that ensures constant delivery of nutrients and growth factors to the culture while preventing the accumulation of toxins. This method results in the large-scale production of assay-ready organoids that are uniform in size and have high viability.
  2. Developed automation methods to streamline the handling of organoid-based assays.
  3. Developed image-based deep learning model for the analysis
  4. Show the use of a high dimensionality approach for organoid profiling

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A walkaway solution for assessing drug effects on patient-derived cancer organoids

Cathy Olsen, PhD
Sr. Application Scientist

Cancer cell lines grown as monolayer cultures (2D) have long served as convenient experimental surrogates for cancers. In recent years, the 3D culture of cancer cells, often alongside other cell types in formats where they can form multi-layered structures, is enabling new models for cancer research that are considered more biologically relevant. Cancer organoids derived from patient tissue offer researchers a highly relevant disease model system, as these organoids and the patients from which they were derived have been shown to respond similarly to drugs.
Cathy Olsen demonstrates a walkaway solution for assessing drug effects on patient-derived cancer organoids

Characterization of organoid response to candidate drug treatment is a powerful research tool that provides a wealth of detailed information, but screening a large number of compounds requires significant effort and hands-on time. Streamlining the process is important for rapid identification of compounds that can be followed up with more time-consuming studies. In this poster, Dr. Olsen demonstrates the methods for analyses of key parameters such as cell viability that allow rapid identification of effective drug candidates and can be combined or followed up with more complex image analysis. The results from viability assays are further hastened through the automation of reagent and plate handling, as well as pre-configured analysis protocols.

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Automation of the full workflow for 3D cancer spheroid assays with CellXpress.ai Automated Cell Culture System

Oksana Sirenko, PhD
Sr. Scientist Assay Development

Finding efficient drug combinations to treat cancer patients is critical for therapy success. Accordingly, there is a critical need to develop methods for efficient testing drug efficacy to discover new therapeutic targets. 3D cancer models are highly valuable tools for cancer research and drug development, however, the complexity of performing 3D assays remains a hurdle for the wide adoption of these methods for compound screening.
Oksana Sirenko describes the automated workflow for 3D cancer spheroid assays with CellXpress.ai Automated Cell Culture System

In this poster, Dr. Sirenko describes how she automated the cell culture process and end-point assays to scale up complex 3D cell-based assays and compound screening. She then shares how how we developed cell culture methods automation methods using the CellXpress.ai Automated Cell Culture System. The CellXpress.ai system enables full automation of 2D or 3D assays for prolonged complex workflows and provides automated plating, passaging, media exchanges, and organoid monitoring, along with compound treatment and endpoint assays.

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Prathyushakrishna Macha, Ph.D.
Oksana Sirenko, PhD

Neural 3D organoids from human induced pluripotent stem cells (iPSC) are a rapidly developing technology with great potential for understanding brain development and neuronal diseases. A promising parallel approach is to assemble similar structures as 3D spheroids or “neurospheres” by using defined combinations of fully differentiated human iPSC-derived cells in tri-culture, including glutamatergic neurons, GABAergic neurons, and astrocytes.
Oksana Sirenko discusses the functional characterization of healthy and Alzheimer’s disease-related 3D neurospheres

Download our poster to learn how this biological system of 3D neurospheres assembled from human iPSC-derived cell types demonstrates a promising tool for disease modeling and compound testing.

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Transform the complexities of 3D cell culture into a reliable and translatable science: Automation of 3D organoid culture and organoid analysis.

Oksana Sirenko, PhD
Sr. Scientist Assay Development

Attrition in the therapeutic pipeline can often be attributed to lack of translational efficacy from the pre-clinical phase to the clinic. Organoids show a great promise as a game-changer in disease modeling and drug screening, since they better resemble tissue structure and functionality, and show more predictive responses to drugs. However, challenges associated with the practical adoption of organoids, such as assay complexity, reproducibility, and the ability to scale up have limited their widespread adoption as a primary screening method in drug discovery.
Oksana Sirenko presents the results from the automation of 3D organoid culture and organoid analysis

To alleviate the bottlenecks that come with labor-intensive manual protocols, we developed the CellXpress.ai Automated Cell Culture System. This revolutionary solution automates the entire organoid culture process for prolonged, complex workflows. The CellXpress.ai system uses machine learning to autonomously manage media exchange, plating, passaging, organoid monitoring, endpoint assays, and complex image analysis. Here we present results from the automation of several commonly used organoid protocols, including the culture of 3D organoids in matrix domes or in low attachment plates.

Here, Dr. Sirenko presents the results from the automation of several commonly used organoid protocols, including the culture of 3D organoids in matrix domes or in the low attachment plates.

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The future of cell culture backed by machine learning and data-driven science

https://share.vidyard.com/watch/xgTqMVm4uWCZ4sfkPxycyE

Feeling inspired to learn more exciting new methods and protocols to automate your complex biology workflows? Click below to start your journey into the...

Future of Cell Culture

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