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SLAS Ignite Collaboration Presentations

SLAS understands the tremendous benefit of collaboration: tapping into the experience, insights and capabilities of peers and complementary organizations to develop the medicines, methods and innovations that improve the human condition.

SLAS Ignite introduced Collaboration Presentations and the Ignite Theater at SLAS2018 to foster scientific innovation through collaboration. Developed specifically for academic researchers and industry scientists, SLAS Ignite Collaboration Presentations enable academic research institutions to showcase their capabilities and latest research to a diverse audience of prospective collaboration partners.  Likewise, industry professionals responsible for partnerships and contract relations can meet with prospective partners from academia. Together, SLAS facilitates connections that result in pioneering new research, innovation breakthroughs and commercialization opportunities for all involved.

The deadline to submit a proposal for presentation has passed. See below for this year's accepted presentations.

 

SLAS Ignite Theater in the Exhibition

SLAS2020

SLAS is proud to provide an annual venue for professional collaboration at its conferences and have collaboration as a key mission of the Society. Bringing together a diverse community of engineers, researchers, scientists, business leaders and pioneering academic experts has enabled SLAS members to advance scientific research by using the latest technologies and insights provided by fellow members of the SLAS community.

Audiences Served

  • Scientists from industry and academic researchers looking for collaboration partners.
  • Business development professionals (from industry or academia) whose responsibilities include finding, funding and formalizing research partnerships and collaborations.

SLAS Ignite Collaboration Presentations at SLAS2020

The 2020 class of SLAS Ignite Collaboration presenters were selected by a review committee based on the quality of their abstract. This year's presentations will be held on Monday, January 27 and Tuesday, January 28. 

Monday, January 27 - 1:15 - 2:15 p.m.

Microphysiological systems (MPS) are designed to mimic human organs and physiology with the aim of improving the drug development process. They have proven to be a powerful tool at research level and a solid basis for the establishment of qualified preclinical assays with improved predictive power. However, one remaining drawback is the lack of comprehensive standardization. This hinders their use for regulatory purposes as well as it impedes the extraction of the full extent of information from acquired data. Moreover, one main advantage of MPS in contrast to animal testing – the insight in “the body” throughout the test assays – cannot be deployed fully as long as assay execution, observation and analysis are highly time consuming and resource binding. This is why there is an immediate demand to automate MPS cultivation and analysis. Concluding, we developed a dedicated system for the cultivation of our TissUse Multi-Organ-Chips.

The Humimic AutoLab cultivates up to 24 Multi-Organ-Chips (MOCs) simultaneously, providing customized incubation and systemic pulsatile media circulation. Regular media exchanges, substance application and sample extraction are executed automatically according to assay specifications. Routine microscopic analyses such as bright field imaging and fluorescence measurements are conducted in scheduled cycles and at any chosen time. To hinder contamination and for operator protection all liquid handling steps are conducted under sterile conditions. Media, substances and samples are stored in a refrigerator at 4 °C, which are delivered on demand via an automatic provisioning system. Cell culture material such as well plates and single-use pipet tips last for a minimum of four days until a restock is necessary. The refrigerator also holds media samples and stores them until further analysis. A dedicated software allows for a coherent and time efficient input of all assay parameters as well as it provides a variety of tools for data analysation. The Humimic LabOS also allows for assay feasibility checks and provides the operator with instructions for equipping the system. The fully automated image acquisition and ensuing analysation will finally allow for a higher comparability of results and new findings through pattern recognition and machine learning algorithms. Transferring our well-established co-culture assays with organ models such as liver, skin, intestine and bone marrow organoids proofed successful and showed a high comparability to the manually conducted assays.

Traditional microscopes used for automated imaging and analysis sets one aback with tens of thousands, if not hundreds of thousands, of dollars. This limits the number of microscopes a lab can afford, hence limiting the number of parallel experiments that can be performed. We present a novel approach by combining low-cost, low-resolution microscopes with advanced computational imaging methods that can extract high-resolution image information in post processing. In addition, we implement novel machine learning methods to jointly optimize the automation task, e.g. cell segmentation, and the data acquisition process, e.g. illumination pattern, to capture less data without losing the performance of the automated task.

Our initial prototype costing ~$150 employed a Raspberry Pi as the computer and a modified Raspberry Pi V2 camera as the low-resolution microscope. A low-cost 16x16 LED array developed for display is used to illuminate the sample and 3D printed parts are used for assembly. LEDs in the array are sequentially illuminated to capture 256 low-resolution images, where the high-resolution information is encoded within these low-resolution images using the aperture synthesis concepts. The captured 256 low-resolution images were combined to achieve 0.8µm resolution, for the first time in a low-cost setting, across 4 mm

The 3D-printed design of our microscope can be easily modified to the specific requirements of a lab, e.g. imaging stress, fibre reorientation in cells under mechanical stimuli require a different setup compared to imaging cell confluency in a petri-dish. Our optics and algorithms still stay valid for all these different configurations and the required modifications in the 3D printed designs are usually minor. This is not possible with commercial systems which are designed for a limited number of imaging applications. Combining latest developments in machine learning makes our approach a powerful tool for laboratory automation and diagnostics in low-resource settings.

Digital enzyme-linked immunosorbent assays (dELISA) allow measurement of biomarkers down to individual molecules. Such technologies have demonstrated great utility in rare biomarker detection and early-stage diagnostics. However, the need for specialized and relatively costly equipment (e.g. the Quanterix Simoa system) has impeded the adoption of digital ELISA technologies for either R&D or clinical diagnostics.  

We have developed a transformative approach to perform ultra-sensitive ELISA assays on microgel particles and acquire quantified analyses with standard flow cytometers. Our approach addresses several challenges to build accessible digital ELISA assays by (1) leveraging the solid support of cytometer compatible highly uniform hydrogel particles, with a high-throughput platform to fabricate these particles with high uniformity, (2) immobilizing amplified signals on individual particles, thus allowing for simple and effective washing, (3) generating a homogenous water-in-oil emulsion by simple pipetting to prevent crosstalk, using the hydrophilic microgel particles to template the formation of emulsion drops.  

We demonstrate the production of monodisperse spherical polyethylene glycol (PEG) hydrogel particles at a rate of 1000 particles per second over more than 10 hours, consistently creating microgel particles < 40 μm in diameter with a < 5% CV. These microgel particles can be stored for several months. Tyramide signal amplification (TSA) was used to generate amplified signals on the particles. Alexa Fluor 488 conjugated tyramide is converted by HRP into short-lived radical intermediates which then covalently link to tyrosine residues on nearby proteins. HRP labeled particles were immediately emulsified in fluorinated oil once suspended in tyramide solutions to minimize crosstalk. By simple pipetting and agitation, the hydrophilic particles template the formation of a highly monodisperse emulsion. At least 500k droplets can be formed within 45 seconds. The emulsion was disrupted after incubation, and the accumulated tyramide signals, which remained bound on the gel particles throughout the rigorous washing, were analyzed by a flow cytometer.  

In our proof-of-concept work based on biotinylated microgel particles and streptavidin labeled HRP, we were able to achieve a sensitivity of ~700 HRP molecules per particle, an improvement of more than 100 folds from unamplified fluorescent labeling, and a dynamic range of >3 orders of magnitudes without sample dilution. We aim for this assay to display single-molecule sensitivity with a multiplex capacity.  

The batch approaches at each step of the assay grants this method high scalability to accommodate a large dynamic range without having to design or redesign any specialized component. The entire workflow, upon acquiring the pre-made hydrogel particles, is performed using basic mixing operations and standard benchtop laboratory equipment without microfluidic chips or pumps. We envision the microgel particles can be fabricated at a central site and widely distributed to speed up the adoption of digital ELISA and other highly sensitive immunoassays."

 

Tuesday, January 28 - 1:15 - 2:15 p.m.

The current effort to grow human tissues as 3D “organoids” for cancer research aims to recapitulate 3D architecture of tumors in an in vitro environment for cancer biology studies and therapeutic development. However, due to various technical challenges, primary 3D organoid culture has not been widely used in a high-throughput screening (HTS) format for chemical screening. Here, we report the miniaturization and development of a multiplexed uHTS and uHCS (MuHTCS) organoid culturing platform for effective compound screening in a 1536-well format. Using  pancreatic patient tumor-derived organoids as a model system, we optimized the 3D organoid culturing conditions with extracellular matrix (ECM). The growth of organoids was monitored by automated imaging. We further developed a multiplexed screening platform to simultaneously monitor the effect of compounds on the growth of organoids for ultraHTS (uHTS) and on the morphological change of  organoids for ultra-high-content screening (uHCS) in a 1536-well plate. The MuHTCS assay has achieved Z’ > 0.5 and signal-to-background (S/B) > 6.  A pilot screening of ~2000 FDA-approved and bioactive compound library has validated the assay for screening. Our data has demonstrated that it is feasible to utilize miniaturized 3D cancer organoids for large scale compound screening. The optimized MuHTC platform provides an efficient approach to accelerate 3-D organoids-enabled screening for drug discovery.

Microscopy images contain tremendous information about the state of cells, tissues and organisms. This morphological information can be quantified and used to compare samples in order to identify, at a single-cell level, how diseases, drugs and genes affect cells. This can uncover small molecules’ mechanism of action, discover disease-associated phenotypes, identify the functional impact of disease-associated alleles and identify novel therapeutics. Two pre-competitive consortia have been established to share best practices and create the world's largest, shared image-based Cell Painting dataset

Molecular information obtained from liquid biopsy is already used to predict disease progression, survival and therapy selection in metastatic patients. However, owing to the low abundance of tumor cells in liquid biopsy samples, their use in functional drug screening assays has been hampered for monitoring patient drug response/resistance, personalized therapy decision and drug discovery.

We have developed a workflow to isolate tumor cells from pleural effusion and malignant ascites samples from metastatic lung and breast cancer patients and subjected them to medium scale drug screens against approved anticancer drug libraries. This approach allows realization of personalized treatment decisions within less than a week by evaluating drug responses directly in patient-derived tumor cells obtained from liquid biopsy.

In patients with no pleural effusion or malignant ascites, we have established another workflow to isolate viable circulating tumor cells (CTCs) from peripheral blood of metastatic patients, from which we have generated 2D and 3D in vitro (spheroids and organoids) and in vivo (CTC-derived xenografts) models. Drug responses in the screens mirror patients’ drug resistance and reveal promising treatment options on an individual patient level. Moreover, high-throughput drug screens in CTC-derived preclinical models closely mimicking patients' setting enable discovery, repurposing and development of more efficient cancer therapeutics.

Integration of drug screening with liquid biopsy-derived tumor cells constitutes a powerful tool to improve personalized treatment strategies and for drug discovery in metastatic patients.


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