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ScreenIn3D Platform Relies on Microfluidics, 3D Modeling to Monitor Cancer Treatment Efficacy

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NEW YORK – Drawing on research from the University of Strathclyde, Glasgow, Scotland-based startup ScreenIn3D is working to commercialize a microfluidic-based platform that can increase the number of analyses that can be done with one solid tumor sample to monitor the efficacy of oncology treatment.

The Onco-Chip 3D technology is an organ-on-a-chip microfluidic that was developed while "bearing in mind the challenges that are present when one works with very precious but limited amounts of patient-derived samples," such as those used in oncology, said Michele Zagnoni, the company's CEO and a staff member in Strathclyde's department of electronic and electrical engineering who helped develop the platform.

A biopsy "is a great chance to have the fingerprint of that individual tumor," but getting enough tissue can be an issue, he said. The Onco-Chip 3D platform "gets you more out of very little."

While the system's development began solely as an academic research project, it has culminated into a commercial product over the past five years, with ScreenIn3D being spun out from the University of Strathclyde in late 2018, Zagnoni said.

The technology is intended to measure the effect of specific therapies when working with small amounts of tissue — in its most recent research, published earlier this year in the IEEE Open Journal of Engineering in Medicine and Biology, the team looked at how the platform could be used to measure the efficacy of chimeric antigen receptor T-cell (CAR-T) therapy. However, the researchers have also applied the technology to chemotherapy and other types of therapies, Zagnoni said.

The platform "basically miniaturizes and makes the most of working with a very small amount of tissue that can then be used to test the efficacy" of different treatments, "hoping to identify a predictive response of the efficacy of that treatment in the person," he said.

To use the platform, a tissue sample — either fresh or frozen — is divided into "much smaller" samples that are then injected into the microfluidic device, Zagnoni said. The device enables the smaller samples, or microtumors, to position themselves into an array and then delivers whatever therapy it's looking at into the tumor via microfluidic networks. The user then monitors what happens to the microtumors via imaging to determine the effect of the therapy. The microfluidic structure of the device is designed with a proprietary process that relies on its geometry, he noted.

The microfluidic networks in the device are able to generate drug concentration gradients and uniquely miniaturized combination studies of different drugs, which is important because "many oncology treatments now are based on combinations — it's not just one drug," Zagnoni said.

Usually for a drug trial, many different samples are needed to conduct combinatorial experiments, but through the Onco-Chip 3D platform, those experiments can be conducted on small amounts of biopsy tissue drawn from one sample. By miniaturizing the amount of tissue sample used, Zagnoni said the technology is able to decrease costs and eliminate the need to take multiple biopsies.

Although the amount of tissue the company receives can be a limiting factor, with one biopsy, the device can quantify drug effects in more than 20 different ways, he said. Different drugs can be combined in different ways on a microtumor, or drugs can be scheduled for different times, and all of these experiments can be done in parallel, Zagnoni said.

The time to results differs depending on the therapy — some can take as little as one week, but if a user wants to monitor the effect of a drug over a longer period of time, it could take more than 15 days, he said. 

The next step for ScreenIn3D is automating the technology to "create a product that is scalable and easy to use" by anyone. The automated prototypes are fully developed, but rather than creating a new instrument the company plans to integrate the devices into existing high content imaging instruments that are already present in R&D labs, Zagnoni said. ScreenIn3D is now in the process of mass manufacturing the devices and standardizing them to fit into current imaging instruments.

Another key element the firm is working on is data interpretation. ScreenIn3D is adapting its current software to incorporate machine learning and artificial intelligence-based algorithms to speed up and automate result extraction. The artificial intelligence will be able to look at "gigabytes of images" and recognize certain features to provide results, according to Zagnoni.

ScreenIn3D plans to partner with existing equipment manufacturers as a way of accelerating distribution of its products by including its device and software with the existing equipment.

Once the automation and interpretation of the device is completed, the company will be able to move from the preclinical market to the clinical market, ultimately finding use for the device in hospitals and cancer centers, Zagnoni said. However, the firm plans to start with preclinical markets and programs that aren't regulated by the US Food and Drug Administration and then move toward regulatory approval in three to four years, he said.

The pharmaceutical industry is a major target for the company and where it will target first, particularly the late-stage drug discovery and development arena, Zagnoni said. The firm also intends to partner with pharma companies to apply the technology to clinical trials and refine patient stratification and selection.

A lot of drug development work is still being done with "suboptimal" tumor models, and ScreenIn3D's technology provides an opportunity "to access a much more advanced model to get better data," he said.

Compared to traditional methods, which use dead tumors that can't provide continuous readouts, the benefit of the Onco-Chip 3D platform is that users can look at a live tumor and get multiple readouts, such as the shape of a tumeroid, continuously over a period of time, said Alex Sim, the company's executive chair. There is "growing evidence of the predictive value" of testing a treatment on a live or patient-derived sample, Zagnoni added.

The company is in the final stages of a fundraising round that is expected to close later this year, although Zagnoni and Sim declined to disclose details, and it has already begun some commercial activities, generating revenue by screening compounds for biopharmaceutical companies. But that screening business is just the first step as the firm prepares for further commercialization, Zagnoni said.

The device's application is not limited to oncology, he added. The company has demonstrated the platform can be used to study endometriosis, showing they can rebuild 3D models of a uterus with very small biopsies. It is working with collaborators in Liverpool, UK, to test treatments for the disease, he said. Another project involves using brain stem cells to create mimics of neurological diseases like Alzheimer's and Parkinson's and test drugs.

"This could become another technology that can access different types of areas," such as different disease states or different clinical applications, Zagnoni said.