ABU DHABI, 4th December, 2025 (WAM) -- Researchers at New York University Abu Dhabi (NYUAD) have developed Spheromatrix, a simple and low-cost technology that enables tumor models to be grown, frozen, and stored for future use in cancer drug testing.

Spheromatrix is made from specially engineered filter paper patterned to support the growth of tumor spheroids in a controlled, reproducible manner. Unlike conventional approaches, which are expensive, complex, and cannot be preserved, this platform enables researchers to build biobanks of "off-the-shelf" tumor models that can be thawed and tested on demand.

The research team that conducted the study is led by Associate Professor of Mechanical Engineering and Bioengineering Mohammad A. Qasaimeh, with first author Postdoctoral Associate Ayoub Glia and colleagues at NYUAD's Advanced Microfluidics and Microdevices Laboratory (AMMLab).

"Spheromatrix represents an important step forward in cancer research," said Qasaimeh, Associate Professor of Engineering at NYU Abu Dhabi. "Its fiber-based structure provides a biocompatible environment for cells, letting tumor models behave more like real cancers. Preserving these models for long-term use speeds up preclinical testing, reduces reliance on animal models, and opens new possibilities for patient-focused research."

The team tested Spheromatrix with commercial chemotherapy drugs on brain tumor models. Preserved tumors responded closely to real patient cancers, demonstrating the platform's potential to provide reproducible, realistic, and scalable systems for drug screening.

"Our goal was to design a platform that is simple, reliable, and affordable, while addressing a major bottleneck in cancer drug development," said Glia. "By engineering paper to support tumor spheroids, we can grow, freeze, and reuse models for multiple experiments. We are now exploring the use of patient-derived samples to enable more personalised cancer therapies."

Spheromatrix could reduce costs and timelines for preclinical testing, provide humane alternatives to animal models, and pave the way for patient-focused precision oncology.