The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a drug discovery platform for preclinical cancer drug testing using a 3D tumor model technology. The technology is designed to reduce time and costs associated with the high failure rate (~95%) of cancer drugs by increasing the likelihood that candidate drugs advancing to animal studies will be effective. The robotic technology will provide a biologically relevant tumor model to test libraries of cancer drugs in the preclinical stage, and replace currently used 2D cancer cell models. This project aims to scale up the 3D tumor model technology to accommodate large drug libraries tested in the pharmaceutical industry, and verify that it meets industry standards and customer needs. The technology will expedite the introduction of effective cancer drugs into the market for patient use, and help reduce the more than half a million of lives that cancer claims annually. The proposed work will significantly facilitate the introduction of the technology into the market as a preclinical cancer drug screening tool by demonstrating its competitive advantages and capabilities to improve cancer drug discovery efforts.This SBIR Phase I project proposes to develop and validate a 3D tumor model technology for high-throughput cancer drug screening in the pharmaceutical industry. Despite widespread interest in 3D cancer cell cultures, existing methods are not currently used in the industry due to their many disadvantages. The proposed technology provides a robust, high-throughput, and cost-effective approach to generate 3D cancer cell cultures for rapid drug screening, beyond what is currently available. This work will evaluate quantitatively the reliability and robustness of 3D cancer cell cultures and costs of cancer drug testing while considering competitive techniques. A major goal is to adapt the technology to a 1536-microwell plate format for highly efficient drug screening, which is not currently available on the market, and validate the capabilities of the technology to predict cancer drug responses in animal studies. This work will involve robotic protocol optimization, imaging analysis of 3D cultures for consistency, proof-of-concept cancer drug screening, and statistical evaluation of robustness. It is anticipated that the work will demonstrate the advantageous capacity and speed of the technology for drug testing, industry-level robustness, compatibility with different cancer cell types, ability to predict animal study drug responses, and low cost.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
