PFI-TT: Development of an Automated Cell Culturing Platform for Highly Efficient and Reliable Drug Testing in Physiologically Representative Disease Models

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project to make drug testing faster and more reliable. This project will build a first-of-its-kind automated cell culturing platform that will allow pharmaceutical companies make faster, more efficient, and reliable predictions regarding whether costly (up to a $billion) animal and human drug trials are justified. This leads to: (1) cheaper, faster, and more reliable data collection per sample, (2) more robust product quality, and (3) a significant labor reduction. Lastly, an education program will be designed to train diverse entrepreneurial students in the time-sensitive financial, legal, managerial, and ethical aspects of commercialization and running biotech startups.The proposed project advances the ability to perform localized cell and/or chemical manipulations (i.e., removal/collection, delivery/addition) within living cultures used as disease models on microscales and without significantly disturbing an ongoing experiment. The benefits articulated above are generated by: (1) real-time non-sacrificial monitoring of the cell behavior (as opposed to the typically sacrificial endpoint analysis necessitated by the conventional products currently on the market); (2) detected problems corrected within the culture immediately (as opposed to waiting until the endpoint analysis to find out about their existence) and in a consistent automated manner; and (3) automation of the manual labor associated with culturing and analyzing the cells. Project objectives are to: (1) Make the culturing platform easier to set up and operate by an inexperienced user. This will be done by bundling its individual hardware and electronics components into a single Plug-and-Play system; (2) Design disposable culturing inserts for ensuring system sterility for the customers and recurring profits for the partnership; and (3) Develop a fabrication recipe that will enable less labor-intensive mass manufacturing of the product than the manual method that was used to create its alpha prototype. This will be accomplished using automated tools like laser-cutting and 3D printing.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.