Using AI to speed up the scientific process is a concept referred to as “self-driving labs,’’ applying the ideas behind self-driving cars to laboratories
Rutgers associate professor of Biomedical Engineering Adam Gormley (left) with his former student, Matthew Tamasi, who serves as Chief Technology Officer of Plexymer, Inc.
A startup company formed based on technology developed at Rutgers seeks to use artificial intelligence and automation to help researchers advance their work faster and make breakthrough discoveries.
“Currently in labs, a scientist follows the conventional scientific method where they come up with a question, develop a hypothesis, design an experiment to test that hypothesis, implement the experiment, analyze the results, and then update their hypotheses,” said Rutgers associate professor of Biomedical Engineering Adam Gormley, who developed the technology with his former student, Matthew Tamasi.
“The question we had was, is that the most effective utilization of a scientist’s time? We thought that maybe outsourcing some of the work such as designing experiments, performing the experiments, and then doing routine analyses may ideally be suited for an automated system, an AI model. Then, the AI model could predict the next best experiment to answer fundamental questions or design material problems.”
Using AI to speed up the scientific process is a concept referred to as “self-driving labs.’’ The idea stemmed from the notion of self-driving cars, except using laboratories, Gormley said.
The technology, being advanced by Plexymer, Inc. was created by Gormley and Tamasi in the Gormley lab. Tamasi now serves as Chief Technology Officer of the company.
“My lab is incredibly excited by the potential of self-driving labs, and we are neatly in the domain of applying these ideas into the fields of biomaterials, drug delivery, and polymer chemistry,” Gormley said.
Polymers are large molecules that are used as the basis for many organic and synthetic materials, including therapeutics. According to Gormley, pharmaceutical and consumer products use a standard set of polymers for their applications, no matter how complex the application is, and he believes custom designed polymers would work better. The challenge, however, is how to discover those custom polymers. That is where Plexymer, with its AI and machine learning technology, comes in.
The goal for Plexymer is to serve as a contract research organization for companies, organizations, or even researchers for whom AI and robotics may be useful to their discovery pipeline and are looking for experts to take their work to the next level. The company’s name stems from a combination of ‘multiplexing’ (evaluating multiple experimental elements simultaneously) and ’polymer’. The benefit of using Plexymer, according to Gormley, is that artificial intelligence cannot be distracted from its work.
“There are lots of things that complicate the schedule of a benchtop scientist on a day-to-day basis, such as meetings, other priorities, and bias,” said Gormley. “AI and automation, on the other hand, do not have any of those issues, especially if you make the process as autonomous as possible. It can potentially significantly improve not just the effectiveness but also the efficiency of the discovery process.”
After developing their technology in the lab, Gormley and Tamasi took part in the Rutgers NSF I-Corps program to learn more about the feasibility of their business model. Following that experience, the two fully explored the idea of what would become Plexymer through the national NSF I-Corps program, which gave them confidence that there was a solid business opportunity for the technology.
“The challenge of companies that have platform technology like ours is that in essence we are a hammer looking for nails,” said Gormley. “We knew we had a good hammer; we just weren’t exactly sure what nails were out there, or even what were the best nails to hammer. Our experience with the regional and national I-Corps programs helped us understand the different problems people were facing and the markets of entry that we felt had the highest level of enthusiasm and viability as a commercial service.”
“Drs. Gormley and Tamasi’s technology has the potential to advance important research in an expedient and efficient manner,” said Deborah Perez Fernandez, executive director of Rutgers Technology Transfer, which negotiated the exclusive license with Plexymer. “We are proud to have supported their work, and we look forward to seeing what they can accomplish.”
“Artificial intelligence and machine learning are both the future and the present, and Plexymer can be at the forefront of blending them with scientific research,” said Vince Smeraglia, executive director of New Ventures within the Office of Research. “Our team will continue to provide support to Plexymer to help it grow in size and scope.”
“I cannot express more gratitude and praise for the Office for Research,” said Gormley. “They are really excellent; they are engaged, they act as mentors, and they care deeply about making companies such as Plexymer successful.”
