Jacobs School Awards First Doctoral Degree in CCBAP

The Department of Pathology and Anatomical Sciences initiated the program to train a new breed of biomedical research scientists, with the first students matriculating into the program in 2017.

“Pathology and anatomical sciences are rapidly evolving due to advances in imaging technology and computational power for analyzing biological structure and function,” says John Kolega, PhD, associate professor of pathology and anatomical sciences and graduate program director for the department.

“The future of these foundational medical disciplines will be driven by scientists whose knowledge of biological principles is supplemented by proficiency in imaging methodologies and quantitative approaches,” he adds. “In order to prepare a new generation of scientists to best engage in that environment, CCBAP integrates training in basic principles of imaging, digital image analysis and computational modeling into the study of biological form and function.”

There are currently 12 students in the program.

“Individuals trained under this new paradigm can conduct research into function and dysfunction of the human body empowered by cutting-edge computational approaches, ultimately providing improved strategies for diagnosis, treatment, or management of injury and disease,” Kolega says.

Brandon G. Ginley, PhD, is the first to earn the degree at the Jacobs School. His dissertation titled “Investigation of Machine Learning Algorithms for Pathologic Assessment of Digitized Kidney Biopsies” was completed under the supervision of Pinaki Sarder, PhD, associate professor of pathology and anatomical sciences. 

“I am proud to be the first person to complete the program and I am also extremely thankful for the diverse set of faculty minds and resources we have in our department which helped me to achieve my thesis goals and become a more well-rounded intellectual,” Ginley says.

Ginley says one of the most attractive things about the program for potential students is the ability to develop a multidisciplinary skill set that will allow them to have a hand in constructing the future.

“All over the country and the globe, governments, industries and health care institutions are greatly increasing funding for the application of computer sciences to investigate massive dataspaces and streamline workflows, particularly for medicine,” he notes.

“This is because machine learning/artificial intelligence (AI) has the potential to revolutionize clinical practice and digital health care companies are already disrupting major markets,” Ginley adds. “The way that research, health care and industry have been headed in the past five years indicate a future where these algorithms are highly integrated with our medical practices to develop the most efficient workflows, diagnostics and treatment regimens for patients.”

Ginley says the value of this skill set is evidenced by two of the Sarder lab’s recent graduates both securing high level positions at Johnson & Johnson.

“Major industry players are putting a lot of funding into securing high-level talent with these skill sets,” he notes. 

Ginley, a postdoctoral researcher in the Department of Pathology and Anatomical Sciences, is focusing on the computational analysis of kidney biopsies using machine learning and AI — a continuation of his thesis work.

“For our upcoming future works, we are highly interested in working on data fusion problems — integrating molecular or genetic sequencing information with a patient’s tissue biopsy information to discover new biological mechanisms, treatment pathways and risk factors — which we believe will be an extremely important component for the future of AI in computational pathology,” he says. 

One of Ginley’s career goals is to create a startup that performs that computational analysis, but can also provide the algorithms to hospitals and clinics to improve patient quality of care.

He continues to work to that end with mentoring and guidance from the startup ventures team at UB’s Business and Entrepreneur Partnerships.

“The algorithms that I developed in my thesis have a lot of applications for a lot of people, but the tricky part of starting a business is finding the best single market to focus on, as focusing on too many avenues is an easy path to startup failure,” Ginley says.