Michael Kane, Ph.D.
Dr. Michael Kane’s professional interests involve aspects of genomics, biomedical informatics, health care technology and higher education. His professional experience includes preclinical research in the pharmaceutical industry, serving as vice president of R&D at a publicly traded genomics/biotechnology company, and co-founding biotechnology companies based on technology and methods that he developed/patented. His primary interests have involved the development and utilization of genomic detection technologies, primarily DNA microarray methods, which have been applied to exploratory discovery efforts in agricultural, ecological, preclinical and clinical studies. His paper on the genomic and algorithmic methods for DNA probe design in DNA microarray detection has been cited by more than 500 articles, has been internationally adopted as a standard method for DNA probe design and sequence analysis in genomics, and is the most common method utilized by commercial DNA microarray probe design software systems. In addition, he has led the efforts to develop data management tools in support of pharmacogenomics and personalized medicine, which have been extensively utilized as a teaching tool for health care professionals, and serve as the basis for a seed-stage health care data management company. Kane also serves as an expert witness in criminal cases involving DNA evidence. Kane is currently a visiting research scientist in the Raabe College of Pharmacy at Ohio Northern University.
“The adoption and utilization of clinical genotyping and personalized medicine in health care depends upon the development of training and education practices to dispel fears and better understand the value of using genomic biomarkers to improve medicinal and therapeutic outcomes.”
“Personalized medicine involves the utilization of patient-specific DNA biomarkers to PREDICT the efficacy and safety of prescription drugs in a given patient.”
“Although newer, faster, cheaper DNA-testing methods are constantly being developed, the key to the successful implementation of personalized medicine lies in the ability to effectively manage patient- and population-specific data, and convert genetic data into useful knowledge in clinical decision support processes in health care.”