Tomomi Takeuchi and Eric Poliner start new positions at Michigan biotech companies
MSU-DOE Plant Research Laboratory (PRL) couple, Tomomi Takeuchi and Eric Poliner, have each joined a Michigan-based biotech company this past month.
Tomomi is employed by Charles River Labs in Mattawan, MI, in the Biomarkers and Investigative Pathology Unit.
Charles River is a drug manufacturer with 90+ facilities in over 20 countries and over 14,000 employees. The company is a contract research organization that offers a range of services that span the drug discovery and development continuum. The company’s site in Mattwan, MI primarily deals with safety assessments of novel therapeutics.
Tomomi, in her new Scientist position, will tackle developing and validating methods and procedures to test chemical entities or study chemical compounds in vitro or in vivo.
"Michigan State University and the Benning lab have been a great place for me to develop my skills as a scientist, and I hope I can apply them in my new job in the industry to make positive impacts on people's lives,” Tomomi says.
Eric, in turn, is a Laboratory Scientist with Physicians Toxicology in Kalamazoo, MI. The company specializes in delivering custom medication monitoring, personalized service, and education. Eric will be developing test protocols for new quality assurance applications.
“I would like to thank and credit PRL for being a great learning environment for me and giving me a lot of opportunity as I move forward with my career,” Eric says.
Congrats Eric and Tomomi!
Researchers are integrating their work into undergraduate cell and molecular biology laboratory courses at Michigan State University through the use of Arabidopsis mutant screenings.
MSU-DOE Plant Research Laboratory (PRL) scientists have published a new study that furthers our understanding of how plants make membranes in chloroplasts, the photosynthesis powerhouse
A new AI system, called DeepLearnMOR, can identify organelles and classify hundreds of microscopy images in a matter of seconds and with an accuracy rate of over 97%. The study illustrates the potential of AI to significantly increase the scope, speed, and accuracy of screening tools in plant biology.