Martha is a chemist with expertise in diverse areas of analytical chemistry. She had worked as an analyst at a licensed 3rd party analytical laboratory where she focused on developing and validating analytical methods for bioequivalence studies. Later, she served as a quality control expert in the analytical domain and as a monitor in clinical trials. Her interest in the clinical industry led her to be a part of two of the biggest hospitals in Mexico where she gained expertise in hematology, microbiology, and blood banking.
Martha holds a bachelor’s degree in Clinical Chemistry from the Faculty of Medicine UANL and a master’s degree in Pharmacy from the Faculty of Chemical Sciences UANL, Mexico.
About
Artificial Intelligence (AI) is a computer program designed by scientists to perform operations typical of human intelligence. AI is everywhere, even in different fields of science, including clinical research, which promotes increasingly accelerated advances in healthcare. Today, researchers can trust AI at each clinical research stage to develop protocols, recruit healthy subjects or patients, share results, and even discover new and more effective drugs. Implementing AI in clinical research can be slow and tedious, as numerous regulatory hurdles can interfere with integrating AI tools.
Some factors that can slow down the advances in AI are the privacy concerns that could arise when handling huge volumes of participant data and some ethical dilemmas. To bridge this gap and accelerate the implementation of AI in clinical research, a Laboratory Information Management System (LIMS) can help.
Who Should Attend?
Recommended attendees include lab managers, directors, quality managers, and technicians of clinical research and cancer labs.
Agenda
A review of the applications of AI in clinical research.
The barriers researchers have to cross to implement AI in their clinical research lab.
How an informatics tool can help break down those barriers with an informatics tool.