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Alex J Rai is the director of clinical chemistry services and a professor in the Department of Pathology and Cell Biology at Columbia University Irving Medical Center. Leveraging his vast experience, Rai focuses on providing quality clinical services and overseeing the laboratory testing services at the medical center. He also keeps a keen eye on emerging trends in the predictive medicine space.
In an interview with Healthcare Tech Outlook, Alex shared his insights on the integration of AI that is changing the landscape of precision medicine and enhancing research for better outcomes. Result Oriented Services Driven by Experience I have been serving in my current role at the Columbia University Medical Center for the last 15 years. During this time, I have gained significant experience in the field of science and research, including managing clinical chemistry services. Unprecedented Growth Fueled by Automation Over the years, automation has been a prevailing trend in the clinical laboratory and research field. It has streamlined outcomes by reducing financial hardships through cost-effective techniques in the industry. One of the challenges in the clinical laboratory space is the aging of technicians and technologists, positioning many of them to retire in the near future. The increasing number of retirees and growing group of new recruits without adequate experience poses a problem. We are getting to a point where the average age is barely high, and the number of trained technologists coming into the industry has gone down. Automation and robotics have brought a new approach that can help address this challenge. Emerging developments in this field mean fewer individuals are required to operate instruments, working in favor of the industry. “Over the years, automation has been a prevailing trend in the clinical laboratory and research field. It has streamlined outcomes by reducing financial hardships through cost-effective techniques in the industry.” Another emerging trend common with automation and robotics is the production of more data, which is beneficial for research. More data allows for the interrogation of samples, gathering of information, and application of it to more complex algorithms. The role of a clinical laboratory scientist or a technologist will undergo enormous change with this technological upgrade. There will also be a greater need to interpret complex results coming from the instrumentation as a result of running more tests for complex algorithms. It is important for us to work through the challenges and come up with the next generation of algorithms that will drive better patient outcomes. Looking Out to the Horizon One of our biggest goals is to monitor some of the advancements in AI and machine learning. For instance, ChatGPT was adopted and popularized in the span of two years, which made a drastic impact on the general public. People were intrigued and sought ways to incorporate the technology into their lives. The main focus for the next 18 to 24 months is the implementation of automation in the field of clinical research. Despite being in the early stages of development, the technology promises great potential. Pearls of Wisdom My advice to peers is to stay abreast of all the latest new developments in the industry. Changes are coming at an incredible pace, and it is imperative that professionals keep up with emerging trends. Engaging with mentors and attending specialized events is helpful to achieve insights and create value for future endeavors. Keep an eye out for how others are exploiting emerging technologies and the kind of efficiencies they are deriving. This can provide a better understanding of how to apply these technologies in one’s individual settings.I agree We use cookies on this website to enhance your user experience. By clicking any link on this page you are giving your consent for us to set cookies. More info