“AI helps us better understand and support patient needs”

Beryl A. Ojwang, MD, MBA, MPH, Associate Medical Director, Oncology & Biosimilars, North America Medical Affairs, shares how technology helps generate patient insights for Teva scientists.

You might say healthcare is my family business. My father is a research scientist and professor of virology, chemistry and biochemistry at Eastern Florida State College. My mother is a registered nurse, and my sister is a pediatric nurse practitioner. Other family members are clinicians. My great-great grandmother and grandmother were community midwives in Kenya, my homeland. It’s a deep tradition.

My dad sparked my interest in science. I loved going to his lab as a kid. He always made it fun, allowing me to mix solutions that changed colors. As I got older, I would read his recent publications, some of which I didn’t understand, so I asked a lot of questions. I was, and still am today, very proud of his work in early revolutionary antiretroviral medicines, which gave hope to people with HIV/AIDS when there was none before.

My educational road had twists and turns, but always brought me back to patients. I always wanted to work in clinical medicine – specifically, I aspired to be a pediatric surgeon. However, the flexible curriculum at Duke University School of Medicine revealed other paths by allowing students to pursue other avenues. In my third year, I decided to pursue a Master of Business Administration (MBA) to understand healthcare as a whole, not just the patient-physician relationship. Even with a dual MD-MBA degree and a concentration in health sector management, my lifelong love of learning led me to a Master of Public Health program. My education gives me a deep foundational knowledge of patients and the complex healthcare systems they navigate.

Working in Teva’s Medical Affairs department keeps me connected with physicians and patients. I love my work at Teva; I began my journey as a Medical Science Liaison (MSL) and now I am an Associate Medical Director in North America Medical Affairs. Healthcare providers (HCPs) have incredible demands on their time and might not have the chance to read the latest data. As an MSL, I brought HCPs up to speed in a straight-forward, nonbiased way, on important information; for example, research that shows a new medicine could interact with other drugs. That was something many clinicians didn’t know, but was extremely important for them to share with patients.

Artificial intelligence is a real time saver. Our Medical Affairs and Medical Information departments receive a lot of information that helps Teva serve patients and HCPs better. How much? Since 2017, we’ve gathered more than 28, 000 medical insights across Medical Affairs. 3,000 of them are on a single oncology medication. One of our databases contains about 32 million individual words! Sifting through that mountain of data can be very time consuming for human beings, which is not ideal when we need an answer quickly! Enter Teva’s Topic Modeling Tool, or ToMoTo – artificial intelligence (AI) software that can rapidly and accurately gather data. When we enter a few key words about a medical condition or product, ToMoTo searches our databases and compiles a report within three to five minutes!

We still need human understanding and wisdom. The potential for ToMoTo and other artificial tools to help us understand and support patient needs is almost endless. However, it’s not a replacement for the interpretation and insights into the human experience that our scientists can provide.

My advice to aspiring scientists is, as challenging as it may be, hone your people skills. You might think that facts and figures and nitty gritty numbers are something people want to hear about, but not everyone wants their information delivered in the same way. Be flexible, and don’t be too hard on yourselves. We all tend to focus too much on our weaknesses instead of our strengths.

If I could meet anyone from history, it would be Rosalind Franklin. She was a British chemist and pioneering X-ray crystallographer whose Photo 51 first showed the double helix of DNA. She didn’t get due credit for her work while alive, but scientists everywhere owe her tremendous respect for her groundbreaking discovery.

You might be surprised to know I come from a large family! I have three biological siblings and five adopted siblings, now ages 27-42. I am the oldest daughter, so I often had the “second mother” role. Our household of 11 had a dynamic environment, which helped me understand how people with similar experiences can have diverse perspectives or handle the same situation differently.

All work and no play? Not me! In addition to being the City of Brotherly Love, Philadelphia is a paradise for foodies like me! Thai food is my favorite, but I enjoy the many elevated American styles that can be found in Rittenhouse Square. I balance all that good eating with exercise – F45, or Functional 45 Fitness, and [Solidcore] pilates challenge me, but I enjoy them! I’ll cap off a good meal and workout by listening to a podcast or watching a Korean drama!

NPS-ALL-NP-01047 JULY 2023

Find out more

• Eran Harary, Head of Early Clinical Development, shares how AI and other cutting-edge technologies have shortened the pharmaceutical R&D process.
• Data scientist Michal Melamed discusses new trends in advanced analytics and AI for patient care.
• Learn how Teva is making innovative use of AI and Advanced Analytics in the pharma and health sector.
• WouId you like to be a part of our team, helping to improve patients’ lives? Check out our Careers page!