Kas Subramanian, PhD LinkedIn

Executive Director, Modeling

Modeling & Simulation

Kas has a strong interest in the role of mathematical methods to aid decision support in drug discovery and development. Prior to joining Applied Biomath, Kas led the Bioinformatics group at Syngene International which integrated data and created models to support programs across the drug discovery pipeline; from target identification and validation through lead optimization and clinical trial design. Prior to Syngene, he was Chief Scientific Officer at Strand Life Sciences Pvt. Ltd where he led the groups involved in the development of the Sarchitect Platform, the Virtual Liver and the interpretation platforms for NGS-based diagnostics. He headed the Collaborative R&D group for immunology products at Entelos and has also worked at Genetic Therapy Inc (Novartis) where he helped found a group to perform research in synthetic and hybrid vectors for gene delivery. In 2015, Kas was elected as a Fellow of the Indian National Academy of Engineering.

He has a B.Tech. in chemical engineering from the Indian Institute of Technology, Bombay and an MS from SUNY at Buffalo. His Ph.D. is in Biomedical Engineering from the Johns Hopkins University, School of Medicine. 

Scientist Spotlight

May 2021

What is your role at Applied BioMath?

“We help pharmaceutical companies make decisions about R&D—from the experiments they should run to which clinical trials to do. We support their decision-making by modeling those situations and helping them figure out next steps.”

What do you love most about working here?

 “There are many things that I love about working here. I am in a field where I have the ability to make a real difference in improving the quality of people’s lives. The fact that I can make an impact is important to me. Secondly, I get to do this every day with some of the smartest and nicest colleagues that I’ve ever had and who make it a pleasure to come to work every day.”

What is the most rewarding part of your job?

“I think the most rewarding part of the job is when our clients tell us that our work had a direct impact on their R&D.”

What made you get into the field of life sciences?

“I have always found life sciences very fascinating. I did very well in biology throughout school, but I loved physics and math, so I decided I wanted to be an engineer. I studied chemical engineering in undergrad, and a request for application to the Johns Hopkins chemical engineering department landed up by happenstance in their biomedical engineering department. When I looked at the application brochure and saw biology and differential equations on the same page; I was hooked. I was fascinated by the thought that I could work on physics, math, and biology all together, and that’s what I did.”

What do you like to do in your spare time?

“I like to read, play tennis, and participate in other outdoor activities. I also really like hearing and playing music. I’ll spend a lot of my free time recording music and doing audio engineering on the side.”

Do you have a motto or personal mantra you live by?

“I think my mantra is that life is too short to regret the things that you have not done. I need to make the best of where I am right now.”

If you won the lottery, what is the first thing you would do?

“If I won the lottery, the first thing I would do is put some money off to the side for my children’s education. The second thing I would do is build a professional music studio and spend a lot of hours there!”

What's a random fun fact about yourself?

"I have done voice overs for a few National Geographic documentaries in the past and found that I now have an IMDB page."

What inspires you every day?

“When I look around me, I realize I’m really lucky to be where I am. I see people around me who do not have the opportunities that I have, people that are trying to live in a world that is really stacked against them and succeeding in spite of the odds. These are the people that inspire me, that make me feel that I need to make my every day count.”


Key Research

  • Two heads are better than one: current landscape of integrating QSP and machine learning
  • Quantitative modeling predicts competitive advantages of a next generation anti‐NKG2A therapy over monalizumab for the treatment of cancer
All publications

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