I am a 2021 MBA Candidate at the University of Florida. Before my MBA study, I had 10 years of experience in life sciences that included roles in R&D, strategy, and venture capital. In the past few years, I developed a keen interest in the role of financial markets as stewards of healthcare innovation. It motivated me to build a collection of machine learning models, some of which I present in this blog. My mission is to develop and popularize a systematic approach to biotech investing. So we can allocate our resources more efficiently and get to new drug approvals faster and cheaper.
More about me
I grew up in the 90s in Kazan, Russia. My great-grandfather was a renowned Soviet mathematician, who made significant contributions to his field. He died long before I was born, but my grandma always talked about his ability to multiply 5-digit numbers in his mind. As a young kid, I thought that if I can become a man of science like he was, I can surely make a mark on the world.
I was not a math wunderkind, but my dad gave me some of his programming textbooks. And at the age of 10, I coded an animated 2D model of the solar system in Turbo Pascal. It ran on MS-DOS and a 286 processor.
I got the planetary dimensions and orbital speeds from the Great Soviet Encyclopedia — sixty-five heavy-bound volumes with dusty, yellowed pages — an heirloom passed on from my great-grandfather.
I felt like an alchemist.
In the early 2000s, our family moved to Miami to join my uncle, who immigrated to the US a decade earlier. I finished high school and began studying chemistry at the University of Florida.
I enjoyed taking advanced math courses outside of my chemistry major. As I progressed through my senior coursework, I experienced joy from seeing how calculus, probability, and quantum theory combine to yield a deeper understanding of chemistry than the simpler problem framework I learned as a junior student.
I later encountered that same feeling of seeing something through multiple prisms while learning finance. Now I will purposely chase it.
I worked in biomedical labs while in school. By the time I graduated, I mastered most experimental techniques and co-authored several publications. I also got to see how biomedical academia is biased in favor of publishing inconclusive and misleading research. I ultimately decided not to pursue an academic career and go into industry.
Over the next six years, I worked as a lead bioengineer on some of the most exciting projects in molecular diagnostics. In the early 2010s, I moved to San Diego to lead a small engineering team at a biotech startup, then I moved to Boston to join the personalized medicine organization at Novartis.
During my four years at Novartis, I was introduced to other aspects of the industry, like strategy and finance. More importantly, I met many like-minded people among local students, entrepreneurs, and industry experts, who will forever remain my closest friends and mentors.
In 2016, I joined RBV Capital, an international boutique venture capital firm that specialized in biotech investments. At the same time, I became keenly interested in machine learning and finance. I discovered that programming languages advanced quite a bit since my Turbo Pascal days, and I started spending all my free time coding in Python to explore financial trends in life sciences.
Living in Europe for three years and traveling around the world in search of promising biotech investments was the adventure of a lifetime. At RBV, I led an investment in Bonti, a non-opioid pain management startup, which was later acquired for close to $300 million and remains the fund’s most profitable investment.
In 2019, I went back to the US to pursue my dream of using finance and AI to help innovative biotech companies develop life-saving treatments.
