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ANNOUNCEMENT

New Member – Dr. Takahiko Koyama

January 31, 2024

Introducing new member of Bio2Q

We are delighted to welcome  Dr. Takahiko KOYAMA as our Principal Investigator at Q core of Bio2Q.

The greeting from Dr. Koyama is as follows:

“Born in Osaka, Japan, I envisioned myself becoming an aerospace engineer designing spacecrafts. After my graduation from high school, I moved to the US to realize my aspiration. After I encountered a book titled QED, authored by Richard Feynman, I was enthralled by the beauty of quantum physics and changed my major. Auspiciously, I could earn a Ph.D. in physics from Cornell University, an underpinning that has propelled me into diverse and impactful roles.

Around the turn of the century, I was alarmed and excited by the Human Genome Project and stepped into the realms of life sciences by joining the University of Pennsylvania as a postdoctoral fellow, where I conducted research on protein flexibility and bioinformatics.

At Takeda Pharmaceutical, my initial work was to discover novel endogenous ligands for GPCRs. Subsequently, I moved to the computational chemistry department, where I engaged in optimizing lead compounds in numerous drug discovery projects, each addressing critical aspects of cancer or central nervous system disorders. I also delved into the field of machine learning, contributing to the design of a High Throughput Screening Library. 

My tenure at IBM Watson Research Center was equally enriching, where I paved the way for genomic medicine, laying the groundwork for Watson for Genomics. In this capacity, I had the privilege of leading a team of brilliant minds across the globe to push the boundaries of precision medicine. On the academic front, my paper titled ‘Variant Analysis of SARS-CoV-2 Genome’ stands as early yet influential contribution to comprehending the pernicious virus responsible for COVID-19. 

Leveraging expertise in AI, quantum computing, and biology, I am thrilled to deepen our comprehension of science of microbiome by deciphering dark matter in metabolomics and unravelling uncharted roles of virome with preemptive applications of quantum machine learning as quantum computing ushers in a new paradigm. “

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