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My Journey to Computational Biology & Roche Sequencing

Every day I am honored to have the opportunity to help make sense of data, for the sake of understanding the science and more so to enable better informed decisions.

How I got into computational biology

For as long as I can remember, I have always wanted to work in the biomedical field and contribute to bettering patient lives. Coupled with a restless urge to build things and solve puzzles, I decided to study bioengineering at MIT. I immersed myself in a variety of projects in academia and industry, where I most enjoyed work with a computational bent, such as finite element modeling of the aortic root to understand a surgical procedure and calibrating a partial least squares regression method to monitor crystallization during drug manufacturing. I have also constantly sought better and more efficient ways to complete repeated tasks, which has naturally led me to coding automation scripts and programs in different languages.

With the advent of more sophisticated technologies that collect and generate ever-growing amounts of data, I have increasingly experienced the challenges associated with having more information than we know what to do with and appreciated the opportunities for insightful data analysis. Every day I am honored to have the opportunity to help make sense of data, for the sake of understanding the science and more so to enable better informed decisions. Whether designing the next experiment in the lab, formulating the next research question for the team, defining the next product feature to develop or, in the future, helping to recommend the best the best treatment decision for a patient, these challenges have the power to one day influence our world.

Why Roche Sequencing Solutions (RSS)

The first time I was exposed to genetics was in middle school at a summer program where we extracted DNA and ran it out on a gel. I have never ceased being fascinated by biological code ever since—DNA encodes life and we get to decipher and potentially modify it! (As a disclaimer, the course included a viewing of the futuristic movie Gattaca which left a profound impression on me that we should develop technologies responsibly.) While pursuing a PhD in George Church’s lab at Harvard Medical School, I worked on synthetic biology projects for microbiome engineering, and always looked forward to checking that the DNA sequences I engineered made it correctly into a plasmid or bacterial genome.

It became part of my morning routine; I would eagerly check my inbox at 6 am for new Sanger sequencing results for my latest cloning experiments.

Certainly one could imagine how exhilarating it was for me when we started getting back troves of data from high-throughput DNA sequencing of different in vitro and in vivo library selection experiments. It was several orders of magnitude more data!

As I was wrapping up my degree, I was attracted to RSS because I wanted to continue working on next-generation sequencing (NGS) data analyses and technology development. I had also completed two summer internships during college at Genentech and Roche, so joining RSS was like returning to family. RSS was a new business area in the larger Roche organization, and I wanted to help build that and make an impact on the future of clinical sequencing. It has been a privilege to work with a talented team across global sites and different functions to develop NGS-based diagnostic products and demonstrate their medical value through clinical projects on real patient samples.

It has been a privilege to work with a talented team across global sites and different functions to develop NGS-based diagnostic products and demonstrate their medical value through clinical projects on real patient samples.

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