When Allen and I meet new faces in networking events, often people are curious about how we met. So now, once and for all, let me tell you. We met in the summer just before my freshman year in Engineering at University of Toronto. He was a year senior to me and we were introduced through some common friends. Once school began, we hung out often in the engineering library in the Sanford Fleming building. And of course being a very smart woman, I picked this very brilliant guy and the rest is history. 😀

Why did I choose to become an engineer? Because I love STEM (Science, Technology, Engineering and Math). In my high school years, I was particularly fascinated by science. Wearing a lab coat, and working with test tubes, bunsen burners and microscopes, etc. were a lot of fun and fascinating. However, one thing was very frustrating. Had I incorrectly set up my experiments, be it with the wrong chemicals or measurements, I had to start the experiment all over again. When the lab assignment deadline is pressing, having to redo it was certainly not a fun thing.

Therefore I always admire scientists who spend so much time to meticulously conduct their experiments to validate their hypothesis. In many experiments, a lot of compounds are involved. A small mishap in the process could cost them months if not years of time and hundreds of thousands of dollars. Unfortunately, currently there is no easy way to allow scientists to quickly and easily search millions of papers to find the data they need, such as antibody usage data. Needless to say, millions of dollars – let alone valuable research time – are wasted in failed experiments that are preventable.

So when I was introduced to BenchSci, I was intrigued. Their team is made up of scientists who truly understand the needs of their fellows. They explained that even though the internet has ease the flow of information within the science community, the cost of retrieving data is still extremely high and ineffective. Not only is scientific information scattered and buried inside millions of scientific publications, but the information is also unorganized and unstructured in such a way that it is very tedious to retrieve and make use of. 

For example, when a scientist would like to use an antibody in one of their experiments on brain cancer cell research, the scientist would have to comb through many publications from many different disciplines in order to understand how other scientists use this specific antibody in their experiments. Sometimes these other experiments may not be even related to cancer research. The scientist would have to draw her own assumptions on the usage and properties of the antibody in order to apply the learnings in her own experiments. 

In other words, collecting information about the usage and properties of different compounds in different scenarios from a totally disorganized arrays of data sources is a painful step in conducting scientific research.

The BenchSci platform leverages machine learning to allow scientists to quickly and easily search millions of publications to find antibody or other compound usage data. Equally importantly, not only does the platform properly organize data for retrieval, but it also connects scientists with many disciplines around the world. The platform enables scientists to share their own proprietary observations pertaining to the antibodies in their own research, which might only be captured in their own laboratory log books. BenchSci is aspired to become a very powerful community of scientists who hold the knowledge that the world awaits to unleash.

In their words:

“BenchSci was born as a result of our team’s continuous struggle of sifting through millions of scientific papers to find the antibody validation data. We are to liberate scientists from the burden of conducting the grunt work when planning experiments and to prevent scientists from spending valuable research time and resources on failed experiments.”

BenchSci is accelerating the pace in global scientific research when groundbreaking scientific discovery is crucial. The success of the platform will contribute directly to the advancement of the medical and pharmaceutical community, food science and many other disciplines that rely on the collective knowledge and success of scientists in the world.

We are so proud that we have the opportunity to invest in BenchSci in May 2016. It is such a privilege to be in the journey with BenchSci founders Liran, Tom, David and Elvis to unleash knowledge in the science community.

– Eva