老司机直播

With Google's backing, 老司机直播 startup BenchSci uses AI to create 'super scientists'

Photo of BenchSci's four founders
BenchSci, which uses machine learning to help scientists scour, select and purchase antibodies for their experiments, has so far raised over $27 million from investors 鈥 including Google鈥檚 Gradient Ventures (photo courtesy of BenchSci)

In less than three years, biomedical firm BenchSci has gone from four people sitting around a table to a 50-strong operation that鈥檚 backed by Google and counts some of the world鈥檚 top pharmaceutical companies among its clients.

It鈥檚 been a heady rise for , which uses machine learning to help scientists scour, select and purchase antibodies for their experiments, saving time and money. To date, BenchSci has raised over $27 million from investors. That includes Google鈥檚 Gradient Ventures, which last year made BenchSci its first investment outside the United States before .

The idea behind BenchSci was birthed from frustrations experienced by chief scientific officer Tom Leung back when he was working on his PhD in epigenetics at 老司机直播. Like many other researchers in the life sciences, Leung saw experiments fail because his antibodies were unable to detect levels of target proteins.

鈥淚t becomes frustrating because, after weeks of preparing and growing cells and collecting samples, the experiment would fail 鈥 not because I did something wrong in the procedure, but because the antibody wasn鈥檛 good at detecting the protein I was looking for,鈥 Leung says.

鈥淭hat really prompted me to think that there has to be a better way for scientists to assess the quality of an antibody product before buying it.鈥

In search of people to collaborate on the idea, Leung sent a LinkedIn message to David Chen, whose doctoral research in neuroscience incorporated elements of machine learning. He also connected with Elvis Wianda, who was doing his PhD in the department of medical biophysics, via 老司机直播鈥檚 Life Sciences Career Development Society.

The trio got to work on a project exploring the use of machine learning to analyze scientific papers and assess antibodies with a degree of precision that wasn鈥檛 possible with existing antibody search engines and review websites.

鈥淢ost websites and other curation efforts look at how many times an antibody has been used, and give you a raw number 鈥 such as this antibody product was used 100 times or 200 times,鈥 says Leung. 鈥淔or a scientist, that鈥檚 not informative enough because those 200 times might have been in completely different experimental settings to what I鈥檓 planning.鈥

BenchSci鈥檚 platform allows scientists to identify the best antibodies for their experiments (image courtesy of BenchSci)

Determined to use cutting-edge technology to improve success rates, Leung, Chen and Wianda got involved with 老司机直播鈥檚 network of accelerators, working with and the  to get BenchSci off the ground.

In 2016, the startup was urged to apply to the (CDL) by Liran Belenzon, then an MBA candidate at the Rotman School of Management who was working a summer job recruiting startups for the lab. CDL, which is affiliated with Rotman, is among the world's leading seed-stage accelerators for companies in technology and the sciences.

Belenzon, who had prior experience as an entrepreneur in his native Israel, later took Rotman鈥檚 CDL course, which gives business students hands-on experience in building early-stage tech companies. That gave him the opportunity to work directly with BenchSci. He eventually joined the company full-time as CEO.

With Belenzon鈥檚 arrival, the trio of scientists behind BenchSci 鈥 Leung, Chen and Wianda 鈥 could now count on an experienced entrepreneurial mind to helm the business.

The company set about raising money, securing $250,000 in pre-seed funding in 2016 before landing investments from the likes of Google鈥檚 Gradient Ventures and Toronto-based Inovia Capital.

Many of the world鈥檚 top pharmaceutical companies now use BenchSci鈥檚 customizable platform, which uses machine learning algorithms to collect antibody data while taking into account the context of specific experiments.

The platform鈥檚 search results come with supporting figures from scientific literature, and include links to approved antibody vendors.

鈥淲e鈥檙e helping pharmaceutical companies go through drug discovery projects faster, saving them months of research time and millions of dollars per year,鈥 Belenzon says.

BenchSci also offers a free version of its platform to academics. It鈥檚 used by more than 30,000 scientists at 3,600 institutes.

鈥淲e want to empower scientists and that鈥檚 why we offer a version that鈥檚 free for academics. There are different features in place as their work is different to that of pharmaceutical companies,鈥 Belenzon says.

BenchSci鈥檚 co-founders are quick to credit 老司机直播 and its network of startup accelerators for bringing them together and connecting them with the people and resources needed to create a successful startup that鈥檚 positioned for rapid growth. 

鈥溊纤净辈 provides a lot of support for people who have ideas but might not have experience or prior knowledge on how to bring their idea to market,鈥 Leung says. 鈥淓veryone has an idea in their head, but executing it and bringing it to market is a completely different ball game.鈥

Belenzon credits CDL in particular for giving BenchSci a place 鈥渢o connect business and technology and form a company around that.鈥 He still maintains ties to CDL, returning every few months to give workshops on fundraising and business storytelling.

He says BenchSci鈥檚 priority for the near term will be to hire more engineers 鈥 the company expects to have more than 100 employees by early 2020 鈥 as it looks to expand from antibodies to reagents and, eventually, building an AI-assisted experimental design platform to help scientists generate hypotheses.

鈥淚 see us solving more and more problems around drug discovery and playing a crucial role in transforming scientists into 鈥榮uper-scientists鈥 and helping them get cures to patients faster,鈥 Belenzon says.

鈥淭o do that, we need more talented people. We鈥檙e hiring a lot from 老司机直播鈥 anyone who wants to do more, have an impact and is passionate about this space 鈥 we want to talk to.鈥

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