TCV’s healthcare team has long been pursuing a thesis around the utilization of healthcare data, particularly for applications in the life sciences industry. Specifically, we believe that companies with proprietary technology that enables them to aggregate, curate, and contextualize healthcare data have a tremendous opportunity to layer on software applications and help address a myriad of downstream use cases for their customers. Our Series C investment in BenchSci, completed in partnership with our friends at iNovia Capital and F-Prime Capital, provides an illustration of this thesis in our portfolio – one of many, we hope, over the next few years. The Series C funding is intended to help BenchSci expand the company’s artificial intelligence and machine learning-enabled software platform into additional applications, rapidly scale headcount, and forward invest in future growth initiatives.
BenchSci was founded in 2015 by CEO Liran Belenzon, Chief Science Officer Tom Leung, Chief Data Officer Elvis Wianda, and co-founder David Chen who met one another through the University of Toronto’s Creative Destruction Lab. The company’s technology platform endeavors to increase productivity and efficiency in the preclinical research process for pharmaceutical and biopharmaceutical organizations. The life sciences industry spends an extraordinary amount on preclinical research as these efforts help develop a pharmaceutical or biopharmaceutical company’s core intellectual property. We estimate global preclinical expenditures at ~$80B annually, or ~40% of total research and development investment for life sciences firms, and scientists at pharmaceutical and biopharmaceutical companies perform tens of thousands of preclinical experiments per year.
Despite this level of investment, preclinical research has long been plagued by inefficiencies. BenchSci’s customers estimate that approximately 80% or more of preclinical experiments performed yield no value to their overall research efforts; relatedly, it is extremely challenging to identify potentially wasteful or redundant experiments a priori. This process continues to be one of trial and error – more “art than science” – and limited technology tools exist to help scientists become more productive. Moreover, the data captured in the context of these efforts exist in disparate, siloed systems, thereby inhibiting information sharing and collaboration even within a life sciences company. Even when successful, a preclinical research process takes between six to seven years on average, thereby delaying time-to-market for life-saving medicines.
The problem described above is the one CEO Liran and his team are determined to solve via technology. The company’s mission is to deliver technology that helps scientists bring novel medicines to market 50% faster by 2025. To do so, BenchSci has built a comprehensive preclinical experiment-focused knowledge graph, encompassing data on over 40 million experiments. Consistent with our framework outlined above, the company has built software and computer vision technology that automates the stitching together and curation of experimental, bioinformatic, and other data from numerous, disparate sources, including its customers’ own internal data. Further, the company’s team of PhD scientists works alongside BenchSci’s product and technology teams to contextualize BenchSci’s 100+ machine learning models and algorithms such that its knowledge graph and results make “scientific sense” to scientist end-users as they leverage the company’s technology platform.
BenchSci’s flagship application was launched in 2017, and leverages artificial intelligence to help scientists select the optimal antibodies and/or reagents to use in their experiments based on experiments previously performed that are relevant to the study in question. This saves scientists significant time and resources – customers indicated to us that they have saved tens of millions in hard costs alone by eliminating redundant/wasteful reagent purchases, not to mention the time savings (several weeks to months per project) and other efficiencies they’ve realized. The company is not stopping there, and we are particularly excited about what BenchSci is going to do next with its breakthrough technology that will shape the future of preclinical research, although we will leave it to Liran and his team to share more in the coming months.
BenchSci’s compelling value proposition, coupled with its reputation for relentless innovation and superb customer service and support, has engendered customer delight, and the company boasts a net promoter score of 80+. Its customers include 16 of the top 20 pharmaceutical companies (by revenue), in addition to over 4,500 leading research centers globally, and its platform is being used regularly by 50,000+ scientists. CEO Liran has scaled the organization to meet latent demand – BenchSci has grown its employee base more than 8x in the past three years, and expects to reach 400+ employees by the end of 2022. The company has been recognized as a Deloitte Tech Fast 50 company and a CIX Top 10 Growth company.
CEO Liran has also lined-up an impressive team of advisors and experts to advise BenchSci on life sciences research and development, organizational culture, and artificial intelligence and machine learning technology, including TCV Venture Partner Jessica Neal (former Chief Talent Officer at TCV portfolio company Netflix).
“BenchSci plays an important role in curating and contextualizing healthcare data to increase productivity in the preclinical research process,” says Jessica, “and I look forward to supporting Liran and his team as they continue to scale.”
Growth metrics and accolades aside, what also impressed us about BenchSci is Liran’s unwavering focus on fostering BenchSci’s culture. Liran believes the company’s distinguished culture is instrumental to its success, and he endeavors to build an inspiring, inclusive, and equitable work environment where employees are set up to thrive and have a meaningful career. Starting with Liran, it was clear during our diligence that BenchSci’s employees pursue continuous improvement and a high-degree of transparency and candor. The results speak for themselves – BenchSci has been named a certified Great Place to Work® and is a top-ranked organization on Glassdoor. We are excited to add Jessica Neal to BenchSci’s advisory board to help Liran continue to develop and grow the company’s culture as BenchSci scales through its next major inflection points.
“Our recent Series C raise enables us to build and deliver a next generation AI solution for global pharmaceutical companies that will enable scientists to exponentially improve their preclinical R&D work,” says BenchSci CEO Liran Belenzon. “We are a mission-driven organization intent on achieving success beyond success, and I’m excited that TCV recognizes our market-leading potential and has chosen to back our meteoric hypergrowth.”
We are off to the races in our partnership with Liran and the BenchSci team, and are incredibly excited to help build a category-defining, generational software company that drives productivity and efficiency in the preclinical research process, thereby bringing novel, life-saving medicines to patients faster.
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The views and opinions expressed are those of the speakers and do not necessarily reflect those of TCMI, Inc. or its affiliates (“TCV”). TCV has not verified the accuracy of any statements by the speakers and disclaims any responsibility therefor. This blog post is not an offer to sell or the solicitation of an offer to purchase an interest in any private fund managed or sponsored by TCV or any of the securities of any company discussed. The TCV portfolio companies identified, if any, are not necessarily representative of all TCV investments, and no assumption should be made that the investments identified were or will be profitable. For a complete list of TCV investments, please visit www.tcv.com/all-companies/. For additional important disclaimers regarding this interview and blog post, please see “Informational Purposes Only” in the Terms of Use for TCV’s website, available at http://www.tcv.com/terms-of-use/
