Advances in science and technology have long fueled innovation across the pharmaceutical industry. For instance, the development of mRNA vaccines to combat the COVID pandemic. And yet, despite significant achievements like this, according to Eroom’s Law (that’s Moore’s Law spelled backwards), drug discovery is only becoming slower and more expensive over time. Put another way, the number of new drugs approved per billion dollars spent on R&D is on the decline — a clear sign that pharmaceutical R&D is becoming less efficient.
For proof, look at the data: Between 2013 and 2020, the average cost to develop a single drug increased from $1.33 billion to $2.44 billion, while development cycles stretched to an all-time high of 7.14 years. Although inefficiency is commonplace across the pharmaceutical industry, one area where it’s particularly rampant is preclinical research. An estimated 50 percent of preclinical experiments are irreproducible and fail to advance drug discovery. At the cost of US$28.2 billion per year, that’s a serious problem.
There are many reasons why scientists might fail to reproduce a particular experiment — experiment protocol, design, and analysis issues, to name just a few. One of the most common reasons is their choice of reagent, the biological compounds they use to track diseases.
Unfortunately, scientists often spend weeks or even months sifting through research to figure out which reagents to use in specific experiments. Not only is that an inefficient process, it often doesn’t work as we described a few years back.
From A to C, We’re All in On BenchSci
Today, we’re excited to announce that we’re leading a Series C investment alongside TCV in BenchSci, a Toronto-based company that’s working to solve that problem. Since its inception, BenchSci has been focused on bringing novel medicine to patients faster by increasing the success rates of experiments.
Our team is no stranger to BenchSci’s story or its founders. Back in 2012, Dennis Kavelman helped fund the creation of CDL Toronto, an initiative within the Rotman School of Management at the University of Toronto that sought to merge science-based projects with business expertise. There in 2015, an MBA student named Liran Belenzon met scientists Tom Leung, David Chen, and Elvis Wianda. Together, they went on to co-found BenchSci.
In 2018, the same year that Dennis joined Inovia, we led the company’s Series A round and have participated in every subsequent funding round since. Throughout the years, we’ve been able to watch Liran and his team execute on their vision and validate product-market fit by securing contracts with the world’s top pharmaceutical companies.
A (Re-)agent of Change
Today, BenchSci’s AI-assisted Antibody and Reagent Selection platform solves many of the challenges that resulted in costly failed experiments. Its knowledge graph automatically ingests and interprets millions of historical experiments from around the world, which saves scientists time and money and leads to more successful experiments.
We strongly believe that opportunities within the preclinical R&D market remain largely untapped. With this latest round of financing, BenchSci will be able to extend the impact of its industry-leading software by driving a suite of new applications that help scientists optimize their experiment designs to maximize their chances for success.
We’re excited to continue our support for BenchSci. Doubling down on a company that we believe in is part of our commitment to being multi-stage investors and long-term partners focused on building sustainable global tech companies.
And while our history with the company extends back to its very origins, it’s BenchSci’s future that really exc
ites us. We look forward to Liran and his team creating a category-defining leader that will defy Eroom’s law by bringing life-saving drugs to market faster and in a more cost-efficient manner. At a time when everyone’s health is even more top of mind than usual, that’s very good news.
Want to learn more? Get in touch.