The Leader in Artificial Intelligence For Drug Discovery
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When you’re a young male, you spend your money on cheap booze, hard drugs, and fast women – and the rest you waste. As you enter old age, you increase your spending on drugs, the type needed to treat the chronic problems you developed from abusing your body so much during your youth. The end result is more than $1.2 trillion spent last year on drugs produced by the pharmaceutical industry.
Drugs are big business, but investing in biotech stocks is extremely risky due to the regulatory risks involved, the uncertainty around a drug’s efficacy and safety, and the cost of taking a drug candidate to market which a pharmaceutical company incurs whether the drug gets approved or not. From an investor’s perspective, it’s best to find a “pick and shovel” business model somewhere in the pharma food chain that makes money regardless of whether or not drugs make it past human trials.
Pharma Picks and Shovels
In the same way Synopsys makes money regardless of who is winning the AI chip battle, companies like Schrodinger (SDGR) make money whether drugs get approved or not. That’s because Schrodinger has developed “an approach to integrate physics-based and machine-learning-based scoring methodologies that allows the machine learning model to interactively prioritize additional molecules for physics-based analyses, known as active learning.” The company then sells these services to everyone who is anyone. All of the top 20 pharmaceutical companies, measured by revenue, used Schrodinger’s software
Even though SDGR isn’t running a traditional software-as-a–service (SaaS) business model, there are still elements of what makes SaaS so attractive:
- High retention rates (subscribers continue to renew their subscriptions)
- Flagship customers on board (reference clients who can help you bring on new clients)
- Increasing customer expenditures as time goes on (something Schrodinger refers to as annual contract value)
There’s a lot to like about Schrodinger, and it’s one of the stocks in the Nanalyze Disruptive Tech Stock Portfolio (soon to be released to Nanalyze Premium subscribers). This means we’re now interested in keeping tabs on Schrodinger’s competition. When we recently saw Atomwise refer to itself as “the leader in artificial intelligence for drug discovery,” we decided to take a closer look.
What the Experts Said
In spring of 2019, we visited the Silicon Valley Vatican to meet with Andrew M. Radin of twoXAR who explained the complex world of drug discovery in such a simple manner that even our MBAs could understand it. For example, here’s how he explained the drug discovery process in the simplest of ways:
- Find a new protein in body to hit with molecule
- Find molecule(s) that binds to protein in body
- Once you find a hit, then turn into something that can be introduced to a living being
During our conversations, one of the companies he mentioned as noteworthy was Atomwise, a startup working with Charles River to offer “AI drug discovery as a service.”
Then it happened again. Late last year, we met with Insilico Medicine co-founder and CEO Alex Zhavoronkov. Again, we heard mention of Atomwise. Here’s an excerpt from that article:
In terms of direct competitors, Zhavoronkov noted that he deeply respects the work being done by San Francisco-based Atomwise, but the technology from others is mostly “smoke and mirrors.” That’s why Insilico is focused on publishing its work in peer-reviewed journals in order to back up its claims. The company has published about 60 papers in the last five years.
After hearing these experts speak so highly of Atomwise, we decided to take a closer look at what they’ve been up to.
A Big Round for Atomwise
Just a few weeks ago, Atomwise closed a $123 million Series B bringing their total funding so far to just over $174 million. The recent financing round includes new backing from two top-10 global insurance companies. Other notable investors include names like Monsanto, Tencent, Baidu Ventures, Khosla Ventures, Draper Associates, and OS Fund. The fresh round of funding will be used to “enable Atomwise to further scale the largest artificial intelligence (AI)-driven drug discovery portfolio in history.” In the simplest of terms, Atomwise “develops artificial intelligence systems using powerful deep learning algorithms and supercomputers for drug discovery.
We first came across Atomwise back in 2017 noting that “if you tried to run their algorithms on a typical laptop they would take 10,000 years, but they’re working with IBM cloud and IBM Watson to make it happen at a fraction of the time.” Fast forward a few years and we looked at Atomwise a second time in a 2019 article on How Computational Chemistry Helps Drug Discovery (again, with Mr. Radin’s help). In that piece, we noted that their deep convolutional neural network, AtomNet, screens between 10 and 20 million compounds a day. These AI tools are enabling exponential improvements to the drug discovery process. Says the company:
- Atomwise delivers results 100 times faster than ultra high throughput screening.
- Our machine learning has improved hit rates by up to 10,000x when compared to wet lab experiments
- We can work on the hardest targets including previously undrugged proteins
An article published by AI chip maker NVIDIA a few years back provides a succinct explanation of the Atomwise value proposition:
For every molecule that becomes a drug, millions might be physically tested and determined to be unsuitable, Heifets said. By using AI to analyze simulations, Atomwise reduces the time researchers spend building and testing new medications that ultimately won’t work out.
Credit: NVIDIA
The article goes on to talk about some notable success stories: a drug candidate that may block Ebola’s entry into healthy cells, and several candidates for multiple sclerosis which have been licensed to a pharmaceutical company in the U.K. for further exploration.
The press release accompanying the latest funding round states that “Atomwise has signed more than $5.5 billion in total deal value with corporate partners to date.” The Company has provided their technology to over 750 research collaborations addressing over 600 disease targets. Named partners include some big names such as Eli Lilly, Bayer, Abbvie, Merck, and Charles River Laboratories.
Over the past three years, our platform AtomNet® has tackled — and succeeded — in finding small molecule hits for more undruggable targets than any other AI drug discovery platform.”
Abraham Heifets, CEO and co-founder of Atomwise.
Speaking of the CEO, we love how he chose to represent his world class team on the Atomwise website.
That’s one of the few times we’ve seen the C-suite occupants listed alongside the people down in the trenches – the administrative assistants, the scientists, the engineers. The positioning of the team members randomizes with every browser refresh, further emphasizing that everyone’s contributions are equally important. It’s the sort of inclusive work environment that the D&I charlatans can only dream about.
All those talented people are responsible for the many success stories that have attracted some of the world’s deepest pockets.
Deep Pockets for Atomwise
Leading the last funding round was Sanabil Investments, a name many might not have heard of, but one we came across during last year’s expedition to the Kingdom of Saudi Arabia where we tried to sell our services to the Saudis find interesting Saudi technology firms to write about – which we did.
Sanabil Investments is just one of many names representing the Saudi Arabian sovereign wealth fund, among the largest in the world, with estimated assets of around $382 billion. They have plenty of resources to perform due diligence, so when they refer to Atomwise as “the number one global leader in applying and scaling its AI platform for drug discovery programs,” they probably reached that conclusion themselves. Having such a strong backer lead their last round means Atomwise should have all the capital they need to grow without having to disclose their inner workings to the rest of the world.
Atomwise Vs. Schrodinger
So, what sort of competitive threat does Atomwise pose to Schrodinger? We have no idea. As we learned in business school, it’s always best to leverage the knowledge of other people and then take credit for it. To that end, we dropped Mr. Radin an email and see if he would be kind enough to give us his take on how these two companies compare. If you’re a Nanalyze Premium subscriber, we’ll let you know what he says.
Conclusion
One wonders when a company feels comfortable referring to itself as a leader. Perhaps it’s when they know that others in the industry highly respect what they do and reflect that sentiment. Atomwise is a leader in drug discovery that just took another round so they can scale. Hopefully, they don’t choose to take the SPAC route, and see an exit via acquisition or by going the traditional IPO route as Schrodinger chose to.
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