Life sciences company Schrödinger (NASDAQ:SDGR) has developed software that could help drug companies develop medicine using artificial intelligence and physics, and it's already being used by a number of big-name pharma companies.
In this video from "Beat & Raise" on Motley Fool Live, recorded on Sept. 23, tech, healthcare, and cannabis editor and analyst Olivia Zitkus and Fool.com contributor Brian Withers take a look at Schrödinger's technology, recent earnings results, and what makes it a stock to watch.
Olivia Zitkus: Sure. I will take this home with Schrödinger before we hop over to some questions from Slido. This is a very complicated stock to end on, so I'm going to do my best to explain what in the world it does. Schrödinger is a pharma software company and more. It basically runs computer simulations that work on AI-driven molecular design. Its platform is all AI and physics-based. It runs various chemical simulations to help companies find basically medicinal combinations that have higher probabilities of success. It's also developing its own medications off of this platform.
Their main idea is basically, if you can compute all relevant molecular properties with high accuracy, with the computer designing drugs and materials so not even just inside the pharma space but materials, too, would have a higher success rate, be faster and they'd be cheaper. It's named Schrödinger after the Schrödinger's cat theory from physics which took me back to high school, and yeah it applies to this stock because they're trying to observe how many possible outcomes that nature could fall to, that could help produce a positive outcome. Go Google Schrödinger's cat, we don't have time for that. That's a whole other rabbit hole.
But it's a very interesting company. Its priorities now, it only IPO'd I think in February 2020, its priorities right now are investments to advance its own drug discovery pipeline using this AI- and physics-driven model and to drive the adoption of its software among other pharma businesses. I should mention, it was actually founded in 1990, only went public in 2020. As investors in situations like this, I want to look at several metrics and qualitative areas in both software. That's the first phase and the drug development spaces. R&D spending, cash on-hand, strength of the pipeline itself, what actual drugs are they working on, collaboration agreements, annual contract value, so you've got this awesome mix of both the software issues that we're used to looking at for SaaS companies and then also these healthcare and drug pipeline issues that I'm used to looking at for biotech.
Just quickly, revenue in their second quarter, that was released on Aug. 12, was up 23% year over year. It came in at $32 million, and software revenue comprised $26.3 million of that, and that segment grew 11% year over year. The business has a good bit of cash on hand. It has about $650 million in cash but that was as of March 31. A couple of its partners that have signed on to develop drugs with its platform, they're pretty big. Bristol Myers Squibb, Zai Lab, Takeda Pharmaceuticals is one as well. Their software annual contract value was up 22% from 2019 to 2020 to about $91 million, their annual contract value and customer retention for high-spending groups over $1 million in annual contract value. The compound annual growth rate for that group is 27%. The high spenders are spending a lot more so far year over year which is great news. Then for the customers who are paying just above $100,000 a year, their compound annual growth rate, I think it's more around 13.
So far, this year, the stock is down about 25% year to date. They are expecting, I think, total revenues of about $130 million at the midpoint, which would represent about 25$increase year over year. It's still a mid-cap company, so there are going to be bigger swings on good and bad news like a lot of the companies we've talked about [laughs] over this past hour. But I think for Schrödinger, it's the tech that's changing the game and the drug development is there as proof of that technological concept, and as proof of that AI- and physics-driven concept. They sound like they're excited about recurring revenue they're high top-line visibility from their software sales, that's what's going to drive growth through them. They've acknowledged that the drug discovery revenue is a little bit less predictable than the software revenue based on the timing of collaborative agreements and milestones as it relate to the development process. Their operations, their expenses aren't done growing either. But if the concept works, which it looks like it does, we can discover new compounds in a fraction of the time it normally takes us and then a fraction of the cost. We can only imagine tapping into the drug discovery space for a lot less money and what a difference that would make. That's Schrödinger, that might be the most complicated stock of the day. [laughs]
Brian Withers: Yeah, that's a super interesting company. I love the use of software to help with shortening the drug discovery timeline. I'm surprised at some of the big pharma companies didn't invent a homegrown solution on their own here. Are these guys an independent, neutral party for the industry and a first-mover?
Zitkus: Yeah, that's a really good question. They are neutral party. They partnered with a lot of different big named pharma companies that you would think if there were a pharma company to move on something like this, they would've done it. Gilead, Takeda. I think Sanofi, I believe Taylor might know as well. Sanofi, I never say that one correctly. Those are big companies that didn't bring the effort under their own roof and decided to partner with Schrödinger to get it done instead. In 2016, Gilead bought a specialized system just for one treatment, development of drugs for one indication rather for $1.2 billion and that was in 2016. You've either got these companies coming in and buying a very specific software that's tailored to that company's drug developing specialty or you've got partnerships like they have now with Bristol Myers Squibb when they're working in tandem to develop the software, iterate together, and do that thing instead they're paying for the computing services in the development process. I think it's a neutral party and definitely has its early mover advantage. I'm not totally sure if it's the first to attempt this type of work but like I said, they've been around since 1990 and they rolled out their first predictor system in 2001. That's a long time, definitely early mover advantage if not first.