Biotech SaaS : Vertical SaaS you are looking for
A few days ago, I had a conversation in a community of people building software for science, Bits in Bio, I got this mail from a founder of a biotech SaaS startup:
The problem makes sense. The technology is already complex but with more scientific jargon, we make it even more complex. It is not just a problem of scientific jargon but a reflection of both pace we are going through and the space we are dealing with, biology. Not blaming anyone, it is science.
Let’s start from the very beginning. Software was on-premise before, meaning- we had to (we still have to in some cases) install it locally in servers or our own personal computers. However, the delivery of software has changed significantly over the past decade . Spending lengthy periods of time installing and updating several and disparate software solutions is no longer required. With access to the internet and a browser, for example, researchers, corporates and individuals alike can tap into a vast array of software solutions. This has been made possible with the advent of cloud services, and especially SaaS i.e. Software as a Service.
SaaS has increasingly become the de-facto way of accessing and consuming software, and it has been widely adopted in several sectors. However, the entry of SaaS solutions in biotech still faces several challenges. Like conventional biotech, SaaS in biotech is also subject to a number of regulatory & compliance hurdles and might require publications in some cases. Much of the innovation within biotech originates from academia🎓 and requires years of research similar to that of deep-tech, particularly in AI based Drug Discovery💊. Likewise, as a field, biotech is characterized by complexities and peculiar processes that are not easily accessible or understandable to an outsider. Most biotech SaaS startups have often been initiated by founders with an excellent academic background in biotech and prior experience in the field further complemented by a background in software or founder with software engineering background collaborating with founders with biotech background. It is not a coincidence. It’s like an unwritten eligibility or process for founders in this space. Maybe a way to show founder-product-market fit.😎
However, the pure academic background of founders can make a date between VC and founders challenging while raising pre seed and seed round.
Danielle Cosio, cofounder of Ontologic says, “It was completely different experience and struggle while dealing with VCs than what we are taught in academia as a life scientist. We have to be broad , look for ways to make it bigger, have to show that the proof of concept has potential to make billion dollar company, if you cannot embrace that language and outlook, you lose the game. ”
👉What is the place of 👩💻SaaS in 👩🔬biotech is the next question?
I remember this “In the gold rush, sell shovels” when I get asked this question. “Shovel” is the place of SaaS if “Gold” is the place of biotech.
SaaS developments in other sectors have been plenty and well documented. In biotech, this might not have been same, but SaaS solutions have the potential to modernize how novel biotech products are: a)discovered, b)developed and c.) distributed
To make it more clear, biology has continuous cycles of experimentation and analysis. Recent science has become more advanced with more data generation power during experimentation. Use of robots, multi-omics technologies , high throughput experiments supported by platform tools like CRISPR, droplet microfluidics, flow cytometry, single cell sequencing and so on, have contributed significantly to a massive amount of biological data. Not to forget, the data is useful only when we can store, manage, visualize and analyze it properly. Here comes the role of SaaS. This is just a brief story of a) discovery process.
But the process does not stop there, next challenge is in b) development stage of biotech product which consists of different trials/ tests before reaching to the market. Clinical trials for drug discovery, also called Valley-of-Death , is the main stage when more than 90% drugs fail. Biotech does not suffer only in healthtech space, it is same case for other sub sectors. Imagine the back story behind the journey from discovery to development to approval to sell Lab-grown meat 🍖 in United States. It is impossible to happen in short period of time with conventional science. We need better scientific tools and platform to scale up the production or test the products or decrease the cost and time-to-market of biotech products. Furthermore, it does not necessarily require biological research/trials, sometimes, it just requires the management of inventory and supply chains in this stage. One interesting example is the role of Scispot as a software to manage the projects, inventory, samples and partners in cellular agriculture space.
Wait! Wait! I was recommended super useful map of early stage R&D : Life Sciences Software Landscape which includes different categories of early stage R&D startups:
See, how much diverse the scope of biotech SaaS is.
Once the biotech product (eg medicine💊) is developed, the next challenge is c) distributing the product to customers. While the distribution phase may not involve intricate technical experimentation, it remains a crucial component of the biotech industry and holds promise as a potential segment for biotech Software as a Service (SaaS) solutions. Rather than dealing with broad segments/customers such as calendar📆, spreadsheets for in case of horizontal SaaS , being purpose specific software might make more sense due to its lower threat of commoditization unlike horizontal SaaS, and higher defensibility . For instance, industry specific cloud solution, Veeva, had 1.85 billion USD of total revenues for fiscal 2022 (different revenue streams included). Unfortunately, it would not be wrong if we say, there is still a lack of industry specific/purpose specific/ vertical SaaS in biotech that is still much needed.
If someone asks me if vertical SaaS is important. I respond like this “Isn’t it good to be great for someone rather than being good for everyone but great for none?”
Then is a market of vertical SaaS smaller than horizontal SaaS? If you think horizontal SaaS has market💹 with customers having computer, then vertical might seem small as it is more industry specific. One thing not to forget: Not every vertical SaaS business is billion dollar business. However, size of total addressable market could be increased even within the vertical by diversifying the revenue streams like Veeva. And for horizontal SaaS: “All that glitters is not gold”
👉SaaS, AI and Biology
Advantages of SaaS adoption in biotech are quite similar to that of SaaS adoption in other sectors. There’s no need to download software, and there’s no need to install disparate modules required for conducting research, visualizing data etc. Researchers and biotechnicians can focus on their work without needing to worry about computing power, storage and maintenance of the underlying computation. Furthermore, the ability to access data from anywhere provides teams with greater flexibility and sharing abilities to name a few benefits. Just last week, I interviewed Amit Sinha, founder of basepair. He told me that their company releases new updates every week to upgrade their software with feedback from customers. SaaS is super friendly in this case, enabling the continuous and rapid integration of updates whilst allowing providers to adapt to the changing needs of users. From the user’s perspective, requirements are more easily and readily available without needing complex or lengthy rollouts by IT teams . Within academia🎓 and the wider industry, users are still facing problems when it comes to analyzing large data sets . SaaS providers like Basepair are helping biologists work more easily, allowing them to take on some of the work that would typically be done by bioinformaticians whilst making bioinformatics🧮 simpler and quicker.
Furthermore, the role that AI can play in biotech cannot be forgotten.. Previous software solutions were based on algorithms designed by engineers. It contributed a lot but we cannot ignore the gaps and challenges that remain in understanding biological complexity. We have been doing what we could do to decode this with all the mathematics that we could possibly leverage. However, several problems remain to be solved. Hence, in such situations, new solutions integrating neural networks/AI emerge as Software 2.0 which may better position us in decoding these challenges. For instance, an AI program called Alphafold has proved capable of solving a 50 year old science challenge of determining the shape of the protein. Not to forget that it does not mean we should underestimate software 1.0 i.e. software without AI integration.
👉Current trend:
Are AI/ML/LLM just buzz words?
LLM (Large Language Model) , algorithm used in ChatGPT, is the new trend in biotech. Interesting news came from Baker lab few months ago when they generated customizatble protein backbones by using the same AI technique that powers text to image models like Midjourney. Similarly, AI has been leveraged to predict the best drug candidates during R&D phases in several techbio companies. The point is simple, there are amazing things happening at the intersection of SaaS solutions and biotech. AI/ML,LLM might not necessarily be buzz words.
👉Edge🔪 of new SaaS startups over biotech giants and big pharmas:
Data is the new edge. Most of the big biotechs and pharmas prefer to have their own inhouse software and engineering teams due to confidentiality and intellectual property concerns. However, the race will be his who can utilizes the data. In the age of open science and rapid digitalization, software developed by small startups might get the benefit of testing and validating their software with different customer . Some even provide a freemium model which eases the adoption of SaaS solutions by users whilst giving them an opportunity to upgrade for more process-specific solutions. This allows for a more iterative approach in which users get what they need whilst limiting over or under utilization both by the provider and the end users.
👉Some time⏲ on the biotech SaaS market
More broadly, the biotech SaaS market could be categorized into segments as presented in the diagram below:
SaaS industry is experiencing continuous growth. It is projected that the global SaaS market will expand from $273.55 billion in 2023 to approximately $908.21 billion by 2030, with an expected annual growth rate of 18.7% during this period. But question is again- Is biotech SaaS market big enough? So here are some breakdowns.
The global clinical trial data management software market is expected to reach a value of around $7 billion by 2030. Likewise, the global healthcare SaaS market is $21.56 billion in 2023 and predicted to attain a size of $51.7 billion by 2028.
The data are quite scattered to estimate the total size of biotech SaaS market. In 2015, the research-based pharmaceutical industry spent roughly $149.8 billion on pharmaceutical R&D globally. Likewise, expenditure in IT/software is also increasing, which was expected to be 54 billion in 2019. Hence, roughly, Total Addressable Market (TAM) for biotech SaaS, particularly SaaS used in pharma R&D, could potentially surpass $38 billion USD.
👉Example of success and the journey
Amongst a few unicorns in the biotech SaaS space, benchling, which was also not the first company to make Electronic Lab Notebook(ELN solutions), was able to stand as an industry specific SaaS provider with a valuation of over $6.1 billion, illustrating the potential for success in this field, This is also evidence that having a real competitor is better than having no competitor at all.
Here’s the illustration of its fund raising journey via river.
While glorifying the benchling, the success of another company, Veeva, in this space cannot be overlooked as well. Veeva was established in 2007. Veeva Systems’ annual revenue for 2023 was $2.155B, a 16.44% increase from 2022. Veeva System’s revenue growth from 2012 to 2021 is 1,328.64%.
Along with these two companies, Komado can also be cosidered as the pioneers of biotech SaaS. Benchling and Komado are the only two startups in the list of Forbes Cloud 100 representing biotech. These three startups are the perfect examples of vertical SaaS success. Here is a comparison of these companies in terms of annual revenue and their valuation:
👉VC and SaaS
There’s no doubt about the strong performance of software and SaaS providers as it relates to VC investors. This is in spite of the recent downturn , in deal value (a decrease from 40.2% deal value in 2022 to 29.3% in 2023). However, the recent boom in deal activity leveraging AI integrated software segments has set it to be one of the strongest performers in Venture Capital . In contrast, biotech and pharma are seen as more resilient in terms of deal value according to the same recent European Venture Report. Resilience of biotech and pharma can make sense for SaaS in the space. For instance, €120.3 million series A fund raised by Ascend Gene and Cell Therapies was used to acquire technology from another startup. So resilience in these sectors also makes sense for SaaS in biotech as platform SaaS can add incredible value to the modern biotech landscape with a high probability for exits through M&A. Danielle in the interview agrees that there is high chance of acquisition of smaller SaaS by bigger SaaS. Likewise, even though IPO might not be favorite exit strategy for VCs, trend of IPO in such startups is also growing.
Goldman Sachs Research says that the pharmaceutical industry has approximately $700 billion for acquisition and R&D investment.😲 Likewise, Veeva in 2013, raised $261 million IPO on its opening day.
Can we say, SaaS in biotech is a safe bet ?
Again if somebody asks me why to invest in biotech SaaS. I would say because it is SaaS. Because it is biotech. And it has high defensibility, clear exit strategy, experienced founders and unsaturated market. Did I generalize more? 🤐
Not to forget, the biggest impact, you as an investor is going to save millions of lives by saving one right company.
Also there is money. 💸
In the biotech world of high risk, high reward, SaaS might bring low risk, high reward. (By low I mean the lower risk than bench science)
Thank you for reading this article. I would like to extend my thanks to Sam and Ronald for their invaluable feedback. A special appreciation to Dr. Danielle Cosio from Ontologic and Dr. Amit Sinha from Basepair for their insightful interviews, which greatly contributed to the understanding of the biotech SaaS industry. I am also thankful to the Bits in Bio community for providing valuable materials, Included VC for support and guidance, and the superheroes, Nikita and Anu, who provided me with a platform to explore the world of VC in depth . Last but certainly not least, I’d like to express my thanks to the anonymous founder who inspired me to undertake this in-depth exploration.
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