The Kickstarter(s) of Biopharma
Or 'What's happening at the intersection of #web3 & life science R&D?'
tl;dr-
Risk & variance in successful biopharma innovation (i.e. ‘from lab to life’ with positive financial ROI) has likely declined over time, evidenced by an increase in probability of success in clinical studies & more sophisticated target validation in preclinical development (i.e. in silico, advanced computational techniques, etc.)
Despite improvements in drug discovery, the cost of drug development remains extremely high; recent estimates suggest median cost ranges between $1B - $3B1
A major cost driver is the adoption & scaling of innovative new technologies to support preclinical validation; for example, the in silico drug discovery market is expected to reach over $5.6B (2021 - 2030 CAGR: 10.4%)
Costs are borne by biopharma companies - particularly innovation-based companies that rely on R&D to refill product pipelines - who often partner with technology companies to access these capabilities
One perspective among life science innovators is the centralization of drug discovery capabilities leads to a lack of new product development for key therapeutic indications
As commercial entities, in silico drug development technology companies generate cash flow by selling to biopharma companies
Biopharma companies historically, given the high risk of failure, have focused R&D resources on high commercial value therapeutic indications, which may create both data & product gaps in key diseases
This tension between public health & financial sustainability has led to legislative solutions to ensure innovation in areas of high unmet medical need with limited commercial viability (e.g. the Orphan Drug Act)
Innovators have looked to create a decentralized alternative to traditional drug discovery - essentially crowdfunding - by using web3 tokens as a fundraising mechanism
Decentralized R&D companies look to aggregate resources from a population of stakeholders; the most common methods are aggregating health or clinical data from individuals, and aggregating financial resources from individual investors (or, for web3 companies, token holders)
Decentralized approaches to R&D are not new; previous examples include LunaDNA (aggregation of individual genetic information) and Sony’s folding@home initiative (aggregating computing power from individuals)
Modern companies exploring this space include Vibe Bio, LabDAO, Molecule, and Druglike
Proof of concept on a successful decentralized web3 model will hinge on whether the model can generate a robust portfolio of assets that are able to be developed & commercialized internally or through an external partner
Sustainability of web3 drug discovery companies often depend on the promise of future cash flows; as Vibe Bio puts it, sustainability is generated when Vibe Bio portfolio assets ‘are commercialized or are licensed by other pharmaceutical companies.’
Unlike other in silico companies (e.g. Exscientia) - who generate cash flow via providing services & outlicensing development rights to biopharma - decentralized R&D company future cash flows are likely solely dependent on their asset portfolio (i.e. molecules)
This strategic criticality means that web3 drug development companies face pressures more akin to biopharma companies themselves as opposed to in silico service providers - which means answering operational questions on developing clinical development capabilities, and strategic questions on how to valuate assets for out-licensing (among others)
Finally, questions remain on whether a crowdfunded governance model - where individual token owners theoretically have a ‘say’ in the company’s direction - is the most efficient model to determine answers to the questions above & execute appropriately
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By the way, Martin Shkreli is one of the founders of Druglike. Since it’s a technology company, I suppose it allows him to continue working in the life sciences despite his ban from the pharmaceutical industry. Funny.
But back to business. I don’t think it’s any surprise to anyone that biopharma companies have always been challenged with balancing the risks of drug development with commercial opportunity to ensure sustainability. I also don’t think it’s a surprise that, on a high level, the emergent consequence is that certain disease areas are more well-funded from an R&D perspective, and certain diseases are not. Even in the broad field of oncology - the poster boy disease for innovation-first, high margin biopharmaceutical products - there are clear disparities that are not easily explained simply by available standard of care options or medical need. Regardless of the cause, we cannot deny that this gap between what disease areas are sustainable commercially and what disease areas have the highest unmet medical need does exist (though, to the industry’s credit, many companies are trying to close that gap as best they can without tanking the company or contributing essentially nothing to healthcare as a whole).
I think the attractiveness of decentralized R&D on a high level shares many similarities with why people like using Kickstarter - it’s a fantastic story. It is also no secret that the public narrative surrounding the biopharmaceutical industry has, for good or for ill, always centered around their financial performance and how that performance may not correlate with better health outcomes (often expressed in some colorful language, like so). All of this practically writes the story of decentralized R&D for you, with a familiar cadence of ‘no cure for your disease because big pharma only cares about money’ followed by ‘here is an alternative where a cure for your disease is possible because you’re in control.’ It is, in many ways, the use of the gap I mention above as a call to action that - if you, as a patient or as a human, want a life saving medication to be developed, then you have to do it yourself because big pharma won’t.
While this narrative device is effective, my focus as a strategist is understanding if the current web3 model actually presents a viable alternative - or, as an old mentor once told me, is the baby actually ugly. If web3 companies were positioning themselves solely as innovation engines - i.e. generate cash flow by selling access to a unique capability, like expert advisors or accessing patient data or decentralized trial recruitment, etc. - then on a high level there’s some amount of sense (although one would argue if the use of blockchain actually has a benefit vs. a traditional web2 solution for that use case). Not only is it a much easier sell, but it’s also extremely low risk - and if there’s one thing you need to know about biopharma, it’s that the sustainability of the entire industry is in part built on smart risk mitigation (with a bit of luck). McKinsey wrote some similar stuff using bigger & more efficient sounding words.
The challenge is that web3 R&D companies are mostly positioning themselves essentially as biotechs; the value is in the assets they are discovering (and, presumably, holding the commercial rights to at the end of the day). This is front and center at Vibe Bio, but is also a consideration for Molecule (via its DAO sub-entities like VitaDAO). Basically, if the assets generated from these approaches aren’t interesting enough to warrant outside investment (i.e. big pharma), then all of the token holders are at risk financially for how much they put in. When you frame up the model in this way, it really does appear to be like a Kickstarter for biotechnology - only unlike a Kickstarter project, there’s a huge risk involved in you never getting anything out of it.
(Ironically, Druglike is probably the least exposed in this way because it is focusing on the capability of decentralizing in silico. Basically, it’s like if Bitcoin and Sony’s folding@home initiative had a child - and in my estimation, Druglike is very much a company that can easily pivot to SaaS as cash flow. LabDAO is the same way in a focus on decentralized capabilities vs. asset portfolios. Their strategic challenge is whether doing research this way is actually cheaper than what’s out there either in a supercomputer somewhere or a central location.)
The question I keep asking myself is - are these companies really prepared to deal with failure? Life sciences is a tough, tough game, and often it’s about what plans you’ve put in place to deal with inevitable failure of your asset in clinical trials that separate the veterans from everyone else. When I see companies like these - who underline their promise of democratizing research with the hope that it will lead to real therapeutic options - I can’t help but wonder what systems have they put in place to really improve their odds of success. For example, how do they ensure decision-makers understand the scientific viability of different assets? Or, what about data governance to ensure that studies will generate data that is viewed as reliable by the scientific community? Or, is there even a strategist who can help provide thinking on the commercial opportunity - and therefore, biopharma willingness to buy?
To web3 adherents who may be reading this and saying ‘ugh, this guy is just spreading FUD’ - look, life sciences is my home industry. I’m not shy about my criticisms of some of its mechanisms, but I’m also not shy about my admiration for the millions upon millions of lives it truly has saved. Developing life-saving medications is a real need that many people have and will continue to have in order to lead healthy, happy lives. Accordingly, the only ideal I hold onto strongly regarding this topic is if you’re going to do a web3 decentralized R&D company, then be thoughtful about it. Building a system crowdfunding clinical trials or matching investigators to funding via tokens is great, but stopping here is naive at best and irresponsible at worst.
The goal is getting something to market, from lab to life. If your solution doesn’t help - or worse, ends up creating friction along that critical path, then go back and build it again until it helps.
Because patients - including the ones who may have believed deeply enough in your story to buy your tokens - deserve nothing less.
-WY
Disclaimer: Analysis of costs is highly dependent on the methodology, the costs selected, and the companies / assets selected. Other factors include the cost of capital and the inclusion of R&D failures in the equation. While this $1-3B may be a useful back-of-the-envelope benchmark to keep in mind, just keep in mind it is a ‘loose’ benchmark; use it for forecasting at your own risk!