As ChatGPT has so aptly demonstrated, AI is now truly entering the mainstream consciousness. That’s why we weren’t very surprised when a slew of investors told us they rarely see a biotech startup that doesn’t incorporate AI in some form or other these days.
“Most of the companies we have seen have an AI component to support the discovery or development processes,” Francisco Dopazo, a general partner at Humboldt Fund told TechCrunch recently.
But despite becoming quite the buzzword, AI’s apparent ubiquity in biotech isn’t actually driving deal flow or higher valuations. So to get a better idea of how AI is affecting biotech in 2022, we asked six investors to tell us what they look for in a biotech startup today.
For Franck Lescure, a partner at Elaia Partners, in biotech, having an AI component isn’t an automatic deal closer. “We do not favor biotech startups with extant AI over those without: Bio-revolution is not only digital. Digital is one tool; the other major tool is the living organism,” he said.
VCs are also increasingly looking for what biotech startups can do with AI beyond just R&D and are wary of companies that use the technology as a marketing tool.
“When evaluating ‘AI for drug discovery companies,’ I view AI as a tool,” Shaq Vayda, principal at Lux Capital, told TechCrunch. “Much like how any modern biotech company is using the latest and greatest tools, AI is becoming more and more common as part of biotech workflows. The bigger question for investors is getting a better understanding of what exactly AI is attempting to model and predict.”
Also, just because a startup uses AI doesn’t mean it can escape being compared to struggling public biotech comparables. “The public markets are the final arbiters of value, and the valuations coming back to earth this year have begun to flow through to startup funding,” said Sarah Guo, founder of Conviction. “I expect we’ll continue to see some digestion through the next year or two, as many midstage companies have built major war chests and don’t yet need to come back to market.”
The survey also covers the implications of U.S sanctions on China for startups in the space, considerations for startups thinking of taking capital from government bodies, how to pitch these investors and more.
We spoke with:
- Robert Mittendorff, M.D, general partner and head of healthcare, B Capital
- James Coates, health and human performance principal, Decisive Point
- Shaq Vayda, principal, Lux Capital
- Franck Lescure, partner, Elaia Partners
- Francisco Dopazo, general partner, Humboldt Fund
- Sarah Guo, founder, Conviction
Robert Mittendorff, M.D, general partner and head of healthcare, B Capital
The NASDAQ Biotechnology Index peaked in 2021. Have declines in the public-market valuations of biotech companies impacted your investments in the sector?
Public market biotechs are dramatically down as interest rates rise and the focus on near-term development outweighs the promise of longer-term results and approvals. As a result, a significant proportion of biotech companies are trading below cash.
Given the substantial and positive flow of data in the space, we view market sentiment as overly negative. These valuations have affected private-market rounds’ size, pricing and structure. Private biotechs are considering the reprioritization of their assets — deciding whether to partner second or third assets with strategics and evaluating structure in tranched financings to reach their fundraising targets.
Of the biotech startups you’ve seen lately, how many had an AI component? Do you favor biotech startups with extant AI capabilities over those without?
AI has become a very important part of next-generation drug discovery in both the small molecule and biologics spaces. Boston Consulting Group (BCG) partner Chris Meier reported in the March 22 Issue of Nature Reviews Drug Discovery that 24 “AI native” drug discovery companies have a combined 160 disclosed discovery programs. We are many more above this.
Recently our own portfolio companies Atomwise and InSilico each inked $1.2 billion deals with Sanofi. Still, the majority of biotechs raising capital are not “AI-enabled.” This isn’t a necessary condition for us, but in many spaces, computational approaches can rapidly improve drug discovery success and speed, at a potentially lower cost.
We also see AI being used in the biologics space, although the technology is used there far earlier. AI-enablement doesn’t increase our interest unless the technology is robust, mature and adds value to the platform in a meaningful way.
IBM sold Watson Health to private equity in 2022 after investing billions into it. What can biotech startups and investors learn from what could be seen as a cautionary tale?
Biotech companies will ultimately be measured largely by their therapeutic pipelines and portfolios rather than by their tech platform.
AI for AI’s sake doesn’t hold water anymore. Results, whether in the form of novel therapeutic programs, diagnostic capabilities or other clinically meaningful outcomes, are necessary.
We know quite a few startups are working on AI-assisted drug or protein discovery. Where else can AI play a role in health tech?
AI is a capability, or more accurately described as a set of computational capabilities that can be applied to a set of problems where conventional techniques have demonstrable limitations. AI technology can play a role in biologics, small molecules and even cell therapy.
We have witnessed its application in every aspect of a biopharmaceutical’s business — from discovery, clinical development and applications in real-world evidence creation to go-to-market motions and post-market patient engagement.
AI is not a monolith; as a set of capabilities, the power of learning systems affords benefits to many previously difficult or intractable problems.
How commercially viable will personalized medicine be in the next five years?
Personalized medicine is already here. See the success in oncology over the last decade, from targeted therapies that are based upon tumor genomics to cell therapies that are N-of-one therapies, where a patient’s own immune cells are engineered to attack the cancer.
Personalized medicine as a viable business has already borne out. The question of how far we can go with personalized therapy is the one being answered in the market today.
Clearly, many therapies do not need hyperpersonalization, but as we learn more about cancer, metabolic disease and neurological disorders, we are enabled with advancements in biologic and computational science to customize or configure therapies for each patient.
Y Combinator welcomed a significant number of health tech startups in its recent batches. Has YC’s presence had any impact on early-stage valuations?
Y Combinator has been a net positive force in driving innovative experimentation at the early stages of company development. Their health tech cohorts are solid, and their apprentice model works well there.
They are still perfecting their approach to projects that focus on biologic science, but I remain optimistic. They have had far less of an effect on valuations for us than the larger momentum firms that recently moved into healthcare over the last few years.
How has due diligence in this space changed in 2022?
We have welcomed the investment environment of 2022 as both companies and venture investors can diligence each other at a more natural pace. Venture capitalists and founders need time in the process of diligence to understand each other, and the fervent environment of 2021 diminished and, in some ways, attempted to commoditize both.
As venture capitalists, we focus on selecting teams and projects that have the highest merit as transformative companies. This exercise takes significant effort and a clear understanding of a number of areas that cannot be accomplished in a day.
Diligence is more efficient now than in 2019, but we have returned to a far healthier pace for both founders and VCs.
Is Big Pharma interacting more with biotech startups this year than in prior years? When approaching yet-private companies in the space, do the majors favor M&A or corporate venture activity?
We are starting to see more deal-related activity pick up, but with a heavy tilt toward business development deals and some corporate venture activity. Biotech has proven its worth as the engine of innovation for the biopharmaceutical industry, and larger strategics have clear programs for engaging with smaller venture-backed entities.
One would imagine given the valuations we are seeing in the venture-backed ecosystem that more M&A would occur given the quality of many of these assets relative to price, but we are at the early stages of that curve.
We heard that U.S. sanctions on China could extend to biotech. What impact could this have on AI-enabled biotech startups elsewhere?
Clearly, CFIUS continues to have important implications on venture financing across all sectors. Biotech is no different, and there may be more sensitivity moving forward, especially as it relates to advanced technologies, particularly in tech and biology.
This may have a modest cooling effect on the pricing of some assets, but I doubt it will affect whether quality companies and teams are funded properly.
Should AI-enabled biotech startups take non-dilutive capital from government entities? Why or why not?
This is a complex question. If the entity is a U.S. government affiliate, the answer is maybe. For other governments, in particular those outside the U.S. or Europe, it is a more challenging question.
Government funding nearly always has conditions of some kind that have to be clearly balanced with the future path of the company. If the funding is from a military source, the implications of dual-use technologies must be considered, and so must be the strategic drift that such funding might encourage.
Are you open to cold pitches? How can founders reach you?
Yes, but warm pitches are usually better. You likely have someone in your network who is also in mine. My email is rmittendorff@bcapgroup.com.
James Coates, health and human performance principal, Decisive Point
The NASDAQ Biotechnology Index peaked in 2021. Have declines in public-market valuations of biotech companies impacted startup investment in the sector?
Definitely. Going public is a preferred exit strategy for many, and those valuations have just been cut by more than 80%, driving down demand for all but the highest-quality startups. As evidenced by the XBI itself, such cycles are part of the sector.
Of the biotech startups you’ve seen lately, how many had an AI component? Do you favor biotech startups with extant AI capabilities over those without?
The ubiquity of AI in pitches that I see is striking. It’s hard for a biotech company to convince me they are doing more than just using AI as a component of their R&D (which they probably ought to be!).
IBM sold Watson Health to private equity in 2022 after investing billions into it. What can biotech startups and investors learn from what could be seen as a cautionary tale?
Commercialization and market expansion are not necessarily immediate downstream consequences of innovation for companies.
We know quite a few startups are working on AI-assisted drug or protein discovery. Where else can AI play a role in health tech?
Anything involving data, be it electronic health records or imaging and image-guided procedures. We’re particularly excited by cognitive neuroscience and human performance in this context.
Y Combinator welcomed a significant number of health tech startups in its recent batches. Has YC’s presence had any impact on early-stage valuations?
We work closely with many innovative ecosystems in health and life sciences. None of the investments we are most excited about are from YC (at this time).
How has due diligence in this space changed in 2022?
As I mentioned in my TechCrunch article: cash runway, non-dilutive capital and market size have reemerged as the key metrics in determining whether or not to invest alongside the science.
Should AI-enabled biotech startups take non-dilutive capital from government entities? Why or why not?
If it aligns with the commercial trajectory of the company, then yes. If the grant or contract doesn’t align with what the company aims to accomplish, they should not take the funding (unless in life support mode!).
Are you open to cold pitches? How can founders reach you?
Always! You can email me or find me on LinkedIn.
Is there anything we didn’t ask about that you want to comment on?
If you’re a neurotech company, synthetic biology startup or have generally cool health or life science deep tech that needs funding, please reach out!
Shaq Vayda, principal, Lux Capital
The NASDAQ Biotechnology Index peaked in 2021. Have declines in public-market valuations of biotech companies impacted startup investment in the sector?
Yes and no. I believe the answer is typically based on where you sit in the broader landscape.
Late-stage investors who are looking to underwrite a liquidity event in the nearer term tend to more heavily weigh the impact of declining public market valuations, and as a result, most of the activity at the mid-to-crossover stages has slowed down in 2022.
However, it’s a very different story at the early stages. Most of these investors tend to have a long enough investing horizon to control for cyclical volatility events and seem to agree that there has never been a more exciting time in the sector to invest.
I believe 2022 is on pace to be the No. 2 (behind 2021) for the number of early-stage biotech deals, and I don’t foresee that slowing down in the future.
Of the biotech startups you’ve seen lately, how many had an AI component? Do you favor biotech startups with extant AI capabilities over those without?
When evaluating “AI for drug discovery companies,” I view AI as a tool. Much like how any modern biotech company is using the latest and greatest tools, AI is becoming more and more common as part of biotech workflows.
The bigger question for investors is getting a better understanding of what exactly AI is attempting to model and predict, and what available data (both public and private) we feel accurately represents a sufficient training dataset.
I believe AI has a tremendous opportunity to improve decision-making and workflow efficiencies with biotech [companies] at large. However, to completely design a commercially approved therapy de novo without human intuition is closer to a pipe dream today.
IBM sold Watson Health to private equity in 2022 after investing billions into it. What can biotech startups and investors learn from what could be seen as a cautionary tale?
Biology is not only complex, it’s incredibly context dependent. While I’m only familiar with the IBM/Watson Health story at a high level, my assumption is that it was another example where people felt that biology is just another unstructured data problem, and that with enough computing power, we can derive meaningful insights.
The best biotech startups embrace technology in their decision-making, but they also tightly couple/integrate their wet lab and dry lab teams. The ability to apply scientific nuance to the tremendous amounts of biologically generated data requires broad teams of domain experts that are able to effectively communicate cross-functional insights. Expertise in technology alone won’t solve these problems.
We know quite a few startups are working on AI-assisted drug or protein discovery. Where else can AI play a role in health tech?
While AI continues to penetrate the industry at large, there has yet to be a commercially approved AI-designed therapy. However, I’m incredibly optimistic. We continue to see the newer cohort of companies tackling more narrowly scoped problems and attempting to work within current workflows.
One example is modeling/predicting ADME properties. Many promising drugs ultimately fail due to poor toxicity data and decisions around compound selection rely on the domain expertise of medicinal chemists — can AI be used to help them with compound prioritization?
Other areas could be helping with patient stratification for clinical trials or even simulating control groups within clinical trials, helping dramatically reduce the time to therapy approval.
How commercially viable will personalized medicine prove in the next five years?
Just following the cost curve of sequencing, we have gone from about $100 million in 2001 for a human genome to $100 cost in 2022. With such an exponential drop in cost, it would be hard to bet against a future in which genetically validated targets lead to “personalized medicines.”
I believe that the biggest impacts in the near term will come in the form of better diagnostics and the ability for people to make better informed lifestyle decisions based on known genetic mutations. There will also be a handful of “low-hanging fruit” that will result in approved therapies for specific cohorts of people.
However, genetics alone won’t solve highly complex diseases, which is why we continue to be excited by cutting-edge technologies in the transcriptome, proteome, metabolome, etc.
Y Combinator welcomed a significant number of health tech startups in its recent batches. Has YC’s presence had any impact on early-stage valuations?
I’m not familiar with the direct impact of YC specifically, but it does serve as an interesting example of more “generalist investors” that are spending time in biotech. I’m of the belief that the best companies are not only interdisciplinary at the team level but also within their shareholders.
Getting investors on your cap table who understand how to build and scale technologies is just as important for this generation of biotechs as those with deep biotech expertise. I believe the general interest has resulted in more competitive deals at the early stages and increased valuations but suspect that will come down slightly in the coming quarters.
How has due diligence in this space changed in 2022?
In order to build a generational biotech today, you need to be exceptional at not only science, but also technology. Investors during due diligence need to be able to comfortably underwrite both.
Good founders are able to tie together a narrative that focuses on how their biological insight led to the discovery of a platform and how they’re planning to industrialize that technology to go after world-changing therapies. Exceptional founders are able to do that as well as understand the macro environment and help investors see how various forms of non-dilutive funding can help the company execute on its milestones and extend runway.
Due diligence in 2022 has focused more on getting comfortable with those in the latter bucket.
Is Big Pharma interacting more with biotech startups this year than in prior years? When approaching yet-private companies in the space, do the majors favor M&A or corporate venture activity?
Big Pharma companies have exceptionally strong balance sheets and have increasingly continued to spend time with startups as they look to diversify their commercial and pipeline strategies. There has been a shift away from working with earlier “pre-clinical” candidates and toward programs that have a closer line of sight to the clinic.
While the broader capital markets were forecasting a highly acquisitive appetite from the top pharma companies due to the depressed valuations, in practice it appears they prefer partnerships and royalty agreements for the later-stage programs and corporate VC as a tool for earlier-stage involvement.
We heard that U.S. sanctions on China could extend to biotech. What impact could this have on AI-enabled biotech startups elsewhere?
There are a handful of contract research organizations (CROs) that operate in China that U.S. biotech companies have historically used for a variety of reasons (price, speed, assay selection, etc.). If these were included as part of the U.S. sanctions, many of these biotechs may have to look for alternatives, which may delay development timelines, program prioritization, etc.
Should AI-enabled biotech startups take non-dilutive capital from government entities? Why or why not?
Every form of non-dilutive funding should be evaluated with the trade-offs required in exchange for taking the funding. Often, the closer the alignment between the grant funding and existing platform development roadmap, the higher likelihood of acceptance — but it should still be weighed against the opportunity cost (i.e., distractions for the team, relevance of data/insights, etc.).
Government entities may expect the platform to continue to develop specific capabilities that may not be aligned with the founder’s roadmap, and therefore could make sense to pass on.
Are you open to cold pitches? How can founders reach you? (Please share an email address if you’d like.)
Sure! Email me.
Franck Lescure, partner, Elaia Partners
The NASDAQ Biotechnology Index peaked in 2021. Have declines in public-market valuations of biotech companies impacted startup investment in the sector?
We need to differentiate the situation for early-stage investors and for later-stage ones. The early-stage investors have been less impacted and/or not yet, because the timing to exit is longer and they know that it’s a cyclical phenomenon.
On the other hand, later-stage investors have shorter cycles between primo investment and exit, so the situation is different. The longer this situation lasts, it might block the value chain of investments by adding difficulties to access the later rounds of financing.
Of the biotech startups you’ve seen lately, how many had an AI component? Do you favor biotech startups with extant AI capabilities over those without?
There is a clear trend toward more AI components in biotech startups. It tends to reach 50% even if it is still at a one-third ratio. Perhaps there is a distortion in our deal flow of incoming projects, because Elaia has a strong reputation in digital before, thanks to its solid reputation in life sciences.
In addition, being able to address specificities of AI projects and biotech projects at the same time is a clear strength and differentiator. It may push projects having both biotech and components to identify us as an investor.
Two kinds of “digital life sciences” projects must be considered:
- Pure biotech projects developing internal AI capacities. In this case, you need to have life sciences investors who benefit from AI expertise.
- Pure digital projects addressing life sciences topics/market (not only healthcare/pharma). You will need AI investors who benefit from life sciences expertise.
Moreover, the business models developed for this emerging sector are mixed between AI business models and biotech business models. You need to be able to navigate the two ecosystems to address these projects adequately and help entrepreneurs choose the proper business model.
We do not favor biotech startups with extant AI over those without: Bio-revolution is not only digital. Digital is one tool; the other major tool is the living organisms.
IBM sold Watson Health to private equity in 2022 after investing billions into it. What can biotech startups and investors learn from what could be seen as a cautionary tale?
Large corporate organizations often struggle to create disruptive technological innovation. This is why they tend to reach out to startups via scouting, open innovation, corporate venture capital and of course, M&A.
As an example, the pharma industry has spent billions of dollars to finally conclude that most of their commercialized products were not coming from their internal R&D but from biotech startups with whom they have partnered. Back in the ‘70s, Genzyme, Amgen or Genentech disrupted the market by developing the first “bio-therapeutics” — therapeutic drugs bio-produced by bugs. These new therapeutics outpaced most drugs commercialized by pharma leaders. This story is well known in the biotech ecosystem.
We know quite a few startups are working on AI-assisted drug or protein discovery. Where else can AI play a role in health tech?
- Diagnostics, including medical imaging and personalized medicine.
- Digital therapeutics.
- Big data analysis, including omics and microbiota analysis.
- Real-world evidence, including epidemiology of pandemics, treatment observance and patient routes.
- Medical device optimization.
How commercially viable will personalized medicine prove to be in the next five years?
It depends on pharma’s willingness and ability to integrate the approach to their day-to-day business.
Y Combinator has welcomed a significant number of health tech startups in its recent batches. Has YC’s presence had any impact on early-stage valuations?
Not in Europe in biotech, but it may impact the digital life science sector because of the digital component.
How has due diligence in this space changed in 2022?
We have seen an exponential increase in concern about climate and environmental issues, whatever the project is — this used to only be a “nice to have.”
We have been doing ESG due diligence for years now and are convinced that it is our responsibility to combine CSR within our investment process as well as our portfolio.
Is Big Pharma interacting more with biotech startups this year than in prior years? And when approaching yet-private companies in the space, do the majors favor M&A or corporate venture activity?
Big Pharma have increased their interest in digital life sciences projects. It did not start in 2022: this is a long-term trend, as AI answers big data issues and may bring additives to real-world evidence.
Big Pharma tend to favor corporate venture when approaching early-stage startups, but when some thresholds are achieved (clinical proof, minimum sales, etc.), then they switch to M&A.
We heard that U.S. sanctions on China could extend to biotech. What impact could this have on AI-enabled biotech startups elsewhere?
The impact will be a strong decrease in the addressable market. AI-enabled biotech can enable more efficiency in Europe and the U.S. and compensate for the lack of experts in China.
Should AI-enabled biotech startups take non-dilutive capital from government entities? Why or why not?
Non-dilutive capital from the government is a way to compensate for a defective market. There is not enough private money to sustain disruptive technology innovation. AI-enabled biotech startups are also concerned by this reality.
One good example is France 2030, with the objective of “decarbonation of French industry.” Means have been defined. Implementation is ongoing.
Are you open to cold pitches? How can founders reach you?
Of course, we love cold pitches and look forward to meeting tech, deep tech and biotech disruptors! Feel free to reach out.
Francisco Dopazo, general partner, Humboldt Fund
The NASDAQ Biotechnology Index peaked in 2021. Have declines in public-market valuations of biotech companies impacted startup investment in the sector?
Yes. Hard data suggests that even though VC biopharma investment kept up a strong pace in Q1 2022 (similar to that of Q1 2021), Q2 2022 was much lower.
This is somewhat consistent with what we have seen out there. Macro issues (interest rates, unemployment, geopolitics, etc.) will continue to influence the dynamics, but technology-related catalysts (e.g., Phase 1 readouts) and strong VC healthcare fundraising over the past 2-4 years should provide some “cushion.”
Of the biotech startups you’ve seen lately, how many had an AI component? Do you favor biotech startups with extant AI capabilities over those without?
Most of the companies we have seen do have an AI component to support their discovery or development processes. These companies are pushing biology to become less artisanal — they want to accelerate the traditional process of observation leading to knowledge, leading to solution/product.
Adding AI/ML capabilities might be the only way to move forward. In terms of favoring one company over another, it all depends on the underlying technology and AI/ML’s role in it.
IBM sold Watson Health to private equity in 2022 after investing billions into it. What can biotech startups and investors learn from what could be seen as a cautionary tale?
I believe the main reason for the disposition was that IBM didn’t have the vertical healthcare expertise and the asset was much more valuable to another player. That makes a lot of sense.
Without really knowing the whole story (the capital IBM invested, its healthcare clients, etc.), I believe the main lesson for us is to always have a clear understanding of whether we are in a great position to create something new — access to the right resources (people, capital) and knowledge of the market.
We know quite a few startups are working on AI-assisted drug or protein discovery. Where else can AI play a role in health tech?
In almost every single step of the drug discovery and development journey. Other examples include clinical trials (selecting the right patients for the right therapies), startup pipeline selection (optimizing the best application for a certain platform technology), animal models (improving correlation between pre-clinical models and clinical outcomes) and manufacturing (scaling production of complex drugs).
How commercially viable will personalized medicine prove to be in the next five years?
Personalized medicine is already commercially viable. I believe it will accelerate in the coming years.
Y Combinator welcomed a significant number of health tech startups in its recent batches. Has YC’s presence had any impact on early-stage valuations?
It’s difficult to discern whether their impact on valuations was significant. However, the number of companies and size of their deals are still a very small proportion of the whole vertical.
How has due diligence in this space changed in 2022?
It really depends on the firm. For us and for the firms we generally partner with, the process has continued to be very similar in terms of scientific and business/commercial rigor. However, timing was a big issue before (needed to move pretty quickly to participate in certain deals), but now there is clearly much more time.
Is Big Pharma interacting more with biotech startups this year than in prior years? When approaching yet-private companies in the space, do the majors favor M&A or corporate venture activity?
Big Pharma has a significant amount of capital to invest in M&A (some estimates indicate about $2 trillion). However, macro factors (maybe together with a couple clinical setbacks) have slowed Big Pharma’s M&A activity (2022 is registering 2018 levels).
I don’t know if Big Pharma is now shifting to more corporate venture activity instead of M&A. Their appetite for business development activity in certain fields such as gene and cell therapies continues to be strong.
We heard that U.S. sanctions on China could extend to biotech. What impact could this have on AI-enabled biotech startups elsewhere?
It will depend on the scope and speed of the sanctions. We already have seen CFIUS impacting some of the deals we have participated in. The impact could range from financing (companies will not be able to tap strong and strategic Chinese capital) and scaling (more difficult access to sophisticated CROs) to business development/commercialization (fewer options for business development deals). It’s clearly a negative short-term/midterm impact to the industry as a whole.
Should AI-enabled biotech startups take non-dilutive capital from government entities? Why or why not?
It really depends on the underlying tech and target disease areas/market. I strongly believe in the merits of objective-specific grants.
Are you open to cold pitches? How can founders reach you? (Please share an email address if you’d like.)
Yes. Email me.
Sarah Guo, founder, Conviction
The NASDAQ Biotechnology Index peaked in 2021. Have declines in public-market valuations of biotech companies impacted startup investment in the sector?
The public markets are the final arbiters of value, and the valuations coming back to earth this year have begun to flow through to startup funding. I expect we’ll continue to see some digestion through the next year or two, as many midstage companies have built major war chests and don’t yet need to come back to market.
Despite that, the biotech economy is clearly in a transformational, exponential phase. The opportunity exists to remake agriculture, medicine and household goods with a combination of new science and computation. With a very long-term view, we’re more excited than ever to invest.
Of the biotech startups you’ve seen lately, how many had an AI component? Do you favor biotech startups with extant AI capabilities over those without?
I am fundamentally a software investor with a longtime passion for both data and bio, and now biotech is experiencing a data explosion. New science, new instruments, increasing robotic automation, and better data collection, infrastructure and algorithms all play a part.
The biotech industry is radically transforming to one of data collection, sense-making and code, and I favor investing in “platform” and software companies that ride this wave. If you look at a company like Moderna, mRNA is a programmable, information-based product: encoded instructions for protein synthesis. Bio sectors will be a key beneficiary of the “software 3.0” revolution.
IBM sold Watson Health to private equity in 2022 after investing billions into it. What can biotech startups and investors learn from what could be seen as a cautionary tale?
Don’t be IBM? Founders already knew that. Less glibly, apart from the management and focus challenges that can plague large companies, this is a classic cautionary tale for tech-in-healthcare.
Innovation is fundamentally slow in healthcare due to attitudes toward risk (many would choose to avoid individual patient harm rather than improve averages) and the lack of aligned economic incentives. However, there are many massive pockets of healthcare where startups can improve outcomes by working with economic incentives instead of against them: direct-to-consumer care, employer-sponsored care, biotech and healthcare IT.
We know quite a few startups are working on AI-assisted drug or protein discovery. Where else can AI play a role in health tech?
While acceleration of discovery is exciting, it’s a pretty naive view that you’ll have one AI model that delivers a drug. So far, most uses of AI address a small slice of the very complicated process to bring a new drug to market, with a lot of emphasis on target identification.
We’ve seen amazing progress over the past few years in AI models for protein folding and docking, which are key scientific problems. But when we look to the commercial side, there are also opportunities for richer use of data and smarter software workflows to increase efficacy and efficiency across the board in healthcare: from diagnostics, telemedicine, clinical trials, patient engagement and clinician decision support to revenue cycle management and claims processing.
How commercially viable will personalized medicine prove to be in the next five years?
This is appearing in many forms, so it depends. As one example, digital communication channels, telemedicine, data collection and richer patient databases can dramatically reduce the cost to address obesity and diabetes in a mass-personalized, longitudinal way.
Y Combinator welcomed a significant number of health tech startups in its recent batches. Has YC’s presence had any impact on early-stage valuations?
No.
How has due diligence in this space changed in 2022?
Theranos was a good reminder to the industry that preeminence in one domain is not a proxy for deep understanding in others. Founder charisma is a powerful drug, but in certain domains like healthcare and fintech, the stakes are higher, and thus confidence in a team’s risk management and ethics is critical.
When making one recent angel investment in a company advancing embryo genetic risk assessment (Orchid Health), I made ten phone calls to people who understood the domain and the amazing founder, Noor Siddiqui. There are no guarantees with startups, but doing the best diligence work you can is a good start.
Is Big Pharma interacting more with biotech startups this year than in prior years? When approaching yet-private companies in the space, do the majors favor M&A or corporate venture activity?
For years, innovation has begun with biotechs, not Big Pharma. Clinical trial budgets tend to come from established players via partnerships first, and then acquisition.
We’ve heard that U.S. sanctions on China could extend to biotech. What impact could this have on AI-enabled biotech startups elsewhere?
The balkanization of science is unfortunate, given it shrinks addressable markets for startups and potentially reduces access to the global state-of-the-art in care, but there are real security risks to consider.
Are you open to cold pitches? How can founders reach you?
Yes! Email me. I’m focused on leading and participating in seed and Series A rounds.