Digital Life Sciences ≠ Digital + Life Sciences and at Elaia, we love it!

Elaia
Elaia
Jun 23 · 16 min read

By Louisa Mesnard, Samantha Jerusalmy, Franck Lescure, Alexis Frentz & Sacha Loiseau

What are the next hot topics as an investor? This multi-billion dollar question is on everybody’s lips. Our crystal ball at Elaia is no more accurate than others. But our analysis has highlighted 5 sectors which we believe will keep growing — even thrive, during and after the crisis. Cloud Infrastructure, Digital Transformation, RetailTech, FinTech and Digital Life Science are compelling investment opportunities due to their transformative potential for businesses and consumers.

We’ll regularly share with you our learnings and insights on each of these game-changing sectors, so stay tuned to Elaia’s Medium account and subscribe to our newsletter!

After having focused on Cloud Infrastructure, Digital Transformation and RetailTech, let’s now tackle why we invest in Digital Life Sciences. We’ll do this in 3 chapters:

Chapter 1: Digital Life Sciences > Digital + Life Sciences

Chapter 2: Key trends

  • Real-world evidence
  • Imaging
  • Big Data
  • Digital diagnostic & therapeutics

Chapter 3: Funding and M&A

Digital Life Sciences > Digital + Life Sciences

After a long courtship, the worlds of Digital and Life Sciences are joining forces to produce an exciting breed of startups. While this trend is becoming clearer each day, the best way to build the right investment team to scout and assess Digital Life Sciences startups is less obvious.

That’s because Digital Life Sciences is more than just a mash-up of Digital and Life Sciences. In this case, the whole is greater than the sum of its parts. This segment has new advantages as well as new constraints.

“Elaia has recognized the gigantic opportunity in this area,” said Elaia Venture Partner Sacha Loiseau. But we also know that many investors in France really have no idea how to tackle these fields.”

Let’s start by defining what Digital Life Sciences is: Focusing on the ways digital advancements are transforming life in all its forms, past and present. This can include plants, animals, viruses and bacteria, single-celled organisms, and even cells, disrupting a wide range of biological-based markets, from medical to veterinary, agriculture, foods and even cosmetics. The growing intersection is why Elaia created a Digital Life Sciences team in 2018 led by partners with expertise in life sciences as well as partners that come from the digital world. “When you’re doing early stage investment, you need to understand the technology and the science behind these technologies. “It’s a natural fit for Elaia, given our long history in deep tech and science-related startups,” said Franck Lescure, Partner at Elaia and former scientist at Genset, one of France’s first biotech startups.“So we are building both sets of expertise into the same team and we work in tandem.”

Elaia knew that communication would be key to building successful Digital Life Sciences startups. Part of Elaia’s value in this realm is our ability to guide those from the Digital and the Life Sciences and help them learn how to speak each other’s language. Smooth communication is key to moving quickly.

There is plenty for both sides to understand.

The View From The Digital World:

Compared to a Digital startup, the stakes involving the ultimate Life Sciences’ end user are higher, especially if it’s a human being. In such cases, depending on the success of your product, you can save a life.

For a product that can have that kind of human impact, it can’t be slapped together like a SaaS service and launched with a MVP in 3 months to early adopters. It typically starts with scientific research being done at the cutting edge of a field. That research has to be peer reviewed and published before it even starts to take the shape of a product. It’s only when this research phase is finally complete and it’s ready to leave the lab, through the creation of a startup spun-out, that Elaia may invest to participate in the development of such a product.

For reasons of obvious caution, especially in the Healthcare environment, Digital Life Sciences startups are likely dealing in a heavily regulated space. Clearing regulatory steps means the company has been able to prove a product is viable, innovative, and better than the existing “gold standard” solutions. This also requires a medical-economic study requested by healthcare funders to certify its economic viability. That’s no surprise for someone coming from the Life Sciences side, but with the exception of those working in FinTech, such scrutiny may be unusual for a Digital team member.

The View From The Life Sciences side:

Thanks to rich new data and analysis tools, digital technologies are reshaping the whole Life Sciences economy, from Healthcare to Agriculture or “White Biotechnologies.” Digital has become attractive and necessary to a Life Sciences person because it allows them to answer questions that had previously been unanswerable. Digital trends in Life Sciences leverage technologies such as Big Data, AI, Cloud-based services, cybersecurity, IoT, VR/AR, RPA, Blockchain, etc. that now apply to this space. Digitalization improvements concern almost any kind of domain in Life Sciences, including heart surgery, medical imaging, drug development, real-time analysis of crops, prediction of pandemics, choice of adequate stents to treat patient stroke, hospital procedures, genomics or microbiota characterization.

In addition, developing software has a major advantage: it goes much faster and costs far less. There is no chemistry or biology slowing things down. As seen from the Life Sciences side, it is also why digital startups are usually dealing with go-to-market, commercialization, and customer management issues at a very early stage in their development. The dynamics of their commercial growth sustain their valuation.

In contrast, Life Sciences projects tend not to have revenue during the first few years of their development. Therefore, Life Sciences investors usually don’t consider commercial and revenue performance, as a key performance indicator as they would with Digital startups. Instead, they weigh the potential commercial performance which may be huge considering the enormous markets concerned, and use it to estimate the proper valuation of the company.

Digital Life Sciences projects lie in between these two extremes, depending on the nature of the project.

Moreover, Digital also does not typically worry as much about patents for their industrial property strategy, which is the lifeblood of Life Sciences. Protecting a company through patents or keeping its secret sauce hidden is a natural reflex for Life Science companies. How should a Digital Life Sciences startup reconcile these two cultures? It takes careful reflection for both sides to strike the right balance.

Why opposites attract…

At first glance, these differences would seem to lead to a culture clash. In reality, the strong points and drawbacks on each side are proving to be complementary in building Digital Life Science winners. By forging Elaia’s team along these fault lines, we know how to bring harmony and stability to these startups and help their employees mesh to pursue breakthrough technologies.

We are witnessing a turning point in Life Sciences thanks to digitalization. This revolution is a crucial period for the sector. In 2019, we saw major advances that gave rise to, among other things, the first drug developed using Artificial Intelligence to treat inflammatory diseases and exoskeletons, and the reconstruction of human organs by 3D cell printing.

The fields of application are numerous and cover the entire patient journey (would it be a human, an animal or a plant) through the healthcare system. Digitization in healthcare is revolutionizing the way we prevent, treat and manage health conditions. As shown below, here are the 8 segments we define as Digital Life Sciences:

1/ Disease prevention and epidemiology: startups intending either to prevent the onset of a health problem or that intend to avoid potential relapses in people who have already been ill.

2/ Patient diagnosis : AI based software for diagnosis of pathologies.

3/ Pharmaceutical research and help in the discovery of new treatments:

  • Digital lab tools: Digital molecule discovery & design.
  • Digital clinical insight: Equipment supporting clinical developments.

4/ Treatment of the patient, whether assisting in surgery, prescription therapy, etc:

  • Assisting on surgery: Software “as” (for assisting) medical devices.
  • Prescription therapy: Digital therapeutics i.e evidence-based therapeutic interventions to patients that are driven by high quality software to prevent, manage, or treat a medical disorder or disease.

5/ Monitoring the effectiveness of the treatment and the patient journey.

6/ Digital healthcare management: Companies helping to optimize automation and workflows of the healthcare systems and organizations.

Again, some of these patient journey segments may fit on animals and plants as well. In fact, in a context of collective awareness of the climate emergency, energy transition and healthy agricultural production, many opportunities are emerging.

In the whole family of Digital Life Sciences, we add:

7/ Digital BioCleantech

8/ Digital Agtech

Based on these definitions, here are a few examples of high potential young startup companies:

Trends We See…

The intersection between Digital and Life Sciences is revolutionary. Digital brings an unprecedented ability to gather information about patients. Whether it’s improving current processes or unleashing new capabilities, Digital Life Sciences are powerful because they offer a new way of understanding the world. There is a potential to gain insights that were not obvious and that do everything from improving diagnostics to making better predictions.

It turns out that medicine, agriculture, and other bio-science related fields are not so very different from other industries undergoing digital transformation. When Digital tools are applied to these sectors, we see rapid improvements.

What makes the whole convergence interesting is that the living is now becoming an object for engineers,” said Elaia Venture Partner David Sourdive. “It is becoming an engineer’s playground. So it’s about managing data. It’s about measuring. It’s about understanding. That means we need to make sense out of what we measure.

While there are many emerging possibilities, we have decided to focus on 4 major Digital Life Sciences trends: Real-world evidence, imaging, big data, and digital therapeutics.

  • Real-world Evidence: As the world digitizes, scientists have a wealth of new tools that allow them to capture information about real-world conditions. As an example, no longer do doctors have to wait for a patient to come by for a check-up to measure their blood pressure, sugar levels, or heart rate.

Patients can be continuously monitored remotely, painting clearer pictures of their health trends rather than just random snapshots. Labs can track the continuous real-time development of molecules. Doctors can also follow treatments to see if they’re effective or not. Sometimes this is as simple as ensuring a patient is taking their medicine as prescribed. i-Virtual has applied computer vision technology to a SaaS platform that detects vital signs. The startup uses signal analysis, artificial intelligence and remote-photoplethysmography to enable remote diagnostics on telemedicine services.

In other areas, such as bird migrations, researchers are drawing links with the spread of the pandemic thanks to real-time tracking that can predict the spread of avian flu. One startup, iMean, is using omics datasets and algorithms to reconstruct Digital twin organisms to improve models for agriculture and industrial biotechnology.

  • Imaging: This sector has been digital for a couple of decades now. The move away from film to digital for procedures like X-rays and Ultrasonography, MRI or CT scanners, has generated an enormous stockpile of information. Hospitals and the entire healthcare system have structured themselves to be able to digitally analyze this stock of information.

Now practitioners have the tools to decode those images in a few seconds using software compared to several dozens of minutes it might have taken a radiologist to spot a cancerous node in someone’s lung. That not only improves outcomes, but it leads to huge productivity gains.

For example, Gleamer uses AI to analyze X-rays, spot broken and dislocated bones, and improve diagnostics for radiologists. inHeart uses digital images to generate 3D maps of the heart and assists cardiologists in catheter ablation procedures. And Dilepix has developed a system that leverages AI and computer vision for monitoring animals on farms or spotting things like crop disease.

Sim&Cure maps the arteries of a patient to create simulations that help neuroradiologists predict how the patient might react after a device is installed securing the treatment of brain aneurysm.

Sim&Cure CEO and co-founder Mathieu Sanchez came from a medical background and he’s pulled other researchers into the company. But to realize his vision for the product, he had to systematically find team members who had the digital skills to round out his training.

“I have the competencies to compute the deployment of the device,” he said. “But I don’t know how to reconstruct the arteries from medical imaging. So at the beginning, the issue was to create this pool of competencies and skills regarding medical images and biomechanics and medical applications. You need to combine everything to create the right tools that are useful for the patient.”

  • Big Data: As it has been for imaging, the sector needs to be structured so that the data is standardized, interoperable, and securely stored. Imaging is an example of the larger impact that big data analysis is having across multiple fields. Even though the first steps of digitization had occurred, it was the arrival of advanced tools like AI that unlocked the true potential.

With all that data being gathered via medical devices and sensors, help is needed to digest and analyze it. That has given rise to tools such as sophisticated conversational agents which are becoming more intelligent as their datasets grow.

But it’s not just machines that are getting smarter. The depth of medical and scientific knowledge is huge but, in the past, such information was not readily accessible. Now doctors and researchers search these data sources more effectively and understand them quickly thanks to tools that either visualize or synthesize it.

In the best cases, these same tools uncover tiny anomalies in the vast genetic code of someone, a critical discovery because one slight difference in DNA could lead to a major illness.

That’s the mission of SeqOne, a genetics startup founded in 2017. The company proposes a universal OS to be used as a platform on which medical practitioners will build add-ons allowing specific genetic analysis related to the disorder they wish to apprehend, including rare genetic diseases, cancer predisposition or treatment responsiveness. SeqOne is a shining example of how a team of geneticists and data scientists can learn to work together to produce innovative products.

A specialist in machine learning is not a specialist in genetics,” said SeqOne co-founder Nicolas Philippe, whose background is genetics. “But eventually we have created a team that speaks the same language. For me, this is the future. If we are going to treat millions of patients, we need the systems experts and algorithms. This digitalization is going to revolutionize medicine.”

Managing new forms of data storage is creating new services. Biomemory Labs store digital data for large companies on DNA drivers, by using the unmatched properties of the DNA molecules, including high stability, independence from energy and power of encoding.

Meanwhile, Aviwell is pioneering new ways of ethical and sustainable farming by leveraging on the link between gut microbiota and growth development. The AI developed by the company allows efficient evaluation of the potential phenotypic improvement of farming animals. As a proof of concept, Aviwell has developed this approach on geese to prevent force-feeding in the production process of natural “foie gras”.

  • Digital Diagnostics & Therapeutics: Digital therapeutics represent a new treatment modality in which digital systems such as smartphone apps are used as regulatory-approved, prescribed therapeutic interventions to treat medical conditions, the famous “Game as a Pill”. Software can be used to treat people or detect/prevent/monitor disease. This is less invasive for the patient and there is obviously value in curing a disease with digital tools rather than a costly procedure and/or a medical device.

We’re seeing tremendous advances here. Digital Life Sciences are opening up avenues such as working with Alzheimer’s patients to stabilize memory. Sounds and images are being used to detect and treat Autism. For example, Mila has developed Adaptive Music Therapy that uses computer vision and audio analysis for measuring cognitive performance that can be used to create a personalized treatment plan.

Tilak Healthcare, an e-health start-up, has created clinically validated mobile medical games to help monitor and rehabilitate patients with ophthalmic chronic diseases. By engaging the player in a series of games that test their eyesight, the app collects data that can be sent to their physician to help with ongoing treatment and monitoring.

In agriculture, MycoPhyto produces fungi that help plants grow naturally without or with drastic decrease of the need for fertilizers and pesticides. This is made possible through a deep analysis of fungi populations in a specific soil and proposal for improvement of plants through implementation of adequate mycorrhizal symbiosis, thanks to a deep analysis of data generated from soil and plants analysis.

Elaia’s excitement and belief in the opportunity around Digital Life Sciences is reflected by the dynamic growth of this sector.

Funding and M&A

In the Digital Health segment alone, Global Market Insights projects that CAGR will rise 28.5% through 2026. That optimism is a large part of the reason that Digital Life Sciences startups attracted $10.2Bn in 2020, according to Crunchbase.

We can also see the growing confidence in Digital Life Sciences by tracking the fundraising trends. The average deal size tripled in 6 years, going from $10.3M in 2013 to $31.9M in 2019. That’s being driven by a larger percentage of later-stage funding.

In part, that can be explained by more repeat investors in this sector. These firms made their first bet, liked what they saw, and have come back for more. Again, using Digital Health as a proxy for Digital Life Sciences, there were 126 first-time investors in 2011, according to Rock Health. By 2020, there were 301 first-time investors and 445 repeat investors.

This is already translating into a remarkable track record of exits. Among the more eye-catching acquisitions, Livongo, which provides a digital coaching platform for patients with chronic diseases, was acquired by Teladoc in 2020 for $18.5bn. Optum bought Change Healthcare and its digital healthcare transformation tools earlier this year for $13Bn.

On the IPO side just last year, prescription medicine dealfinder GoodRX went public at a $13Bn valuation, telehealth platform Armwell for $4Bn, and health benefits platform Accolade for $1.2Bn.

Naturally, these exits have been concentrated in the Digital Health area, which is more mature. But we’re expecting other aspects of Digital Life Sciences, such as in AgTech or in lab tools, to follow the same trajectory in the years to come.

Take for example the lab tool Aqemia, deep tech startup developing a groundbreaking molecule matching solution for drug discovery, that has already received funding and support from Sanofi.

Valuations And Liquidity

As with so much else about Digital Life Sciences, when it comes to valuations and liquidity, it’s important to understand how the Digital and the Life Sciences aspects influence these markets.

Indeed, strong barriers to entry exist in e-health to bring a concept to the market: necessary prior marketing authorization, a classification in the case of a medical device, one or more data security devices that comply with the GDPR, clinical studies carried out in hospitals to prove the effectiveness of the device, etc.

For example, take a startup developing a medical device. Revenues are not the key to valuation as they would be for a purely digital startup. Instead, once regulatory and pharmaco-economic hurdles are cleared, and before the launch of the product, the company is valued based on this certification and the size of the market this certification will potentially open to the product.

Much more than the top line generated, investors are looking at the size of the addressable market. If a disease is already being treated using other methods or drugs, we know the size of the potential market. Such approval tells us there is a high probability the device will attract sizable revenues. That potential is what matters to someone who may eventually want to acquire the company. They would consider the acquisition price to be low-risk because that authorization ensures a high rate of market success for the product.

In addition, once that startup shows it has good technology that solves an issue, it then starts to become clear where the company sits inside an existing ecosystem, whether that’s medical or agricultural. Whereas a Digital startup might be able to launch and sell a product on its own, a Life Sciences startup will likely depend on how it interacts with existing players such as insurance companies, hospitals, and other treatment providers. Where it falls in that value chain and how it disrupts them will point to the potential size of its market, and is another key for its valuation.

As for liquidity, Life Sciences have traditionally been more liquid — and at an earlier stage — than Digital startups. Historically, Life Science companies such as Big Pharmas like to acquire these companies just before or just after the treatments are being commercialized. These preemptive deals essentially treat these biotech startups as a way to outsource their drug development pipeline with a limited risk.

We see a similar trend now in Digital Life Sciences. While this sector is already mature in the U.S., it’s now advancing rapidly in Europe thanks to greater late-stage funding for these startups. They are able to stay private longer, avoid being forced to IPO too early, get the funding they need to get through their various trials and approvals, and then reach the acquisition stage where their valuations — and investor returns — are greater. This European market stands on the cusp of massive opportunity thanks to its wealth of talent and world-class research labs. Being a brand new segment, the exit path for Digital Life Sciences lies somewhere between the two separate segments.

That’s why Elaia believes now is the time to dig deeper into Digital Life Sciences and support the deeply transformational companies that are arising.

While Covid has accelerated this sector, we had already started investing and made the most of our Digital Life Sciences investments pre-pandemic,” said Elaia Partner Samantha Jerusalmy. “We have long believed that the success of these segments will happen only if Digital developments fit properly in the existing part of Life Sciences. That foresight has put us in a strong position.

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