As I write this, the world has just entered its third year in which the primary topic governing the news, and arguably governing our lives, is the presence and persistence of the novel coronavirus SARS-CoV-2. First reported on December 12, 2019, we seem trapped in a never-ending year now in its 758th day. The virus continues to evolve 鈥� the mutations from the Wuhan strain have now taken us more than halfway through the Greek alphabet 鈥� with Omicron鈥檚 relentless wave of transmission delivering a powerful reminder of the need to improve detection, response, and variant-proof protection. The waxing and waning of infections, hospitalizations, and mounting deaths leaves us grieving, whiplashed, and exhausted: none more so than health care workers and other first responders on the front lines.
I had hoped to pen this Annual Letter in the wake of the pandemic to share my thoughts on what the crisis has revealed about societal preparedness generally, and about the biotech industry specifically. Unfortunately, we are not yet in the pandemic鈥檚 wake: We remain in its grasp. In fact, I am among the millions who contracted the Omicron variant going into the holiday season.
This note therefore begins en media res 鈥� in the middle. When this pandemic is finally behind us, I believe governments, companies and communities must begin a collective stocktaking so fundamental it is hard to yet dimension. But already, at this stage, we can see the ways in which the pandemic has revealed the future of biotechnology, an industry I have contributed to and watched evolve over the past 35 years. The crisis has thrown into relief the powerful forces shaping our industry, and those forces, taken together and furthered by innovation, capital, and talent, make it possible to totally rethink how we define and approach illness and disease, and protect and prolong our health.
This letter explores four of the forces shaping biotech鈥檚 future: programmable medicines and digital biology; machine learning and artificial intelligence; the exponential value potential of bioplatforms; and a pandemic-inspired regulatory reset.
Programmable Medicines and the Advent of Digital Biology
As journalists and others work to capture the history of how mRNA vaccines were developed and deployed, there is one question I get over and over again as the co-founder and chairman of : Were you stunned that your vaccine worked? Were you bowled over when you first heard the trial results showing 94.5% efficacy? My answer 鈥撯�渘o, it wasn鈥檛 surprising鈥� 鈥� is short on dramatic reveal, but inevitable in the era of programmable medicines. More importantly, it speaks to the shift from a probabilistic drug discovery industry characterized by multiple 鈥渟hots on goal鈥� to the deterministic approach enabled by digital biology.
What鈥檚 meant by a programmable medicine?
In the world of computation, programming means giving a computer a set of instructions to conduct a set of calculations or tasks, yielding a very predictable and expected result. This hasn鈥檛 really been possible in biology. We鈥檝e simply tried a lot of experimental approaches to adapt or mimic the biology or behavior of cells, animals and people and hoped one of those shots went in. Over the last decade, our understanding of biology has increased exponentially, and scientists have created new tools to perturb biology more directly and deliberately. As a result, we can start to think of drugs as instructions or programs that have predictable outcomes and vice versa, we can envision an outcome, and then design the right program to achieve it. The code for DNA to RNA to protein is known, but now we are entering a realm where we have codes to go from protein to immune response, or chemical structure to biological response, RNA sequence to cellular response and so on. The building blocks of these biological modalities can be arranged rationally to achieve the desired effects in the human body. Welcome to the era of Programmable Medicines.
In the case of the Moderna vaccine, we long knew that the spike protein on the coronavirus played a critical role in its ability to enter and infect cells. We knew that generating an immune response against this protein would prevent the virus from infecting the cells. We also knew from the years of work we had done at Moderna that we could encode the protein sequence of virtually any antigen from programmed mRNA and elicit an immune response against that protein. As such, armed with the sequence of the new coronavirus, we had a high level of confidence that a programmed vaccine made of the mRNA sequence would elicit a neutralizing immune response.
Flagship companies such as and are creating programmable medicines in the realm of proteins/antibodies and small molecules, respectively, where the programming code to create the right protein for the right target, or the right small molecule to get the right cellular biology, is elucidated and leveraged.
Contrast this with the drug discovery paradigm we鈥檝e relied on to date, which has produced important and occasionally transformative new therapies for patients, but it is ultimately a game of chance. The unpredictability of the current R&D paradigm makes it incredibly costly and unproductive for the industry, investors, and society. The advent of programmable medicines and digital biology can change the paradigm to one that is more deterministic and highly productive.
Programmable medicines are part of a larger transformative force that is already being felt: 鈥渄igital biology鈥� or the conversion of physical matter into information. Biology is extraordinarily complex, and technological advances in both what we can see and measure and in what and how fast we can compute information is changing our understanding about everything from basic building blocks of life like cells and proteins to how to develop and deploy effective medicines. It is changing not just treatment but discovery and assessment.
Turning biological problems into 鈥渄igital problems鈥� holds tremendous promise, as Flagship companies , and others powerfully demonstrate. Just as the term 鈥渂iotechnology鈥� was introduced to describe the application of engineering and biosciences principles to raw materials to create new products, we believe the next century will be one of 鈥渄igital biology,鈥� in which complex biological problems are translated into computational ones. The applications are limitless, as is the potential. Take, for example, the burgeoning applications of machine learning (ML) and artificial intelligence (AI) to biology.
The Convergence of Biology and AI
As my colleagues Armen Mkrtchyan and Karim Lakhani write in an essay published by Flagship earlier this week:
We believe AI and biology are the principal and mutually enabling innovation engines of our generation, particularly so when combining forces. Applying machine learning to large biological datasets has begun to elucidate the cause-and-effect relationships underlying human genetics and disease. In the opposite direction, we have only scratched the surface in terms of leveraging biology to advance AI research. (Read full essay here).
One aspect of this powerful convergence that particularly excites me is the ability to harness machine learning to computationally generate new scientific hypotheses that can then be explored and tested.
AI and ML tools also enable what I think of as disease time travel. What do I mean by that? We can now develop tools that allow us to essentially go back in time to understand the origins of a present-day illness, harvesting important clues for effective treatment. Similarly, we can use biological datasets to travel forward and predict the future: for example, our recently launched Flagship company can, with just a few milliliters of blood, detect genetic patterns that, without intervention, will lead to a future tumor in a particular tissue of origin. We can also get increasingly better at time traveling to the onset of future pandemics and designing vaccines with antibody nets that safeguard against multiple future scenarios.
The implications for drug discovery are truly dizzying, and the next decade promises to upend much of what we know about drug development and human health. It should follow, therefore, that capital markets are reflecting this enthusiasm and sense of possibility, but in fact, the picture there was very mixed in 2021.
The Biotech Business Environment and the Hunt for Value
On the one hand, 2021 was an extraordinary year for life science investment, with several chart-topping raises by early-stage companies. More private capital flowed into early-stage biotech companies 鈥� and in larger amounts 鈥� than in any year I can remember. A recent article in Boston Business Journal the top 10 biotech investment rounds in the Boston area in 2021: the average raised was $397 million. Just four or five years ago, a typical Series B raised $50 million.
On the other hand, the story in public markets was quite different, and 2021 was largely considered a rout for biotech: a cooling off from the coronavirus-led enthusiasm that fueled the sector鈥檚 stocks in 2020. But public market performance doesn鈥檛 tell the whole story of the hunt for value in biotech, or even the most interesting part.
We鈥檝e always believed that multiproduct bioplatform companies are most likely to create exponential potential. As my colleagues Stephen Berenson and Andy Oh explain:
Bioplatforms have several advantages. They have the potential to create numerous product opportunities not only in parallel but also in a highly efficient manner as learning effects from platform optimization and program data create a virtuous cycle of innovation and improvement. They can create multiple related (highly correlated) or unrelated (low correlated) programs, in which the success of a vanguard program substantially derisks future highly correlated follow-on programs. They have the flexibility to rapidly enable new programs in response to unforeseen opportunities. Each of these advantages helps mitigate development risk, enhances potential returns and strengthens the opportunity to build long-term sustainable businesses. (Read full essay here).
Public market investors nonetheless remain biased toward single-asset biotechs. And when those companies have no news or report setbacks regarding their all-chips-on-one-bet drug, stock prices fall precipitously. When fast-moving biotech platform companies fueled by private capital go public, they often run headlong into this brick wall of bias, effectively discouraging this more impactful form of innovation and the diversified product portfolios that result.
A Post-Pandemic Regulatory Reset
What other forces, beyond the market, have the power to either fuel or frustrate biotech innovation? The regulatory framework, responsible for assuring safety and efficacy before products come to market.
The lengthy 鈥� and very resource-intensive 鈥� regulatory approval process to bring drugs or diagnostics to market has been a gating factor, along with the costly and often specialized process of then manufacturing these products at scale once approved.
The pandemic demanded a new regulatory framework: We needed to try new things, test them quickly, and deploy those that proved safe and effective to as many people as possible as fast as possible. Since December of 2020, the Food and Drug Administration, World Health Organization, and other regulatory bodies have authorized for emergency use or approved for commercial distribution at least two dozen vaccines and therapeutics for COVID-19, as well as numerous tests. To take the example I know best, mRNA vaccines went from being commercially non-existent in January of 2020, dosed in a small number of humans across a dozen or so clinical trials, to more than three billion doses of life-saving mRNA vaccines delivered to people across the world.
We now know what is possible when regulatory authorities operate with urgency and balance societal risk with societal benefit. How will these learnings shape regulatory approaches going forward? How should they?
Flagship鈥檚 Jim Gilbert, Kathy Biberstein and Stephen Hahn share their thoughts on elements of a 鈥淕oldilocks鈥� regulatory framework:
Life sciences innovation will benefit from a range of factors that will allow it to become more 鈥減rogrammable鈥� and 鈥渆ngineerable鈥� vs. its historic 鈥渟erendipity鈥� through lab and real-world trial and error innovation. 鈥� To support the global scaling of breakthrough innovation to preempt and address fundamental human and planet health challenges, the 鈥淕oldilocks鈥� regulatory framework for life sciences should aspire to be as innovative as the science it is regulating and as bold as the problems the innovation is looking to address. (Read full essay here).
What now?
In the early days of the pandemic, I lost my father-in-law to COVID-19. The optimism and sense of purpose that fueled Moderna鈥檚 all-out effort to deliver safe and effective vaccines was, for me, tempered by grief and sense of loss: for my own family, as for millions of families throughout the world, the lifesaving innovation of mRNA vaccines came too late.
As the grandson of Armenian genocide survivors, I have dedicated time and effort to the task of deriving meaning out of loss, and forging progress out of pain. In my philanthropic endeavors this mindset led to the Aurora Humanitarian Initiative, founded on behalf of survivors and rooted in the belief that a brighter future lies with those who are committed to helping and honoring those who have been lost.
While we read official numbers like 5.5 million dead due to COVID-19, many point to excess deaths around the world during this period that . In its final accounting, this pandemic will likely log a death toll that far surpasses the mass casualties of the genocides and holocaust of the past century. How will we make meaning of this incomprehensible level of loss? How will we 鈥� the survivors 鈥� better the world with the new knowledge and innovation that has emerged through the necessity of crisis? I鈥檒l leave you with a few ideas.
- We can prioritize health security and invest in preemptive health.
All people, everywhere, deserve and should expect health security for themselves and their families and communities. Governments as well as the private sector should embrace an obligation to not only prepare for future pandemics but do everything possible to prevent viral outbreaks from becoming pandemics.
Similarly, we have now directly experienced the devastating collision of the fast pandemic of COVID-19 with the slow pandemics of chronic disease. Preemptive medicine can prevent or delay the onset of disease using new and emerging tools to detect pathways toward disease and interrupt those pathways, helping us 鈥� individually and collectively 鈥� to be more resilient in the face of infectious disease. How? Lord Ara Darzi, the leader of our Preemptive Health and Health Security Initiative, explains in this piece written with Flagship鈥檚 Tom Kibasi:
New tools are being developed that will enable individuals to manage their own health by providing them with AI-enabled applications to assess their health status and determine if preemptive medicine interventions may be beneficial to avoid progression to a chronic disease.
Far superior ways to engage, involve and empower citizens to improve their own health will be central to a preemptive medicine paradigm precisely because the absence of symptoms means that participation is a choice, rather than a compulsion to alleviate pain or discomfort.
Early detection also offers an opportunity to radically change people鈥檚 relationship with their own health by empowering them to control their own health future with the information and the tools to preempt disease and reverse or manage a predisease condition. (Read full essay here).
- We can get serious about tackling common illness.
Since the advent of modern medicine we have focused more on treating the symptoms we can see and measure than on addressing the underlying disease. The tools now at our disposal compel us to bring new focus to the root causes of the common illnesses that afflict hundreds of millions of people each year. In a piece published by my colleagues Doug Cole and Christopher Austin, both physician-scientists, they issue a clarion call to improve health for millions:
It is time for biotechnology companies to tackle the common illnesses that most people suffer from by determining the diseases that cause them. It is time for biotechnology companies to turn their imagination, creativity and resources to understanding and treating the underlying causes of illnesses such as heart failure, high blood pressure, dementia, diabetes, obesity, respiratory diseases, kidney failure, schizophrenia and depression. (Read full essay here).
- We can bring pioneering innovation to our efforts to protect our planet and scale them.
Just as there is little gained from healing an organ inside a dying body, prolonging human health and longevity won鈥檛 matter without a healthy planet to call home. While we are known primarily for our work in human health at Flagship, our life science companies such as , , , and , pioneer new solutions to sustainable agriculture, carbon capture, and farmer-focused carbon markets. We don鈥檛 see human health and the health of our planet as separable.
- We can lead with imagination, rather than reason.
I have often asked why we expect extraordinary breakthroughs from reasonable people doing reasonable things. That has never made sense to me.
I am not, to be clear, making an argument against reason: I am making the argument against reason alone, and encouraging the question. What is our reliance on reason, on 鈥渟afe thinking,鈥� or adjacent discovery, suppressing? The answer, to me, is the big scientific breakthroughs that come from bold scientific leaps. As the ballast for all else we might seek to accomplish, we can dream big, and leap boldly and imagine without the constraints of reason. Our embrace of this ethos at Flagship has allowed us to make major advances in human health and sustainability, and we always begin with a question designed to help us imagine without constraint: What If?
Perhaps a second question for all of us 鈥� in and beyond biotech 鈥� to take into 2022 is: What Now? We鈥檝e entered the year with hard-earned wisdom: We know what it looks like to be a step behind a global pathogen, and what it costs. What Now? We know how quickly new therapies can be tested, approved, and scaled. What Now?
We have a history of emerging from major global crises with new global paradigms, and new institutions to support them. From World War II emerged the United Nations, and a network of global agencies and secretariats aimed at promoting cooperation and keeping the peace. From the terrorist attacks of 9/11 emerged a major reorganization and consolidation of certain government agencies and functions, and a fundamental relook at everything from how we monitor the movement of money to how we screen airline passengers.
What will emerge from the shocks and dislocations, the inventions and innovations, the losses and the lessons of the past 24 months? The answer is up to us.
