The Bio Revolution: Innovations transforming economies, societies, and our lives

| Report
Advances in biological science could transform economies and societies, helping to tackle global challenges from climate change to pandemics.

A confluence of advances in biological science and accelerating development of computing, automation, and artificial intelligence is fueling a new wave of innovation. This Bio Revolution could have significant impact on economies and our lives, from health and agriculture to consumer goods, and energy and materials.

Some innovations come with profound risks rooted in the self-sustaining, self-replicating, and interconnected nature of biology that argue for a serious and sustained debate about how this revolution should proceed. Accidents can have major consequences—and, especially if used unethically or maliciously, manipulating biology could become a Pandora’s box that, once opened, unleashes lasting damage to the health of humans, ecosystems, or both. The risks are particularly acute because many of the materials and tools are relatively cheap and accessible. Moreover, tackling these risks is complicated by a multiplicity of jurisdictional and cultural value systems, which makes collaboration and coordination across countries difficult.

However, new biological applications are already improving our response to global challenges including climate change and pandemics. Global responses to the novel coronavirus—SARS-CoV-2—illustrated substantial advances in biological science in just the past few years. The speed with which scientists sequenced the virus’s genome—weeks rather than months—bore witness to the new world of biology described in this research. However, sequencing is just the start: biological innovations are enabling the rapid introduction of clinical trials of vaccines, the search for effective therapies, and a deep investigation of both the origins and the transmission patterns of the virus.

As much as 60 percent of the physical inputs to the global economy could, in principle, be produced biologically—about one-third of these inputs are biological materials (wood or animals bred for food) and the remaining two-thirds are nonbiological (plastics or fuels) but could potentially be produced or substituted using biology. Therefore, it is possible that bio innovations could impact up to 60 percent of physical inputs, although attaining that full potential is a long way off. Even modest progress toward it could transform economies, societies, and our lives, including what we eat and wear, the medicines we take, the fuels we use, and how we construct our physical world. In human health, at least 45 percent of the current global disease burden could be addressed using science that is conceivable today.

A pipeline of about 400 use cases, almost all scientifically feasible today, is already visible. These applications alone could have direct economic impact of up to $4 trillion a year over the next ten to 20 years. More than half of this direct impact could be outside human health in domains such as agriculture and food, consumer products and services, and materials and energy production. Taking into account potential knock-on effects, new applications yet to emerge, and additional scientific breakthroughs, the full potential could be far larger.

Section 1

Biological innovation covers four arenas

The current innovation wave in biology has been propelled by a confluence of breakthroughs in the science itself, together with advances in computing, data analytics, machine learning, artificial intelligence (AI), and biological engineering that are enabling and accelerating the change. This revolution has been decades in the making. The $3 billion, 13-year effort to map the human genome that began in 1990 is a foundational building block, but the power of this map only began to materialize when it became cheaper and faster to sequence DNA. The cost of DNA sequencing has been decreasing at a rate faster than Moore’s Law. Advances in lower-cost and high-throughput screening have helped lower the costs of entry, accelerate the pace of experimentation, and generate new forms of data—to help us better understand biology.

Innovations are grouped into four arenas: (1) biomolecules—the mapping, measuring, and engineering of molecules; (2) biosystems—the engineering of cells, tissues, and organs; (3) biomachines—the interface between biology and machines; and (4) biocomputing—the use of cells or molecules such as DNA for computation (Exhibit 1).

A confluence of breakthroughs in biological science, with the development of computing, automation, and AI, are fueling a new wave of innovation.

Major breakthroughs in each of the four arenas are reinforcing one another. In biomolecules and biosystems, advances in omics and molecular technologies are enhancing our understanding of biological processes, as well as enabling us to engineer biology. The ability also exists to engineer or modify a living cell to cure or prevent disease; for example, the groundbreaking CRISPR tool allows scientists to edit genes more quickly and precisely than previous techniques. Essentially the same process is being applied to manufacturing everything from textiles to meat. Advances in biomachines and biocomputing both involve deep interaction between biology and machines; it is becoming increasingly possible to measure neural signals and power precise neuroprosthetics. It is now also possible to store the world’s wealth of data using DNA. The storage density of DNA is about one million times that of hard-disk storage.

Section 2

New biological capabilities could bring about meaningful change across economies and societies

New biological capabilities have the potential to bring sweeping change to economies and societies:

Biological means could be used to produce a large share of the global economy’s physical materials, potentially with improved performance and sustainability. Fermentation, for centuries used to make bread and brew beer, is now being used to create fabrics such as artificial spider silk. Biology is increasingly being used to create novel materials that have unique qualities, introduce entirely new capabilities, are biodegradable, and/or produced in a way that emits significantly less carbon. Some companies are already using genetically engineered microbes to create biofuels for the aviation and marine industries.

Increased control and precision in methodology is occurring across the value chain, from delivery to development and consumption with more personalization. Advances in molecular biology have made R&D and delivery processes more precise, predictable, and deliberate—enabling rational design rather than discovery by accident. Increasing knowledge of human genomes and the links between certain genes and diseases is enabling the spread of personalized medicine and precision agriculture.

Technically, one kilogram of raw DNA could store the entirety of the world’s data.

The capability to engineer and reprogram human and nonhuman organisms is increasing. Gene therapies could offer complete cures of some diseases. Crops can be genetically engineered to produce higher yields and be more heat- or drought-resistant, for instance—traits that are becoming even more important given climate change.

New methodologies using automation, machine learning, and proliferating biological data are enhancing discovery, throughput, and productivity in R&D. Biology and computing together are accelerating R&D, thereby addressing a productivity challenge. McKinsey analysis in 2017 found that the ratio of revenue to R&D spending in the biopharmaceutical industry hit a productivity nadir between 2008 and 2011. Biotech companies and research institutes are increasingly using robotic automation and sensors in labs that could increase throughput up to ten times. Advanced analytics using machine learning can provide better insights during the R&D process.

Potential is growing for interfaces between biological systems and computers. A new generation of biomachine interfaces relies on close interaction between humans and computers. Such interfaces include neuroprosthetics that restore lost sensory functions (bionic vision) or enable signals from the brain to control physical movement. Biocomputers that use biology to mimic silicon are being researched, including the use of DNA to store data. DNA is about one million times denser than hard-disk storage; technically, one kilogram of raw DNA could store the entirety of the world’s data.

Section 3

Today’s pipeline of applications is a fraction of the far-reaching impacts expected ahead

For this research, a library of about 400 use cases was compiled that already constitute a visible pipeline for the years ahead. The library comprises applications that are scientifically feasible today and likely to be commercially viable by 2050. Over the next ten to 20 years these applications alone could have direct economic impact of between $2 trillion and $4 trillion globally per year.

Human health and performance has the clearest pipeline from research to commercialization. The science is advanced, and the market is generally accepting of innovations. However, more than half of the direct impact of the applications in the library over the next ten to 20 years is likely to be outside health, primarily in agriculture and consumer products (Exhibit 2).

More than half of the impact is outside of healthcare in agriculture, consumer, and other areas.

Over this period, applications will tend to be in four key domains:

Human health and performance. Applications include cell, gene, and RNA therapies to treat or even prevent disease, a range of anti-aging treatments to extend lifespans, innovations in reproductive medicine, and improvements to drug development and delivery and new predictive modelling of human health and disease. Many more options are being explored and becoming available to treat monogenic (caused by a single gene) diseases such as sickle-cell anemia, polygenic diseases such as cardiovascular disease, and infectious diseases such as malaria. The direct annual global potential impact is estimated at $0.5 trillion to $1.3 trillion over the next ten to 20 years, or 35 percent of the total (including impact from biomachine interfaces).

Agriculture, aquaculture, and food. Applications in this domain include innovative new ways to conduct breeding of animals and plants using molecular or genetic markers that are many times quicker than established selective-breeding methods; new, more precise tools for the genetic engineering of plants; fast-developing work using the microbiome of plants, soil, animals, and water to improve the quality and productivity of agricultural production; and the development of alternative proteins including lab-grown meat. Direct annual impact could be between about $0.8 trillion and $1.2 trillion over the next ten to 20 years, or 36 percent of the total.

Consumer products and services. Opportunities are opening up to use increasing volumes of biological data to offer consumers personalized products and services based on their biological makeup. Applications in this domain include direct-to-consumer genetic testing, beauty and personal care increasingly based on increased knowledge of the microbiome as microbiome testing spreads, and innovative approaches to wellness (or fitness) not only in humans but in pets. There could be annual direct economic impact over the next ten to 20 years of $200 billion and $800 billion, or 19 percent of the total (including impact from biomachine interfaces).

The direct annual global impact of the Bio Revolution could be $2 trillion to $4 trillion in 2030-40.

Materials, chemicals, and energy. New biological ways of making and processing materials, chemicals, and energy could transform many industries and our daily lives, although the economics are challenging. Applications in this domain include innovations related to production of materials such as improved fermentation processes, new bioroutes utilizing the ability to edit the DNA of microbes to develop novel materials with entirely new properties (self-repairing fabrics is one example), and building on advances in biofuels to innovate new forms of energy storage. Over the next ten to 20 years, the direct annual global impact could be $200 billion to $300 billion a year, or 8 percent of the total.

Biology has many other potential applications, although some of these are likely to be further in the future. It could be deployed to help the environment through biosequestration—using biological processes to capture carbon emissions from the atmosphere—and bioremediation. Impact is also emerging in biomachine interfaces and biocomputing where the science and development is at an early stage but applications are promising. Applications that have already been developed include neuroprosthetics to restore hearing and vision.

The direct potential impact of the around 400 use cases may only be a small portion of the potential scale of impact. Many other innovations are being developed in private labs or in the defense industry where developments remain confidential for commercial or national security reasons.

Eventually impact will radiate out to almost every sector of the economy with effects on societies and the environment as biological innovation transforms profit pools, value chains, and business models. In the years ahead, if you are not using biology to make products, you will very likely be consuming them. The impact could go much further, with biology potentially being used to address some of the great challenges of our time including mitigating climate change. By 2040 to 2050, the direct applications we sized could reduce annual average man-made greenhouse-gas emissions by 7 to 9 percent from 2018 emissions levels.

Section 4

Biological innovation has profound and unique risks

Profound risks accompany this surge of innovation in biology. Get it right and the benefits could be very significant; get it wrong and there could be disastrous consequences at the population level. These risks introduce a unique set of considerations which, if not managed properly, could potentially outweigh the promised benefits of a particular application:

  • Biology is self-replicating, self-sustaining, and does not respect jurisdictional boundaries. For example, new genetically engineered gene drives applied to the vectors that spread disease (mosquitoes in the case of malaria) could have enormous health benefits, but such gene drives can be difficult to control and can potentially permanently change ecosystems.
  • The interconnected nature of biology can increase the potential for unintended consequences. Changes to one part of the system can have cascading effects and unintended consequences across entire ecosystems or species. Gene editing could also have unintended or “off-target” effects.
  • Low barriers to entry open the door to potential misuse with potentially fatal consequences. Some biological technologies are relatively cheap and accessible. Commercial kits to perform CRISPR gene editing are being sold relatively cheaply on the internet.
  • Differing value systems make it hard to forge consensus, including on life and death issues. Technical and scientific issues, such as embryo editing, quickly become moral questions, and often, decisions across these issues are expressions of one’s value system. The challenge of cooperation and coordination of value-systems across cultures and jurisdictions is no easy task, particularly when advances in these scientific domains could be seen as a unique competitive advantage for businesses or economies.
  • Privacy and consent issues are fundamental. Concerns about personal privacy and consent are rife, given that the cornerstone of biological advances is data mined from our bodies and brains.
  • Unequal access could perpetuate socioeconomic disparity, with potentially regressive effects. Biological advances and their commercial applications may not be accessible to all in equal measure, thereby exacerbating socioeconomic disparity. At a country level, developments are advancing quickest and most broadly in relatively rich countries.

These risks demand a considered response and potentially new approaches. In past waves of technological change, regulation has emerged in response to innovations; in biology, there is a strong argument for a proactive approach. Regulation will be important, but so too will oversight and monitoring of science even as it develops. The choices scientists make will help determine what kinds of technologies develop. International collaboration and coordination will be valuable as biology doesn’t respect borders—as we experienced in early 2020 with the rapid spread of COVID-19.

Section 5

In the journey to adoption, science is just the starting point

Risks need to be addressed, but beyond that there are many stages to negotiate as innovations move from the lab to adoption. The journey to adoption has three broad stages: scientific research; commercialization; and then diffusion. For biological applications to diffuse and deliver impact, six broad factors play a role; they determine whether adoption occurs and how long it takes:

  • Investment in scientific research. Funding, tools, talent, and access to data are necessary and powerful elements of the investment needed to enable scientists to be successful. It tends to take years of research and sizable investment in these capabilities to get an idea to the point at which a product or service is scientifically feasible.
  • Four factors play a role in commercialization and diffusion. First, a new biology-based product or service needs to compete with existing products and services not only on cost but also by offering higher quality or new properties or, indeed, by meeting a need not fulfilled by existing offerings. The second factor is whether business models are suitable for what may be a fast-changing landscape. Third, a new biology-based product and service needs to hit the right potential customers with go-to-market elements including pricing, sales, and marketing. The fourth factor is the ability to scale up operations.
  • Risk and mechanisms governing use. Given the profound and unique risks accompanying biological innovation, mechanisms governing use, including broad acceptance from society and regulation, are key at all stages. About 70 percent of the total potential impact could hinge on consumer, societal, and regulatory acceptance, based on an analysis of areas where regulations exist today in major economies.

The pace and extent of adoption will vary enormously depending on the application and the domain. Some applications including using new bioroutes to manufacture drugs are already showing robust signs of early commercial adoption. Others such as CAR T-cell therapy for cancer have recently become commercially viable, adoption is early, and could increase rapidly in the near term over the coming decade. Yet others such as using genetically engineered plants to sequester CO2 show promise in scientific research but commercial viability and adoption by farmers or other buyers is likely further out (Exhibit 3).

More than half of the impact is outside of healthcare in agriculture, consumer, and other areas.
Section 6

Striking a balance that enables potential to be captured while managing risks

Given the breadth of change that likely lies ahead, innovators, businesses, governments, and individuals need to become literate in biological science in order to understand the fundamental shifts under way, seize the large potential benefits, but in a way that ensures that innovation is safe for citizens and society.

Innovators. Scientists govern their own research processes. Peer review is a powerful internal governing mechanism to ensure that research is accurate and well grounded. But scientists cannot operate in a vacuum; to an extent, they need to take into account the views of society in the research they propagate. The scientific community must play a consistent and effective oversight role.

Businesses should consider how to take advantage of biological innovation, potentially adapt strategies. The Bio Revolution could transform entire value chains, and companies in virtually every sector may need to adapt strategies. Given the uncertainty and evidently varied timing of adoption for different applications, companies should consider a portfolio-based approach toward investment. By its nature, biological innovation is cross-discipline and, as such, it is unlikely that any business that exists today can go it alone. Large companies should consider the degree to which they develop the full range of necessary capabilities in-house or “buy in” what they need through mergers and acquisitions, and partnerships. As in the Digital Revolution, some companies should consider how to use platform-based business models that can seize cross-sector opportunities, reduce marginal costs, and drive combinatorial innovation by leveraging growing biological data. Among other aspects to consider are the range of opportunities for more personalized and precise offerings enabled by growing biological data, and innovative revenue models that could help accelerate diffusion.

The Bio Revolution could transform entire value chains, and companies in virtually every sector may need to adapt strategies.

Civil society, governments, and policy makers need to inform themselves about biological advances and respond to them effectively. Several governments including those of China, the United Kingdom, and the United States have set the tone for biological innovation with published strategic plans and goals intended to catalyze biological innovation and capture its benefits. However, innovation needs to be balanced by mechanisms to govern use and misuse, and whether existing professional and regulatory mechanisms are fit for purpose must be considered.

Individuals and consumers may be pivotal to the adoption path of biological advances. To contribute effectively to what can be controversial debates (consider embryo editing as an example), individuals need to seek to understand the benefits versus the risks. They also need to appreciate that there are personal trade-offs. DTC testing, for instance, provides individuals with potentially valuable insights into the probability of contracting certain diseases, but mining that information may compromise their privacy.

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