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Cloud Biology in Agriculture: Taking Big Data to a New Level

April 27, 2016

Editor’s Note: Tomorrow at the Global AgInvesting Forum in New York, the first panel discussing Cloud Biology in agriculture will convene involving Matthew Crisp, CEO of Benson Hill Biosystems, Ignacio Martinez, partner at Flagship Ventures, Randy Ouzts, US rice manager of Crop Production Services, and led by moderator Joshua Hofheimer, partner at Sidley Austin.

In this guest commentary exclusively for AgFunderNews, Crisp discusses how the concepts of Cloud Biology have been utilized in other industries and highlights the enormous potential for this convergence space to enable biology-based ag solutions.

Benson Hill Biosystems is an agriculture technology company that’s unlocking the genetic potential of plants to enhance the performance of crops and the sustainability of food, feed, and fiber.

Matt Crisp
Matt Crisp


Big data is revolutionizing agricultural innovation – but not just through precision agriculture. For the last few years, we’ve heard about the role big data analytics can play to advance agriculture through precision agriculture and farmer practices. But there are other applications of big data that can have a profound impact on crop performance.

What is Cloud Biology?

The convergence of big data analytics and cloud computing with biological expertise is greatly accelerating innovation in many industries, and most recently in agriculture. The combination of these various disciplines represents the foundation of Cloud Biology, an emerging field that is transforming not only what agricultural challenges we can tackle through innovation, but who is empowered to innovate.

Sequencing, genotyping, and phenotyping costs have tumbled in recent years, and at the same time, we continue to witness dramatic increases in both computing power and accessibility. Thanks to AWS and others, gone are the days of needing an onsite system admin to build a technology business. Data can be stored, accessed, and analyzed at scale in the cloud by even entry-level users.

Couple this with rapidly improving analytics and with biology – that is, actually implementing outputs from a machine learning engine, then ground-truthing results and delivering superior products – and this defines the potential of Cloud Biology. How much is undertaken “in the cloud” – or virtual to the user – will evolve at different rates in different verticals over time. Suffice it to say that we are at the threshold of realizing this next generation of innovation, even in complex systems like plants.

Concepts of Cloud Biology in action

The concepts that embody Cloud Biology are not new. One element – virtualization, or complete outsourcing of program execution – has successfully been realized in drug development. After large-scale pharmaceutical research underwent significant contraction more than a decade ago, a network of capable CROs (contract research organizations) and CMOs (contract manufacturing organizations) emerged. Through economies of scale, shared risk models, and greater efficiencies, they helped kick-start virtual drug development companies that include investment successes such as FerroKin BioSciences and Angiosyn. Companies like these can operate far more efficiently than their prior counterparts and can now advance well into human clinical trials with only a handful of actual employees.

In the industrial biotechnology arena where microbial cell systems are used as a production platform to produce biology-based products, companies like Zymergen and Ginkgo BioWorks are employing robotics and automation to reduce to practice biological solutions. Applying certain of these engineering principles is enabling innovation at a level of sophistication and scale that is orders of magnitude greater than what was experienced only a few years ago. As a result, these companies are able to engineer microbes for a broad range of uses that impact our health and environment at a fraction of the cost and the time than would be incurred in a traditional organization.

Merging many of the concepts above, Emerald Cloud Lab is lowering barriers to entry and helping to level the playing field to encourage more people and organizations to conduct early experimentation and life sciences research and development. This is an example of the clouding of biology, as Vijay Pande of a16z recently described. Emerald Cloud Lab’s web-based life sciences laboratory is almost the apex of Cloud Biology and they, like us at Benson Hill, only decided to open up their platform after building a robust solution for internal consumption.

Biology is messy, especially in Ag

As anyone working in this space appreciates, biology is still messy, and exponentially more so in eukaryotic systems such as plants and mammalian cells. For crop improvement, harnessing the full value of big data and computational power to deliver intelligent, actionable insights that will move the dial in agriculture, requires grounding with deep biological expertise, reduction to practice – i.e. getting beyond ‘in silico’ modeling and actually creating something – then validating its performance in the field.

In the near future, we will also see more examples of how engineering principals are extending beyond the hardware to the biology itself. Synthetic biology brings the principles of engineering and system design to the organism level, which is further accelerating with the uptake of genome editing tools. As Liz Stinson recently described in Wired and Sveta McShane in SingularityHUB, we can expect that this exciting intersection, and the tools being built around it, will empower a new generation of biological engineers and pioneers.

A more predictable version of biology will first be realized in simpler biological systems or processes in defined production environments, such as well-characterized bacteria being used as a production chassis in a highly controlled fermentation system. For complex cell systems in less controlled or uncontrolled environments – crop genetics comes to mind – we expect that Cloud Biology will play an enormous role in innovation. More robust predictive models can help innovators tackle these tough product development challenges – especially by incorporating the insight of a community of such innovators through a modern artificial intelligence platform like IBM’s Watson.

Where is Cloud Biology in Ag?

Cloud Biology in agriculture is in its infancy, but we will soon see progress similar to what has been experienced in other industries. Its adoption will significantly accelerate our ability to innovate and empower users – whether they have extensive technological or scientific training or not – to design and execute experimentation in a manner that goes beyond in silico results and leads to tangible commercial products that can be monetized.

One company already applying the principles above is the stealthy Flagship VentureLabs company, CiBO Technologies. CiBO not only utilizes the classical big data that is rapidly being democratized by many precision ag companies, but it’s combining this with real outcomes – ground-truthing the biology at the crop-level and in a manner that requires insight beyond weather data, a mathematical model and some sensors.

At Benson Hill Biosystems, we built a platform and used it to model plant primary metabolism and identify genes to improve photosynthesis and crop productivity. Given the success of the platform, we recently decided to open it up and allow for its broader application and enablement. In the last few months we have migrated our entire computational infrastructure to the cloud and are at the cusp of making this platform available to benefit the broader agricultural community, where it will grow with collective input and enable our partners to harness natural and novel genetic variation through breeding, trait development, and/or genome editing.

We believe that Cloud Biology in ag will break open a new frontier of innovation. But the most exciting part is not how it can accelerate innovation, but who it will empower to innovate. For years, agtech innovation has largely been concentrated within companies with the largest R&D budget or the most market share. Innovation, particularly in complex arenas like crop genetics, required a scale and infrastructure that was cost-prohibitive for most organizations. This is the case no more.

A New Era of Innovation in Agriculture is Not a Choice

A new era of innovation and a new generation of innovators is an imperative. Never before has so much been expected from agriculture, and never have the risks to agricultural progress been greater. Population growth and rising consumer expectations coupled with climate change and diminishing natural resources compound the challenges that we face.

Historically, barriers to entry for biology-based agtech have been high and venture investment relatively low. This is changing, and coincidentally at the same time as a commodity down cycle, a contraction of large-scale research spending, and talent availability.

The time has never been better for a disruptive acceleration in agtech innovation, one that can empower new players in the ag value chain to participate, benefit and significantly enhance crop performance. The time has come to leverage the full power of Cloud Biology to advance agriculture.

What do you think? Get in touch [email protected]

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