Decoding successful AgTech: Insights from experts in agriculture R&D and product commercialization

Ag Playbook has been released to guide startups, investors and industry on how to develop new agricultural products, beware of pitfalls and enhance the likelihood of success for all stakeholders. Edited by Leaps by Bayer, the Ag Playbook harnesses the expertise of a consortium of experts, including former ag executives, investors and startup CEOs.

″The Playbook aims to bring transparency and a shared nomenclature of R&D in agriculture to aid entrepreneur and investor alike in bringing new innovations to the AgTech sector. The goal is to raise all tides across innovators in our industry. This Playbook simplifies the complex process of AgTech product development, covering everything from R&D and regulatory strategy to scaling and market entry. It creates a common language among entrepreneurs, investors and industry players, making collaboration more effective and hopefully increase the chance for novel innovations to make it to the farm,″ says Paimun Amini, Senior Director of Venture Investments for Agriculture at Leaps by Bayer.

In this interview, Paimun will talk about common pitfalls and evolving role of AI highlighted in the Ag Playbook and advice for the stakeholders.

What are the most common pitfalls startups face in R&D, production and field/registration trials for crop protection products, and how to avoid them?

Each subsection of the Crop Protection chapter actually has a call out for ″Opportunities and Pitfalls″, so I’m happy to highlight a few of them:

- In Hit Finding & Screening, a potential pitfall is optimizing a crop protection chemistry of interest without analyzing its productions costs early. If the synthesis of that small molecule product requires expensive intermediates, catalysts, or conditions, while the efficacy may be great, the product will never make economic sense. Having an analysis done early can prevent months of lost time and research dollars.

- In Field Testing, testing against the current best-in-class products or process (positive control) is key. Often we see company spend money on field trials testing against the null hypothesis (no treatment), however, having early results against the best-in-class positive control groups can inform early on if this product can complement or fit into the modern farming practice and compete on price or efficacy. How a product compares will be one of the first questions many commercialization partner or investors will look to better understand when assessing a new Crop Protection Small Molecule product.

How do you see the role of AI and computational platforms evolving in the hit finding?

AI and computational platforms are already having a tremendous impact on hit finding today. Whether it’s the use of Schoedinger software or companies like Atomwise (admittedly a Leaps portfolio company), the use of AI for in silico screening is already minimizing the level of high-throughput physical screening needed to find ″hits″ today. This will only continue to increase as the models incorporate ADMET (absorption, digestion, metabolization, excretion, and toxicity) and cost considerations (see cost problem above) when generating leads for hits.

How have R&D costs changed over time, and what strategies can companies use to manage these costs?

R&D costs and time to develop products have generally increased over these past two decades. Strategies to mitigate these costs can include: 1) leveraging non-dilutive capital and grants from institutions like ARPA-E or FFAR, 2) partnering with key Ag advocacy groups who have research funds, and 3) leveraging the testing infrastructure of incumbents to mitigate some of the large costs associated with field testing.

What are the key considerations when designing field trials for crop protection products? 

See the positive control answer above. I would also add location and field selection to ensure the proper statistical power, but also environmental diversity is represented. In a field trial for a fungicide, it will be hard to prove efficacy if there was never a disease that emerged in the field. Ensuring geographic diversity and in field randomization can secure against selection bias and Ag’s biggest challenge: weather.

What advice would you give to startups navigating the complex regulatory landscape for crop protection products?

Seek experts, engage the material online, and engage the regulators to create a regulatory strategy early on. We have this a part of Phase 1 in the playbook for good reason. The regulatory environment continues to evolve and developing a strategy early can help the company better plan for its product development and approval cycle.

Working with partners and farmers is crucial for establishing consumer trust. What advice do you have for AgTech developers working with them?

As creating a regulatory strategy is part of Phase I, Phase 0 includes extensive interviews and meetings with farmers and customers. For advice:

1) Don’t just conduct farmer/customer interviews looking for confirmation bias about your new product. Before bringing up your product concept have the farmer walk you through their operations and how they current solve the currently problem you believe your product will help with, this informs your ″positive control″.

2) Engage at a community level with state Farm Bureaus or larger national organizations to hear how farmers are speaking about their challenges. This can provide less biased view and drive better engagement with farming community.

View Ag Playbook here >>