Deep Dive: Life in the lab

Driven by demand for sustainable food, alternative proteins are booming. But lab research is key, unlocking tastier plant-based options and even cultivated meat. Here, Lloyd Fuller explores the science and technologies behind the future of food, from optimizing protein compositions to harnessing the power of AI

Within the dynamic alternative proteins landscape, laboratory research and development plays a pivotal role as the engine of innovation. Several transformative technologies are propelling this innovation forward. Advanced computational methods help design superior proteins, while CRISPR allows for precise modifications to existing ones. High-throughput screening techniques rapidly identify the most promising protein candidates, and cutting-edge analytical tools provide deep insights into protein structure and functionality. This confluence of technologies is accelerating development, paving the way for next-generation alternative proteins that are tastier, more nutritious, and more sustainable.

Some of you may recall that, back in April 2024, Protein Production Technology International hosted a fascinating webinar sponsored by Elementar Americas – ‘Accelerating alternative protein innovation in the lab’, which touched on a lot of these innovations, and more.

Elemental analysis

As attendees learned, nitrogen protein analysis plays a vital role throughout the alternative protein lifecycle, from evaluating protein content in crops to ensure optimal breeding choices, to monitoring quality control during production and optimizing protein content in R&D. It also plays a critical role in upscaling production efficiently, verifying protein content for accurate labeling that complies with evolving regulations, and ensuring outgoing goods meet the highest standards. Elementar manufactures Dumas combustion analyzers that precisely measure protein content.

As we discussed life in the lab, we heard that challenges exist, including adhering to ever-changing regional standards, performing rapid analyses for high-throughput facilities, maintaining accurate and precise data with low detection limits, keeping instruments up and running, managing ownership costs, and analyzing a diverse range of sample types (liquids, pastes, solids).

Highlighting the company’s role in the alt protein space is Joseph Thomas, CEO, Elementar Americas. “The alternative protein industry faces a crucial challenge – delivering products with nutritional value comparable to traditional foods,” he begins. “Our solutions for elemental analysis allow producers to fortify their products and provide consumers with clear nutritional data.”

Quality control is another critical area, according to Thomas. “Regular elemental analysis throughout the production process, from start to finish, ensures batch-to-batch consistency. This not only benefits consumers but also paves the way for standardization within the industry,” a topic we revisit in this article. Regulatory compliance is also paramount. “We understand the importance of adhering to evolving regulations, just like the ‘black and white’ labeling introduced earlier,” continues Thomas. “Our long history in this space allows us to stay ahead of the curve and ensure our clients meet the latest standards.”

However, Elementar Americas isn’t just about compliance. “Our instrumentation empowers researchers to develop and optimize new alternative protein products,” notes Thomas. “The last thing scientists need is to be bogged down by manual analysis. Our goal is to streamline the process.”

The scaling conundrum

Discussed at great length during the webinar, scaling up from the lab to large-scale production is one of the biggest pain points facing startups today. Scaling up requires not just replicating a lab process but completely redesigning it for a new environment, while securing resources, maintaining product quality, and adhering to regulations. It’s a complex and expensive undertaking for any startup. “Cost-effectiveness is a major concern for any new company,” agrees Thomas. Elementar’s equipment, though, empowers startups with the data and insights they need to navigate the challenges of scaling up alternative protein production. “This includes aspects such as regulatory compliance, rapid assessments, accuracy, precision, reproducibility, maintenance, and low cost of ownership. Versatility is also crucial. The types of samples analyzed can vary greatly throughout the production process, from the beginning to the end of the value chain. Implementing brand-new technologies at every step can be incredibly expensive. All these factors can significantly impact the bottom line. In short, these seemingly small cost increases can add up quickly for a new organization.”

Choosing between in-house and outsourced analysis is also a decision to be made, and depends on a variety of factors such as production volume, budget, and desired level of control. “Having this capability in-house offers significant advantages, particularly for large-scale operations and high-throughput facilities,” believes Jessica Mannix, Application Chemist at Elementar Americas. “In-house analysis translates to cost-effectiveness by reducing reliance on external labs. It also allows for real-time control, letting you analyze samples immediately after formulation and at various production stages to identify and address any protein loss early on. Additionally, in-house analysis gives you more control over the process, ensuring samples haven’t undergone changes, such as moisture loss during transportation to external labs. Overall, having in-house protein quantification provides greater control, efficiency, and cost-effectiveness.”

With startups in the alternative protein space constantly tweaking formulations for color, taste, and texture, maintaining protein content throughout the whole process is crucial. “It’s the moneymaker, especially for companies competing for a place on grocery store shelves,” believes Mannix. And that’s where automation can be hugely beneficial. “The beauty of automated features in in-house analysis lies in their efficiency. Imagine loading sample crucibles onto a carousel, adjusting the order remotely, and having the instrument automatically power on, adjust temperature, and even switch off gas flow – all based on a schedule. This eliminates the need for 24/7 staffing. We can simply leave our prepped samples to be analyzed overnight and access the data the next morning.”

R&D bottlenecks

Also appearing as a panelist on the webinar was Priera Panescu Scott, Lead Scientist – Plant Based Specialist at The Good Food Institute, whose role focuses on accelerating the plant-based meat industry through analyzing the entire landscape, identifying emerging technological solutions and bottlenecks, and communicating with other scientists about advancing alternative protein research. But what are some of those bottlenecks? “It depends on the specific protein and product,” she says. “That’s the scientific answer, right? Different projects have different hurdles. But zooming out, there are some common ones. First, there’s a lot of duplicated effort. People reinvent the wheel because information isn’t readily available. I’ve seen grants wasted on methods that already exist elsewhere. Open access to research findings would be a game-changer. Second, collaboration can be a bottleneck. Finding the right partners and utilizing them effectively is a challenge. Finally, commercialization isn’t always considered upfront. Amazing lab breakthroughs can get lost if long-term cost and taste haven’t been factored in. Research needs to bridge the gap between the lab and grocery store.”

Given her day-to-day work, what ideas does Panescu Scott propose to alleviate the pressures? “As a scientist, what really gets me going might sound nerdy – data maintenance! Imagine well-organized databases designed for lab use, fostering collaboration and knowledge sharing. This would eliminate so much duplicated effort, freeing us up for the truly exciting stuff: innovation! We’ve been at this plant-based protein thing for over a decade, yet mass adoption remains elusive. What if we could streamline data management and focus on the next level of breakthroughs?”

Another area to consider is supply chain consolidation. “Why do we have to segment everything so much? We fractionate ingredients, remove water, only to add it back during extrusion! Seems a bit silly, right? Can we develop techniques that bypass these unnecessary steps? Can we go straight from crop to extruder, eliminating the drying and reconstituting stages, a costly and energy-intensive process?”

Standardization

Elementar’s Thomas already touched on standardization of methods. “It might seem restrictive at first, but it’s actually the key that unlocks true flexibility and innovation,” Panescu Scott maintains. “Currently, everyone’s doing things a bit differently, which stifles progress. By standardizing how we analyze protein functionality, digestibility, and characteristics, we can move beyond a narrow focus on individual proteins. Imagine a collaborative effort where we can build on each other’s work, asking, ‘What’s the next level? How can we push the boundaries of innovation together?’ Standardization would be the foundation for groundbreaking discoveries in the alt protein industry.”

But with the emergence of technologies such as advanced fermentation and cell-cultivated meat, standardized methods – essential for consistency and comparison – will need to be adapted or even completely revamped to accommodate these advancements. How big of a hurdle would that be? “Standardization has been a game-changer for dairy, and it’s the missing piece the alternative protein industry desperately needs,” Panescu Scott feels. “But achieving this is not easy. There are two main roadblocks: limited open access to standardized methods – developing them takes time and resources, and some stakeholders want a return on investment, which can be a barrier for startups and smaller labs. Secondly, there’s a lack of collaboration across the industry. Everyone operates in silos. Collaboration and open access to these methods would be immensely beneficial.”

Another major hurdle in plant-based protein development is ingredient batch-to-batch variability. So, how does Panescu Scott see researchers tackling that challenge? “I can’t say enough about high-throughput analysis!” she says. “It allows us to rapidly assess ingredients and adjust processes on the fly. This is crucial because, let’s face it, achieving perfect ingredient consistency can be tough. From an agricultural standpoint, maximizing diversity is key for environmental resilience. We don’t want to rely on just a few plant varieties! So, for me, the ideal solution isn’t ‘fixing’ variability, but rather understanding and accommodating it.”

High-throughput analysis lets us do just that. “We can embrace diverse crops while still producing consistent final products,” the GFI scientist proposes. “Of course, we’ll likely need a two-pronged approach: optimizing our agricultural practices upstream and using high-throughput analysis to adapt our processes downstream. Embracing diversity while achieving consistent quality, that’s the holy grail – and high-throughput analysis is a key weapon in our arsenal.”

The bigger picture

“At the Plant Food Innovation Center, protein analysis is certainly vital, although it’s just the first piece of the puzzle,” says Karthik Pandalaneni, Assistant Director. “We believe composition analysis is the ideal starting point for any investigation, whether we’re looking at a new plant material, body fat, a cake mix, or a protein ingredient. This initial analysis helps us understand the big picture: what exactly are we working with? How much fat, starch, and protein does it contain? Knowing the complete composition allows us to strategically approach the next steps. We can then delve deeper, analyzing how these components interact and synergize within the product. This initial analysis is crucial for guiding our entire development process.”

As far as emerging technologies are concerned, collaborating with Microsoft on AI for plant-based proteins, especially, blew Pandalaneni’s mind. “Initially, I couldn’t imagine how AI could even be applied in food science,” he admits. “But after diving into the project, I was amazed. We have a massive database thanks to our collaborative industry partners. It includes information on various plant protein sources, processing methods, and solvents. This data is being used to train AI, and while we’re still in the early stages, it holds immense promise.”

Ultimately, Pandalaneni says, the goal is to streamline R&D. “Ideally, with a robust AI model, we wouldn’t have to constantly repeat everything from scratch. For example, if you’re evaluating a new ingredient for a beverage, AI could analyze its structure, function, and nutritional profile to recommend which tests are most relevant. This could save time and resources by quickly identifying potential beverage applications with good storage stability, flavor, and sedimentation properties. Building a truly comprehensive AI requires in-depth data analysis, and there’s a lot of work ahead. But the potential benefits are enormous – streamlining methods, shortening development timelines, and maybe even someday enabling rapid field assessment of crops or ingredients.”

Data, data, data

Data, as we know, is the lifeblood of alternative protein product development at the lab scale. “Startups live and die by data, using it to raise capital, progress from lab to pilot scale, and iterate based on observations,” states Michael Spinelli, Founder & Chief Strategy Officer at NewEpoch. “It informs every step, from design and engineering to ensuring the final product’s nutritional integrity.”

A common challenge, though, is how a lab-scale protein’s functionality and nutritional profile translates to large-scale production. “Scaling up involves a complex interplay of process engineering, chemical interventions, thermal processing, and even acid-base chemistry,” Spinelli adds. “Each step can alter the protein’s properties, including hydration state, dehydration state, and overall structure. Data is crucial for tracking the changes and making adjustments.”

And that highlights the importance of strong lab support. “I’ve been fortunate to collaborate with talented analysts and benefit from the work of the Good Food Institute,
which promotes open access to data and information. While alt proteins are a growing field, our understanding of protein science itself remains limited. We need advances in instrumentation, imaging, protein quantitation, and quality assessment methods. By investing in these areas, we can unlock the full potential of alternative proteins.”

And let’s not forget that the data obtained from lab scale processing and analysis is also essential in scaling a process. “It plays a crucial role in translating lab-scale discoveries to pilot-scale systems,” Spinelli reports. “Consider design engineering for unit operations – factors such as vessel construction and pump selection are critical. Proteins can be prone to foaming under high shear stress during wet-stream processing. Lab-scale data on a protein’s structural and functional characteristics, like foaming capacity and stability, is invaluable here. Understanding foaming behavior also helps us select the right pump to prevent undesirable foaming at various stages.”

This extends beyond just foaming, too. “Emulsification is also key,” says Spinelli. “I’ve learned this the hard way – using an anti-foaming agent can create a stable emulsion, but then hinder protein fractionation downstream. This highlights the importance of comprehensive data analysis at the lab scale to avoid such pitfalls when scaling up.”

‍

‍