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Artificial intelligence is transforming what is possible in agriculture, but industry leaders should be wary of investing in AI without first laying the groundwork.
The use cases are promising, especially for an industry navigating volatile fertilizer costs, unpredictable weather, and margins that leave little room for error. Research shows AI-enabled predictive models can improve crop yield by 26%, reduce water use by 41%, and cut chemical usage by 33%.
However, what AI vendors usually won’t tell you is that these solutions are only effective if you have a clean, solid data foundation. However, at Reltio, we have experience in this area, including leading technology strategy at a major agricultural distributor and building a data platform used by enterprises worldwide–we’ve seen it first hand.
Vendor conversations in agriculture tend to follow a familiar pattern. The pitch leads with grand promises around using AI to monitor crop health in real time, optimize irrigation, and squeeze more yield from every acre.
The promise is compelling, but what rarely comes up is the question of whether the data foundation underneath those promises is accurate and complete. If not, there is a real and significant risk that AI will generate misleading outputs that seem authoritative but inspire action that is, at best, counterproductive.
For instance, a yield prediction model fed inconsistent historical data will generate imprecise forecasts. Similarly, a precision irrigation system drawing on fragmented sensor data will make watering decisions that waste resources instead of saving them.
In each case, the AI is failing because the data it was trained on was not sufficient to produce trustworthy outputs. In agriculture, every AI hallucination is a liability, and the likelihood of error is high.
The data landscape across a modern agricultural operation or a large distributor serving thousands of growers is extraordinarily complex.
Modern farming environments make extensive use of IoT devices and machinery. Irrigation systems are automated, tractors navigate fields autonomously, and drones capture field imagery at scale.
However, machine data is disparate by nature. Add in external sources, including weather feeds, U.S. Department of Agriculture data, and third-party market information, and the question of how you bring all of it together into something coherent becomes a significant undertaking.
Agricultural AI also needs to understand more than just customer attributes; it needs to understand the land: GPS coordinates, farm boundaries, field blocks, and soil variation across a single property. Where do you apply fertilizer, and at what rate, and in which specific area of the farm? Not all parts of a field are the same, and an AI system that treats them as if they are will produce recommendations that are at best imprecise and at worst damaging.
There is also a compliance dimension due to the chemicals and the responsibility involved. Operational AI in agriculture needs significantly more checks and governance than it might in a lower-stakes environment. When a flawed recommendation gets acted upon in the field, the consequences can be severe.
Data readiness is the difference between AI delivering on its promise vs. a “garbage in, garbage out” scenario. Fundamentally, being ready for AI means having a data model that accurately reflects how the business operates.
For a company like Wilbur-Ellis, a 104-year-old, family-owned agricultural distributor, that means understanding who your customers are, which fields they farm, which inputs they need, which suppliers those inputs come from, what they paid last season, and how all of that connects to margin. That information needs to be current, consistent, and accessible across the organization, rather than locked in separate systems that were never designed to talk to each other.
Similarly, for farming operations themselves, data readiness means having a reliable, connected picture of what is happening across every field: soil health records, input application histories, yield data from previous seasons, equipment performance, and real-time sensor readings from irrigation systems.
Governance matters just as much as structure. Prices change, relationships evolve, and suppliers come and go. An AI system drawing on data that was accurate six months ago but has not been maintained will make recommendations based on a version of the business that no longer exists.
The good news is that the path to data readiness is feasible. It starts with a strong data model: a single, governed source of truth that connects customers, suppliers, products, pricing, orders, and margins in a way that reflects how the organization operates.
From there, it requires data pipelines fast enough to deliver insights when decisions need to be made, governance frameworks that keep that data trustworthy over time, and security controls that ensure sensitive commercial information is accessible to the right people under the right conditions.
This is precisely the challenge that Reltio, an SAP company, was built to solve. Reltio enables companies to unify their fragmented data so AI agents and systems can operate from a complete picture of the business. Reltio builds a trusted system of context, known as the context intelligence layer, that brings all entities, relationships, rules together under one roof and makes business data easy to access and interpret.
For Wilbur-Ellis, building that trustworthy data foundation has meant being able to ask more complex questions and trust the answers, which is the precondition for any AI system to be genuinely useful.
The question worth asking before the next AI conversation is not whether the use case is promising. It almost certainly is. The question is whether the underlying data foundation is strong enough to make the output trustworthy.
Agriculture has always required its leaders to make high-stakes decisions under uncertainty, and AI offers the genuine prospect of making those decisions faster and better informed. That prospect is only achievable for organizations that have done the foundational work first, and the businesses that will get the most from AI are the ones investing in that foundation now.
This content was produced by Reltio. It was not written by MIT Technology Review’s editorial staff.
Having higher levels of vitamins A and D in the body could help improve lung function in adults with asthma, suggests research led by Brigham and Women’s Hospital in Boston.
The study, published in the journal Thorax, also showed that higher vitamin A levels could also benefit lung health in children with asthma.
“Vitamins A and D are key regulators of gene expression involved in lung development and immune function…Both vitamins have complex roles in asthma and lung function,” write lead author Michael McGeachie, PhD, assistant professor at Brigham and Women’s Hospital, and colleagues.
“Vitamin A deficiency is more common in people with asthma and is linked to airway hyperresponsiveness. Moderate intake in childhood may improve lung function and reduce asthma risk, whereas excessive intake may increase adult-onset asthma risk. Vitamin D deficiency is associated with poorer lung function, increased exacerbations and worse disease control, although results are variable due to diet, age and sun exposure.”
In this study, the researchers evaluated data from two asthma study cohorts—the Genetic Epidemiology of Asthma in Costa Rica Study including 1,165 children with asthma and the adult Omic Determinants of Longitudinal Lung Function in Asthma cohort including 1,041 adults with the condition.
The researchers looked at both circulating vitamin A and D in both groups and also looked at links with epigenetic regulation.
In children, there were no significant links between lung function and vitamin D levels. Higher vitamin A levels were linked to better breathing capacity though. For each step up in vitamin A levels, the amount of air the children could blow out in the first second was about 2.5 percentage points higher, and the total amount of air they could breathe out was about 7.6 percentage points higher.
In the adults, one step up in vitamin A levels was linked to a 4.7 unit increase in the amount of air they could blow out in the first second and a 3.4 unit increase in the total amount of air they could breathe out. The effect of vitamin D levels in this group was smaller, but statistically significant, with lung function improvements between 0.16-0.18 units per step up in vitamin D levels.
The researchers also looked at DNA methylation and at several epigenetic clocks that estimate a person’s biological age from methylation patterns in the adult cohort. They found that adults with higher vitamin A and vitamin D levels had fewer methylation tags at key control sites in the IRF5 gene than those with lower levels and showed changes in small regulatory micro RNAs that respond to vitamin levels. These epigenetic changes were linked to better lung function and slower biological aging.
The epigenetic tests suggest that vitamins influence lung function and aging partly by producing these epigenetic changes, rather than only through a direct effect, according to the researchers.
“While future studies to replicate these findings in independent populations are needed to confirm the generalizability and robustness of these observations,” write Sze Man Tse, MD, and Geneviève Mailhot, PhD, of the CHU Sainte-Justine Research Center, Montreal, and the University of Montreal in an accompanying editorial in the same journal, “subsequent interventional studies examining the impact of vitamin supplementation on biological ageing and on IRF5 function will be particularly relevant.”
The post Vitamins A and D Help Improve Lung Function in People with Asthma appeared first on Inside Precision Medicine.
Cytiva has completed an expansion of its Logan, UT, facility that effectively doubles its liquid media production capacity, a project designed to support supply chain continuity for customers relying on the company for their cell culture needs.
The company has completed its animal-derived component-free (ADCF) liquid media expansion facility (A1X), Pierre-Alain Ruffieux, Cytiva group executive, bioprocess, told GEN in an interview conducted from the company’s booth during the Biotechnology Innovation Organization (BIO) International Convention recently held in San Diego. He said the completion was celebrated with a ceremony on the site.
Cytiva detailed the expansion project in a May 12 post on its website: The ADCF liquid media expansion facility (A1X) has larger mixing tanks than the existing facility, supporting batch sizes from 700 L up to 13,000 L—compared with batch sizes of 100 L to 10,000 L supported by Cytiva’s existing facility.
Also, the A1X facility uses mixing tanks and liquid media transfer lines comprised of AL6XN and 316 L stainless steel. This differs from the existing facility equipment, which is comprised solely of 316 L stainless steel. AL6XN is a low-carbon, high-purity stainless-steel alloy that is more resistant to wear and corrosion than 316 L, representing an upgrade to the product contact layer versus the existing facility equipment.
The expanded site’s added liquid capacity comes from the addition of three manifold fill lines, three filling manifolds, six mixing tanks, six formulation booths, and a utility building to support large volume liquid media production. Housed in the utility building are a 45,000 L tank and process water system, a 55,000 L tank and water for injection system, a clean steam generator, and additional supporting utilities.
“In addition to the added capacity, Cytiva has updated several aspects of the manufacturing floor layout and equipment, improvements designed to shorten production cycle time, improve safety, and minimize product risk,” the company explained. “The updates also establish closed systems for cleaning and a controlled environment for the transport and handling of raw materials and finished goods.”
Previously, Cytiva completed expanding its dry powder and liquid media manufacturing capacity for large-volume customers and added high-speed bottle filling for smaller-volume users. The company also opened an expanded staging area for finished goods, as well as a new centralized 10,000-square-foot quality control lab to support increased manufacturing.
During a wide-ranging interview, Ruffieux discussed Cytiva’s approach to AI and several recent Cytiva announcements.
“We see two major impacts from AI on what we are doing,” Ruffieux explained. “The first one, and I always like to start with the customers because it’s really our focus: We see our customers accelerating and increasing the number of targets they are doing. AI is helping them to have more targets and in a faster time,” Ruffieux said. “It’s putting pressure on the CMC folks, and I think it’s where we play: They ask us to provide innovative solutions to go faster.”
Cytiva’s focus on AI is two-fold, he continued.
“One, we are developing intelligent equipment which is using AI to be easier for customers to use and which are more functional; that is one aspect. It’s also delivering more experience in a shorter time frame,” Ruffieux said. “It’s a kind of next level of DoE [design of experiments], but it’s also delivering a productivity aspect because the goal is to have equipment which requires either fewer people or fewer people with less specific knowledge of the equipment.”
Like a growing number of companies in and outside biopharma, Ruffieux said, Cytiva has fully embraced AI “to make our product better, to make the customer experience better, but also to improve our internal processes.”
“We see AI helping us to develop software, writing new software to go faster and better. AI is very powerful for reviewing documents and doing things,” he explained. “It’s amazing what we can do both in writing code, but also perhaps as importantly, as we validate the code and we test everything, the use of AI is allowing our people to work in a much more comprehensive way, in a much faster way.”
AI also adds a layer, he said, to the continuous improvement ethos that Cytiva and other Danaher-owned companies practice through the Danaher Business System (DBS). Since the mid-1980s, Danaher has carried out an ongoing company-wide Kaizen or continuous improvement effort based on lean manufacturing and anchored on DBS, a common culture and operating system focused on people, plans, processes, and performance.
“AI is an additional pillar to this system, really helping the company to be more efficient and to drive business,” Ruffieux said.
Cytiva’s customers, he continued, have not specifically asked about AI. So what are customers telling the company that they want?
“What customers want is Cytiva delivering solutions which help them to innovate, produce drugs, and accelerate these processes. And AI is one of the attributes, but they don’t have a specific task on AI,” Ruffieux replied. “In discussing with senior customers, people are interested in the outcome, not in the product itself. So it’s not AI for AI, it’s AI for a business outcome. And in life science, the business outcome is quality. It’s reliability. It’s speed. It’s customers asking, can we help them to be better?”
Last month, Cytiva hailed the FDA’s granting its Advanced Manufacturing Technology (AMT) designation to the company for its Elevecta
transient cell line for adeno-associated virus (AAV) manufacturing, one of the first gene therapy manufacturing technologies to receive the designation. Customers using the Elevecta transient cell line will benefit, according to Cytiva, from a clear, predictable regulatory and quality framework for gene therapy development.
Through its AMT designation, the FDA recognizes drug manufacturing technologies that it deems to have elevated the reliability, quality, and robustness of advanced therapeutics manufacturing. By enabling a streamlined Chemistry, Manufacturing, and Controls (CMC) review and frequent communication with the FDA, designees count on the AMT designation to help accelerate their manufacturing-related development timelines and create a meaningful advantage through faster time to market.
“This recognition by the FDA is giving confidence and trust for our customers: If they use this cell line to produce AAV, they know that the agency has seen the technical advantage and it’s confidence on the regulatory pathway,” Ruffieux said. “This recognition by that regulatory body is giving trust to the work of the company in helping customers develop drugs, which is really where we position ourselves as true partners.”
Elevecta is designed to significantly reduce the formation and encapsidation of host cell DNA (hcDNA).
“What is beautiful with that is, we get a reduction of 99% of the host cell DNA. You don’t have to worry any more about the host cell DNA which is coming with your product. Again, that is a huge advantage for the customer using that,” Ruffieux said. “This is the kind of innovation we are really proud to bring to our customers.”
Operating from hubs in Marlborough, MA, Amersham, U.K., Uppsala, Sweden, and Shanghai, Cytiva is a unit of Danaher that was re-launched in 2020 after Danaher spent $21.4 billion for the former biopharma business of GE Healthcare Life Sciences. Danaher oversees a global family of more than 20 operating companies focused on biotech and life sciences, as well as diagnostics, water quality, and product identification.
Earlier this month, the company said that eight of its 2,000 L single-use Xcellerex bioreactors were among equipment contained in the new GMP-2 manufacturing facility inaugurated in Wuhan, China, by Chime Biologics, a decade-long customer that has used equipment made by Cytiva and its predecessor company.
“I want to put that in a larger context: At Cytiva, we really bring to the customers the entire workflow, which is really exciting for small to mid-sized customers. Coming to us, they really get a full facility that is working, really, from A−Z,” Ruffieux said. “It’s starting from an expansion of the cell line, to freezing the drug substance. It’s about a fully integrated solution that helps the customer to have that. And we have multiple facilities like that, that we are building every year for customers across the world.”
“We make significant investments to be able to supply our customers with what they need into different regions, in-region-for-region,” Ruffieux said.
In-region-for-region refers to Cytiva’s ongoing effort to satisfy customer demand for manufacturing tools and services usable within their regions of the world.
“This is really helping us and the customer to secure supply independent of any disruption,” he added. “Since COVID-19, we have seen multiple disruptions worldwide. And really, our original presence is giving confidence to customers that they will get what they need, independent of whatever crisis is happening across the world.”
Worldwide, the United States and European Union have championed “reshoring” efforts by drug developers and tools/technology providers across biopharma to manufacture more of their products within their regions rather than in China or elsewhere in Asia.
“When there is investment, it’s definitely always a tailwind,” Ruffieux said. “We welcome investment, and we are happy to support all customers to put up new facilities, and for the opportunity these facilities offer to position our equipment.”
The post Cytiva Completes Doubling of Utah Site’s Liquid Media Production Capacity appeared first on GEN – Genetic Engineering and Biotechnology News.