By: Casey L. Bradley, Ph.D. - February 19th, 2026; President and Founder of Animistic
Formulation has long been a core competency at Animistic and foundational to the career of our founder, Dr. Casey L. Bradley. Across 25 years spanning animal production, academic research, animal feed manufacturing, and product innovation, one pattern has remained consistent.
As Dr. Bradley observes,
“When formulation is treated as a math problem, the system eventually exposes the gaps.”
Many individuals and companies approach formulation as a matter of arithmetic. Adjust the protein. Balance the lysine. Optimize the cost. Meet the specification.
Arithmetic solves the immediate equation.
But arithmetic doesn’t scale.
Architecture does.
Animal feed manufacturing is where weak formulation structure gets exposed first.
True formulation is not the starting point of a product. It is the structural expression of decisions made long before ingredients are ever entered into a matrix. When formulation becomes the first step, innovation becomes reactive. When formulation is the final structural layer of a well-designed system, innovation becomes intentional.
Within this insight, we outline our approach to formulation as architecture—exploring how weak structure creates downstream complexity, how oversimplification limits strategic flexibility, and how intentional design protects both performance and brand integrity.
Many formulation platforms were built on linear programming models, often using the Simplex Method to identify an optimal solution. The arithmetic goal is clear: minimize the total cost of ingredients—the objective function—while meeting defined constraints. The user inputs minimum and maximum nutrient specifications, ingredient availability, and inclusion limits. Once the “formulate” button is pressed, linear algebra determines the least-cost solution within those boundaries.
Modern software has evolved. Today’s systems may monitor ingredient availability, forecast usage, integrate with production scheduling, and even track sustainability metrics or projected animal outcomes.
Yet despite these advancements, the core logic remains linear.
Animals are not.
Formulation does not operate within a static equation. It operates within biological and manufacturing systems—dynamic environments that expose structural assumptions linear models cannot anticipate.
Linear models assume additive effects. Living systems exhibit interactive effects.
Choline chloride illustrates this clearly. Choline is required across species, and typical feedstuffs rarely supply sufficient levels to meet physiological demand. From a formulation perspective, it is an efficient correction to a nutrient gap. Yet its chemical properties complicate the system. Choline chloride is hygroscopic and corrosive, accelerating the degradation of fat-soluble vitamins A, E, and K when included in vitamin–trace mineral premixes (Singh et al., 2010). What appears biologically necessary can, if structurally misplaced, reduce shelf life, compromise nutrient stability, and introduce manufacturing risk.
Biology supports its inclusion. Architecture determines where and how it belongs.
Energy metabolism provides an even more integrated example. A swine diet can be formulated to 3,000 kcal/kg of gross or metabolizable energy using conventional ingredients without supplemental fat. On paper, the requirement is met. Yet net energy availability may diverge significantly once fiber fractions, fermentation dynamics, and heat increment are considered. The biological response is not purely caloric—it is hormonal, microbial, and behavioral.
Dietary fat has been shown to stimulate peptide YY (PYY), a gut-derived hormone associated with satiety signaling (Adrian et al., 1985; Batterham et al., 2006). But fat is not the only architectural lever influencing this pathway. The use of xylanase, by increasing arabinoxylan degradation and short-chain fatty acid production, may also alter satiety signaling through microbial fermentation pathways (Tolhurst et al., 2012). Two different formulation decisions—one altering lipid density, the other modifying carbohydrate structure—can influence similar physiological signals through entirely different mechanisms.
Insoluble fiber fractions further complicate the system by affecting gut fill, gastric emptying, and voluntary intake. Formulating for a commercial finisher pig differs materially from formulating for a show pig or a companion animal. In some markets, stool structure becomes a proxy for digestive performance and product quality. The biological endpoint is not identical across contexts, even when nutrient targets appear similar.
Immune status adds another layer. Nutrient partitioning shifts when animals are challenged. Research in swine nutrition has shown that pigs experiencing immune activation, including PRRS infection, often respond differently to dietary protein structure than healthy pigs. Work by Boyd and Greiner (2012) suggests that immune-challenged pigs may benefit from higher soybean meal inclusion, whereas healthy pigs can often perform efficiently on lower crude protein, crystalline amino acid–fortified diets. The “optimal” formula is therefore not fixed—it is conditional on physiological state.
The linear model identifies a least-cost solution under static constraints. The living system continuously redefines those constraints.
Linear formulation assumes stable inputs. Living systems operate within variability.
Ingredient nutrient profiles are often treated as static values within formulation matrices. In practice, they are dynamic. Moisture shifts. Protein varies by growing region and season. Mycotoxin burden fluctuates. Fat oxidizes in storage. Even global supply chains introduce systemic uncertainty—as illustrated when the BASF vitamin A precursor plant experienced an explosion in July 2024, disrupting availability and pricing across markets. Formulation architecture must anticipate disruption, not assume continuity.
Corn provides a clear example of why formulation architecture must anticipate variability. The three largest global producers—the United States, Argentina, and Brazil—do not produce nutritionally identical grain. In a controlled broiler study where diets differed only by corn origin, Vargas et al. (2023) reported no significant differences in body weight, body weight gain, or feed intake from 1 to 35 days of age. However, feed conversion ratio (FCR) differed meaningfully. Broilers fed diets containing corn from Argentina exhibited a higher FCR (1.452 g:g) compared to those fed corn from the United States or Brazil (1.434 g:g; p = 0.002)
The compositional differences help explain the divergence. Corn from the United States contained higher starch content, whereas Brazilian corn contained higher fat and total fatty acid concentrations. Additionally, phosphorus, calcium, and potassium digestibility differed by origin.
On paper, “corn” is a single input. In biological systems, origin alters chemical composition, digestibility, and feed efficiency—even when diets are formulated to identical nutrient specifications.
Uncertainty also resides within animal feed manufacturing systems. Mixing uniformity is not guaranteed. Inclusion sequence matters. This is a feed mill process reality, not a spreadsheet problem. A 0.01% feed additive cannot be effectively dispersed if added prematurely to a mixer dominated by 70% grain inclusion. Mixer type and residence time influence coefficient of variation (CV), with paddle mixers often requiring approximately three minutes for adequate mixing compared to 0.75–1 minute for double shaft ribbon mixers (Kansas State University, 2016). Architecture must account for equipment capability.
Premix design therefore becomes contextual. A premix built for a 1920-era mill with limited mixing precision cannot mirror one designed for a 2025 automated facility with advanced batching control. Inclusion rates, particle size, and dispersion strategy must reflect manufacturing reality.
Even software integration introduces risk. If formulation architecture is misaligned with batching and production systems, nutrient variation may occur from bite to bite. The matrix may be precise. The delivery may not be.
Variability is not a flaw in the system. It is the condition under which the system must operate.
Strong architecture anticipates it. Weak architecture assumes it away.
Beyond biological interaction and ingredient variability, time itself introduces architectural pressure.
Nutrient requirements are not static. They evolve continuously across the lifespan of a living organism—whether in meat production systems or companion animals.
Each incremental change in body weight alters maintenance demand. Growth shifts amino acid requirements. Reproductive status redirects mineral and energy partitioning. Immune activation diverts nutrients toward survival rather than performance. What is “optimal” at 25 kilograms is not optimal at 125 kilograms. What supports rapid growth may not support longevity.
Precision nutrition technologies continue to advance, yet formulation remains a population-level exercise. Even the most sophisticated systems cannot tailor each meal to each individual animal in real time. Architecture must therefore account for biological drift across life stage and health status rather than assuming static requirement models.
Context sensitivity extends beyond physiology and into risk management. A swine diet and a sheep diet may be manufactured in the same facility within hours of each other. High copper sulfate inclusion rates that support swine performance can pose severe toxicity risks to sheep if cross-contamination occurs. Formulation architecture must integrate species-specific risk tolerance and sequencing protocols into manufacturing design.
Physical form introduces another architectural layer. Coarse versus finely ground corn alters digestibility and gastric integrity. Mash and pelleted diets behave differently in feeders and within the gastrointestinal tract. Ingredient bin identification and sequencing errors can shift the nutritional outcome of an otherwise precise formulation. A laying hen and a finishing pig may both require energy and protein—but their physiological objectives and digestive dynamics differ fundamentally.
Market context adds further complexity. Ingredient sourcing for companion animals often carries higher quality standards, traceability expectations, and in some cases human-grade positioning. Pricing sensitivity, consumer perception, and product form become architectural constraints alongside biological requirements. A formulation built for livestock performance cannot simply be translated into the pet space without structural reconsideration.
Life stage, species, manufacturing flow, and market expectation all redefine the boundaries within which formulation must operate.
Architecture is not merely about meeting nutrient targets. It is about designing within biological, operational, and contextual realities simultaneously.
Complexity is inevitable. Fragility is not.
Before a single ingredient is entered into a matrix, decisions have already been made that shape what formulation can—and cannot—become.
Every nutritionist understands the disruption that occurs when formulation software changes, whether through executive decision or organizational transition. The discomfort is not merely technical. It reveals something deeper: formulation systems encode philosophy. The structure of the software reflects assumptions about precision, speed, risk tolerance, and operational constraints.
A consulting nutritionist formulating for ten producers across five feed mills operates within a fundamentally different architecture than a nutritionist managing swine diets from a single facility. A company like Animistic, formulating across species—from pigs to geckos—must design systems that accommodate biological diversity, manufacturing variability, and differing market expectations simultaneously.
Philosophy becomes operational reality.
In one mill, optimizing a precise tryptophan-to-lysine ratio by including 0.13 kilograms of L-tryptophan may be viewed as a mark of nutritional rigor. In another facility, where ingredient bins are fixed and labor efficiency is prioritized, hand-adding micro-inclusions disrupts throughput and increases error risk. The formulation may be biologically elegant yet operationally misaligned.
Architecture precedes ingredients.
Consider facility design. A feed mill engineered for cattle feed manufacturing and beef feedlot diets operates under different physical and process constraints than one producing extruded dog food. Storage capacity, ingredient bin configuration, scale sensitivity, grinding systems, pelleting versus extrusion capabilities—all shape what formulations are feasible. Attempting to overlay a new product category onto a facility not designed for it exposes architectural limits.
Labor structure is equally influential. If a mill is optimized to operate with six employees and two are absent due to extended leave, formulation complexity may need to adjust. Ingredient handling steps, batching precision, and sequencing protocols must reflect human capacity. Architecture is not only mechanical; it is organizational.
Formulation is therefore not the starting point of product development. It is the downstream expression of strategic, operational, and philosophical decisions made upstream.
When architecture is intentional, formulation becomes powerful.
When architecture is assumed, formulation becomes constrained.
Paper tolerates precision. Steel does not.
A formulation can meet every nutrient specification, satisfy the objective function, and align with biological targets—yet fail the moment it enters the physical world. Animal feed manufacturing is where assumption meets consequence. It is where chemistry, physics, moisture, temperature, and time exert pressure on theoretical precision.
Early in her career, Dr. Casey L. Bradley experienced this intersection firsthand.
In an effort to lower feed costs and capture value for both the customer and the pigs, she incorporated an opportunity ingredient into a swine diet. On paper, the decision was defensible. Nutrient specifications were met. Economic targets improved. The formulation aligned with performance objectives.
But chemistry was quietly at work.
The interaction between sugar or lactose levels and the hygroscopic nature of the base mix created a physical instability that had not been fully anticipated. The product did not behave as expected during manufacturing and delivery. What looked precise in the matrix proved fragile in the system.
The phone calls came—first from the mill, then from leadership.
Rather than withdraw support, Paul Kalmbach, Mill Manager Jerry, and customer Jim Heimerl leaned in. They recognized the intent behind the decision: to do what was right for the pigs and the customer. They did not abandon the experiment. They examined it.
That moment became formative.
The formulation was not biologically incorrect. The economic logic was sound. But the architecture was incomplete. Moisture dynamics, ingredient chemistry, and physical flow characteristics had not been integrated fully into the decision framework.
Manufacturing is not a passive conduit for formulation. It is an active variable. Hygroscopic ingredients alter bulk density and flowability. Sugars and lactose shift moisture equilibrium and caking risk. Particle size influences segregation and uniformity. Thermal processing changes starch structure and nutrient availability. These feed processing techniques shape outcomes as much as the nutrient matrix. The system responds to chemistry whether the matrix anticipates it or not.
Gravity enforces discipline.
Since that experience, manufacturing feasibility has never been treated as a downstream check. It is an upstream architectural consideration. Ingredient chemistry, moisture behavior, equipment capability, and delivery logistics are evaluated before optimization is complete.
Formulation that cannot survive manufacturing is not precision.
It is theory.
Architecture anticipates gravity.
Formulation architecture does not begin with ideal inputs. It begins with reality.
Ingredient matrices assume representative values. Markets deliver variability.
The Vargas et al. (2023) study provides a controlled example. When broiler diets were formulated identically except for corn origin, growth rate did not differ significantly. Yet feed conversion ratio shifted measurably, with Argentine-origin corn producing a higher FCR compared to U.S. and Brazilian corn. Digestibility of phosphorus, calcium, and potassium also differed among origins.
These were not formulation errors. They were input differences.
In commercial systems, variability compounds through genetic background, agronomic conditions, drying temperature, storage duration, kernel hardness, lipid oxidation, and mycotoxin burden. Formulating on average nutrient values assumes consistency across batches. Production economics expose that assumption quickly.
Poor inputs do not always produce visible failure. More often, they produce silent inefficiency:
Each adjustment carries cost.
Palatability introduces an additional, often underestimated variable. While broilers have limited taste receptor complexity compared to companion animals, feed aroma, fat oxidation, ingredient freshness, and physical texture still influence intake behavior. In high-value companion animals—such as a prize-winning detection dog with an enhanced olfactory capacity—the tolerance for ingredient inconsistency narrows dramatically. Oxidized fats, inconsistent protein sources, or subtle flavor shifts may not alter nutrient specifications on paper, yet they can alter voluntary intake, owner perception, and product loyalty.
The matrix may meet specifications. The animal—and the market—still decide.
Weak architecture absorbs input variability reactively. Strong architecture anticipates it—through tighter ingredient specifications, oxidation monitoring, supplier qualification, near-infrared validation, and structured substitution protocols.
The true cost of poor inputs is not merely performance drift. It is an architectural strain across biology, manufacturing, and consumer trust.
Weak architecture rarely fails immediately. It erodes gradually.
At small scale, inconsistencies are absorbed. A reformulation here. A customer call there. A minor production adjustment. The system compensates.
At scale, compensation becomes exposure.
Customer loyalty is often the first silent casualty. In livestock feed manufacturing, incremental performance drift—slightly higher FCR, marginal carcass inconsistency, uneven pellet durability—reduces confidence. In companion animal markets, inconsistency in palatability, stool quality, coat condition, or product form is interpreted not as biological variability, but as brand instability. Margin erosion becomes trust erosion.
Animal performance follows. Weak architecture amplifies variability across batches and facilities. The same formula, executed under slightly different conditions, produces different outcomes. Nutrition becomes reactive rather than predictive.
Product form becomes vulnerable. Flowability issues, segregation, moisture instability, fat oxidation, pellet durability decline, extrusion inconsistency—each reflects architecture that did not fully integrate chemistry and process capability. Manufacturing absorbs strain until it cannot.
Employees feel it as well.
When systems lack structure, technical teams operate in crisis cycles. Reformulation requests increase. Customer complaints accelerate. Quality control intensifies. Talented employees become firefighters rather than architects. Over time, engagement declines and institutional knowledge leaves with them.
The most severe consequences emerge when architecture intersects with regulation.
In regulated industries, weak structural controls around ingredient sourcing, species segregation, labeling accuracy, or nutrient claims can trigger stop-sale orders, recalls, financial penalties, and in extreme cases, criminal liability. Regulatory action is rarely the result of a single formulation miscalculation. It is the cumulative exposure of architectural blind spots.
Scale does not create weakness.
Scale reveals architecture.
Strong architecture creates consistency across facilities, teams, markets, and time. Weak architecture multiplies variability until it becomes visible.
Architecture is not a theoretical exercise. It is a safeguard for performance, people, and reputation.
Architecture is not built in theory. It is built through deliberate decisions—often long before ingredients are entered into a formulation system.
Whether you are formulating diets, leading a technical team, or scaling an organization, formulation architecture shapes both your risk profile and your future opportunity.
Examine your decision logic, not just your nutrient matrix.
Document the assumptions behind your formulations. What variability are you accounting for? What manufacturing constraints are implicit? What biological states are assumed? Can your formula tolerate substitution, ingredient drift, moisture fluctuation, or shifts in life-stage demand without structural collapse?
Precision is not achieved when the software produces an optimal solution. It is achieved when the solution performs consistently under real-world biological and manufacturing conditions.
Architecture begins with disciplined foresight.
Ensure that formulation philosophy is documented and transferable.
When architecture exists only in the mind of a single nutritionist, variability becomes inevitable. Align procurement, quality control, manufacturing, and nutrition under shared architectural principles. Define ingredient specifications intentionally. Integrate monitoring systems that detect drift before performance exposes it.
Ask whether your team is reacting to variability—or anticipating it.
Strong architecture reduces crisis cycles. It frees technical talent to innovate rather than constantly troubleshoot.
Assess whether your formulation architecture expands optionality—or constrains it.
As product lines grow, facilities expand, or markets diversify, weak architecture multiplies complexity. Strong architecture enables disciplined growth. It protects customer trust, supports employee stability, and reduces regulatory exposure.
At scale, formulation is no longer a technical function alone. It becomes fiduciary responsibility.
Architecture is not a cost center. It is risk mitigation, brand protection, and strategic leverage.
Strategic Reflection
Formulation determines more than nutrient compliance.
It determines whether innovation is reactive or intentional.
It determines whether variability erodes margin or is absorbed gracefully.
It determines whether scale strengthens the system—or exposes it.
The question is not whether your formulas meet today’s specifications.
The question is:
What does your formulation architecture enable long-term?
