The nutraceutical industry is evolving, shifting its focus from ingredients to biology. A new approach introduces a computational method to design nutraceuticals targeting specific health issues by prioritizing biological problems over individual components.
The Problem with Population Averages
Traditional nutraceutical development often relies on population averages, assuming that what works for most will work for all. However, the gut microbiome varies significantly between individuals, influenced by factors like diet, geography, and genetics.
A 2025 study in Nature Microbiology highlighted the diverse ways gut bacteria metabolize plant compounds, challenging the one-size-fits-all approach. This variation shows the need for a more personalized strategy in nutraceutical formulation.
A Target-First Approach
The new method starts with a specific biological target, such as a disrupted metabolic pathway or immune mechanism, rather than a particular ingredient. This shift ensures that the formulation addresses the root cause of a health condition.
For instance, in the case of the gut microbiome, the process involves identifying disrupted microbial pathways and insufficient metabolites. The formulation is then tailored to support the production of these necessary molecules, using food-grade inputs.
The gut microbiome’s role in health is increasingly recognized, impacting areas from metabolic health to neurological function. This growing understanding demands a more targeted approach to nutraceutical formulation, one that considers individual biological needs.
Computational Modeling in Action
Computational modeling plays a key role in this new approach. Genome-scale metabolic modeling simulates gut bacteria behavior across thousands of microbiome profiles, identifying disrupted pathways and potential food-grade compounds for intervention.
An AI retrosynthesis engine further refines this process, working backward from the biological target to identify the most efficient set of precursors. This ensures each ingredient has a clear, defined role in the formulation.
At Enbiosis, this method is applied by creating a digital twin of the gut microbiome for a specific health condition. Simulations across diverse microbiome profiles result in a formulation tailored to the condition’s unique biology.
While computational modeling is powerful, it does not replace the need for clinical evidence. The first formulation developed using this approach targets dry eye, a condition linked to gut microbiome composition.
A prospective pilot study of a food-grade oral formulation targeting the gut–eye axis demonstrated meaningful changes across multiple clinical endpoints, including tear production and patient-reported symptom scores. Participants took the formulation once daily for eight weeks, with effects maintained through a follow-up assessment at week sixteen. A randomized controlled trial is currently underway. (Article submitted for peer review)
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This method is not limited to dry eye. Its applications extend to various health areas, including metabolic health, skin conditions, and neurological health, where the gut microbiome plays a significant role.
The approach offers a systematic way to develop formulations across different health domains, grounded in the same biological and computational principles.
For conditions influenced by the gut microbiome, the question is whether the formulation reflects the underlying biology.
The science of the gut microbiome is advancing rapidly, and the gap between biological understanding and formulation design is becoming more apparent. A target-first approach, supported by computational modeling and clinical research, is becoming practical.
Personalized Formulations Based on Biological Targets
The process begins by identifying a specific health condition and creating a digital twin of the associated gut microbiome. This model simulates the unique biological environment of the condition, moving beyond population averages.
Formulations are then developed to target the specific biological needs identified, using food-grade inputs. This ensures the product is tailored to address the root cause of the health issue, rather than a generalized approach.
The Shift from Ingredient to Biology
Traditional nutraceutical development often begins with an ingredient, assuming its efficacy without full establishment. This has led to products with uncertain effectiveness and limited scientific evidence.
Applications Across Health Domains
The computational modeling approach extends to various health areas where the gut microbiome is significant.
In metabolic health, it targets insulin resistance and glycaemic regulation. For skin conditions like psoriasis, research explores the gut-skin axis for tailored solutions. In neurological health, the approach examines the link between microbial composition and cognitive function.
The authors of this approach are from Enbiosis Biotechnology, a company leading the development of microbiome-targeted nutraceutical formulations.
