The nutraceutical industry is evolving. A new approach to formulation is emerging, one that prioritizes biology over ingredients. This shift, driven by advancements in computational modeling and a deeper understanding of the gut microbiome, promises to address the limitations of traditional methods.
The Problem with Population Averages
Historically, nutraceutical development has relied on identifying promising ingredients and testing their efficacy. However, this approach often overlooks the individual variability of the gut microbiome. A 2025 study in Nature Microbiology highlighted the significant differences in how individuals metabolize plant compounds, showing the need for a more personalized approach.
The gut microbiome’s role in metabolic health, immune function, and neurological processes is now well-established. This complexity demands a formulation strategy that targets specific biological pathways rather than relying on population averages.
A Target-First Approach
The new methodology begins with identifying disrupted biological targets associated with specific health conditions. For instance, in the case of dry eye, the focus is on the gut-eye axis and its impact on tear film dysfunction.
Computational models, such as genome-scale metabolic simulations, are employed to analyze thousands of microbiome profiles. These models pinpoint metabolic pathways and food-grade compounds that can address the identified disruptions. AI retrosynthesis then identifies the optimal ingredients to achieve the desired biological effect.
This process ensures that each ingredient serves a defined purpose, backed by computational evidence, before clinical trials even begin.
At Enbiosis, this approach is exemplified through the creation of digital twins of the gut microbiome for specific health conditions. Simulations across diverse microbiome profiles guide the development of formulations tailored to individual biological needs.
A pilot study on a dry eye formulation demonstrated significant improvements in tear production and patient-reported symptoms. This success, currently under randomized controlled trial, highlights the potential of this target-first strategy.
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The implications extend beyond dry eye. This framework is applicable to various health areas, including metabolic health, skin conditions, and neurological function, where the gut microbiome plays a key role.
For the nutraceutical industry, this shift means a higher bar for formulation. It’s no longer sufficient to rely on ingredient-based approaches. The focus must be on biological targets, validated through computational modeling and clinical evidence.
The Role of Computational Modeling
Computational modeling is at the heart of this new approach.
This process involves creating a digital twin of the gut microbiome for a specific health condition. Simulations are then run across diverse microbiome profiles to develop a formulation tailored to the biology of that condition, rather than relying on population averages.
For instance, in the case of metabolic health, the focus is on identifying microbial pathways linked to insulin resistance and glycaemic regulation. The computational models help pinpoint the exact food-grade inputs needed to support the production of insufficient metabolites.
An AI retrosynthesis engine further refines this process by working backward from the biological target to identify the smallest set of food-grade precursors required.
Expanding Applications and Industry Impact
As the first formulation developed through this engine reaches the market, it marks the beginning of a new era in nutraceutical formulation—one that prioritizes biology over ingredients and evidence over assumption.