Using AI-powered digital twin microbiome modeling, Enbiosis develops targeted nutraceutical formulations supporting a broad range of health areas from cognitive function to skin and eye health.
Billions of people live with chronic health conditions inadequately addressed by existing solutions. Pharmaceuticals can be effective but frequently fail to address the underlying metabolic drivers of disease, and often carry significant side effect profiles. Traditional supplements, meanwhile, have relied on a trial-and-error approach: select a generic ingredient, test it in a small cohort, and hope for a signal. Neither approach has delivered a reliable mechanism for designing interventions around specific biological targets.
There is a better way. And it starts in the gut.
A Platform Built Around Biological Targets
Instead of starting with an ingredient list, the platform first asks a different question: which biological pathways are disrupted for a specific health condition, and which significant compounds crucial for key functions are altered as a result?
To answer that, the Enbiosis platform uses genome-scale metabolic models of gut bacteria combined with an AI retrosynthesis engine. Because gut microbiome composition varies significantly between individuals, the system runs simulations across thousands of real human microbiome profiles. This allows the platform to identify disrupted pathways and define molecular targets before any ingredient is selected.
The retrosynthesis engine then works backwards from the target molecule. It searches the full landscape of gut microbial metabolism to find the minimal set of food-grade precursors that gut bacteria can convert into that molecule. Every ingredient in the final formulation already exists in the food supply. What changes is how they are combined and what the gut microbiome does with them.
The result is a formulation built around a specific biological outcome, with a scientific rationale in place before clinical studies begin. All formulations are composed of food-grade ingredients, compliant with FDA and EFSA standards.
Clinical Validation: The Gut-Eye Axis
The first clinical application targeted the gut-eye axis in dry eye condition. Research has established that gut barrier function and systemic inflammation are linked to ocular surface health, and that short-chain fatty acids produced in the gut carry immunomodulatory properties.
Food-grade substrates were selected based on their predicted capacity to modulate this pathway. In a prospective pilot study, patients using the Enbiosis formulation showed meaningful improvements in tear production, outperforming standard of care. The study is currently submitted for peer review.
A Broader Pipeline
The dry eye application demonstrated that the same computational engine can be directed at any health condition with a documented gut microbiome connection. The platform is currently being applied across a range of indications including type 2 diabetes, irritable bowel syndrome, Alzheimer’s disease, Parkinson’s disease, psoriasis, vitiligo, eczema, and age-related macular degeneration.
Each indication runs through the same formulation design process. While the target changes with each indication, the underlying methodology remains consistent.
Computational models depend on the quality of underlying biological data, and in silico predictions require clinical confirmation. The approach informed and accelerated the path to evidence. It did not replace it.
Source: Enbiosis, How AI and Digital Twin Technology Are Changing Nutraceutical Formulation, Digital Twin AI Technology, Esra Sensez
References
- Mardinoglu, A., & Palsson, B. Ø. (2025). Genome-scale models in human metabologenomics. Nature Reviews Genetics, 26(2), 123–140.
- Nalbantoglu, O. U., Ermis, B. H., & Gundogdu, A. (2025). Deep learning-enhanced wellness scores: A population level study on gut microbiome profiling and health prediction. Biomedical Signal Processing and Control, 110, 108146.
- Tîrziu, A.-T., et al. (2024). From gut to eye: exploring the role of microbiome imbalance in ocular diseases. Journal of Clinical Medicine, 13(18), 5611.
- Kim, C. H. (2023). Complex regulatory effects of gut microbial short-chain fatty acids on immune tolerance and autoimmunity. Cellular & Molecular Immunology, 20(4), 341–350.
- Karakan, T., et al. (2022). Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome. Gut Microbes, 14(1), 2138672.
Authors:
Assoc. Prof. Ozkan Ufuk Nalbantoglu
Chief Technical Officer (CTO)
Associate Professor specializing in bioinformatics, deep learning and microbiome data analysis. Holds patents for AI-based disease diagnostics using intestinal microbiome data, driving the core Enbiosis Enbiosis AI engine.
LinkedIn: Ufuk Nalbantoglu
Disclosure: The author is employed by Enbiosis Biotechnology
Esra Sensez
Scientific Content and Research Associate
Focuses on translating complex microbiome science into accessible and evidence-based content. With a background in bioengineering, she works at the intersection of AI-driven formulation technology and scientific communication.
LinkedIn: Esra Sensez
Disclosure: The author is employed by Enbiosis Biotechnology.
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