Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)

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Digital-Twin Modelling of the Gut Microbiome to Guide Personalized Probiotic-Drug Combinations

Authors
Nishita Burade1, Gayatri Sharma1, Sampathi Sunitha1, *, Jagadish V. Tawade2, Nitiraj V. Kulkarni1, 2
1School of Pharmacy, Vishwakarma University, Pune, 411048, Maharashtra, India
2Department of Mathematics, Vishwakarma University, Pune, Maharashtra, India
*Corresponding author. Email: s.sunitha@vupune.ac.in
Corresponding Author
Sampathi Sunitha
Available Online 6 January 2026.
DOI
10.2991/978-94-6463-948-3_34How to use a DOI?
Keywords
Digitl Twin; Gut Microbiome; Probiotic Drug Combination
Abstract

We present the concept of an online-twin method of simulation of the gut microbiome to create personalized probiotic-drug interventions. We propose integration of host data, microbiome sequencing, metabolic models and simulations in order to predict individual response to treatment. Studies indicate that intestinal microbes may block, promote, or enhance the toxicity of drugs, e.g., cyclophosphamide, levodopa and racecadotril. These data are employed by the digital twin to recreate microbial changes, drugs metabolism, and probiotics. Machine learning systems and artificial gut systems are used to predict in real-time the profile of metabolites and make recommendations on the design of targeted probiotic mixtures. Case studies like Consti Biome and Sensi Biome show that the interventions are more effective when implemented according to the bowel habits and the microbiota profile of a person.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
Series
Advances in Intelligent Systems Research
Publication Date
6 January 2026
ISBN
978-94-6463-948-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-948-3_34How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Nishita Burade
AU  - Gayatri Sharma
AU  - Sampathi Sunitha
AU  - Jagadish V. Tawade
AU  - Nitiraj V. Kulkarni
PY  - 2026
DA  - 2026/01/06
TI  - Digital-Twin Modelling of the Gut Microbiome to Guide Personalized Probiotic-Drug Combinations
BT  - Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
PB  - Atlantis Press
SP  - 476
EP  - 489
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-948-3_34
DO  - 10.2991/978-94-6463-948-3_34
ID  - Burade2026
ER  -