AI in probiotic research is enabling significant breakthroughs in the understanding and application of probiotics. Through data mining and predictive analytics, AI algorithms can identify patterns in microbiome compositions that contribute to health benefits, guiding the selection of effective probiotic strains. Additionally, AI-driven technologies streamline the process of fermentation and production by predicting optimal growth conditions for probiotic microorganisms. The integration of AI in research also facilitates real-time monitoring of clinical trials, enabling faster and more accurate assessments of probiotic efficacy. With AI’s capacity to process large datasets and model complex biological systems, the future of probiotic research promises more targeted and individualized probiotic therapies, enhancing their potential in disease prevention and treatment.
Title : Overcoming manufacturing challenges in next-generation probiotics: From anaerobic cultivation to clinical-grade formulation
Jason Ryan, Sacco System, Australia
Title : Treating irritable bowel syndrome patients with a balanced multi-strain synbiotic – results from a multi-center, randomized, double-blind, placebo-controlled clinical trial (the ViIBS trial)
Henning Sommermeyer, Calisia University, Poland
Title : Global regulatory trends on the use of probiotics and prebiotics in foods and food supplements
David Pineda Ereno, DPE International Consulting, Belgium
Title : Biochemical profile and nutripotential glimpses of Terminalia arjuna bark extract
Suriyavathana Muthukrishnan, Periyar University, India
Title : A case-cohort study of the outcomes of probiotics on wound healing in a private hospital in Abu Dhabi
Najat Amharar, Burjeel, United Arab Emirates
Title : Potential for prebiotic food supplement production from by-products of dried persimmon (Diospyros kaki)
Yasin Ozdemir, Ataturk Horticultural Central Research Institute, Turkey