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 : Probiotics in the prevention and treatment of atherosclerotic cardiovascular disease: Focus on molecular mechanisms
Dipak P Ramji, Cardiff University, United Kingdom
Title : Effect of dietary probiotic on the pH and colour characteristics of carcasses, breast fillets and drumsticks of broilers
Nurinisa Esenbuga, Ataturk University, Turkey
Title : Phytochemical analysis and antioxidant activity of Physalis minima
Suriyavathana Muthukrishnan, Periyar University, India
Title : Scale up for manufacturing next generation probiotics: Process development strategies and processes to fast track products into the market
Jason Ryan, Sacco System, Australia
Title : Bacillus subtilis natto: A next-generation probiotic with positive implications in immunological, metabolic, and neurological health
Roberto Ricardo Grau, National University of Rosario, Argentina
Title : Canned cherries made with lactitol or xilitol: A dietetics and prebiotic alternative to reduce its caloric value
Mariela Maldonado, CONICET-UTN FRM, Argentina