Probiotic Y7 with amino acids in early Parkinson's disease
Tests a probiotic and amino acid mix in people with early Parkinson's disease.
Plain-language title generated from the registry record
Registry title: Developing Precision Microbiota-Based Cocktail Modification Therapy to Delay the Progression of Parkinson's Disease (PD) - Use Preclinical Human Trials to Confirm the Impact of the Optimal "Probiotic Y7, Tryptophan and Branched-chain Amino Acid" Cocktail Formula on Early Stage PD Patients
Key facts
- Where
- Taipei, TaiwanSee the site
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 30 and 85 years old?
Source: NCT07619560, who can take part
Where in Taiwan
- Taipei Medical University HospitalTaipei, TaiwanTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Taipei Medical University
- Trial code
- NCT07619560
- Record updated
- 2 June 2026
- Original description
Preclinical human trials will be utilized to validate the research direction, followed by clinical trials to assess the impact of a cocktail formula product containing the optimal probiotic Y7 combined metabolites on motor, cognitive, and non-motor functions in early Parkinson's disease patients. The study aims to recruit 120 patients (stage 1-3) and employ a two-arm, randomized controlled trial (RCT) design, dividing subjects into intervention and control groups for a 12 weeks trial period. Commercial development will be contingent upon the clinical trial outcomes, evaluating whether the product offers clinical benefits such as delaying Parkinson's disease progression in motor, cognitive, and non-motor functions. Additionally, a personalized and precise prognosis prediction model for Parkinson's disease will be established. This model will gather comprehensive clinical data, including motor function assessments (functional tests, UPDRS), biochemical markers, questionnaire responses, and genotype data (TPM array), as well as metabolite and microbial data. Through integrated analysis of this biological information using machine learning techniques, a personalized and accurate prognosis prediction model for Parkinson's disease will be developed. This model will predict the disease status of PD patients 12 weeks later, accounting for factors such as cocktail therapy. The results will empower PD patients to understand their individual disease progression and treatment prognosis, enabling them to prepare accordingly. Moreover, this model will aid researchers in identifying patient profiles more likely to benefit from treatment, thereby enhancing the evaluation of the efficacy and applicability of cocktail therapy.Read full original descriptionShow less
Developing Precision Microbiota-Based Cocktail Modification Therapy to Delay the Progression of Parkinson's Disease - Use Preclinical Human Trials to Confirm the Impact of the Optimal "Probiotic Y7, Tryptophan and Branched-chain Amino Acid" Cocktail Formula on Early Stage Parkinson's Disease Patient
Preclinical human trials will be utilized to validate the research direction, followed by clinical trials to assess the impact of a cocktail formula product containing the optimal probiotic Y7 combined metabolites on motor, cognitive, and non-motor functions in early Parkinson's disease patients. The study aims to recruit 120 patients (stage 1-3) and employ a two-arm, randomized controlled trial (RCT) design, dividing subjects into intervention and control groups for a 12 weeks trial period. Commercial development will be contingent upon the clinical trial outcomes, evaluating whether the product offers clinical benefits such as delaying Parkinson's disease progression in motor, cognitive, and non-motor functions. Additionally, a personalized and precise prognosis prediction model for Parkinson's disease will be established. This model will gather comprehensive clinical data, including motor function assessments (functional tests, UPDRS), biochemical markers, questionnaire responses, and genotype data (TPM array), as well as metabolite and microbial data. Through integrated analysis of this biological information using machine learning techniques, a personalized and accurate prognosis prediction model for Parkinson's disease will be developed. This model will predict the disease status of PD patients 12 weeks later, accounting for factors such as cocktail therapy. The results will empower PD patients to understand their individual disease progression and treatment prognosis, enabling them to prepare accordingly. Moreover, this model will aid researchers in identifying patient profiles more likely to benefit from treatment, thereby enhancing the evaluation of the efficacy and applicability of cocktail therapy.
Inclusion: Subject Inclusion Criteria:; Age between 30-85 years old; Diagnosed with early-stage Parkinson's disease (Hoehn and Yahr scale stage 1-3); Brain MRI confirms striatal degeneration in the basal ganglia region, with no history of stroke; Responds to Parkinson's disease-related medications (e.g., Levodopa); Free of any major or acute illnesses; Able to comply with the 12 weeks intervention and required assessments for the study.
Exclusion: Presence of major or acute illness before or during the study; Co-existing intestinal co-infections, such as CDI, E. coli, Salmonella, Shigella, Campylobacter, plague, or cytomegalovirus; Allergic to the intervention product; Unable to complete interviews or has mobility issues; Pregnant or breastfeeding women.