Resources

• Pujia C et al. “The Role of Mobile Apps in Obesity Management: Systematic …” (2025) — found that smartphone apps demonstrate a modest but statistically significant effect on weight loss and BMI over 4-6 months. PubMed Central
  
  

  • ✅ Supports your app-based delivery model
    
    

  • ⚠️ Effect size modest; needs long-term data
    
    

• Gemesi K et al. “Efficacy of an app-based multimodal lifestyle intervention …” (2024) — randomised‐controlled trial (n≈168) of an app-delivered multimodal weight-loss programme in people with BMI 30-40 kg/m², demonstrated weight reduction versus wait-list control. Nature
  
  

  • ✅ Stronger evidence for multimodal app approach (diet + activity + behaviour)
    
    

  • ⚠️ Limited to 12-24 weeks follow-up
    
    

• Couto FFS et al. “Mobile and Web Apps for Weight Management in Adults with Overweight or Obesity: Umbrella Review” (2025) — meta-review of systematic reviews found mobile apps effective for weight management; web‐only interventions less consistent. MDPI
  
  

  • ✅ Supports emphasis on mobile app rather than only web portal
    
    

  • ⚠️ Variation in app features; your differentiation matters
    
    

• Ghelani DP et al. “Mobile Apps for Weight Management: A Review of the Clinical Evidence” (2020) — narrative review showing apps may be useful as adjuncts to conventional strategies. Frontiers
  
  

  • ✅ Historical evidence base
    
    

  • ⚠️ Less high-quality RCTs then
    
    

Take-away: Digital app delivery is supported by the literature and aligns with your ObeCure platform. To strengthen your case, you’ll want to emphasise features where your app adds value (e.g., local food database, Indian diet specificity, integrated product supplementation, AI-behaviour tracking) and plan for long-term follow-up/maintenance data.

Baba Y et al. “Effect of Continuous Ingestion of Bifidobacteria and Inulin on Reducing Body Fat: A Randomized, Double-Blind, Placebo-Controlled, Parallel-Group Comparison Study” (2023) — in 120 subjects, combined inulin + Bifidobacterium reduced abdominal fat compared to placebo. MDPI

• ✅ Directly supports inulin (which you include in CleanDrink™) for body fat/visceral fat reduction
  
  

• ⚠️ Specific probiotic strain + inulin; your formula may differ
  
  

Neyrinck AM et al. “Interest of inulin in obesity: comparison of the prebiotic …” (2025) — suggests inulin‐enriched diet more efficient to improve weight and some clinical outcomes. PubMed Central

• ✅ Reinforces prebiotic (inulin) benefit
  
  

• ⚠️ Prebiotic only; your formula adds other components
  Take-away: Your use of inulin in CleanDrink™ is supported by data in obesity/abdominal fat reduction. You should highlight that your formulation also uses PHGG (partially hydrolysed guar gum) and Amla/fennel extracts as novel adjuncts (and note that clinical evidence for those may be more limited).

• Salehi A et al. “The Anti-Obesity Effects of Triphala and Triphala Guggul: A Systematic Review and Meta-Analysis of Clinical Trials” (2025) — concludes oral Triphala may reduce body weight in individuals with obesity in the short term, but evidence is inconsistent and long-term safety/optimal dosing not yet clear. ResearchGate+1
  
  

  • ✅ Direct support for Triphala (which you include in MealFix™)
    
    

  • ⚠️ Evidence variable; mostly short term; heterogenous dosing
    
    

• Net-Anong S et al. “Triphala, Trikatu, and Benjakul” (2025) — in vitro & in vivo data show anti-obesity, anti-adipogenic, anti-inflammatory effects of Triphala extract. JAPSONLINE
  
  

  • ✅ Preclinical mechanistic support
    
    

  • ⚠️ Translational to human trials still limited
    
    

• Anh NH et al. “Ginger on Human Health: A Comprehensive Systematic …” (2020) — systematic review of RCTs showing ginger has multiple health-benefits; though not all specific to weight/obesity. MDPI
  
  

  • ✅ Adds plausibility for ginger extract (in MealFix™)
    
    

  • ⚠️ Less strong human RCTs for weight reduction specifically
    Take-away: The herbal component of your formula has supportive evidence, especially Triphala and to some extent ginger. However you’ll need to clearly position them as adjunctive/supportive rather than standalone efficacy—and emphasise that your combined formulation is an innovative blend requiring its own evidence in future.
    
    

Teke J et al. “Artificial intelligence for obesity management: A review of …” (2025) — reviews platforms that integrate RCTs + large observational studies using AI/ML, showing clinically meaningful weight loss (5–10%) in scalable models. ScienceDirect

• ✅ Supports your plan to integrate AI/behaviour tracking/monitoring in ObeCure
  
  

• ⚠️ Many studies are proof-of-concept or observational, long‐term outcomes unclear
  
  

Shen Z et al. “COBRA: Multimodal Sensing Deep Learning Framework for Remote Chronic Obesity Management via Wrist-Worn Activity Monitoring” (2025, preprint) — shows deep learning model with wrist sensors could classify behaviour categories relevant to obesity (food intake, activity, sedentary) with high accuracy. arXiv

• ✅ Cutting-edge evidence for sensor + AI monitoring
  
  

• ⚠️ Preprint, not yet in peer-review journal; mostly technological rather than large population weight-outcomes
  Take-away: The behavioural/AI monitoring element of your protocol is supported and positions ObeCure on the frontier. Clearly communicate this as a differentiator and plan to collect your own real-world data to strengthen claims.

Your 3 sessions/day structure (core concept, interpretation, clinical/procedural) is aligned with a digital/app-based delivery model; the evidence supports using mobile platforms in lifestyle/obesity interventions.

CleanDrink™ (with inulin & PHGG) is underpinned by data on inulin for abdominal fat reduction; you can state that your formulation is based on published prebiotic research and further tailored for Indian context.

MealFix™ (with Triphala, ginger, cumin, PHGG, inulin) is supported in principle by phytochemical research and traditional use; you can frame it as an adjunctive botanical + prebiotic approach consistent with emerging evidence.

The AI/monitoring layer of ObeCure (tracking diet, activity, behaviours, sensors) is supported by review and emerging studies, setting your platform apart from simpler calorie-tracking apps.