Our Mission

At BLOSMM (Body Liberation Optimized Through Science & Metabolic Mastery), we pioneer the next frontier of precision weight loss: unlocking the full potential of Tirzepatide through rigorous research. Our goal is to redefine metabolic optimization by combining cutting-edge peptide science with individualized dosing strategies that maximize efficacy while minimizing side effects.

Why Tirzepatide?

As the first dual GIP/GLP-1 receptor agonist approved for obesity, Tirzepatide represents a quantum leap in metabolic therapy, but its true potential lies in how we use it. BLOSMM focuses on:
✔ Microdosing Protocols – Minimizing side effects (nausea, fatigue) while sustaining weight loss.
✔ Personalized Titration – Tailoring doses to genetic, metabolic, and lifestyle factors.
✔ Synergistic Stacks – Researching compounds that enhance Tirzepatide’s effects (e.g., Lipo-CRetatrutide).

The BLOSMM Difference

1. Beyond “One-Size-Fits-All” Dosing

We reject the industry’s standard dosing escalations (2.5 mg → 5 mg → 10 mg, etc.). Instead, our research explores aligning drug release with physiological rhythms and optimizing pharmacodynamic outcomes.

  • Ultra-low micro doses (0.25–1 mg/week) for sensitive responders.
  • Customized dosing (e.g., 2x/week doses vs. single bolus).
  • Tapering strategies to prevent rebound weight gain.

2. Lab-Verified Purity & Stability

Every Tirzepatide sample in our studies is:

  • HPLC-tested for peptide integrity (guaranteed >99% purity).
  • Stored properly  to prevent degradation.
  • Benchmarked against pharmaceutical-grade reference standards.

3. Data-Driven Accountability

We track (anonymized) metrics from our research cohorts:

  • Appetite suppression curves
  • Side Effects and adverse events
  • Weight loss results  

Who We Serve

  • Researchers – Access our Tirzepatide Microdosing Database (dosing schedules, adverse event logs).
  • Clinicians – Download patient titration templates for off-label use.
  • Biohackers – Join our N=1 Trial Registry to contribute self-reported data.