The science behind Astrand stacks
Statistical Reasoning
Our Diamond Standards
LUMEN
Statistical Reasoning
24.2%
of people meet both strength & cardio guidelines
Most people aren’t consistently hitting the baseline inputs that drive physique and performance changes — so execution and recovery become the bottleneck.
33.2%
of people report short sleep — less than 7 hours
A third of adults aren’t getting enough sleep — one of the most evidence-backed drivers of recovery and body composition outcomes.
12%
of supplements are third-party certified —study sample
In one retail survey, only 12% of products carried third-party certification — quality standards aren't assumed
Clinical Studies First
We prioritize ingredients supported by credible clinical studies rather than hype, trends, or “theoretical” formulas.
Effective Dosing Targets
We formulate stacks with optimal dose amounts that make sense for the goal as dose determines outcome.
Third-Party Tested
We verify beyond internal checks to support purity, label accuracy, and batch-to-batch consistency.
cGMP Manufacturing
Produced under standardized manufacturing controls designed for reliability and repeatability.
LUMEN
Literature-verified Utility &
Mechanism Evaluation Network
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Literature Scan
We start with the strongest available evidence and work downward. Human data is prioritized, with attention to study design, sample relevance, duration, and outcome consistency. If an ingredient’s support is thin, inconsistent, or purely theoretical, it doesn’t advance.
Utility Check
Evidence isn’t enough — utility matters. We assign each ingredient to a specific performance objective inside the stack — strength/size, leanness, training output, recovery, sleep, hydration. If the outcome isn’t clear, measurable, and aligned to the stack’s goal, the ingredient is rejected.
Mechanism Map
We validate the mechanism so the ingredient has a defined role, not a marketing claim. This step ensures the stack is engineered — each ingredient supports a pathway that makes sense in context, rather than a “kitchen sink” formula.
Timeline to notice
Dose determines outcome. We compare published effective ranges to real serving amounts, check feasibility of consistent use, and avoid under-dosed inclusions that exist only to look impressive on a label. If the dose can’t realistically produce the intended effect, it doesn’t make the stack.
Notes for Use
We standardize execution. Timing, context (with/without food), training-day vs rest-day logic, and practical constraints are defined so the stack runs the same way in real life as it does on paper. This is how we reduce variability and make results more predictable.
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