Across Alzheimer's, heart failure, epilepsy, and cancer, the same pattern keeps appearing: patients with similar diagnoses respond differently to the same drugs, and metabolic differences predict who benefits. This site collects the evidence, proposes a framework, and invites scrutiny.
These papers define what metabolic state medicine is, propose a mechanistic framework, and examine the published clinical evidence.
Why metabolic state medicine exists as a category. Compares conventional pathological approaches to metabolic-state-aware approaches across five disease areas.
A conservative, testable definition. What it includes, what it excludes, where the evidence is strongest and where it's weakest.
Three things had to converge: measurement tools, delivery mechanisms, and mechanistic understanding of how metabolic substrates regulate inflammation, gene expression, and cell fate.
A review of published clinical trial data examining metabolic subgroup effects. Draws on trials including DAPA-HF, EMPEROR-Reduced, and published checkpoint inhibitor subgroup analyses.
How metabolic state operates above individual pathways: coordinating inflammation, rewriting the epigenome, and influencing cell fate decisions. A proposed mechanistic architecture.
A three-tier definition: substrate availability, endocrine counter-regulation, and cellular bioenergetics. With proposed biomarker thresholds and a trial protocol design.
Each paper examines published evidence for metabolic gating in a specific disease area and proposes testable interventions.
Examines why anti-amyloid drugs show differential efficacy in APOE4 carriers, drawing on published ARIA-E incidence data and FDG-PET studies of brain glucose hypometabolism.
Reviews published evidence on substrate switching in heart failure, including PCr/ATP depletion data and SGLT2 inhibitor trial results, proposing metabolic state as the variable explaining divergent outcomes.
Examines published data showing that BMI predicts checkpoint inhibitor response in melanoma, and proposes a metabolic fuel reserve explanation grounded in T-cell bioenergetics research.
Good science defines its boundaries. These papers examine failure modes and what would need to be proven for the hypothesis to hold.
Adherence confounding, reverse causality, subgroup multiplicity, proxy inflation. An honest examination of every way this framework could be wrong.
Proposed metabolic enrichment strategies, biomarker panels, and stratification designs for testing this framework in actual clinical trials.
"Metabolic state may be the most overlooked variable in drug response. If that's true, it changes how medicine works. We don't want to prove it alone."
This is not a finished story. The evidence is early. Some of it is computational, some is drawn from published trials, and much of it remains to be tested prospectively. What makes the hypothesis worth pursuing is that the same metabolic pattern keeps appearing across diseases that otherwise have nothing in common.
We're looking for scientists, clinicians, and researchers who find this question worth asking.
Whether you study one of these diseases, work in metabolic science, or see patterns in your own clinical data that this framework might explain, we'd like to hear from you.