Multi-peptide cycles run $795–$1,295 and churn the moment a response is slow. CellWise ranks an 88+ peptide library, always expanding as new compounds clear our pipeline, against each patient’s single-cell phenotype. You get an explicit AVOID list and a transcriptomic reason to defend every 503A protocol.
Each one is a place you lose a patient, a cycle, or a night of sleep. Here's what CellWise does about it.
Multi-peptide cycles are expensive, and patients churn the moment a response is slow. CellWise ranks the library against each patient's immuno-metabolic phenotype, so you build the stack on molecular fit instead of a generalized goal.
Peptide selection has always leaned on clinical instinct. The immuno-metabolic axis and an explicit AVOID list give you an objective, transcriptomic reason for every compound you start or hold.
The FDA is actively restricting BPC-157, TB-500, KPV, and MOTS-c. CellWise puts a transcriptomic justification on file for every off-label protocol, so your compliance posture keeps up with the compounding landscape.
The clinical home base. Use-case assessments, immuno-metabolic phenotyping, the therapeutic target map, stress profiling, and more, all in one report.
The quantitative, visual view of the patient's raw biomarker data, shown as a population-vs-patient overview.
A filterable, gene-level interface over the patient's complete dataset, exposing the top cell populations carrying each signal.
Test a clinical hypothesis against the patient's own molecular data and re-run it in seconds.
Assay-independent surveillance across dosing phases, peptide-specific labs, and wearable trends, with no repeat sequence required.
Immune age, senescence, and the 12 hallmarks from one PBMC sample, for cell-resolved biological aging.
Re-assay a patient and see the gene-expression deltas across key biomarkers, so you see what has shifted since the last screen.
Reviewers read the same donor in isolation and converged on the same compound match, the same AVOID call, and the same follow-up labs.
The GLP-1/GIP recommendation is well-grounded. I would have considered semaglutide for metabolic reasons anyway, but the PBMC mechanistic context (GLP-1R on monocytes reducing pro-inflammatory cytokine secretion) gives me a molecular rationale to present to the patient that increases adherence.
Placing the patient on the glycolytic–oxidative axis before I build a stack is exactly the objective baseline peptide prescribing has always been missing.
Having a transcriptomic reason for each AVOID call is the difference between defending a 503A protocol and hoping no one asks.