Every drug in a psychiatric regimen doesn't just affect one receptor. It occupies many — at different strengths, across different systems, simultaneously. CYPnosis models that complexity directly: estimating how much of each key receptor is occupied by each drug at a given dose, then combining those estimates across the entire regimen to show the total receptor load a patient is carrying.
Dose-anchored. Not categorical.
Most tools tell you a drug "has H1 activity" or "is anticholinergic." CYPnosis calculates occupancy — how much of a given receptor is actually engaged at the dose your patient is taking. That distinction matters. A low-dose quetiapine prescribed for sleep engages H1 and 5-HT2A substantially before D2 becomes relevant. A high-dose regimen tells a different story. The model reflects that difference, rather than flattening it into a label.
Interactions update the occupancy math automatically.
When a co-prescribed inhibitor raises a drug's plasma exposure, receptor occupancy rises with it. CYPnosis connects the pharmacokinetic engine to the receptor model directly — the AUCR calculated from metabolic interaction data feeds into the concentration estimate used for binding calculations, without a separate step. A clinician can see, concretely, how an enzyme inhibitor doesn't just raise drug levels — it shifts receptor occupancy across the profile.
Polypharmacy makes receptor burden invisible. CYPnosis makes it visible.
Three drugs at moderate H1 occupancy each produce a combined load that no single package insert reflects. The multi-ligand competitive binding model underlying CYPnosis ensures that combined occupancy across a regimen is calculated correctly — adding any drug always increases shared receptor pressure, and the math guarantees that. The combined view shows where burden is accumulating across sedation, metabolic receptor load, orthostasis, anticholinergic load, and serotonergic activity simultaneously.
Twenty-plus receptors. Clinically organized.
The receptor panel covers the systems that matter most in psychiatric polypharmacy: dopamine (D1, D2, D3, D4), serotonin (SERT, 5-HT1A, 5-HT2A, 5-HT2C, 5-HT3, 5-HT7), histamine (H1), muscarinic (M1), adrenergic (α1, α2), norepinephrine and dopamine transporters (NET, DAT), and sigma-1. Ki values are drawn from peer-reviewed literature and the NIMH PDSP database, with a confidence rating attached to each data point so the quality of the underlying evidence is always visible.
PET-grounded benchmarks for antipsychotic dosing.
For D2, two occupancy thresholds from the PET imaging literature are annotated directly in the interface: the efficacy range (≥65%) and the elevated EPS risk range (≥80%). These apply to pure antagonists. Partial agonists — aripiprazole being the most clinically important example — are flagged throughout the model, because the occupancy math and clinical interpretation are different. The 80% EPS threshold does not apply where it shouldn't.
Five burden signals. No dose required.
Alongside the dose-dependent occupancy model, CYPnosis generates five receptor burden indices derived from binding affinity data alone: sedation, metabolic receptor load, orthostasis, anticholinergic burden, and serotonergic load. These provide a rapid regimen-level signal that doesn't require precise dosing data — useful for screening, for regimen review, and for communicating receptor load to colleagues or patients in plain terms.
What this is — and what it isn't
Receptor occupancy estimates are mechanistic outputs. They reflect binding affinity and modeled free drug concentration at the receptor site. They are not outcome predictions, and they do not substitute for clinical judgment, therapeutic drug monitoring, or established prescribing guidelines. Data confidence is displayed for every receptor and every drug, because knowing the limits of the model is part of using it well.