Personal Agent Supplement Pharmacokinetic Halflife Skill
by alphaparkinc
README.md
# Personal Agent Supplement Pharmacokinetic Halflife Skill
[](https://github.com/Alpha-Park)
[](https://github.com/alphaparkinc)
[](https://www.python.org/)
[](https://modelcontextprotocol.io/)
[](https://github.com/Alpha-Park)
Zero-dependency supplement pharmacokinetics modeler, elimination half-life decay tracker, competitive absorption conflict matrix evaluator, and optimal ingestion scheduler.
## Architecture
```mermaid
flowchart TD
OralDose[Compound Name, Dose mg, Elapsed Hours] --> PKModeler[One-Compartment Pharmacokinetic Modeler]
PKModeler --> ActiveDose[Active Plasma Circulating Level mg]
PKModeler --> WashoutCalc[95% Elimination & 99% Full Washout Latencies]
RegimenStack[Daily Supplement Stack & Timestamps] --> InteractionEngine[Transporter Competition Matrix]
InteractionEngine --> DMT1Filter[Divalent Cation Transporter Competition: Zn vs Fe vs Ca]
InteractionEngine --> LipidCheck[Lipophilic Bioavailability Micelle Validation]
InteractionEngine --> OptimizedSchedule[Staggered Chronobiological Regimen]
```
## Quickstart
```python
from client import PersonalAgentSupplementPharmacokineticHalflife
agent = PersonalAgentSupplementPharmacokineticHalflife()
res = agent.model_compound_clearance_curve(compound_name="caffeine", dose_mg=200.0, time_elapsed_hours=6.0)
print(f"Active Plasma Dose: {res['active_circulating_dose_mg']} mg | 95% Clear: {res['hours_until_95pct_clearance']} hrs")
```
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