By name: tooluniverse-pharmacokinetics description: "Pharmacokinetic (PK) analysis of concentration-time data — non-compartmental analysis (NCA) for Cmax, Tmax, AUC (0-t and 0-∞), terminal half-life, clearance (CL), volume of distribution (Vd), MRT, and absolute bioavailability (F). Also one-compartment fitting. Use when you have plasma/serum drug concentrations over time after a dose and need PK parameters, or to compute bioavailability from IV + oral AUCs. NOT for ADMET property prediction from structure (use tooluniverse-admet-prediction)."
Pharmacokinetic (PK) Analysis — Non-Compartmental Analysis
Turn a concentration-vs-time profile after a dose into the standard PK parameters, and compute bioavailability from IV + oral data. Non-compartmental analysis (NCA) is the model-independent workhorse used for most PK reporting.
When to use this
- You have measured plasma/serum (or other matrix) drug concentrations at known times after a dose.
- You need Cmax/Tmax/AUC/half-life/clearance/Vd, or absolute bioavailability F.
- Comparing exposure (AUC, Cmax) between formulations, doses, or routes.
This is measured-data PK. For predicting ADMET properties from a chemical structure, use tooluniverse-admet-prediction.
Step 1 — Prepare the concentration-time data
| Issue | What to do |
|---|---|
| Units — be consistent | One time unit (h), one concentration unit (mg/L or ng/mL), one dose unit (mg). Pass them as time_unit/conc_unit/dose_unit. CL and Vd come back in derived units (e.g. L/h, L). |
| Route matters | Set route to iv or po/oral. CL and Vd are only directly interpretable for IV data; from oral data they are apparent (CL/F, Vd/F) because absorption is incomplete. |
| Include t=0 | For IV bolus include the t=0 (back-extrapolated) point; for oral the pre-dose value is usually 0. |
| BLQ (below limit of quantification) | Leading BLQs before the first measurable → treat as 0; BLQs in the terminal tail → drop them (don't set to 0, it corrupts the terminal slope). |
| Sampling design | You need enough late points to define the terminal phase (≥3 points clearly in the log-linear decline) or the half-life and AUC0-∞ are unreliable. |
| Single vs multiple dose | NCA here assumes a single dose. For steady-state, analyze one dosing interval (AUC0-τ) and say so. |
Step 2 — Run NCA
tu run NCA_compute_parameters '{
"times":[0,0.5,1,2,4,8,12,24],
"concentrations":[0,2.5,4.8,6.1,4.2,2.1,1.0,0.2],
"dose":100, "route":"iv",
"dose_unit":"mg", "conc_unit":"mg/L", "time_unit":"h"}'
Returns Cmax, Tmax, Clast, Tlast, AUC0_last, AUC0-inf, AUC_extrapolation_pct, lambda_z, t_half, r_squared_terminal_fit, clearance_CL, volume_distribution_Vd, MRT_iv, with a units block. AUC uses the FDA/EMA linear-up / log-down trapezoidal method.
For a CSV profile (with BLQ handling), scripts/nca_from_csv.py computes the same parameters locally.
Other tools:
NCA_fit_one_compartment— fit a 1-compartment model (k, V, CL) when you want a parametric model instead of NCA.NCA_calculate_bioavailability— absolute F fromauc_po,dose_po,auc_iv,dose_iv(see Step 4).
Step 3 — Interpret the parameters
| Parameter | Meaning | Notes / sanity |
|---|---|---|
| Cmax / Tmax | Peak concentration & time to peak — absorption rate/extent. | For IV bolus Cmax is at t=0; a later Tmax means absorption (oral) or distribution. |
| AUC0-t / AUC0-∞ | Total exposure (area under the curve). The key exposure metric. | AUC0-∞ extrapolates the tail using Clast/lambda_z. |
| AUC_extrapolation_pct | % of AUC0-∞ that was extrapolated beyond the last point. | >20% → AUC0-∞ (and anything derived from it) is unreliable; report AUC0-last instead and note insufficient sampling. |
| lambda_z / t_half | Terminal elimination rate constant and half-life. | Trust only if r_squared_terminal_fit ≥ ~0.95 and ≥3 terminal points were used. |
| CL (clearance) | Volume cleared per time = Dose/AUC0-∞ (IV). |
From oral data this is CL/F (apparent). |
| Vd | Volume of distribution = CL/lambda_z (IV). |
From oral data this is Vd/F (apparent). |
| MRT | Mean residence time. | Longer MRT = slower overall elimination. |
Step 4 — Absolute bioavailability (F)
F needs the same drug given both IV and orally (ideally same subjects, dose-normalized):
tu run NCA_calculate_bioavailability '{"auc_po":35.0,"dose_po":200,"auc_iv":43.4,"dose_iv":100}'
F = (AUC_po / Dose_po) / (AUC_iv / Dose_iv). Report as a fraction or %. F near 1 = well absorbed; low F = poor absorption or high first-pass metabolism. F > 1 signals a data/dosing error (recheck units and doses).
Step 5 — Quality gotchas (state these)
- Extrapolation >20% → don't report AUC0-∞/CL/Vd as reliable; the profile wasn't followed long enough.
- Bad terminal fit (
r_squared_terminal_fit< 0.9, or <3 tail points) → half-life is unreliable. - CL/Vd from oral data are apparent (CL/F, Vd/F) — never present them as true clearance/volume without IV data.
- Units drive CL/Vd — a wrong conc unit silently scales them. Always check the returned
unitsblock. - Flip-flop kinetics (absorption slower than elimination) makes the "terminal" slope reflect absorption, not elimination — suspect it when oral t½ ≫ IV t½.
Honest limitations
- NCA is model-independent and robust but gives no mechanistic structure (no separate absorption/distribution rate constants) — use
NCA_fit_one_compartmentor population PK for that. - AUC accuracy depends entirely on sampling density around Cmax and in the terminal phase.
- Single-dose assumptions; for steady state analyze one interval (AUC0-τ) and accumulation separately.
Related skills
tooluniverse-admet-prediction— predict ADME properties from structure (no measured data).tooluniverse-dose-response— IC50/EC50 potency from concentration-response (not time-course).tooluniverse-statistical-modeling— compare PK parameters across groups.