Non-Compartmental Analysis (NCA)
A Complete Beginner's Guide

1. What is Non-Compartmental Analysis?

Non-Compartmental Analysis (NCA) is the most commonly used method for analyzing pharmacokinetic (PK) data from clinical and preclinical studies. Unlike compartmental modeling, NCA does not assume any specific structural model for how a drug distributes in the body. Instead, it uses mathematical techniques — primarily numerical integration — to calculate key PK parameters directly from observed concentration-time data.

NCA is often the first step in any PK analysis workflow. It provides essential summary parameters like AUC (area under the curve), Cmax (peak concentration), half-life, clearance, and volume of distribution. These parameters are routinely reported in:

• Phase I clinical trials — dose-ranging studies and first-in-human PK
• Bioequivalence (BE) studies — comparing generic vs. innovator formulations
• Preclinical PK studies — ADME characterization in animal models
• Regulatory submissions — FDA, EMA, and PMDA filings

2. Concentration-Time Profiles

Every NCA analysis starts with a concentration-time profile — a series of measurements showing drug concentration in a biological matrix (typically plasma) at various time points after dosing.

For an oral (extravascular) dose, a typical profile looks like this:

• Absorption phase — concentration rises as the drug is absorbed from the GI tract
• Peak (Cmax) — the maximum concentration reached, occurring at time Tmax
• Elimination phase — concentration declines as the drug is metabolized and excreted
• Terminal phase — the final, approximately log-linear decline used for half-life estimation

For an intravenous (IV) bolus dose, there is no absorption phase — concentration starts at its highest and declines immediately.

3. Key NCA Parameters

Here are the primary parameters computed in a standard NCA analysis:

4. AUC Calculation: The Trapezoidal Rule

AUC is the most fundamental NCA parameter. It represents the total drug exposure — the integral of the concentration-time curve. Since we have discrete data points (not a continuous function), we approximate the integral using the trapezoidal rule.

Linear Trapezoidal Rule

For each pair of adjacent time points, the area of the trapezoid is:

Log-Linear Trapezoidal Rule

When concentration is declining (Cᵢ₊₁ < Cᵢ), the log-trapezoidal method provides a better approximation because drug elimination typically follows first-order (exponential) kinetics:

Linear-up Log-down Method

The Linear-up Log-down method is the most widely used approach in modern NCA software (including Phoenix WinNonlin, Kinetica, and PK-Swift). It combines both rules:

• Ascending segments (Cᵢ₊₁ ≥ Cᵢ): Use the linear trapezoidal formula
• Descending segments (Cᵢ₊₁ < Cᵢ): Use the log-linear trapezoidal formula

This approach is recommended by Gabrielsson & Weiner (2016) and is the standard method described in most pharmacokinetic textbooks.

5. Terminal Phase & Half-Life

The terminal elimination rate constant (λz) is estimated by fitting a linear regression to the natural logarithm of concentration versus time in the terminal phase:

The half-life is then derived directly from λz:

Selecting Terminal Phase Points

Choosing the correct terminal phase points is critical for accurate λz estimation. The "Best Fit" algorithm used by PK-Swift and commercial software:

1. Considers all subsets of ≥ 3 consecutive points after Tmax
2. Requires that all points have positive concentration
3. Requires a negative slope (indicating elimination)
4. Selects the subset with the highest adjusted R²
5. Ties are broken by choosing the largest number of points

6. Derived Parameters

Once AUC and λz are calculated, several important PK parameters can be derived:

Clearance (CL/F)

For extravascular dosing, apparent clearance is:

This tells us how efficiently the body removes the drug. Higher clearance = faster elimination.

Volume of Distribution (Vz/F)

A large Vz suggests the drug distributes extensively into tissues. A small Vz suggests it stays mainly in plasma.

Mean Residence Time (MRT)

MRT represents the average time a drug molecule spends in the body. AUMC (Area Under the First Moment Curve) is calculated similarly to AUC but using the t × C product.

7. Best Practices & Common Pitfalls

• Minimum 8–10 time points for reliable parameter estimation (at least 3 in the terminal phase)
• Include a pre-dose (t=0) measurement — especially important for IV dosing and baseline correction
• Check AUC extrapolation % — if AUC₀₋∞ has >20% extrapolated, the terminal phase may be poorly characterized
• Validate λz visually — always inspect the log-linear plot to ensure the selected regression points make pharmacological sense
• Handle BLQ data appropriately — pre-Cmax BLQ values are typically set to 0; post-Cmax BLQ may be set to 0 or handled with specific rules
• Report dose-normalized parameters when comparing across dose groups

8. Try It Yourself

Next: Theophylline Case Study — Step-by-Step NCA Walkthrough →