NON-COMPARTMENTAL MODEL

Also called as the model independent method, as does not require assumption of specific compartment model.
Ø  Non – compartmental models describe the pharmacokinetics of drug disposition using time and concentration parameters.
Ø  This method can however be applied to any compartment model provided the drugs or metabolites follow linear kinetics.
Ø  The approach based on statistical moments theory, involves the collection of experimental data following a single dose of drug.
Ø  If one considers the time course of drug concentration in plasma as a statistical distribution curve, then:
MRT = AUMC
                           AUC
Where MRT= Mean residence time
            AUMC= area under the first moment curve
            AUC= area under the zero moment curve.



AUMC is obtained from a plot of product of plasma concentration and time (C*t) versus time t from zero to infinity. Mathematically, it is expressed by equation:

AUC is obtained from a plot of plasma drug concentration versus time from zero to infinity. Mathematically, it is expressed by equation:
Practically, the AUMC and AUC can be calculated from the respective graphs by trapezoidal rule.







AUC and AUMC plots
Ø  MRT is defined as the average amount of time spent by the drug in the body before being eliminated.
Ø  Non – compartmental model is widely used to estimate the important pharmacokinetic parameters like bioavailability, clearance and apparent volume of distribution .The method is also useful in determining half life, rate of absorption and first order absorption rate constant of drug.
ADVANTAGES OF NON-COMPARTMENTAL MODEL
o   Ease of derivation of pharmacokinetic parameters by simple algebraic equations.
o   The same mathematical treatment can be applied to almost any drug or metabolite provided they follow first order kinetics.
o   A detailed description of drug disposition characteristics is not required.

DISADVANTAGE

It provides limited information regarding the plasma drug concentration – time profile, more often it deals with averages.

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