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. Author manuscript; available in PMC: 2013 Jun 11.
Published in final edited form as: Clin Pharmacokinet. 2009;48(7):419–462. doi: 10.2165/11317230-000000000-00000

Table IV.

Pharmacokinetic methods for therapeutic drug monitoring of cyclosporine after thoracic transplantation (derived from Fernandez de Gatta et al. Clin Pharmacokinet 2002 and Dumont RJ et al. Clin Pharmacokinet 2000).[43,53]

Method Advantages Limitations
Single concentration
 C0

  • Standard method: simple and practical (inpatients and outpatients)

  • Does not reflect absorption, drug exposure, or elimination

  • Does not give information on other PK parameters

  • Prediction of clinical outcome: conflicting data
 C2

  • Surrogate marker of absorption (Neoral®)

  • Higher sensitivity as indicator of AUC and clinical effect than C0

  • Rigid collection time

  • No distinction between poor absorbers and slow absorbers

  • Prediction of clinical outcome: conflicting data
 Other time points (C3, C4, C6)

  • C0 better correlated with AUC

  • Rigid collection time

  • No distinction between poor absorbers and slow absorbers

  • Hardly any data on their relationship with clinical outcomes
AUC
 Full

  • The best indicator of drug exposure, absorption profile and clinical outcome

  • Characterization of abnormal absorption patterns on concentration-time profile

  • Allows the calculation of oral pharmacokinetic parameters

  • Reduces analytical variability

  • Need for multiple blood samples: impractical for routine clinical use

  • Expensive

  • Inconvenient for patients (outpatients ++)

  • Optimal targets to be defined for most immunosuppressants
 Abbreviated (ex: 4 h post-dose)

  • Good predictor of absorption profile and full AUC

  • Further studies required

  • Optimal targets to be defined
Sparse sampling strategies

  • Balance between precision and practicality

  • Acceptable predictor of AUC

  • Multi-linear regression not based on a PK model. Equations result from correlations and cross-correlations between sampling times and AUC

  • Rigid collection times

  • Analytical method- and centre-specific, often not validated in independent populations
Bayesian forecasting

  • Flexibility in sampling times

  • Limited number of samples needed

  • Can easily be integrated in clinical practice

  • Simultaneous estimation of individual PK parameters and exposure indices

  • Identification of absorption or elimination problems (e.g., gastroparesis)

  • Only a few studies in small populations

  • Predictive performance not tested

  • Requires sophisticated PK models and software