• Translational and Clinical Pharmacology
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• v.26 no.4
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• pp.150-154
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• 2018

This tutorial reviews the principles of dose individualisation with an emphasis on target concentration intervention (TCI). Once a target effect is chosen then pharmacodynamics can predict the target concentration and pharmacokinetics can predict the target dose to achieve the required response. Dose individualisation can be considered at three levels: population, group and individual. Population dosing, also known as fixed dosing or "one size fits all" is often used but is poor clinical pharmacology; group dosing uses patient features such as weight, organ function and comedication to adjust the dose for a typical patient; individual dosing uses observations of patient response to inform about pharmacokinetic and pharmacodynamics in the individual and use these individual differences to individualise dose.

• Korean Journal of Clinical Pharmacy
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• v.27 no.4
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• pp.258-266
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• 2017

Objective: To develop a population pharmacokinetics (PK)/pharmacodynamics (PD) model for alcohol in healthy volunteers and to elucidate individual characteristics to affects alcohol's PK or PD including dissolved oxygen. Methods: Following multiple intakes of total 540 mL alcohol (19.42 v/v%) to healthy volunteer, blood alcohol concentration was measured using a Breathe alcohol analyser (Lion SD-400 $Alcolmeter^{(R)}$). A sequential population PK/PD modeling was performed using NONMEM (ver 7.3). Results: Eighteen healthy volunteer were included in the study. PK model of alcohol was well explained by one-compartment model with first-order absorption and Michaelis-Menten elimination kinetics. $K_a$, V/F, $V_{max}$, $K_m$ is $8.1hr^{-1}$, 73.7 L, 9.65 g/hr, 0.041 g/L, respectively. Covariate analysis revealed that gender significantly influenced $V_{max}$ (Male vs Female, 9.65 g/hr vs 7.38 g/hr). PD model of temporary systolic blood pressure decreasing effect of alcohol was explained by biophase model with inhibitory $E_{max}$ model. $K_{e0}$, $I_{max}$, $E_0$, $IC_{50}$ were $0.23hr^{-1}$, 44.9 mmHg, 138 mmHg, 0.693 g/L, respectively. Conclusion: Model evaluation results suggested that this PK/PD model was robust and has good precision.

• Journal of Gastric Cancer
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• v.4 no.2
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• pp.59-74
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• 2004

This report attempts to explain the (i) implications of comorbidity for research and practice in the fieldo of oncology, (ii) the approach for dosing of anti-cancer drugs in the presence of comorbidity, as an example of its clinical application, and finally (iii) the dosing guidelines for the anticancer drugs clinically active in gastric cancer in the presence of renal or liver dysfunction. This has resulted from the idea of approaching comorbidity in a systematic way and of integrating it with oncologic decisions. Various methods have been used to assess comorbidity. However, significant work remains to be done to analyze how various diseases combine to influence the oncologic outcome. The main end-point explored so far has been mortality, but a largely open challenge remains to correlate comorbidity with treatment tolerance and functional and quality of life, as well as to integrate it in clinical decision-making. Cancer chemotherapy in comorbidity should be considered as an example of the need for dose optimization in individual patients, and it should be determined by considering the basic principles of the pharmacokinetics and the pharmacodynamics of the agents. This review analyzes the available data on the pharmacokinetics and the toxicities of anti-cancer agents in the comorbidity population.

• The Korean Journal of Physiology and Pharmacology
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• v.15 no.2
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• pp.67-81
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• 2011

Epilepsy is a chronic disease occurring in approximately 1.0% of the world's population. About 30% of the epileptic patients treated with availably antiepileptic drugs (AEDs) continue to have seizures and are considered therapy-resistant or refractory patients. The ultimate goal for the use of AEDs is complete cessation of seizures without side effects. Because of a narrow therapeutic index of AEDs, a complete understanding of its clinical pharmacokinetics is essential for understanding of the pharmacodynamics of these drugs. These drug concentrations in biological fluids serve as surrogate markers and can be used to guide or target drug dosing. Because early studies demonstrated clinical and/or electroencephalographic correlations with serum concentrations of several AEDs, It has been almost 50 years since clinicians started using plasma concentrations of AEDs to optimize pharmacotherapy in patients with epilepsy. Therefore, validated analytical method for concentrations of AEDs in biological fluids is a necessity in order to explore pharmacokinetics, bioequivalence and TDM in various clinical situations. There are hundreds of published articles on the analysis of specific AEDs by a wide variety of analytical methods in biological samples have appears over the past decade. This review intends to provide an updated, concise overview on the modern method development for monitoring AEDs for pharmacokinetic studies, bioequivalence and therapeutic drug monitoring.

• Translational and Clinical Pharmacology
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• v.26 no.4
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• pp.160-165
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• 2018

Indobufen ($Ibustrin^{(R)}$), a reversible inhibitor of platelet aggregation, exists in two enantiomeric forms in 1:1 ratio. Here, we characterized the anti-platelet effect of S- and R-indobufen using response surface modeling using $NONMEM^{(R)}$ and predicted the therapeutic doses exerting the maximal efficacy of each enantioselective S- and R-indobufen formulation. S- and R-indobufen were added individually or together to 24 plasma samples from drug-naïve healthy subjects, generating 892 samples containing randomly selected concentrations of the drugs of 0-128 mg/L. Collagen-induced platelet aggregation in platelet-rich plasma was determined using a Chrono-log Lumi-Aggregometer. Inhibitory sigmoid $I_{max}$ model adequately described the anti-platelet effect. The S-form was more potent, whereas the R-form showed less inter-individual variation. No significant interaction was observed between the two enantiomers. The anti-platelet effect of multiple treatments with 200 mg indobufen twice daily doses was predicted in the simulation study, and the effect of S- or R-indobufen alone at various doses was predicted to define optimal dosing regimen for each enantiomer. Simulation study predicted that 200 mg twice daily administration of S-indobufen alone will produce more treatment effect than S-and R-mixture formulation. S-indobufen produced treatment effect at lower concentration than R-indobufen. However, inter-individual variation of the pharmacodynamic response was smaller in R-indobufen. The present study suggests the optimal doses of R-and S-enantioselective indobufen formulations in terms of treatment efficacy for patients with thromboembolic problems. The proposed methodology in this study can be applied to the develop novel enantio-selective drugs more efficiently.