Quantitative modeling of tumor dynamics and development of drug resistance in non-small cell lung cancer patients treated with erlotinib.

Insight into the development of treatment resistance can support the optimization of anticancer treatments. This study aims to characterize the tumor dynamics and development of drug resistance in patients with non-small cell lung cancer treated with erlotinib, and investigate the relationship between baseline circulating tumor DNA (ctDNA) data and tumor dynamics. Data obtained for the analysis included (1) intensively sampled erlotinib concentrations from 29 patients from two previous pharmacokinetic (PK) studies, and (2) tumor sizes, ctDNA measurements, and sparsely sampled erlotinib concentrations from 18 patients from the START-TKI study. A two-compartment population PK model was first developed which well-described the PK data. The PK model was subsequently applied to investigate the exposure-tumor dynamics relationship. To characterize the tumor dynamics, models accounting for intra-tumor heterogeneity and acquired resistance with or without primary resistance were investigated. Eventually, the model assumed acquired resistance only resulted in an adequate fit. Additionally, models with or without exposure-dependent treatment effect were explored, and no significant exposure-response relationship for erlotinib was identified within the observed exposure range. Subsequently, the correlation of baseline ctDNA data on EGFR and TP53 variants with tumor dynamics' parameters was explored. The analysis indicated that higher baseline plasma EGFR mutation levels correlated with increased tumor growth rates, and the inclusion of ctDNA measurements improved model fit. This result suggests that quantitative ctDNA measurements at baseline have the potential to be a predictor of anticancer treatment response. The developed model can potentially be applied to design optimal treatment regimens that better overcome resistance.

Anti-cancer treatment schedule optimization based on tumor dynamics modelling incorporating evolving resistance.

Quantitative characterization of evolving tumor resistance under targeted treatment could help identify novel treatment schedules, which may improve the outcome of anti-cancer treatment. In this study, a mathematical model which considers various clonal populations and evolving treatment resistance was developed. With parameter values fitted to the data or informed by literature data, the model could capture previously reported tumor burden dynamics and mutant KRAS levels in circulating tumor DNA (ctDNA) of patients with metastatic colorectal cancer treated with panitumumab. Treatment schedules, including a continuous schedule, intermittent schedules incorporating treatment holidays, and adaptive schedules guided by ctDNA measurements were evaluated using simulations. Compared with the continuous regimen, the simulated intermittent regimen which consisted of 8-week treatment and 4-week suspension prolonged median progression-free survival (PFS) of the simulated population from 36 to 44 weeks. The median time period in which the tumor size stayed below the baseline level (TTS

Population Pharmacokinetic and Pharmacogenetic Analysis of Mitotane in Patients with Adrenocortical Carcinoma: Towards Individualized Dosing.

BACKGROUND: Mitotane is the only approved treatment for patients with adrenocortical carcinoma (ACC). A better explanation for the variability in the pharmacokinetics (PK) of mitotane, and the optimization and individualization of mitotane treatment, is desirable for patients. OBJECTIVES: This study aims to develop a population PK (PopPK) model to characterize and predict the PK profiles of mitotane in patients with ACC, as well as to explore the effect of genetic variation on mitotane clearance. Ultimately, we aimed to facilitate mitotane dose optimization and individualization for patients with ACC. METHODS: Mitotane concentration and dosing data were collected retrospectively from the medical records of patients with ACC taking mitotane orally and participating in the Dutch Adrenal Network. PopPK modelling analysis was performed using NONMEM (version 7.4.1). Genotypes of drug enzymes and transporters, patient demographic information, and clinical characteristics were investigated as covariates. Subsequently, simulations were performed for optimizing treatment regimens. RESULTS: A two-compartment model with first-order absorption and elimination best described the PK data of mitotane collected from 48 patients. Lean body weight (LBW) and genotypes of CYP2C19*2 (rs4244285), SLCO1B3 699A>G (rs7311358) and SLCO1B1 571T>C (rs4149057) were found to significantly affect mitotane clearance (CL/F), which decreased the coefficient of variation (CV%) of the random inter-individual variability of CL/F from 67.0 to 43.0%. Fat amount (i.e. body weight - LBW) was found to significantly affect the central distribution volume. Simulation results indicated that determining the starting dose using the developed model is beneficial in terms of shortening the period to reach the therapeutic target and limit the risk of toxicity. A regimen that can effectively maintain mitotane concentration within 14-20 mg/L was established. CONCLUSIONS: A two-compartment PopPK model well-characterized mitotane PK profiles in patients with ACC. The CYP2C19 enzyme and SLCO1B1 and SLCO1B3 transporters may play roles in mitotane disposition. The developed model is beneficial in terms of optimizing mitotane treatment schedules and individualizing the initial dose for patients with ACC. Further validation of these findings is still required.

A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors.

Increasing knowledge of intertumor heterogeneity, intratumor heterogeneity, and cancer evolution has improved the understanding of anticancer treatment resistance. A better characterization of cancer evolution and subsequent use of this knowledge for personalized treatment would increase the chance to overcome cancer treatment resistance. Model-based approaches may help achieve this goal. In this review, we comprehensively summarized mathematical models of tumor dynamics for solid tumors and of drug resistance evolution. Models displayed by ordinary differential equations, algebraic equations, and partial differential equations for characterizing tumor burden dynamics are introduced and discussed. As for tumor resistance evolution, stochastic and deterministic models are introduced and discussed. The results may facilitate a novel model-based analysis on anticancer treatment response and the occurrence of resistance, which incorporates both tumor dynamics and resistance evolution. The opportunities of a model-based approach as discussed in this review can be of great benefit for future optimizing and personalizing anticancer treatment.

Pharmacokinetic-pharmacodynamic analysis of ciprofloxacin in elderly Chinese patients with lower respiratory tract infections caused by Gram-negative bacteria.

BACKGROUND: Ciprofloxacin is usually used in the treatment of lower respiratory tract infections (LRTIs). Recent studies abroad have shown ciprofloxacin is inadequately dosed and might lead to worse outcomes. The aim of this study was to perform pharmacokinetic and pharmacodynamic analyses of ciprofloxacin in elderly Chinese patients with severe LRTIs caused by Gram-negative bacteria. METHODS: From September 2012 to June 2014, as many as 33 patients were empirically administered beta-lactam and ciprofloxacin combination therapy. Patients were infused with 200 or 400 mg of ciprofloxacin every 12 h, which was determined empirically by the attending physician based on the severity of the LRTI and the patient's renal condition. Ciprofloxacin serum concentrations were determined by high-performance liquid chromatography. Bacterial culture was performed from sputum samples and/or endotracheal aspirates, and the minimum inhibitory concentrations (MICs) of ciprofloxacin were determined. The ratios of the area under the serum concentration-time curve to the MIC (AUC/MIC) and of the maximum serum concentration of the drug to the MIC (Cmax/MIC) were calculated. The baseline data and pharmacokinetic parameters were compared between clinical success group and clinical failure group, bacteriologic success group and bacteriologic failure group. RESULTS: Among the 33 patients enrolled in the study, 17 were infected with Pseudomonas aeruginosa, 14 were infected with Acinetobacter baumannii, and two were infected with Klebsiella pneumoniae. The mean age of the patients was 76.9 ± 6.7 years. Thirty-one patients (93.4%) did not reach the target AUC/MIC value of >125, and 29 patients (87.9%) did not reach the target Cmax/MIC value of >8. The AUC/MIC and Cmax/MIC ratios in the clinical success group were significantly higher than those in the clinical failure group (61.1 [31.7-214.9] vs. 10.4 [3.8-66.1], Z = -4.157; 9.6 [4.2-17.8] vs. 1.3 [0.4-4.7], Z = -4.018; both P < 0.001). The AUC/MIC and Cmax/MIC ratios in the patients for whom the pathogens were eradicated were significantly higher than those in the patients without the pathogens eradicated (75.3 [31.7-214.9] vs. 10.5 [3.8-66.1], Z = -3.938; 11.4 [4.2-17.8] vs. 1.4 [0.4-5.4], Z = -3.793; P < 0.001 for both). Receiver operating characteristic curve analysis showed that the AUC/MIC and Cmax/MIC values were closely associated with clinical and bacteriologic efficacies (P < 0.001 in both). CONCLUSIONS: Ciprofloxacin is inadequately dosed against Gram-negative bacteria, especially for those with relatively high MIC values. Consequently, the target values, AUC/MIC > 125 and Cmax/MIC > 8, cannot be reached.

Quantitative systems pharmacology analysis of drug combination and scaling to humans: the interaction between noradrenaline and vasopressin in vasoconstriction.

BACKGROUND AND PURPOSE: Development of combination therapies has received significant interest in recent years. Previously, a two-receptor one-transducer (2R-1T) model was proposed to characterize drug interactions with two receptors that lead to the same phenotypic response through a common transducer pathway. We applied, for the first time, the 2R-1T model to characterize the interaction of noradrenaline and arginine-vasopressin on vasoconstriction and performed inter-species scaling to humans using this mechanism-based model. EXPERIMENTAL APPROACH: Contractile data were obtained from in vitro rat small mesenteric arteries after exposure to single or combined challenges of noradrenaline and arginine-vasopressin with or without pretreatment with the irreversible α-adrenoceptor antagonist, phenoxybenzamine. Data were analysed using the 2R-1T model to characterize the observed exposure-response relationships and drug-drug interaction. The model was then scaled to humans by accounting for differences in receptor density. KEY RESULTS: With receptor affinities set to published values, the 2R-1T model satisfactorily characterized the interaction between noradrenaline and arginine-vasopressin in rat small mesenteric arteries (relative standard error ≤20%), as well as the effect of phenoxybenzamine. Furthermore, after scaling the model to human vascular tissue, the model also adequately predicted the interaction between both agents on human renal arteries. CONCLUSIONS AND IMPLICATIONS: The 2R-1T model can be of relevance to quantitatively characterize the interaction between two drugs that interact via different receptors and a common transducer pathway. Its mechanistic properties are valuable for scaling the model across species. This approach is therefore of significant value to rationally optimize novel combination treatments.

Population pharmacokinetics analysis of olanzapine for Chinese psychotic patients based on clinical therapeutic drug monitoring data with assistance of meta-analysis.

PURPOSE: The aim of this study was to build an eligible population pharmacokinetic (PK) model for olanzapine in Chinese psychotic patients based on therapeutic drug monitoring (TDM) data, with assistance of meta-analysis, to facilitate individualized therapy. METHODS: Population PK analysis for olanzapine was performed using NONMEM software (version 7.3.0). TDM data were collected from Guangzhou Brain Hospital (China). Because of the limitations of TDM data, model-based meta-analysis was performed to construct a structural model to assist the modeling of TDM data as prior estimates. After analyzing related covariates, a simulation was performed to predict concentrations for different types of patients under common dose regimens. RESULTS: A two-compartment model with first-order absorption and elimination was developed for olanzapine oral tablets, based on 23 articles with 390 data points. The model was then applied to the TDM data. Gender and smoking habits were found to be significant covariates that influence the clearance of olanzapine. To achieve a blood concentration of 20 ng/mL (the lower boundary of the recommended therapeutic range), simulation results indicated that the dose regimen of olanzapine should be 5 mg BID (twice a day), ≥ 5 mg QD (every day) plus 10 mg QN (every night), or >10 mg BID for female nonsmokers, male nonsmokers and male smokers, respectively. CONCLUSION: The population PK model, built using meta-analysis, could facilitate the modeling of TDM data collected from Chinese psychotic patients. The factors that significantly influence olanzapine disposition were determined and the final model could be used for individualized treatment.

[Population pharmacokinetics of ciprofloxacin in Chinese elderly patients with lower respiratory tract infection].

OBJECTIVE: To analyse population pharmacokinetic (PPK) parameter values of ciprofloxacin in Chinese elderly patients with lower respiratory tract infection. METHODS: Hospitalized in Respiratory Intensive Care Unit (RICU) due to severe lower respiratory tract infection and at high risks of Pseudomonas aeruginosa. 43 consecutive elderly patients received an intravenous infusion of ciprofloxacin at a dose of 200/400 mg every 12/24 h empirically. Plasma samples were drawn from Day 4 and at 1, 2, 3, 4, 6, 8 and 12 h after infusion. The serum concentrations of ciprofloxacin were determined by high-performance liquid chromatography (HPLC). Ciprofloxacin population pharmacokinetic analysis was conducted by the NONMEM 7.3.0 software. RESULTS: Forty patients aged (78 ± 9) years completed the study. A total of 210 serum concentrations were detected. The mean values of clearance and volume of distribution (V1) were 17.8 L/h and 49.8 L respectively. The serum creatinine level influenced ciprofloxacin according to the equation: Clearance - 17.8 × [1 - 0.001 3 × (serum creatinine - 67)] × e(η1i) × 0.659(n) (at a dose of 200 mg, n - 1, at a dose of 400 mg, n - 0; ηi for inter individual random variation). The values of clearance and V1 were multiplied by 0.659 at a dose of 200 mg. At the doses of 200 and 400 mg, the maximum steady-state concentrations (C(max)) were (4.2 ± 1.1) and (5.3 ± 1.21) mg/L, the minimum steady-state concentrations (C(min)) (1.1 ± 1.1) and (0.8 ± 0.4) mg/L and the area under concentration-time curve measured in steady-state up to 24 h after dosing (AUC(0-24 h)) were (45.5 ± 28.1) and (47.2 ± 11.3) mg · h · L⁻¹ respectively. CONCLUSIONS: The clearance of ciprofloxacin in elderly patients significantly decreases as compared with adult patients. Ciprofloxacin PPK model shows a significant influence of serum creatinine level on ciprofloxacin clearance. A single dose of 400 mg may increase serum drug concentration, but causes no in vivo drug retention.