Population and Bayesian pharmacokinetics in oncology

Therapeutic drug monitoring of cancer chemotherapy

Therapeutic drug monitoring is not routinely used for chemotherapy agents. There are Several reasons, but one major drawback is the lack of established therapeutic Concentration ranges. Combination chemotherapy makes the establishment of Therapeutic ranges for individual drugs difficult, the concentration-effect relationship for a single drug may not be the same as when that drug is used in a drug combination. Pharmacokinetic optimization protocols for many classes of cytotoxic compounds exist in specialized centers, and some of these protocols are now part of large multicentre trials. Nonetheless, TDM clearly has the potential to improve the clinical use of chemotherapy gents, most of which have very narrow therapeutic indices and highly variable pharmacokinetics. A substantial body of literature accumulating during the past 15 years demonstrates relationships between systemic exposure to various chemotherapy agents and their toxic or therapeutic effects. This article reviews TDM concepts in addition to tools based on pharmacokinetic modeling of chemotherapy agents. The administered dose of chemotherapy agents is sometimes adjusted individually using either a priori or a posteriori methods. These models can only be applied by using the same dose and schedule as the original study. Bayesian estimation offers more flexibility in blood sampling times and, owing to its precision and to the amount of information provided is the method of choice for ensuring that a given patient benefits from the desired systemic exposure. Moreover, the role and application of Pharmacogenetics as a tool for individualizing chemotherapy is discussed highlighting the agents and mechanisms that have been well studied and defined and their relevance to clinical practice. Finally, this paper address issues critical to the optimal use of TDM in a clinical setting, and the role of clinical pharmacist in this regard. In addition, it discusses future developments in this field that can contribute to improving cancer chemotherapy In terms of patient outcome and survival. J Oncol Pharm Practice (2007) 13: 207—221.

Genetic variability in the multidrug resistance associated protein-1 (ABCC1/MRP1) predicts hematological toxicity in breast cancer patients receiving (neo-)adjuvant chemotherapy with 5-fluorouracil, epirubicin and cyclophosphamide (FEC)

BACKGROUND

To assess the impact of single-nucleotide polymorphisms (SNPs) on predefined severe adverse events in breast cancer (BC) patients receiving (neo-)adjuvant 5-fluorouracil (FU), epirubicin and cyclophosphamide (FEC) chemotherapy.

PATIENTS AND METHODS

Twenty-six SNPs in 16 genes of interest, including the drug transporter gene ABCC1/MRP1, were selected based on a literature survey. An additional 33 SNPs were selected in these genes, as well as in 12 other genes known to be involved in the metabolism of the studied chemotherapeutics. One thousand and twelve female patients treated between 2000 and 2010 with 3-6 cycles of (neo-)adjuvant FEC were genotyped for these SNPs using Sequenom MassARRAY. Severe adverse events were evaluated through an electronic chart review for febrile neutropenia (FN, primary end point), FN first cycle, prolonged grade 4 or deep (<100/µl) neutropenia, anemia grade 3-4, thrombocytopenia grade 3-4 and non-hematological grade 3-4 events (secondary end points).

RESULTS

Carriers of the rs4148350 variant T-allele in ABCC1/MRP1 were associated with FN relative to homozygous carriers of the G-allele [P = 0.0006; false discovery rate (FDR) = 0.026]. Strong correlations with secondary end points such as prolonged grade 4 neutropenia (P = 0.002, FDR = 0.046) were also observed. Additionally, two other SNPs in ABCC1/MRP1 (rs45511401 and rs246221) correlated with FN (P = 0.007 and P = 0.01, respectively; FDR = 0.16 and 0.19), as well as two SNPs in UGT2B7 and FGFR4 (P = 0.024 and P = 0.04; FDR = 0.28 and 0.38).

CONCLUSION

Genetic variability in ABCC1/MRP1 was associated with severe hematological toxicity of FEC.

Dose calculation of anticancer drugs

BACKGROUND

Anticancer drugs are characterized by a narrow therapeutic window and significant inter-patient variability in therapeutic and toxic effects. Current body surface area (BSA)-based dosing fails to standardize systemic anticancer drug exposure and other alternative dosing strategies also have their limitations. Just as important as the initial dose selection is the subsequent dose revision to ensure the dose is correct.

OBJECTIVE

To provide an insight into the different dose individualization and dose adjustment methods, their feasibility and applicability in daily oncology practice and to suggest a practical framework for dose calculation and a basis for future research.

METHODS

Review of relevant literature related to dose calculation of anticancer drugs.

RESULTS

Strategies using clinical parameters, genotype and phenotype markers, and therapeutic drug monitoring all have potential and each has a role for specific drugs. However, no one method is a practical dose calculation strategy for many or all drugs.

CONCLUSION

Given that BSA-dosing leads to significant underdosing it is not reasonable to use this as the sole method of dose calculation. Because of wide disparity in individual patient characteristics and elimination mechanisms, we are unlikely to find the 'Holy Grail' of a single individualized dosing strategy for every patient and anticancer drug in the near future. We propose a pragmatic, although invalidated system for initial dose calculation using dose clusters and structured subsequent dose revision based on treatment-related toxicities and therapeutic drug monitoring. These models need to be tested in clinical trials.

A systematic review of limited sampling strategies for platinum agents used in cancer chemotherapy

Despite evidence in the literature suggesting that a strong correlation exists between the pharmacokinetic parameters and pharmacodynamic effect of anticancer agents, many of these agents are still dosed by body surface area. Therapeutic drug monitoring with the aim of pharmacokinetic-guided dosing would not only maintain target concentrations associated with efficacy but may potentially minimise the likelihood of dose-related systemic toxicities. The pharmacokinetic parameter that displays the best correlation with the pharmacodynamics of anticancer drugs is the area under the plasma concentration-time curve (AUC). However, accurate determination of the AUC requires numerous blood samples over an extended interval, which is not feasible in clinical practice. Therefore, limited sampling strategies (LSSs) have been proposed as a means to accurately and precisely estimate pharmacokinetic parameters with a minimal number of blood samples. LSSs have been developed for many drugs, particularly ciclosporin and other immunosuppressants, as well as for certain anticancer drugs. This systematic review evaluates LSSs developed for the platinum compounds and categorises 18 pertinent citations according to criteria adapted from the US Preventive Services Task Force. Thirteen citations (four level I, six level II-1, three level II-2) pertained to LSSs for carboplatin, four citations (one level II-1, one level II-2, two level III) to cisplatin LSSs, and one citation (level II-2) to nedaplatin. Based on the current evidence, it appears that LSSs may be useful for pharmacokinetic-guided dosage adjustments of carboplatin in both adults and children with cancer. Although some validation studies suggest that LSSs can be extended to different cancer populations or different chemotherapy regimens, other studies dispute this finding. Although the use of LSSs to predict the pharmacokinetic parameters of cisplatin and nedaplatin appear promising, the quality of evidence from published studies does not support routine implementation at this time.LSSs represent one approach in which clinicians can make specific dosage adjustments for individual patients to optimise outcomes. However, the limitations of these strategies must also be taken into consideration. There is also a need for prospective studies to demonstrate that application of LSSs for platinum agents ultimately improves patient response and decreases systemic toxicities.

Pharmacokinetic, biochemical and clinical effects of dimethyltriazenoimidazole-4-carboxamide-bischloroethylnitrosourea combination therapy in patients with advanced breast cancer

We assessed whether split dosing with the methylating agent DTIC is an effective strategy for inactivating the DNA repair protein O6-alkylguanine DNA-ATase in order to decrease tumour resistance to BCNU. ATase levels in PBMCs were used as a surrogate for tumour ATase depletion to determine whether this correlated with either the pharmacokinetics of DTIC and its major metabolite AIC or other clinical sequelae. Two 1 hr infusions of DTIC (400 mg/m(2)) 4 hr apart followed another 4 hr later by BCNU (75 mg/m(2)) were administered every 6 weeks in 7 patients with heavily pretreated advanced breast cancer. The extent and kinetics of ATase depletion and recovery in PBMCs varied not only between patients but also between cycles in the same patient. Serial FNAs showed heterogeneity in tumour ATase expression but no clear pattern of change in ATase activity. DTIC and AIC exhibited biphasic clearance from the blood, consistent with a 2-compartment pharmacokinetic model. The AUC of AIC was strongly correlated with the percentage decrease in PBMC ATase levels. There were no clinical responses, and toxicity in neutrophils and platelets was marked. Split-dose DTIC therefore does not appear to be a clinically effective approach to overcome O(6)-alkylating agent resistance in advanced breast cancer.

Application of pharmacokinetic modelling to the routine therapeutic drug monitoring of anticancer drugs

Over the last 10 years, proofs of the clinical interest of therapeutic drug monitoring (TDM) of certain anticancer drugs have been established. Numerous studies have shown that TDM is an efficient tool for controlling the toxicity of therapeutic drugs, and a few trials have even demonstrated that it can improve their efficacy. This article critically reviews TDM tools based on pharmacokinetic modelling of anticancer drugs. The administered dose of anticancer drugs is sometimes adjusted individually using either a priori or a posteriori methods. The most frequent clinical application of a priori formulae concerns carboplatin and allows the computation of the first dose based on biometrical and biological data such as weight, age, gender, creatinine clearance and glomerular filtration rate. A posteriori methods use drug plasma concentrations to adjust the subsequent dose(s). Thus, nomograms allowing dose adjustment on the basis of blood concentration are routinely used for 5-fluorouracil given as long continuous infusions. Multilinear regression models have been developed, for example for etoposide, doxorubicin. carboplatin, cyclophosphamide and irinotecan, to predict a single exposure variable [such as area under concentration-time curve (AUC)] from a small number of plasma concentrations obtained at predetermined times after a standard dose. These models can only be applied by using the same dose and schedule as the original study. Bayesian estimation offers more flexibility in blood sampling times and, owing to its precision and to the amount of information provided, is the method of choice for ensuring that a given patient benefits from the desired systemic exposure. Unlike the other a posteriori methods, Bayesian estimation is based on population pharmacokinetic studies and can take into account the effects of different individual factors on the pharmacokinetics of the drug. Bayesian estimators have been used to determine maximum tolerated systemic exposure thresholds (e.g. for topotecan or teniposide) as well as for the routine monitoring of drugs characterized by a very high interindividual pharmacokinetic variability such as methotrexate or carboplatin. The development of these methods has contributed to improving cancer chemotherapy in terms of patient outcome and survival and should be pursued.

Adaptive control methods for the dose individualisation of anticancer agents

Numerous studies have found a clear relationship between systemic exposure and the toxicity or (more rarely) the efficacy of anticancer agents. Moreover, the clearance of most of these drugs differs widely between patients. These findings, combined with the narrow therapeutic index of anticancer drugs, suggest that patient outcome would be improved if doses were individualised to achieve a target systemic exposure. Bayesian maximum a posteriori probability (MAP) forecasting is an efficient and robust method for the optimisation of drug therapy, but its use for anticancer drugs is not yet extensive. The aim of this paper is to review the application of population pharmacokinetics and MAP to anticancer drugs and to evaluate whether and when MAP Bayesian estimation improves the clinical benefit of anticancer chemotherapy. For each drug, the relationships between pharmacokinetic variables [e.g. plasma concentration or the area under the concentration-time curve] and pharmacodynamic effects are described. Secondly, the methodologies employed are considered and, finally, the results are analysed in terms of predictive performance as well as, where possible, the impact on clinical end-points. Some studies were retrospective and intended only to evaluate individual pharmacokinetic parameter values using very few blood samples. Among the prospective trials, a few studied the pharmacokinetic/pharmacodynamic relationships which provided the basis for routine pharmacokinetic monitoring. Others were performed in clinical context where MAP Bayesian estimation was used to determine maximum tolerated systemic exposure (e.g. for carboplatin, topotecan, teniposide) or for pharmacokinetic monitoring (e.g. for methotrexate or platinum compounds). Indeed, its flexibility in blood sampling times makes this technique much more applicable than other limited sampling strategies. These examples demonstrate that individual dose adjustment helps manage toxicity. The performance of pharmacokinetic monitoring is linked to the methodology used at each step of its design and application. Moreover, a limitation to the use of pharmacokinetic monitoring for certain anticancer drugs has been the difficulty in obtaining pharmacokinetic or pharmacodynamic data. Recent progress in analytical methods, as well as the development of noninvasive methods (such as positron emission tomography) for evaluating the effects of chemotherapy, will help to define pharmacokinetic-pharmacodynamic relationships. Bayesian estimation is the strategy of choice for performing pharmacokinetic studies, as well as ensuring that a given patient benefits from the desired systemic exposure. Together, these methods could contribute to improving cancer chemotherapy in terms of patient outcome and survival.

In vivo monitoring of drugs using radiotracer techniques

There is an increasing realization of the role of non-invasive monitoring of drug pharmacology. In this review, we discuss the role of positron emission tomography in such monitoring of tumour and normal tissue drug pharmacokinetics as well as assessment of tumour response, drug-receptor interactions and mechanisms of drug action and resistance. These studies represent a multidisciplinary research effort involving radiochemists, imaging scientists, clinicians, pharmacologists and mathematical modellers. This review evaluates achievements in the field from assessment of commonly used therapeutic agents such as 5-fluorouracil to target specific molecules such as markers for gene expression. It is envisaged that application of this technology will facilitate rational drug design and rapid translation of new ideas to the bedside.