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

Quantification of biochemical PSA dynamics after radioligand therapy with [177Lu]Lu-PSMA-I&T using a population pharmacokinetic/pharmacodynamic model

BACKGROUND

There is an unmet need for prediction of treatment outcome or patient selection for [177Lu]Lu-PSMA therapy in patients with metastatic castration-resistant prostate cancer (mCRPC). Quantification of the tumor exposure-response relationship is pivotal for further treatment optimization. Therefore, a population pharmacokinetic (PK) model was developed for [177Lu]Lu-PSMA-I&T using SPECT/CT data and, subsequently, related to prostate-specific antigen (PSA) dynamics after therapy in patients with mCRPC using a pharmacokinetic/pharmacodynamic (PKPD) modelling approach.

METHODS

A population PK model was developed using quantitative SPECT/CT data (406 scans) of 76 patients who received multiple cycles [177Lu]Lu-PSMA-I&T (± 7.4 GBq with either two- or six-week interval). The PK model consisted of five compartments; central, salivary glands, kidneys, tumors and combined remaining tissues. Covariates (tumor volume, renal function and cycle number) were tested to explain inter-individual variability on uptake into organs and tumors. The final PK model was expanded with a PD compartment (sequential fitting approach) representing PSA dynamics during and after treatment. To explore the presence of a exposure-response relationship, individually estimated [177Lu]Lu-PSMA-I&T tumor concentrations were related to PSA changes over time.

RESULTS

The population PK model adequately described observed data in all compartments (based on visual inspection of goodness-of-fit plots) with adequate precision of parameters estimates (< 36.1% relative standard error (RSE)). A significant declining uptake in tumors (k14) during later cycles was identified (uptake decreased to 73%, 50% and 44% in cycle 2, 3 and 4-7, respectively, compared to cycle 1). Tumor growth (defined by PSA increase) was described with an exponential growth rate (0.000408 h-1 (14.2% RSE)). Therapy-induced PSA decrease was related to estimated tumor concentrations (MBq/L) using both a direct and delayed drug effect. The final model adequately captured individual PSA concentrations after treatment (based on goodness-of-fit plots). Simulation based on the final PKPD model showed no evident differences in response for the two different dosing regimens currently used.

CONCLUSIONS

Our population PK model accurately described observed [177Lu]Lu-PSMA-I&T uptake in salivary glands, kidneys and tumors and revealed a clear declining tumor uptake over treatment cycles. The PKPD model adequately captured individual PSA observations and identified population response rates for the two dosing regimens. Hence, a PKPD modelling approach can guide prediction of treatment response and thus identify patients in whom radioligand therapy is likely to fail.

Limited sampling strategies for therapeutic drug monitoring of anti-tuberculosis medications: A systematic review of their feasibility and clinical utility

Therapeutic drug monitoring (TDM) is recommended for medications with high inter-individual variability, narrow therapeutic index drugs, possible drug-drug interactions, drug toxicity, and subtherapeutic concentrations, as well as to assess noncompliance. The area under the plasma concentration-time curve (AUC) is a significant pharmacokinetic parameter since it calculates the drug's total systematic exposure in the body. However, multiple blood samples from the patient are required to calculate the area under the curve, which is inconvenient for both the patient and the healthcare professional. To alleviate the issue, the limited sampling strategy (LSS) was devised, in which sampling is minimized while obtaining complete and precise findings to anticipate the area under the curve. One can reduce costs, labor, and discomfort for patients and healthcare workers by applying this limited sampling strategy. This article examines a systematic evaluation of all the limited sampling done in anti-tuberculosis (anti-TB) medications resulting from the literature search of several research papers. This article also briefly describes the two methodologies: Multiple regression analysis (MRA) and the Bayesian approach used to develop a limited sampling strategy model. Anti-TB medications have been found to have considerable inter-individual variability, and isoniazid has a narrow therapeutic index, both of which are criteria for therapeutic drug monitoring. To avoid multi-drug resistance and therapy failure, it is proposed that limited sampling strategy-based therapeutic drug monitoring of anti-TB medications be undertaken to generate an individualized dose regimen, particularly for individuals at high risk of treatment failure or delayed response.

Pharmacokinetics of single- and multiple-dose flumatinib in patients with chronic phase chronic myeloid leukemia

Introduction

Flumatinib is a novel, oral breakpoint cluster region-abelson (BCR-ABL) tyrosine kinase inhibitor that has demonstrated manageable safety and promising efficacy in patients with newly diagnosed chronic phase (CP) chronic myeloid leukemia (CML).

Methods

This study evaluated the pharmacokinetic (PK) profiles of flumatinib mesylate tablets at a dose of 400 mg and 600 mg in patients with CML-CP. The study was registered at chictr.org Identifier (ChiCTR2100044700). In this open-label, pharmacokinetic study, eligible patients were administered a single-dose of flumatinib 400 mg or 600 mg on day 1, followed by 2-day washout and 8 consecutive days of once-daily administration. Serial plasma samples were assayed for flumatinib and its metabolites (N-demethylate metabolite M1 and amide-bond hydrolytic metabolite M3).

Results

Twenty-nine patients were assigned to flumatinib 400 mg (n=14) or 600 mg (n=15). Serum concentrations of flumatinib reached maximum measured plasma concentration (Cmax) at a median time of 2 hours after each single dose, and then eliminated slowly with a mean apparent terminal disposition half-life (t1/2) from 16.0 to 16.9 hours. Following single- and multiple-dose administration, flumatinib exposure (Cmax, area under the concentration-time curve from 0 to t hours (AUC_0-t), area under the concentration-time curve from 0 hours to infinity (AUC_0-∞)) increased in an approximately dose-proportional manner. There was approximately 4.1- and 3.4- fold drug accumulation at steady-state after multiple-dose administration at 400 mg and 600 mg, respectively. The drug-related AEs associated with both treatments were primarily low-grade and tolerable events.

Conclusion

Analysis of PK parameters indicated that flumatinib exposure increased in an approximately dose-proportional manner. Further research needs to be conducted in a large sample-size study.

Bayesian method application: Integrating mathematical modeling into clinical pharmacy through vancomycin therapeutic monitoring

The most recent consensus guidelines for dosing and monitoring vancomycin recommended the use of area-under-the-curve with Bayesian estimation for therapeutic monitoring. As this is a modern concept in the practice of clinical pharmacy, the main objective of this review is to introduce the fundamentals of Bayesian estimation and its mathematical application as it relates to vancomycin therapeutic drug monitoring. In addition, we aim to identify pharmacokinetic (PK) software programs that incorporate Bayesian estimation for vancomycin dosing and to describe the PK models utilized in those software programs for the adult population. Twelve software programs that utilize Bayesian estimation were identified, which included: Adult and Pediatric Kinetics, Best Dose, ClinCalc, DoseMeRx, ID-ODS, InsightRx, MwPharm++, NextDose, PrecisePK, TDMx, Tucuxi, and VancoCalc. The software programs varied in the population PK models used as the Bayesian a priori. With the presence of various vancomycin Bayesian software programs, it is important to choose those that utilize PK models reflective of the specific patient population.

Therapeutic Drug Monitoring of Targeted Anticancer Protein Kinase Inhibitors in Routine Clinical Use: A Critical Review

BACKGROUND

Therapeutic response to oral targeted anticancer protein kinase inhibitors (PKIs) varies widely between patients, with insufficient efficacy of some of them and unacceptable adverse reactions of others. There are several possible causes for this heterogeneity, such as pharmacokinetic (PK) variability affecting blood concentrations, fluctuating medication adherence, and constitutional or acquired drug resistance of cancer cells. The appropriate management of oncology patients with PKI treatments thus requires concerted efforts to optimize the utilization of these drug agents, which have probably not yet revealed their full potential.

METHODS

An extensive literature review was performed on MEDLINE on the PK, pharmacodynamics, and therapeutic drug monitoring (TDM) of PKIs (up to April 2019).

RESULTS

This review provides the criteria for determining PKIs suitable candidates for TDM (eg, availability of analytical methods, observational PK studies, PK-pharmacodynamics relationship analysis, and randomized controlled studies). It reviews the major characteristics and limitations of PKIs, the expected benefits of TDM for cancer patients receiving them, and the prerequisites for the appropriate utilization of TDM. Finally, it discusses various important practical aspects and pitfalls of TDM for supporting better implementation in the field of cancer treatment.

CONCLUSIONS

Adaptation of PKIs dosage regimens at the individual patient level, through a rational TDM approach, could prevent oncology patients from being exposed to ineffective or unnecessarily toxic drug concentrations in the era of personalized medicine.

Therapeutic drug monitoring of oral targeted antineoplastic drugs

PURPOSE

This review provides an overview of the current challenges in oral targeted antineoplastic drug (OAD) dosing and outlines the unexploited value of therapeutic drug monitoring (TDM). Factors influencing the pharmacokinetic exposure in OAD therapy are depicted together with an overview of different TDM approaches. Finally, current evidence for TDM for all approved OADs is reviewed.

METHODS

A comprehensive literature search (covering literature published until April 2020), including primary and secondary scientific literature on pharmacokinetics and dose individualisation strategies for OADs, together with US FDA Clinical Pharmacology and Biopharmaceutics Reviews and the Committee for Medicinal Products for Human Use European Public Assessment Reports was conducted.

RESULTS

OADs are highly potent drugs, which have substantially changed treatment options for cancer patients. Nevertheless, high pharmacokinetic variability and low treatment adherence are risk factors for treatment failure. TDM is a powerful tool to individualise drug dosing, ensure drug concentrations within the therapeutic window and increase treatment success rates. After reviewing the literature for 71 approved OADs, we show that exposure-response and/or exposure-toxicity relationships have been established for the majority. Moreover, TDM has been proven to be feasible for individualised dosing of abiraterone, everolimus, imatinib, pazopanib, sunitinib and tamoxifen in prospective studies. There is a lack of experience in how to best implement TDM as part of clinical routine in OAD cancer therapy.

CONCLUSION

Sub-therapeutic concentrations and severe adverse events are current challenges in OAD treatment, which can both be addressed by the application of TDM-guided dosing, ensuring concentrations within the therapeutic window.

Feasibility of Extrapolating Randomly Taken Plasma Samples to Trough Levels for Therapeutic Drug Monitoring Purposes of Small Molecule Kinase Inhibitors

Small molecule kinase inhibitors (SMKIs) are widely used in oncology. Therapeutic drug monitoring (TDM) for SMKIs could reduce underexposure or overexposure. However, logistical issues such as timing of blood withdrawals hamper its implementation into clinical practice. Extrapolating a random concentration to a trough concentration using the elimination half-life could be a simple and easy way to overcome this problem. In our study plasma concentrations observed during 24 h blood sampling were used for extrapolation to trough levels. The objective was to demonstrate that extrapolation of randomly taken blood samples will lead to equivalent estimated trough samples compared to measured C_min values. In total 2241 blood samples were analyzed. The estimated C_trough levels of afatinib and sunitinib fulfilled the equivalence criteria if the samples were drawn after T_max. The calculated C_trough levels of erlotinib, imatinib and sorafenib met the equivalence criteria if they were taken, respectively, 12 h, 3 h and 10 h after drug intake. For regorafenib extrapolation was not feasible. In conclusion, extrapolation of randomly taken drug concentrations to a trough concentration using the mean elimination half-life is feasible for multiple SMKIs. Therefore, this simple method could positively contribute to the implementation of TDM in oncology.

A Critique of Pharmacokinetic Calculators for Drug Dosing Individualization

The 'one-dose-fits-all' approach where drug dosing regimen is prescribed according to recommendations from a summary of product characteristics is not appropriate for many patients whose clinical characteristics significantly differ from the most frequent ones in a population, as it cannot guarantee optimal exposure of target tissues to the drug. Our aim here is to provide a concise review of pharmacokinetic calculators currently available for clinical use and, at the same time, to suggest the minimum standards that they should satisfy to be routinely used in clinical practice. A systematic search of Medline, Ebsco, Scopus, Scindeks, Cochrane Library and Google Scholar was performed to find publications about available pharmacokinetic calculators for drug dose individualization. Theoretically well-founded and mathematically correct calculators for many drugs are available, but only a few calculators for specific drugs have been validated in clinical practice or through clinical trials, and the results published in peer-reviewed journals. The majority of available pharmacokinetic calculators for drug dosing individualization remain unvalidated, i.e., there is no evidence of their efficacy and safety in real-life clinical settings. Pharmacokinetic calculators for drug dose individualization are irreplaceable tools for achieving precision medicine, where dosing regimens are tailored to the needs and personal characteristics of each patient, maximizing efficacy and minimizing toxicity.

DOX sensitized upconversion metal-organic frameworks for the pH responsive release and real-time detection of doxorubicin hydrochloride

Drug resistance is a major obstacle in cancer treatment, and designing a material that monitors real-time drug release remains a top priority. In this study, metal-organic frameworks doped with lanthanum and thulium were synthesized and then coated with aminated silica to form La/Tm-MOF@d-SiO2 as a drug carrier. Doxorubicin hydrochloride (DOX) was selected as a drug model, and the drug loading and release were investigated. It was found that the release of DOX under acidic conditions reached an optimal level, indicating the pH-responsiveness of La/Tm-MOF@d-SiO2. Under acidic conditions (pH = 5.8), upconversion fluorescence was generated after loading DOX on La/Tm-MOF@d-SiO2. At pH = 5.8, the longer the drug released, the stronger the upconversion fluorescence. It was found that the upconversion fluorescence intensity is directly proportional to the amount of drug released; thus, the real-time monitoring of DOX release in tumor cells can be performed based on the upconversion fluorescence.

MTXPK.org: A Clinical Decision Support Tool Evaluating High-Dose Methotrexate Pharmacokinetics to Inform Post-Infusion Care and Use of Glucarpidase

Methotrexate (MTX), an antifolate, is administered at high doses to treat malignancies in children and adults. However, there is considerable interpatient variability in clearance of high‐dose (HD) MTX. Patients with delayed clearance are at an increased risk for severe nephrotoxicity and life‐threatening systemic MTX exposure. Glucarpidase is a rescue agent for severe MTX toxicity that reduces plasma MTX levels via hydrolysis of MTX into inactive metabolites, but is only indicated when MTX concentrations are > 2 SDs above the mean excretion curve specific for the given dose together with a significant creatinine increase (> 50%). Appropriate administration of glucarpidase is challenging due to the ambiguity in the labeled indication. A recent consensus guideline was published with an algorithm to provide clarity in when to administer glucarpidase, yet clinical interpretation of laboratory results that do not directly correspond to the algorithm prove to be a limitation of its use. The goal of our study was to develop a clinical decision support tool to optimize the administration of glucarpidase for patients receiving HD MTX. Here, we describe the development of a novel 3‐compartment MTX population pharmacokinetic (PK) model using 31,672 MTX plasma concentrations from 772 pediatric patients receiving HD MTX for the treatment of acute lymphoblastic leukemia and its integration into the online clinical decision support tool, MTXPK.org. This web‐based tool has the functionality to utilize individualized demographics, serum creatinine, and real‐time drug concentrations to predict the elimination profile and facilitate model‐informed administration of glucarpidase.

Prospective validation of a model-informed precision dosing tool for vancomycin in intensive care patients

AIMS

Vancomycin is an important antibiotic for critically ill patients with Gram-positive bacterial infections. Critically ill patients typically have severely altered pathophysiology, which leads to inefficacy or toxicity. Model-informed precision dosing may aid in optimizing the dose, but prospectively validated tools are not available for this drug in these patients. We aimed to prospectively validate a population pharmacokinetic model for purpose model-informed precision dosing of vancomycin in critically ill patients.

METHODS

We first performed a systematic evaluation of various models on retrospectively collected pharmacokinetic data in critically ill patients and then selected the best performing model. This model was implemented in the Insight Rx clinical decision support tool and prospectively validated in a multicentre study in critically ill patients. The predictive performance was obtained as mean prediction error and relative root mean squared error.

RESULTS

We identified 5 suitable population pharmacokinetic models. The most suitable model was carried forward to a prospective validation. We found in a prospective multicentre study that the selected model could accurately and precisely predict the vancomycin pharmacokinetics based on a previous measurement, with a mean prediction error and relative root mean squared error of respectively 8.84% (95% confidence interval 5.72-11.96%) and 19.8% (95% confidence interval 17.47-22.13%).

CONCLUSION

Using a systematic approach, with a retrospective evaluation and prospective verification we showed the suitability of a model to predict vancomycin pharmacokinetics for purposes of model-informed precision dosing in clinical practice. The presented methodology may serve a generic approach for evaluation of pharmacometric models for the use of model-informed precision dosing in the clinic.

The Steps to Therapeutic Drug Monitoring: A Structured Approach Illustrated With Imatinib

Pharmacometric methods have hugely benefited from progress in analytical and computer sciences during the past decades, and play nowadays a central role in the clinical development of new medicinal drugs. It is time that these methods translate into patient care through therapeutic drug monitoring (TDM), due to become a mainstay of precision medicine no less than genomic approaches to control variability in drug response and improve the efficacy and safety of treatments. In this review, we make the case for structuring TDM development along five generic questions: 1) Is the concerned drug a candidate to TDM? 2) What is the normal range for the drug's concentration? 3) What is the therapeutic target for the drug's concentration? 4) How to adjust the dosage of the drug to drive concentrations close to target? 5) Does evidence support the usefulness of TDM for this drug? We exemplify this approach through an overview of our development of the TDM of imatinib, the very first targeted anticancer agent. We express our position that a similar story shall apply to other drugs in this class, as well as to a wide range of treatments critical for the control of various life-threatening conditions. Despite hurdles that still jeopardize progress in TDM, there is no doubt that upcoming technological advances will shape and foster many innovative therapeutic monitoring methods.

Randomized study of individualized pharmacokinetically-guided dosing of paclitaxel compared with body-surface area dosing in Chinese patients with advanced non-small cell lung cancer

AIMS

This prospective, randomized study was initiated to assess the impact of pharmacokinetically (PK)-guided paclitaxel (PTX) dosing on toxicity and efficacy compared with body-surface area (BSA)-based dosing in Chinese non-small cell lung cancer patients.

METHODS

A total of 319 stage IIIB/IV non-small cell lung cancer patients receiving first-line chemotherapy were enrolled. Patients were randomized to receive 3-weekly carboplatin plus PTX at a starting dose of 175 mg/m² with subsequent PTX dosing based on either BSA or PK-guided dosing targeting time above a PTX plasma concentration of 0.05 μmol/L (PTX_Tc > 0.05 ) between 26 and 31 hours. The primary safety endpoint was grade 4 haematological toxicity. The secondary endpoints were neuropathy, objective response rate, progression-free survival and overall survival.

RESULTS

In total, 275 (86%) patients completed ≥2 cycles of chemotherapy (140 in BSA arm and 135 in PK arm). In cycle 1, with the same PTX dose, average PTX_Tc > 0.05 was 37 hours (range = 18-57 hours). Over cycles 2-4, patients in the PK arm had significantly lower average PTX doses and exposure compared with the BSA arm (128 vs 161 mg/m² , P < .0001 and 29 vs 35 hours, P < .0001). PK-guided dosing significantly reduced the cumulative incidence of grade 4 haematological toxicity (15% vs 24%, P = .004), grade 4 neutropenia (15% vs 23%, P = .009) and grade ≥ 2 neuropathy (8% vs 21%, P = .005). Objective response rate (32% vs 26%, P = .28) and overall survival (21.0 vs 24.0 months, P = .815) were similar in PK and BSA arms. Progression-free survival was slightly improved in PK arm (4.67 vs 4.17 months, P = .026).

CONCLUSION

PK-guided PTX dosing significantly reduced grade 4 haematological toxicities and grade ≥ 2 neuropathy without an adverse impact on clinical outcomes.

Integrated Microfluidic Devices Fabricated in Poly (Methyl Methacrylate) (PMMA) for On-site Therapeutic Drug Monitoring of Aminoglycosides in Whole Blood

On-site therapeutic drug monitoring (TDM) is important for providing a quick and accurate dosing to patients in order to improve efficacy and minimize toxicity. Aminoglycosides such as amikacin, gentamicin, and tobramycin are important antibiotics that have been commonly used to treat infections of chronic bacterial infections in the urinary tract, lung, and heart. However, these aminoglycosides can lead to vestibular and auditory dysfunction. Therefore, TDM of aminoglycosides is important due to their ototoxicity and nephrotoxicity. Here, we have developed a hot embossed poly (methyl methacrylate) (PMMA) microfluidic device featuring an electrokinetic size and mobility trap (SMT) to purify, concentrate, and separate the aminoglycoside antibiotic drugs amikacin, gentamicin, and tobramycin. These drugs were separated successfully from whole blood within 3 min, with 30-fold lower detection limits compared to a standard pinched injection. The limit of detections (LOD) were 3.75 µg/mL for gentamicin, 8.53 µg/mL for amikacin, and 6.00 µg/mL for tobramycin. These are sufficient to cover the therapeutic range for treating sepsis of 6⁻10 μg/mL gentamicin and tobramycin and 12⁻20 μg/mL of amikacin. The device is simple and could be mass produced via embossing or injection molding approaches.

The impact of tacrolimus exposure on extrarenal adverse effects in adult renal transplant recipients

AIMS

Tacrolimus has been associated with notable extrarenal adverse effects (AEs), which are unpredictable and impact patient morbidity. The association between model-predicted tacrolimus exposure metrics and standardized extrarenal AEs in stable renal transplant recipients was investigated and a limited sampling strategy (LSS) was developed to predict steady-state tacrolimus area under the curve over a 12-h dosing period (AUC_ss,0-12h ).

METHODS

All recipients receiving tacrolimus and mycophenolic acid ≥6 months completed a 12-h cross-sectional observational pharmacokinetic-pharmacodynamic study. Patients were evaluated for the presence of individual and composite gastrointestinal, neurological, and aesthetic AEs during the study visit. The associations between AEs and tacrolimus exposure metrics generated from a published population pharmacokinetic model were investigated using a logistic regression analysis in NONMEM 7.3. An LSS was determined using a Bayesian estimation method with the same patients.

RESULTS

Dose-normalized tacrolimus AUC_ss,0-12h and apparent clearance were independently associated with diarrhoea, dyspepsia, insomnia and neurological AE ratio. Dose-normalized tacrolimus maximum concentration was significantly correlated with skin changes and acne. No AE associations were found with trough concentrations. Using limited sampling at 0, 2h; 0, 1, 4h; and 0, 1, 2, 4h provided a precise and unbiased prediction of tacrolimus AUC (root mean squared prediction error < 10%), which was not well characterized using trough concentrations only (root mean squared prediction error >15%).

CONCLUSIONS

Several AEs (i.e. diarrhoea, dyspepsia, insomnia and neurological AE ratio) were associated with tacrolimus dose normalized AUC_ss,0-12h and clearance. Skin changes and acne were associated with dose-normalized maximum concentrations. To facilitate clinical implementation, a LSS was developed to predict AUC_ss,0-12h values using sparse patient data to efficiently assess projected immunosuppressive exposure and potentially minimize AE manifestations.

An insight into medicinal chemistry of anticancer quinoxalines

Quinoxalines are benzopyrazines containing benzene and pyrazine rings fused together. In the recent past, quinoxalines have attracted Medicinal Chemists considerably for their syntheses and chemistry due to their distinct pharmacological activities. Diverse synthetic protocols have been developed via multicomponent reactions, single pot synthesis and combinatorial approach using efficient catalysts, reagents, and nano-composites etc. Further, the versatility of the quinoxaline core and its reasonable chemical simplicity devise it extremely promising source of bioactive compounds. Therefore, a wide variety of bioactive quinoxalines has been realised as antitumour, antifungal, anti-inflammatory, antimicrobial, and antiviral agents. Already, a few of them are clinical drugs while many more are under various phases of clinical trials. Present review focuses on chemistry and pharmacology (both efficacy and safety) of quinoxalines and also provides some insight in to their structure-activity relationship.

Enzyme autoinduction by mitotane supported by population pharmacokinetic modelling in a large cohort of adrenocortical carcinoma patients

OBJECTIVE

Mitotane is used for the treatment of adrenocortical carcinoma. High oral daily doses of typically 1- 6 g are required to attain therapeutic concentrations. The drug has a narrow therapeutic index and patient management is difficult because of a high volume of distribution, very long elimination half-life, and drug interaction through induction of metabolizing enzymes. The present evaluation aimed at the development of a population pharmacokinetic model of mitotane to facilitate therapeutic drug monitoring.

METHODS

Appropriate dosing information, plasma concentrations (1137 data points) and covariates were available from therapeutic drug monitoring (TDM) of 76 adrenocortical carcinoma patients treated with mitotane. Using nonlinear mixed effects modeling, a simple structural model was first developed, with subsequent introduction of metabolic autoinduction. Covariate data were analyzed to improve overall model predictability. Simulations were performed to assess the attainment of therapeutic concentrations with clinical dosing schedules.

RESULTS

A one-compartment pharmacokinetic model with first order absorption was found suitable to describe the data, with an estimated central volume of distribution of 6086 L related to a high interindividual variability of 81.5%. Increase in clearance of mitotane during treatment could be modeled by a linear enzyme autoinduction process. Body mass index was found to have an influence upon disposition kinetics of mitotane. Model simulations favor a high dose regimen to rapidly attain therapeutic concentrations, with the first TDM suggested on day 16 of treatment to avoid systemic toxicity.

CONCLUSION

The proposed model describes mitotane pharmacokinetics and can be used to facilitate therapy by predicting plasma concentrations.

Precision Medicine with Imprecise Therapy: Computational Modeling for Chemotherapy in Breast Cancer

Medical oncology is in need of a mathematical modeling toolkit that can leverage clinically-available measurements to optimize treatment selection and schedules for patients. Just as the therapeutic choice has been optimized to match tumor genetics, the delivery of those therapeutics should be optimized based on patient-specific pharmacokinetic/pharmacodynamic properties. Under the current approach to treatment response planning and assessment, there does not exist an efficient method to consolidate biomarker changes into a holistic understanding of treatment response. While the majority of research on chemotherapies focus on cellular and genetic mechanisms of resistance, there are numerous patient-specific and tumor-specific measures that contribute to treatment response. New approaches that consolidate multimodal information into actionable data are needed. Mathematical modeling offers a solution to this problem. In this perspective, we first focus on the particular case of breast cancer to highlight how mathematical models have shaped the current approaches to treatment. Then we compare chemotherapy to radiation therapy. Finally, we identify opportunities to improve chemotherapy treatments using the model of radiation therapy. We posit that mathematical models can improve the application of anticancer therapeutics in the era of precision medicine. By highlighting a number of historical examples of the contributions of mathematical models to cancer therapy, we hope that this contribution serves to engage investigators who may not have previously considered how mathematical modeling can provide real insights into breast cancer therapy.

Simple and rapid monitoring of doxorubicin using streptavidin-modified microparticle-based time-resolved fluorescence immunoassay

Developing a simple analytical method suitable for therapeutic drug monitoring in a clinical setting is key to establishing guidelines on accurate dose administration and the advancement of precision medicine. We devised a simple rapid analytical method through the combination of streptavidin-modified microparticles and a time-resolved fluorescence immunoassay for therapeutic drug monitoring. The analytical performance of this method was investigated and validated using clinical samples. By determination of doxorubicin concentration, the proposed assay has shown a satisfactory linear range of detection (3.8-3000 ng mL-1) with a limit of detection of 3.8 ng mL-1 and an IC50 of 903.9 ng mL-1. The intra and inter-assay coefficients of variation were 4.12-5.72% and 5.48-6.91%, respectively, and the recovery was acceptable. The applicability of the proposed assay was assessed by comparing the determined results with those measured by LC-MS/MS, presenting a satisfactory correlation (R 2 = 0.9868). The proposed assay, which shows satisfactory analytical performance, has great potential for application in the field of TDM in the future.

Impact of Pretreatment Neutrophil Count on Chemotherapy Administration and Toxicity in Dogs with Lymphoma Treated with CHOP Chemotherapy

BACKGROUND

Prechemotherapy absolute neutrophil count (ANC) cutoffs are arbitrary and vary across institutions and clinicians. Similarly, subjective guidelines are utilized for the administration of prophylactic antibiotics in neutropenic dogs.

OBJECTIVES

To evaluate the impact of various ANC cutoffs on chemotherapy administration in dogs with lymphoma treated with CHOP chemotherapy and to determine whether an association between prechemotherapy ANC and subsequent toxicity exists. The secondary objective was to evaluate a currently used ANC cutoff to indicate prescription of prophylactic antibiotics.

ANIMALS

Dogs diagnosed with lymphoma treated with CHOP chemotherapy (n = 64).

METHODS

Six hundred and fifteen ANCs were stratified into 6 classes. The 3 ANC cutoffs 1.5 × 103 /μL, 2.0 × 103 /μL, and 2.5 × 103 /μL were assessed. The presence of an association between prechemotherapy ANC class and toxicity was determined. Afebrile neutropenic dogs with ANC <1.5 × 103 /μL but above the criteria for prophylactic antibiotics were evaluated.

RESULTS

Chemotherapy was not administered in 7% of visits with an ANC cutoff of 1.5 × 103 /μL; chemotherapy would not have been administered in 10% and 16% of visits with an ANC cutoff of 2.0 × 103 /μL or 2.5 × 103 /μL, respectively. There was no association among the 3 lower prechemotherapy ANC classes and toxicity. All dogs with ANC 0.75-1.5 × 103 /μL recovered spontaneously without medical intervention.

CONCLUSION AND CLINICAL IMPORTANCE

The number of dose delays was minimized with a prechemotherapy ANC cutoff of 1.5 × 103 /μL, and the prechemotherapy ANC class 1.5-1.99 × 103 /μL was not associated with an increased toxicity. Further investigation of an ANC cutoff near 0.75 × 103 /μL in which to prescribe prophylactic antibiotics is indicated.

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in Chinese liver transplant patients

WHAT IS KNOWN AND OBJECTIVES

Tacrolimus (TAC) is widely used as part of immunosuppressive regimens. There is great interindividual variation on the disposition of TAC. The aim of this study was to develop a population pharmacokinetic (PPK) model for Chinese liver transplant patients and evaluate genetic polymorphism and other possible factors on the PK parameters. The exposure of TAC is to be estimated through Bayesian modelling.

METHODS

A total of 47 sets of rich-time PK and 1234 conventional therapeutic drug monitoring (TDM) data were collected from 125 Chinese liver transplant patients. The pathophysiological data of these patients were recorded. CYP3A5*3 and ABCB1 genotypes were determined for each patient. The PPK model for TAC was established by nonlinear mixed-effects modelling (nonmem). The impact of pathophysiology and genotype on PPK parameters was evaluated. Bayesian estimators for the area under concentration-time curve (AUC) of TAC were validated.

RESULTS

A two-compartment model with lag time was found to be the most suitable model for the pooled full PK and TDM data for Chinese liver transplant patients. The CL/F, V₂ /F, Q/F, V₃ /F, K_a and lag time were 17.4±0.81 L/h, 165±44.1 L, 54.9±25.8L/h, 594±87.5 L, 0.51±0.095 L/h and 1.57±0.34 h. Post-operative day (POD), creatinine clearance (CLcr) and ABCB1 C3435T genotypes were found to have significant influences on CL/F (P<.01). ABCB1 C3435T genotypes showed a significant correlation with V₂ /F (P<.01). C₀ -C₂ and C₀ -C₂ -C₄ were shown to be suitable for the estimation of AUC in Chinese liver transplant patients.

WHAT IS NEW AND CONCLUSION

A PPK model for TAC was established successfully in Chinese liver transplant patients. POD, CLcr and ABCB1 C3435T genotypes were shown to have significant effects on CL/F. The AUC of TAC in Chinese liver transplant patients could be estimated through Bayesian modelling, based on which individualized immunosuppressive regimens can be designed.

Measures of 6-mercaptopurine and methotrexate maintenance therapy intensity in childhood acute lymphoblastic leukemia

PURPOSE

Normal white blood cell counts (WBC) are unknown in children with acute lymphoblastic leukemia (ALL). Accordingly, 6-mercaptopurine (6MP) and methotrexate (MTX) maintenance therapy is adjusted by a common WBC target of 1.5-3.0 × 10⁹/L. Consequently, the absolute degree of myelosuppression is unknown for the individual child and we wanted to evaluate this.

METHODS

A median of 22 (range 8-27) 6MP/MTX metabolite samples and 100 (range 25-130) blood counts during therapy and 10 (range 2-15) off therapy were collected in 50 children with ALL. Differences between off-therapy and on-therapy WBCs [including absolute neutrophil (ANC) and lymphocyte counts (ALC)] were used to retrospectively approximate the absolute myelosuppression (="delta-") and association with age, sex and 6MP/MTX doses explored. We applied linear mixed models to estimate on-therapy counts by 6MP/MTX metabolites: DNA-incorporated thioguanine nucleotides (DNA-TGN), erythrocyte thioguanine nucleotides (ery-TGN), erythrocyte-methylated 6MP metabolites (ery-MeMP) and erythrocyte MTX polyglutamates with 2-6 glutamate residues (ery-MTXpg_2-6).

RESULTS

On-therapy WBC was correlated with ANC and ALC (r _s  = 0.84 and r _s  = 0.33, p values <0.001), whereas ANC was weakly correlated with ALC (r _s  = -0.11, p < 0.001), and neither significantly correlated with age. Off-therapy ALC, but not ANC, was strongly correlated with age (r _s  = -0.68 and -0.18, p < 0.001 and p = 0.22). Delta-ALC decreased with increasing age (r _s  = -0.69, p < 0.001). Incorporation of DNA-TGN was positively associated with ery-TGN (p < 0.001), ery-MeMP (p < 0.001) and ery-MTXpg_2-6 (p = 0.047). On-therapy ALC decreased with increasing DNA-TGN level (p < 0.001, model adjusted for off-therapy ALC), whereas on-therapy ANC could not be modeled reliably.

CONCLUSION

Measurements of 6MP/MTX metabolites could supplement blood counts in assessing therapy intensity, but require prospective validation.

Species differences in tumour responses to cancer chemotherapy

Despite advances in chemotherapy, radiotherapy and targeted drug development, cancer remains a disease of high morbidity and mortality. The treatment of human cancer patients with chemotherapy has become commonplace and accepted over the past 100 years. In recent years, and with a similar incidence of cancer to people, the use of cancer chemotherapy drugs in veterinary patients such as the dog has also become accepted clinical practice. The poor predictability of tumour responses to cancer chemotherapy drugs in rodent models means that the standard drug development pathway is costly, both in terms of money and time, leading to many drugs failing in Phase I and II clinical trials. This has led to the suggestion that naturally occurring cancers in pet dogs may offer an alternative model system to inform rational drug development in human oncology. In this review, we will explore the species variation in tumour responses to conventional chemotherapy and highlight our understanding of the differences in pharmacodynamics, pharmacokinetics and pharmacogenomics between humans and dogs. Finally, we explore the potential hurdles that need to be overcome to gain the greatest value from comparative oncology studies.

Effect of Kidney Function on Drug Kinetics and Dosing in Neonates, Infants, and Children

Neonates, infants, and children differ from adults in many aspects, not just in age, weight, and body composition. Growth, maturation and environmental factors affect drug kinetics, response and dosing in pediatric patients. Almost 80% of drugs have not been studied in children, and dosing of these drugs is derived from adult doses by adjusting for body weight/size. As developmental and maturational changes are complex processes, such simplified methods may result in subtherapeutic effects or adverse events. Kidney function is impaired during the first 2 years of life as a result of normal growth and development. Reduced kidney function during childhood has an impact not only on renal clearance but also on absorption, distribution, metabolism and nonrenal clearance of drugs. 'Omics'-based technologies, such as proteomics and metabolomics, can be leveraged to uncover novel markers for kidney function during normal development, acute kidney injury, and chronic diseases. Pharmacometric modeling and simulation can be applied to simplify the design of pediatric investigations, characterize the effects of kidney function on drug exposure and response, and fine-tune dosing in pediatric patients, especially in those with impaired kidney function. One case study of amikacin dosing in neonates with reduced kidney function is presented. Collaborative efforts between clinicians and scientists in academia, industry, and regulatory agencies are required to evaluate new renal biomarkers, collect and share prospective pharmacokinetic, genetic and clinical data, build integrated pharmacometric models for key drugs, optimize and standardize dosing strategies, develop bedside decision tools, and enhance labels of drugs utilized in neonates, infants, and children.

Inter occasion variability in individual optimal design

Inter occasion variability (IOV) is of importance to consider in the development of a design where individual pharmacokinetic or pharmacodynamic parameters are of interest. IOV may adversely affect the precision of maximum a posteriori (MAP) estimated individual parameters, yet the influence of inclusion of IOV in optimal design for estimation of individual parameters has not been investigated. In this work two methods of including IOV in the maximum a posteriori Fisher information matrix (FIM_MAP) are evaluated: (i) MAP_occ—the IOV is included as a fixed effect deviation per occasion and individual, and (ii) POP_occ—the IOV is included as an occasion random effect. Sparse sampling schedules were designed for two test models and compared to a scenario where IOV is ignored, either by omitting known IOV (Omit) or by mimicking a situation where unknown IOV has inflated the IIV (Inflate). Accounting for IOV in the FIM_MAP markedly affected the designs compared to ignoring IOV and, as evaluated by stochastic simulation and estimation, resulted in superior precision in the individual parameters. In addition MAP_occ and POP_occ accurately predicted precision and shrinkage. For the investigated designs, the MAP_occ method was on average slightly superior to POP_occ and was less computationally intensive.

Enzyme-responsive doxorubicin release from dendrimer nanoparticles for anticancer drug delivery

Background

Since cancer cells are normally over-expressed cathepsin B, we synthesized dendrimer-methoxy poly(ethylene glycol) (MPEG)-doxorubicin (DOX) conjugates using a cathepsin B-cleavable peptide for anticancer drug targeting.

Methods

Gly-Phe-Leu-Gly peptide was conjugated with the carboxylic acid end groups of a dendrimer, which was then conjugated with MPEG amine and doxorubicin by aid of carbodiimide chemistry (abbreviated as DendGDP). Dendrimer-MPEG-DOX conjugates without Gly-Phe-Leu-Gly peptide linkage was also synthesized for comparison (DendDP). Nanoparticles were then prepared using a dialysis procedure.

Results

The synthesized DendGDP was confirmed with ¹H nuclear magnetic resonance spectroscopy. The DendDP and DendGDP nanoparticles had a small particle size of less than 200 nm and had a spherical morphology. DendGDP had cathepsin B-sensitive drug release properties while DendDP did not show cathepsin B sensitivity. Further, DendGDP had improved anticancer activity when compared with doxorubicin or DendDP in an in vivo CT26 tumor xenograft model, ie, the volume of the CT26 tumor xenograft was significantly inhibited when compared with xenografts treated with doxorubicin or DendDP nanoparticles. The DendGDP nanoparticles were found to be relatively concentrated in the tumor tissue and revealed stronger fluorescence intensity than at other body sites while doxorubicin and DendDP nanoparticles showed strong fluorescence intensity in the various organs, indicating that DendGDP has cathepsin B sensitivity.

Conclusion

DendGDP is sensitive to cathepsin B in tumor cells and can be used as a cathepsin B-responsive drug targeting strategy. We suggest that DendGDP is a promising vehicle for cancer cell targeting.

Genetic and metabolic determinants of methotrexate-induced mucositis in pediatric acute lymphoblastic leukemia

Methotrexate (MTX) is an effective and toxic chemotherapeutic drug in the treatment of pediatric acute lymphoblastic leukemia(ALL). In this prospective study, we aimed to identify metabolic and genetic determinants of MTX toxicity. One hundred and thirty-four Dutch pediatric ALL patients were treated with four high infusions MTX (HD-MTX: 5 g m(-2)) every other week according to the DCOG-ALL-10 protocol. Mucositis (National Cancer Institute grade ⩾ 3) was the most frequent occurring toxicity during the HD-MTX phase (20%) and occurred especially after the first MTX course. Mucositis was not associated with plasma MTX, plasma folate or plasma homocysteine levels. Patients with mucositis had higher erythrocyte folate levels at the start of protocol M than patients without mucositis (median 1.4 vs 1.2 μmol l(-1), P<0.008), this could reflect an increased MTX uptake in mucosal cells of patients with mucositis. From 17 single-nucleotide polymorphisms in the MTX pathway, only patients with the wild-type variant of rs7317112 SNP in the ABCC4 gene had more mucositis (AA (39%) vs AG/GG (15%), P=0.016). We found no evidence that erythrocyte folate levels mediate in the association between the rs7317112 and mucositis.

Exercise mitigates cardiac doxorubicin accumulation and preserves function in the rat

PURPOSE

Doxorubicin (DOX) is an effective antineoplastic agent with well-characterized cardiotoxic effects. Although exercise has been shown to protect against DOX cardiotoxicity, a clear and concise mechanism to explain its cardioprotective effects is lacking. The purpose of this study was to determine if exercise training reduces cardiac DOX accumulation, thereby providing a possible mechanism to explain the cardioprotective effects of exercise against DOX toxicity.

METHODS

Sprague-Dawley rats were randomly assigned to 1 of 3 primary experimental groups: sedentary (n = 77), wheel running (n = 65), or treadmill (n = 65). Animals in wheel running and treadmill groups completed 10 weeks of exercise before DOX treatment. DOX was administered 24 hours after the last training session as a bolus intraperitoneal injection at 10 mg/kg. Subgroups of rats from each primary group were killed at 1, 3, 5, 7, and 9 days after DOX exposure to assess cardiac function and DOX accumulation.

RESULTS

Ten weeks of exercise preconditioning reduced myocardial DOX accumulation, and this reduction in accumulation was associated with preserved cardiac function.

CONCLUSIONS

These data suggest that the cardioprotective effects of exercise against DOX-induced injury may be due, in part, to a reduction in myocardial DOX accumulation.

Pharmacogenetics, enzyme probes and therapeutic drug monitoring as potential tools for individualizing taxane therapy

The taxanes are a class of chemotherapeutic agents that are widely used in the treatment of various solid tumors. Although taxanes are highly effective in cancer treatment, their use is associated with serious complications attributable to large interindividual variability in pharmacokinetics and a narrow therapeutic window. Unpredictable toxicity occurrence necessitates close patient monitoring while on therapy and adverse effects frequently require decreasing, delaying or even discontinuing taxane treatment. Currently, taxane dosing is based primarily on body surface area, ignoring other factors that are known to dictate variability in pharmacokinetics or outcome. This article discusses three potential strategies for individualizing taxane treatment based on patient information that can be collected before or during care. The clinical implementation of pharmacogenetics, enzyme probes or therapeutic drug monitoring could enable clinicians to personalize taxane treatment to enhance efficacy and/or limit toxicity.

Influence of a priori Information, Designs, and Undetectable Data on Individual Parameters Estimation and Prediction of Hepatitis C Treatment Outcome

Hepatitis C viral kinetic analysis based on nonlinear mixed effect models can be used to individualize treatment. For that purpose, it is necessary to obtain precise estimation of individual parameters. Here, we evaluated by simulation the influence on Bayesian individual parameter estimation and outcome prediction of a priori information on population parameters, viral load sampling designs, and methods for handling data below detection limit (BDL). We found that a precise estimation of both individual parameters and treatment outcome could be obtained using as few as six measurements in the first month of therapy. This result remained valid even when incorrect a priori information on population parameters was set as long as the parameters were identifiable and BDL data were properly handled. However, setting wrong values for a priori population parameters could lead to severe estimation/prediction errors if BDL data were ignored and not properly accounted in the likelihood function.

Benchmarking therapeutic drug monitoring software: a review of available computer tools

Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

Kinetic nomograms assist individualization of drug regimens

BACKGROUND AND OBJECTIVES

Therapeutic drug monitoring is applied to a range of drugs. To predict an appropriate dosing regimen, models based on Bayesian techniques have been used. However, this approach requires a well trained professional and sophisticated software. The objectives of this study were first to develop kinetic nomograms as a useful tool to achieve individual drug blood concentrations within the therapeutic window, using few samples and in a short period of time; and second to evaluate the performance of these nomograms in dosage adjustment and compare them with the Bayesian procedure by use of simulation.

METHODS

Kinetic nomograms involve collection of concentration-time profiles following repeated administrations of a fixed identification protocol and targeting of a steady-state concentration. The profiles divide the concentration-time space into several areas, each of them corresponding to a given adjusted drug dose. Kinetic nomograms are grounded on the statistical description of the interindividual variability provided by population pharmacokinetic approaches. To use them, the assayed drug concentration in a blood sample is first located in the kinetic nomogram and then the dose corresponding to the area containing this location is read. Evaluation of performance and comparison with the traditional Bayesian procedure were done by a simulation study using the immunosuppressant drug sirolimus (rapamycin). All calculations were performed by use of Matlab software.

RESULTS

The simulation study confirmed the need for individual dosage adjustment; 71.6% of individuals underwent modification of the identification protocol of 1 mg twice daily in order to reach steady-state trough concentrations of 8 ng/mL. When the regimens were adjusted by kinetic nomograms and the Bayesian procedure, the steady-state trough concentrations of sirolimus showed low variability (coefficients of variation [CVs] of 23.4% and 24.0%, respectively) as compared with those obtained by standard recommended protocols of 4 mg once daily (CV 68.6%). The doses adjusted by kinetic nomograms and the Bayesian procedure were linearly linked and highly correlated (r = 0.96), and both provided simultaneous control of minimum and maximum drug concentrations (63.9% and 68.7% of cases between 6 and 20 ng/mL, respectively).

CONCLUSION

Kinetic nomograms allow rapid and reliable dosage adjustment after the start of drug therapy. They are interesting alternatives to the cumbersome Bayesian procedure, and they provide dosage adjustment even for drugs that exhibit large intraindividual variability. In the clinical context, kinetic nomograms render individual dosage adjustment a simplified bedside application, and they could assist population studies aiming at dose individualization.

Nanomedicine Faces Barriers

Targeted nanoparticles have the potential to improve drug delivery efficiencies by more than two orders of magnitude, from the ~ 0.1% which is common today. Most pharmacologically agents on the market today are small drug molecules, which diffuse across the body’s blood-tissue barriers and distribute not only into the lesion, but into almost all organs. Drug actions in the non-lesion organs are an inescapable part of the drug delivery principle, causing “side-effects” which limit the maximally tolerable doses and result in inadequate therapy of many lesions. Nanoparticles only cross barriers by design, so side-effects are not built into their mode of operation. Delivery rates of almost 90% have been reported. This review examines the significance of these statements and checks how far they need qualification. What type of targeting is required? Is a single targeting sufficient? What new types of clinical challenge, such as immunogenicity, might attend the use of targeted nanoparticles?

Model-based neutrophil-guided dose adaptation in chemotherapy: evaluation of predicted outcome with different types and amounts of information

One of the most employed approaches to reduce severe neutropenia following anticancer drug regimens is to reduce the consecutive dose in fixed steps, commonly by 25%. Another approach has been to use pharmacokinetic (PK) sampling to tailor dosing, but only rarely have model-based computer approaches utilizing collected PK and/or pharmacodynamic (PD) data been used. A semi-mechanistic model for myelosuppression that can characterize the interindividual and interoccasion variability in the time-course of neutrophils following administration of a wide range of anticancer drugs may be used in a clinical setting for model-based dose individualization. The aim of this study was to compare current stepwise procedures to model-based dose adaptation by simulations, and investigate if the overall dose intensity in the population could be increased without increasing the risk of severe toxicity. The value of various amounts of PK- and/or PD-information was compared to standard dosing strategies using a maximum a posteriori procedure in NONMEM. The results showed that when information on neutrophil counts was available, the additional improvement from PK sampling was negligible. Using neutrophil sampling at baseline and an observation near the predicted nadir increased the number of patients in the target range by 27% in comparison with a one-sided 25% dose adjustment schedule, while keeping the number of patients experiencing severe toxicity at a comparable low level after five courses of treatment. High interindividual variability did not limit the benefit of model-based dose adaptation, whereas high interoccasion variability was predicted to make any dose adaptation method less successful. This study indicates that for successful model-based dose adaptation clinically, there is no need for drug concentration sampling, and that one extra neutrophil measurement in addition to the pre-treatment value is sufficient to limit severe neutropenia while increasing dose intensity.

Sex-specific aspects of tumor therapy

There is increasing evidence that sex-specific differences in toxicity profiles and outcome after radiotherapy are accumulating in medical oncology, and that treatment strategies may require some modification. Furthermore, sex-specific differences in the sensitivity to genotoxic and therapeutical agents are also of general concern for risk estimation. This review is focussed on the specific influence of sex on these endpoints covering both a clinical and a biological point of view. In this paper, the literature was systematically reviewed with respect to sex-specific differences in tumor and normal tissue sensitivity after exposure to ionizing radiation, as well as to the relevant underlying molecular and cellular mechanisms. Although a number of data on sex-specific differences are available and remarkable differences on clinical, molecular, and cellular levels have been reported, a firm conclusion on any existing sex-specific differences is not yet possible. Future studies are required and should be focussed on this aspect of individual radiosensitivity.