Interactions between natural products and cancer treatments: underlying mechanisms and clinical importance.

Natural products, also referred to as dietary supplements, complementary and alternative medicines, and health or food supplements are widely used by people living with cancer. These products are predominantly self-selected and taken concurrently with cancer treatments with the intention of improving quality of life, immune function and reducing cancer symptoms and treatment side effects. Concerns have been raised that concurrent use may lead to interactions resulting in adverse effects and unintended treatment outcomes. This review provides an overview of the mechanisms by which these interactions can occur and the current evidence about specific clinically important natural product-drug interactions. Clinical studies investigating pharmacokinetic interactions provide evidence that negative treatment outcomes may occur when Hypericum perforatum, Grapefruit, Schisandra sphenanthera, Curcuma longa or Hydrastis canadensis are taken concurrently with common cancer treatments. Conversely, pharmacodynamic interactions between Hangeshashinto (TJ-14) and some cancer treatments have been shown to reduce the side effects of diarrhoea and oral mucositis. In summary, research in this area is limited and requires further investigation.

Audit of Data Sharing by Pharmaceutical Companies for Anticancer Medicines Approved by the US Food and Drug Administration.

Importance: Emerging policies drafted by the pharmaceutical industry indicate that they will transparently share clinical trial data. These data offer an unparalleled opportunity to advance evidence-based medicine and support decision-making. Objective: To evaluate the eligibility of independent, qualified researchers to access individual participant data (IPD) from oncology trials that supported US Food and Drug Administration (FDA) approval of new anticancer medicines within the past 10 years. Design, Setting, and Participants: In this quality improvement study, a cross-sectional analysis was performed of pivotal clinical trials whose results supported FDA-approved anticancer medicines between January 1, 2011, and June 30, 2021. These trials' results were identified from product labels. Exposures: Eligibility for IPD sharing was confirmed by identification of a public listing of the trial as eligible for sharing or by receipt of a positive response from the sponsor to a standardized inquiry. Main Outcomes and Measures: The main outcome was frequency of IPD sharing eligibility. Reasons for data sharing ineligibility were requested and collated, and company-, drug-, and trial-level subgroups were evaluated and presented using χ2 tests and forest plots. Results: During the 10-year period examined, 115 anticancer medicines were approved by the FDA on the basis of evidence from 304 pharmaceutical industry-sponsored trials. Of these trials, 136 (45%) were eligible for IPD sharing and 168 (55%) were not. Data sharing rates differed substantially among industry sponsors, with the most common reason for not sharing trial IPD being that the collection of long-term follow-up data was still ongoing (89 of 168 trials [53%]). Of the top 10 anticancer medicines by global sales, nivolumab, pembrolizumab, and pomalidomide had the lowest eligibility rates for data sharing (<10% of trials). Conclusions and Relevance: There has been a substantial increase in IPD sharing for industry-sponsored oncology trials over the past 5 years. However, this quality improvement study found that more than 50% of queried trials for FDA-approved anticancer medicines were ineligible for IPD sharing. Data accessibility would be substantially improved if, at the time of FDA registration of a medicine, all data that support the registration were made available.

Physiologically Based Pharmacokinetic Modeling Approaches for Patients With SARS-CoV-2 Infection: A Case Study With Imatinib.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which causes coronavirus disease 2019 (COVID-19), manifests as mild respiratory symptoms to severe respiratory failure and is associated with inflammation and other physiological changes. Of note, substantial increases in plasma concentrations of α1 -acid-glycoprotein and interleukin-6 have been observed among patients admitted to the hospital with advanced SARS-CoV-2 infection. A physiologically based pharmacokinetic (PBPK) approach is a useful tool to evaluate and predict disease-related changes on drug pharmacokinetics. A PBPK model of imatinib has previously been developed and verified in healthy people and patients with cancer. In this study, the PBPK model of imatinib was successfully extrapolated to patients with SARS-CoV-2 infection by accounting for disease-related changes in plasma α1 -acid-glycoprotein concentrations and the potential drug interaction between imatinib and dexamethasone. The model demonstrated a good predictive performance in describing total and unbound imatinib concentrations in patients with SARS-CoV-2 infection. PBPK simulations highlight that an equivalent dose of imatinib may lead to substantially higher total drug concentrations in patients with SARS-CoV-2 infection compared to that in patients with cancer, while the unbound concentrations remain comparable between the 2 patient populations. This supports the notion that unbound trough concentration is a better exposure metric for dose adjustment of imatinib in patients with SARS-CoV-2 infection, compared to the corresponding total drug concentration. Potential strategies for refinement and generalization of the PBPK modeling approach in the patient population with SARS-CoV-2 are also provided in this article, which could be used to guide study design and inform dose adjustment in the future.

Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib.

PURPOSE: This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. METHODS: PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. RESULTS: The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase (5th to 95th percentiles of prediction of 1.4-3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, 5th to 95th percentile: 1.1-1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0-1.2). CONCLUSION: PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies.

Physiologically-based pharmacokinetic model predictions of inter-ethnic differences in imatinib pharmacokinetics and dosing regimens.

AIMS: This study implements a physiologically-based pharmacokinetic (PBPK) modelling approach to investigate inter-ethnic differences in imatinib pharmacokinetics and dosing regimens. METHODS: A PBPK model of imatinib was built in the Simcyp Simulator (version 17) integrating in vitro drug metabolism and clinical pharmacokinetic data. The model accounts for ethnic differences in body size and abundance of drug-metabolising enzymes and proteins involved in imatinib disposition. Utility of this model for prediction of imatinib pharmacokinetics was evaluated across different dosing regimens and ethnic groups. The impact of ethnicity on imatinib dosing was then assessed based on the established range of trough concentrations (Css,min ). RESULTS: The PBPK model of imatinib demonstrated excellent predictive performance in describing pharmacokinetics and the attained Css,min in patients from different ethnic groups, shown by prediction differences that were within 1.25-fold of the clinically-reported values in published studies. PBPK simulation suggested a similar dose of imatinib (400-600 mg/d) to achieve the desirable range of Css,min (1000-3200 ng/mL) in populations of European, Japanese and Chinese ancestry. The simulation indicated that patients of African ancestry may benefit from a higher initial dose (600-800 mg/d) to achieve imatinib target concentrations, due to a higher apparent clearance (CL/F) of imatinib compared to other ethnic groups; however, the clinical data to support this are currently limited. CONCLUSION: PBPK simulations highlighted a potential ethnic difference in the recommended initial dose of imatinib between populations of European and African ancestry, but not populations of Chinese and Japanese ancestry.

Is there scope for better individualisation of anthracycline cancer chemotherapy?

Anthracyclines are used to treat solid and haematological cancers, particularly breast cancers, lymphomas and childhood cancers. Myelosuppression and cardiotoxicity are the primary toxicities that limit treatment duration and/or intensity. Cardiotoxicity, particularly heart failure, is a leading cause of morbidity and mortality in cancer survivors. Cumulative anthracycline dose is a significant predictor of cardiotoxicity risk, suggesting a role for anthracycline pharmacokinetic variability. Population pharmacokinetic modelling in children has shown that doxorubicin clearance in the very young is significantly lower than in older children, potentially contributing to their higher risk of cardiotoxicity. A model of doxorubicin clearance based on body surface area and age offers a patient-centred dose-adjustment strategy that may replace the current disparate initial-dose selection tools, providing a rational way to compensate for pharmacokinetic variability in children aged <7 years. Population pharmacokinetic models in adults have not adequately addressed older ages, obesity, hepatic and renal dysfunction, and potential drug-drug interactions to enable clinical application. Although candidate gene and genome-wide association studies have investigated relationships between genetic variability and anthracycline pharmacokinetics or clinical outcomes, there have been few clinically significant reproducible associations. Precision-dosing of anthracyclines is currently hindered by lack of clinically useful pharmacokinetic targets and models that predict cumulative anthracycline exposures. Combined with known risk factors for cardiotoxicity, the use of advanced echocardiography and biomarkers, future validated pharmacokinetic targets and predictive models could facilitate anthracycline precision dosing that truly maximises efficacy and provides individualised early intervention with cardioprotective therapies in patients at risk of cardiotoxicity.

Physiologically-Based Pharmacokinetic Predictions of the Effect of Curcumin on Metabolism of Imatinib and Bosutinib: In Vitro and In Vivo Disconnect.

PURPOSE: This study aimed to investigate the potential pharmacokinetic interactions between curcumin, imatinib and bosutinib, combining In Vitro and in silico methods. METHODS: In Vitro metabolism of imatinib and bosutinib were investigated in pooled human liver microsomes and recombinant CYP3A4 enzyme in the presence and absence of curcumin and curcumin glucuronide using an LC-MS/MS assay for N-desmethyl metabolites. A physiologically-based pharmacokinetic (PBPK) model for curcumin formulated as solid lipid nanoparticles (SLN) was constructed using In Vitro glucuronidation kinetics and published clinical pharmacokinetic data. The potential effects of curcumin coadministration on systemic exposures of imatinib and bosutinib were predicted in silico using PBPK simulations. RESULTS: Curcumin demonstrated potent reversible inhibition of cytochrome P450 (CYP)3A4-mediated N-demethylation of imatinib and bosutinib and CYP2C8-mediated metabolism of imatinib with inhibitory constants (ki,u) of ≤1.5 µmol. L-1. A confirmatory In Vitro study with paclitaxel, the 6α-hydroxylation of which is exclusively mediated by CYP2C8, was consistent with a potent inhibition of this enzyme by curcumin. Curcumin glucuronide also inhibited both CYP enzymes In Vitro, albeit to a lesser extent than that of curcumin. PBPK model simulations predicted that at recommended dosing regimens of SLN curcumin, coadministration would result in an increase in systemic exposures of imatinib and bosutinib of up to only 10%. CONCLUSION: A PBPK model for curcumin in a SLN formulation was successfully developed. Although curcumin possesses a strong In Vitro inhibitory activity towards CYP3A4 and CYP2C8 enzymes, its interactions with imatinib and bosutinib were unlikely to be of clinical importance due to curcumin's poor bioavailability.

Potential for pharmacokinetic interactions between Schisandra sphenanthera and bosutinib, but not imatinib: in vitro metabolism study combined with a physiologically-based pharmacokinetic modelling approach.

AIMS: This study aimed to investigate the potential interaction between Schisandra sphenanthera, imatinib and bosutinib combining in vitro and in silico methods. METHODS: In vitro metabolism of imatinib and bosutinib using recombinant enzymes and human liver microsomes were investigated in the presence and absence of Schisandra lignans. Physiologically-based pharmacokinetic (PBPK) models for the lignans accounting for reversible and mechanism-based inhibitions and induction of CYP3A enzymes were built in the Simcyp Simulator (version 17) and evaluated for their capability to predict interactions with midazolam and tacrolimus. Their potential effect on systemic exposures of imatinib and bosutinib were predicted using PBPK in silico simulations. RESULTS: Schisantherin A and schisandrol B, but not schisandrin A, potently inhibited CYP3A4-mediated metabolism of imatinib and bosutinib. All three compounds showed a strong reversible inhibition on CYP2C8 enzyme with ki of less than 0.5 µmol L-1 . The verified PBPK models were able to describe the increase in systemic exposure of midazolam and tacrolimus due to co-administration of S. sphenanthera, consistent with the reported changes in the corresponding clinical interaction study (AUC ratio of 2.0 vs 2.1 and 2.4 vs 2.1, respectively). The PBPK simulation predicted that at recommended dosing regimens of S. sphenanthera, co-administration would result in an increase in bosutinib exposure (AUC ratio 3.0) but not in imatinib exposure. CONCLUSION: PBPK models for Schisandra lignans were successfully developed. Interaction between imatinib and Schisandra lignans was unlikely to be of clinical importance. Conversely, S. sphenanthera at a clinically-relevant dose results in a predicted three-fold increase in bosutinib systemic exposure.

Optimization of a clofarabine-based drug combination regimen for the preclinical evaluation of pediatric acute lymphoblastic leukemia.

BACKGROUND: The aim of this study was to improve the predictive power of patient-derived xenografts (PDXs, also known as mouse avatars) to more accurately reflect outcomes of clofarabine-based treatment in pediatric acute lymphoblastic leukemia (ALL) patients. PROCEDURE: Pharmacokinetic (PK) studies were conducted using clofarabine at 3.5 to 15 mg/kg in mice. PDXs were established from relapsed/refractory ALL patients who exhibited good or poor responses to clofarabine. PDX engraftment and response to clofarabine (either as a single agent or in combinations) were assessed based on stringent objective response measures modeled after the clinical setting. RESULTS: In naïve immune-deficient NSG mice, we determined that a clofarabine dose of 3.5 mg/kg resulted in systemic exposures equivalent to those achieved in pediatric ALL patients treated with clofarabine-based regimens. This dose was markedly lower than the doses of clofarabine used in previously reported preclinical studies (typically 30-60 mg/kg) and, when scheduled consistent with the clinical regimen (daily × 5), resulted in 34-fold lower clofarabine exposures. Using a well-tolerated clofarabine/etoposide/cyclophosphamide combination regimen, we then found that the responses of PDXs better reflected the clinical responses of the patients from whom the PDXs were derived. CONCLUSIONS: This study has identified an in vivo clofarabine treatment regimen that reflects the clinical responses of relapsed/refractory pediatric ALL patients. This regimen could be used prospectively to identify patients who might benefit from clofarabine-based treatment. Our findings are an important step toward individualizing prospective patient selection for the use of clofarabine in relapsed/refractory pediatric ALL patients and highlight the need for detailed PK evaluation in murine PDX models.

Wnt receptor gene FZD1 was associated with schizophrenia in genome-wide SNP analysis of the Australian Schizophrenia Research Bank cohort.

OBJECTIVES: Large-scale genetic analysis of common variation in schizophrenia has been a powerful approach to understanding this complex but highly heritable psychotic disorder. To further investigate loci, genes and pathways associated more specifically in the well-characterized Australian Schizophrenia Research Bank cohort, we applied genome-wide single-nucleotide polymorphism analysis in these three annotation categories. METHODS: We performed a case-control genome-wide association study in 429 schizophrenia samples and 255 controls. Post-genome-wide association study analyses were then integrated with genomic annotations to explore the enrichment of variation at the gene and pathway level. We also examine candidate single-nucleotide polymorphisms with potential function within expression quantitative trait loci and investigate overall enrichment of variation within tissue-specific functional regulatory domains of the genome. RESULTS: The strongest finding (p = 2.01 × 10-6, odds ratio = 1.82, 95% confidence interval = [1.42, 2.33]) in genome-wide association study was with rs10252923 at 7q21.13, downstream of FZD1 (frizzled class receptor 1). While this did not stand alone after correction, the involvement of FZD1 was supported by gene-based analysis, which exceeded the threshold for genome-wide significance (p = 2.78 × 10-6). CONCLUSION: The identification of FZD1, as an independent association signal at the gene level, supports the hypothesis that the Wnt signalling pathway is altered in the pathogenesis of schizophrenia and may be an important target for therapeutic development.

Clinical Pharmacokinetic and Pharmacodynamic Considerations in the (Modern) Treatment of Melanoma.

Targeted therapies, based on identification of common oncogenic mutations such as BRAF V600E/K and monoclonal antibody immunotherapies, have transformed the treatment of melanoma. Dual mitogen-activated protein kinase (MAPK) pathway inhibition of BRAF V600E/K and MEK 1/2 kinases with BRAF-MEK inhibitors using dabrafenib-trametinib, vemurafenib-cobimetinib and encorafenib-binimetinib is now the standard of care for BRAF V600E/K tumours. Monoclonal antibodies, such as pembrolizumab and nivolumab, against programmed cell death protein (PD-1) on T cells, as well as ipilimumab against cytotoxic T lymphocyte antigen-4 (CTLA-4), enable restoration of suppressed T-cell antitumour response, and have also shown improved clinical benefit compared with traditional chemotherapy. Exploration of different combination therapies, sequence of treatment, and dosing strategies is ongoing, and the understanding of the pharmacokinetics (PK) and pharmacodynamics (PD) of these new agents is fundamental in devising the optimal regimen. Preclinical and clinical studies, as well as population PK modelling, provide essential data in terms of PK parameters, metabolism, interpatient variability, drug interactions and PD effects at the target. This review gathers the current evidence and understanding of the clinical PK and PD of drugs used in the modern treatment of melanoma, and the factors determining drug disposition, exposure and clinical response, and also highlighting areas of further research.

Physiologically Based Pharmacokinetic Modelling of Hyperforin to Predict Drug Interactions with St John's Wort.

BACKGROUND AND OBJECTIVES: Herb-drug interactions with St John's wort (SJW) have been widely studied in numerous clinical studies. The objective of this study was to develop and evaluate a physiologically based pharmacokinetic (PBPK) model for hyperforin (the constituent of SJW responsible for interactions), which has the potential to provide unique insights into SJW interactions and allow prediction of the likely extent of interactions with SJW compared to published interaction reports. METHODS: A PBPK model of hyperforin accounting for the induction of cytochrome P450 (CYP) 3A, CYP2C9 and CYP2C19 was developed in the Simcyp® Simulator (version 17) and verified using published, clinically observed pharmacokinetic data. The predictive performance of this model based on the prediction fold-difference (expressed as the ratio of predicted and clinically observed change in systemic exposure of drug) was evaluated across a range of CYP substrates. RESULTS: The verified PBPK model predicted the change in victim drug exposure due to the induction by SJW (expressed as area under the plasma concentration-time curve (AUC) ratio) within 1.25-fold (0.80-1.25) of that reported in clinical studies. The PBPK simulation indicated that the unbound concentration of hyperforin in the liver was far lower than in the gut (enterocytes). Simulations revealed that induction of intestinal CYP enzymes by hyperforin was found to be more pronounced than the corresponding increase in liver CYP activity (15.5- vs. 1.1-fold, respectively, at a hyperforin dose of 45 mg/day). CONCLUSION: In the current study, a PBPK model for hyperforin was successfully developed, with a predictive capability for the interactions of SJW with different CYP3A, CYP2C9 and CYP2C19 substrates. This PBPK model is valuable to predict the extent of herb-drug interactions with SJW and help design the clinical interaction studies, particularly for new drugs and previously unstudied clinical scenarios.

Pharmacokinetic and cytokine profiles of melanoma patients with dabrafenib and trametinib-induced pyrexia.

PURPOSE: The combination of a BRAF inhibitor dabrafenib and a MEK inhibitor trametinib (CombiDT) has improved outcomes compared with chemotherapy or BRAF inhibitor monotherapy in advanced BRAF V600E/K melanoma. However, CombiDT causes a high incidence of pyrexia and treatment interruptions. Pharmacokinetic analysis may provide an explanation for the pyrexia. METHODS: 34 patients with Stage 3 BRAF V600 melanoma were treated with CombiDT on a clinical trial between August 2014 and June 2017. Plasma concentrations of drugs and metabolites were determined using validated LC-MS assays, in addition to analysis of a panel of cytokines. RESULTS: Pyrexia was experienced by 71% of the patients, with an additional 17% requiring dose interruption related to a pyrexia-like prodrome. Dabrafenib concentrations ranged from 4.0 to 4628 ng/ml and trametinib from 1.0 to 45 ng/ml in 34 patients. N-desmethyl-dabrafenib was the most prevalent metabolite, followed by carboxy- and hydroxy-dabrafenib. No definitive association between pyrexia and AUC or Cmin of the drugs, or metabolites could be observed. The level of IL-1B at the early during treatment (EDT) (as a % of pre-treatment) was higher in the pyrexia group (median 109% (range 32-681%) than in the no-incidence group [56% (26-79%)] (p = 0.029). Similarly, the level of IL-6 at EDT was higher in the pyrexia group [181% (34-3156%) vs 73% (57-101%)] (p = 0.028). CONCLUSIONS: No apparent associations between pyrexia and exposure to the drugs or metabolites could be observed. Greater elevations in IL-1B and IL-6 were observed in patients with pyrexia during the first week of treatment compared to those without pyrexia.

Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide Optimal Dosing Regimens for Imatinib and Potential Drug Interactions in Paediatrics.

Long-term use of imatinib is effective and well-tolerated in children with chronic myeloid leukaemia (CML) yet defining an optimal dosing regimen for imatinib in younger patients is a challenge. The potential interactions between imatinib and coadministered drugs in this "special" population also remains largely unexplored. This study implements a physiologically based pharmacokinetic (PBPK) modeling approach to investigate optimal dosing regimens and potential drug interactions with imatinib in the paediatric population. A PBPK model for imatinib was developed in the Simcyp Simulator (version 17) utilizing in silico, in vitro drug metabolism, and in vivo pharmacokinetic data and verified using an independent set of published clinical pharmacokinetic data. The model was then extrapolated to children and adolescents (aged 2-18 years) by incorporating developmental changes in organ size and maturation of drug-metabolising enzymes and plasma protein responsible for imatinib disposition. The PBPK model described imatinib pharmacokinetics in adult and paediatric populations and predicted drug interaction with carbamazepine, a cytochrome P450 (CYP)3A4 and 2C8 inducer, with a good accuracy (evaluated by visual inspections of the simulation results and predicted pharmacokinetic parameters that were within 1.25-fold of the clinically observed values). The PBPK simulation suggests that the optimal dosing regimen range for imatinib is 230-340 mg/m2/d in paediatrics, which is supported by the recommended initial dose for treatment of childhood CML. The simulations also highlighted that children and adults being treated with imatinib have similar vulnerability to CYP modulations. A PBPK model for imatinib was successfully developed with an excellent performance in predicting imatinib pharmacokinetics across age groups. This PBPK model is beneficial to guide optimal dosing regimens for imatinib and predict drug interactions with CYP modulators in the paediatric population.

The role of solute carrier (SLC) transporters in actinomycin D pharmacokinetics in paediatric cancer patients.

BACKGROUND: Actinomycin D is used for treatment of paediatric cancers; however, a large inter-patient pharmacokinetic (PK) variability and hepatotoxicity are significant limitations to its use and warrant further investigation. Elimination of actinomycin D may be mediated by transporters, as the drug does not seem to undergo significant metabolism. We investigated the role of solute carrier (SLC) transporters in actinomycin D PK. METHODS: Fourteen key SLCs were screened through probe substrate uptake inhibition by actinomycin D in HEK293 cells. Uptake of actinomycin D was further studied in candidate SLCs by measuring intracellular actinomycin D using a validated LCMS assay. Pharmacogenetic analysis was conducted for 60 patients (Clinical trial: NCT00900354), who were genotyped for SNPs for OAT4 and PEPT2. RESULTS: OAT4, OCT2, OCT3 and PEPT2 showed significantly lower probe substrate uptake (mean ± SD 75.0 ± 3.5% (p < 0.0001), 74.8 ± 11.2% (p = 0.001), 81.2 ± 14.0% (p = 0.0083) and 70.7 ± 5.7% (p = 0.0188)) compared to that of control. Intracellular accumulation of actinomycin D was greater compared to vector control in OAT4-transfected cells by 1.5- and 1.4-fold at 10 min (p = 0.01) and 20 min (p = 0.03), and in PEPT2-transfected cells by 1.5- and 1.7-fold at 10 min (p = 0.047) and 20 min (p = 0.043), respectively. Subsequent clinical study did not find a significant association between OAT4 rs11231809 and PEPT2 rs2257212 genotypes, and actinomycin D PK parameters such as clearance (CL) and volume of distribution (Vd). CONCLUSION: Transport of actinomycin D was mediated by OAT4 and PEPT2 in vitro. There was a lack of clinical significance of OAT4 and PEPT2 genotypes as predictors of actinomycin D disposition in paediatric cancer patients.

A Strategy to Refine the Phenotyping Approach and Its Implementation to Predict Drug Clearance: A Physiologically Based Pharmacokinetic Simulation Study.

The phenotyping approach to predict drug metabolism activity is often hampered by a lack of correlation between the probe and the drug of interest. In this article, we present a strategy to refine the phenotyping approach based on a physiologically based pharmacokinetic simulation (implemented in Simcyp Simulator version 17) using previously published models. The apparent clearance (CL/F) of erlotinib was better predicted by the sum of caffeine and i.v. midazolam CL/F (r2  = 0.60) compared to that of either probe drug alone. The clearance of atorvastatin and repaglinide had a strong correlation (r2  = 0.70 and 0.63, respectively) with that of pitavastatin (a SLCO1B1 probe). Use of multiple probes for drugs that are predominantly metabolized by more than one cytochrome P450 (CYP) enzyme should be considered. In a case in which hepatic uptake transporters play a significant role in the disposition of a drug, the pharmacokinetic of a transporter probe will provide better predictions of the drug clearance.

Investigating the potential impact of dose banding for systemic anti-cancer therapy in the paediatric setting based on pharmacokinetic evidence.

BACKGROUND: To make systemic anti-cancer therapy (SACT) preparation more practicable, dose-banding approaches are currently being introduced in many clinical centres. The present study aimed to determine the potential impact of using recently developed National Health Service in England (NHSE) dose-banding tables in a paediatric setting. METHODS: Using pharmacokinetic parameters obtained from 385 drug administrations in 352 children aged from 1 month to 18 years, treated with five drugs (dactinomycin, busulfan, carboplatin, cyclophosphamide and etoposide), individual exposures (area under the plasma drug concentration versus time curve; AUC) obtained using doses rounded according to the published NHSE tables were calculated and compared with those obtained by standard dose calculation methods. RESULTS: For all five drugs, the relative variation between the NHSE dose and the recommended dose (RecDose) (standard individually calculated dose) was between -6% and +5% as expected. In terms of AUC, there was no statistically significant difference in precision between exposures obtained by the RecDose and those obtained with dose banding (absolute value of relative difference 15-34%). CONCLUSION: Based on pharmacokinetic data for these five drugs, the results generated support the implementation of NHSE dose-banding tables. Indeed, inter-patient variability in drug clearance and exposure far outweighs the impact of relatively small drug dose changes associated with dose banding.

Curcumin as a clinically-promising anti-cancer agent: pharmacokinetics and drug interactions.

INTRODUCTION: Curcumin has been extensively studied for its anti-cancer properties. While a diverse array of in vitro and preclinical research support the prospect of curcumin use as an anti-cancer therapeutic, most human studies have failed to meet the intended clinical expectation. Poor systemic availability of orally-administered curcumin may account for this disparity. Areas covered: This descriptive review aims to concisely summarise available clinical studies investigating curcumin pharmacokinetics when administered in different formulations. A critical analysis of pharmacokinetic- and pharmacodynamic-based interactions of curcumin with concomitantly administered drugs is also provided. Expert opinion: The encouraging clinical results of curcumin administration are currently limited to people with colorectal cancer, given that sufficient curcumin concentrations persist in colonic mucosa. Higher parent curcumin systemic exposure, which can be achieved by several newer formulations, has important implications for optimal treatment of cancers other than those in gastrointestinal tract. Curcumin-drug pharmacokinetic interactions are also almost exclusively in the enterocytes, owing to extensive first pass metabolism and poor curcumin bioavailability. Greater scope of these interactions, i.e. modulation of the systemic elimination of co-administered drugs, may be expected from more-bioavailable curcumin formulations. Further studies are still warranted, especially with newer formulations to support the inclusion of curcumin in cancer therapy regimens.

A population pharmacokinetic model of AT9283 in adults and children to predict the maximum tolerated dose in children with leukaemia.

AIMS: AT9283 is used to treat patients with solid tumours and patients with leukaemia. However, the maximum tolerated dose (MTD) for children with leukaemia remains unknown due to early termination of the Phase I trial. The aim of this study was to develop a population model of AT9283 to describe the pharmacokinetics in adults and children and to estimate the MTD in children with leukaemia. METHODS: Data from Phase I dose-escalation studies in adults and children were used to build a population pharmacokinetic model (NONMEM v7.3). Potential covariates investigated included body weight, body surface area (BSA), glomerular filtration rate (GFR), age and sex. Model-derived area under the concentration-time curve was used to investigate the relationship between dose and exposure in adults and children. RESULTS: The plasma concentrations of AT9283 (n = 1770) from 92 patients (53 adults, 39 children) were used to build a two-compartment model with all pharmacokinetic parameters scaled using body weight. Renal function (GFR), but not BSA, was a significant covariate for the clearance of AT9283. In children with leukaemia (median weight 16 kg), a flat dose of 500 mg 72 h-1 provided similar drug exposures at the MTD as the adult population. The estimated MTD for children with leukaemia, therefore, is 30 mg kg-1  72 h-1 . CONCLUSION: For adults, GFR was a significant predictor of clearance, whilst body-weight based dosing was more useful than BSA in determining the drug exposure in children. The MTD was estimated to be 30 mg kg-1  72 h-1 children with leukaemia.

Towards a Model-Based Dose Recommendation for Doxorubicin in Children.

Following the publication of our paper regarding a population-based model of doxorubicin pharmacokinetics in children in Clinical Pharmacokinetics last year (Voller et al. 54:1139-1149, 2015), we have received many inquiries on the practical clinical consequences of this model; however, a population-based model is only one of the aspects to be taken into account when developing dosing algorithms. In addition, any new method of dose calculation would need clinical validation and, subsequently, a new clinical trial. However, such a trial, especially with regard to burden to the children involved, requires optimal preparation and the selection of the best hypotheses. The European Paediatric Oncology Off-Patent Medicines Consortium (EPOC), represented by the authors, would therefore like to initiate an interdisciplinary discussion on the clinical and pharmacological goals for dose calculation. This current opinion summarizes the existing knowledge on the pharmacokinetics and pharmacodynamics of doxorubicin. Our aim was to define the clinical needs as precisely as possible, with the intention of stimulating discussion between the clinical pediatric oncologist and the pediatric pharmacologist. By doing so, we hope to define surrogates for best practice of a common doxorubicin dose in children. The intent is for a trial to validate a rational dose calculation rule, leading to a regulatory process and subsequent labeling.