Simultaneous determination of three tyrosine kinase inhibitors and three triazoles in human plasma by LC-MS/MS: applications to therapeutic drug monitoring and drug-drug interaction studies

Tyrosine kinase inhibitors (TKIs) and triazole antifungals are the first-line drugs for treating chronic myeloid leukemia (CML) and fungal infections, respectively, but both suffer from large exposure differences and narrow therapeutic windows. Moreover, these two types of drugs are commonly used together in CML patients with fungal infections. Multiple studies and guidelines have suggested the importance of therapeutic drug monitoring (TDM) of TKIs and triazoles. Currently, methods for the simultaneous determination of both types of drugs are limited. We developed a simple, rapid, and reliable liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of three commonly used TKIs (imatinib, dasatinib, and nilotinib) and three commonly used triazoles (voriconazole, itraconazole, and posaconazole) in human plasma. The analytes were eluted on a Welch XB-C18 analytical column (50 × 2.1 mm, 5 µm) at 0.7 mL/min, using a gradient elution of 10 mM ammonium formate (A) and methanol-acetonitrile-isopropanol (80:10:10, v/v/v) containing 0.2 % formic acid (B) with a total analysis time of 3.5 min. The calibration curves were linear over the range from 20 to 4000 ng/mL for imatinib and nilotinib, from 2 to 400 ng/mL for dasatinib, and from 50 to 10,000 ng/mL for voriconazole, itraconazole, and posaconazole. Selectivity, accuracy, precision, recovery, matrix effect, and stability all met the validation requirements. The method was successfully used for TDM in CML patients who co-treated with both TKIs and triazoles. Drug-drug interaction analysis between TKIs and triazoles showed that a significant positive correlation was observed between imatinib and voriconazole, as well as dasatinib and voriconazole. Therefore, this method can be well applied in clinical TDM for patients receiving TKIs, triazoles, or both simultaneously.

Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic

Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.

Preclinical Systemic Pharmacokinetics, Dose Proportionality, and Central Nervous System Distribution of the ATM Inhibitor WSD0628, a Novel Radiosensitizer for the Treatment of Brain Tumors

Radiation therapy, a standard treatment option for many cancer patients, induces DNA double-strand breaks (DSBs), leading to cell death. Ataxia telangiectasia mutated (ATM) kinase is a key regulator of DSB repair, and ATM inhibitors are being explored as radiosensitizers for various tumors, including primary and metastatic brain tumors. Efficacy of radiosensitizers for brain tumors may be influenced by a lack of effective drug delivery across the blood-brain barrier. The objective of this study was to evaluate the systemic pharmacokinetics and mechanisms that influence the central nervous system (CNS) distribution of WSD0628, a novel and potent ATM inhibitor, in the mouse. Further, we have used these observations to form the basis of predicting effective exposures for clinical application. We observed a greater than dose proportional increase in exposure, likely due to saturation of clearance processes. Our results show that WSD0628 is orally bioavailable and CNS penetrant, with unbound partitioning in CNS (i.e., unbound tissue partition coefficient) between 0.15 and 0.3. CNS distribution is not limited by the efflux transporters P-glycoprotein and breast cancer resistant protein. WSD0628 is distributed uniformly among different brain regions. Thus, WSD0628 has favorable pharmacokinetic properties and potential for further exploration to determine the pharmacodynamics-pharmacokinetics efficacy relationship in CNS tumors. This approach will provide critical insights for the clinical translation of WSD0628 for the treatment of primary and secondary brain tumors. SIGNIFICANCE STATEMENT: This study evaluates the preclinical systemic pharmacokinetics, dose proportionality, and mechanisms influencing CNS distribution of WSD0628, a novel ATM inhibitor for the treatment of brain tumors. Results indicate that WSD0628 is orally bioavailable and CNS penetrant without efflux transporter liability. We also observed a greater than dose proportional increase in exposure in both the plasma and brain. These favorable pharmacokinetic properties indicate WSD0628 has potential for further exploration for use as a radiosensitizer in the treatment of brain tumors.

Physiologically based pharmacokinetic modeling of imatinib and N-desmethyl imatinib for drug-drug interaction predictions

The first-generation tyrosine kinase inhibitor imatinib has revolutionized the development of targeted cancer therapy and remains among the frontline treatments, for example, against chronic myeloid leukemia. As a substrate of cytochrome P450 (CYP) 2C8, CYP3A4, and various transporters, imatinib is highly susceptible to drug-drug interactions (DDIs) when co-administered with corresponding perpetrator drugs. Additionally, imatinib and its main metabolite N-desmethyl imatinib (NDMI) act as inhibitors of CYP2C8, CYP2D6, and CYP3A4 affecting their own metabolism as well as the exposure of co-medications. This work presents the development of a parent-metabolite whole-body physiologically based pharmacokinetic (PBPK) model for imatinib and NDMI used for the investigation and prediction of different DDI scenarios centered around imatinib as both a victim and perpetrator drug. Model development was performed in PK-Sim® using a total of 60 plasma concentration-time profiles of imatinib and NDMI in healthy subjects and cancer patients. Metabolism of both compounds was integrated via CYP2C8 and CYP3A4, with imatinib additionally transported via P-glycoprotein. The subsequently developed DDI network demonstrated good predictive performance. DDIs involving imatinib and NDMI were simulated with perpetrator drugs rifampicin, ketoconazole, and gemfibrozil as well as victim drugs simvastatin and metoprolol. Overall, 12/12 predicted DDI area under the curve determined between first and last plasma concentration measurements (AUClast) ratios and 12/12 predicted DDI maximum plasma concentration (Cmax) ratios were within twofold of the respective observed ratios. Potential applications of the final model include model-informed drug development or the support of model-informed precision dosing.

Current Progress on the Influence Human Genetics Has on the Efficacy of Tyrosine Kinase Inhibitors Used to Treat Chronic Myeloid Leukemia

The use of tyrosine kinase inhibitors (TKIs) has become the mainstay of treatment in patients suffering from chronic myeloid leukemia (CML), an adult leukemia caused by a reciprocal translocation between chromosomes 9 and 22, which creates an oncogene resulting in a myeloproliferative neoplasm. These drugs function by inhibiting the ATP-binding site on the fusion oncoprotein and subsequently halting proliferative activity. The goal of this work is to investigate the current state of research into genetic factors that influence the efficacy of four FDA-approved TKIs used to treat CML. This overview attempts to identify genetic criteria that could be considered when choosing one drug over the others and to identify where more research is needed. Our results suggest that the usual liver enzymes impacting patient response may not be a major factor affecting the efficacy of imatinib, nilotinib, and bosutinib, and yet, that is where most of the past research has focused. More research is warranted on the impact that human polymorphisms of the CYP enzymes have on dasatinib. The impact of polymorphisms in UGT1A1 should be investigated thoroughly in other TKIs, not only nilotinib. The role of influx and efflux transporters has been inconsistent thus far, possibly due to failures to account for the multiple proteins that can transport TKIs and the impact that tumors have on transporter expression. Because physicians cannot currently use a patient's genetic profile to better target their treatment with TKIs, it is critical that more research be conducted on auxiliary pathways or off-target binding effects to generate new leads for further study. Hopefully, new avenues of research will help explain treatment failures and improve patient outcomes.

Recent developments in antimalarial drug discovery

Although malaria remains a big burden to many countries that it threatens their socio-economic stability, particularly in the countries where malaria is endemic, there have been great efforts to eradicate this disease with both successes and failures. For example, there has been a great improvement in malaria prevention and treatment methods with a net reduction in infection and mortality rates. However, the disease remains a global threat in terms of the number of people affected because it is one of the infectious diseases that has the highest prevalence rate, especially in Africa where the deadly Plasmodium falciparum is still widely spread. Methods to fight malaria are being diversified, including the use of mosquito nets, the target candidate profiles (TCPs) and target product profiles (TPPs) of medicine for malarial venture (MMV) strategy, the search for newer and potent drugs that could reverse chloroquine resistance, and the use of adjuvants such as rosiglitazone and sevuparin. Although these adjuvants have no antiplasmodial activity, they can help to alleviate the effects which result from plasmodium invasion such as cytoadherence. The list of new antimalarial drugs under development is long, including the out of ordinary new drugs MMV048, CDRI-97/78 and INE963 from South Africa, India and Novartis, respectively.

CYP2D6 and CYP2C8 pharmacogenetics and pharmacological interactions to predict imatinib plasmatic exposure in GIST patients

AIMS

Patients on treatment with oral fixed dose imatinib are frequently under- or overexposed to the drug. We investigated the association between the gene activity score (GAS) of imatinib-metabolizing cytochromes (CYP3A4, CYP3A5, CYP2D6, CYP2C9, CYP2C19, CYP2C8) and imatinib and nor-imatinib exposure. We also investigated the impact of concurrent drug-drug-interactions (DDIs) on the association between GAS and imatinib exposure.

METHODS

Serial plasma samples were collected from 33 GIST patients treated with imatinib 400 mg daily within a prospective clinical trial. Imatinib and nor-imatinib C_trough were quantified by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Genetic polymorphisms with a functional impact on imatinib-metabolizing cytochromes were identified and a GAS was calculated for each gene. A DDI-adjusted GAS was also generated.

RESULTS

Imatinib and nor-imatinib C_trough were measured in 161 plasma samples. CYP2D6 GAS and metabolizer status based on genotype were associated with imatinib and (imatinib + nor-imatinib) C_trough . CYP2D6 poor and intermediate metabolizers were predicted to have a lower nor-imatinib/imatinib metabolic ratio than normal metabolizers (0.197 and 0.193 vs. 0.247, P = .0205), whereas CYP2C8*3 carriers had a higher ratio than CYP2C8*1/*1 patients (0.263 vs. 0.201, P = .0220). CYP2C9 metabolizer status was inversely related to the metabolic ratio with an effect probably driven by the linkage disequilibrium between CYP2C9*2 and CYP2C8*3. The CYP2D6 DDI-adjusted GAS was still predictive of imatinib exposure.

CONCLUSIONS

These findings highlight that CYP2D6 plays a major role in imatinib pharmacokinetics, but other players (i.e., CYP2C8) may influence imatinib exposure. These findings could drive the selection of patients more susceptible to imatinib under- or overexposure who could be candidates for personalized treatment and intensified monitoring strategies.

The Application of Virtual Therapeutic Drug Monitoring to Assess the Pharmacokinetics of Imatinib in a Chinese Cancer Population Group

PURPOSE

Imatinib is used in gastrointestinal stromal tumours (GIST) and chronic myeloid leukaemia (CML). Oncology patients demonstrate altered physiology compared to healthy adults, e.g. reduced haematocrit, increased α-1 acid glycoprotein, decreased albumin and reduced glomerular filtration rate (GFR), which may influence imatinib pharmacokinetics. Given that Chinese cancer patients often report raised imatinib plasma concentrations and wider inter-individual variability reported in trough concentration when compared to Caucasian cancer patients, therapeutic drug monitoring (TDM) has been advocated.

METHOD

This study utilised a previously validated a Chinese cancer population and assessed the impact of imatinib virtual-TDM in Chinese and Caucasian cancer populations across a dosing range from 200-800 mg daily.

RESULTS

Staged dose titration to 800 mg daily, resulted in recapitulation to within the target therapeutic range for 50 % (Chinese) and 42.1% (Caucasian) subjects possessing plasma concentration < 550 ng/mL when dosed at 400 mg daily. For subjects with plasma concentrations >1500 ng/mL when dosed at 400 mg daily, a dose reduction to 200 mg once daily was able to recover 67 % (Chinese) and 87.4 % (Caucasian) patients to the target therapeutic range.

CONCLUSION

Virtual TDM highlights the benefit of pharmacokinetic modelling to optimising treatments in challenging oncology population groups.

Real-world efficacy and safety outcomes of imatinib treatment in patients with chronic myeloid leukemia: An Australian experience

Tyrosine kinase inhibitors (TKI) have revolutionized the treatment of chronic myeloid leukemia (CML), but patients still experience treatment-limiting toxicities or therapeutic failure. To investigate the real-world use and outcomes of imatinib in patients with CML in Australia, a retrospective cohort study of patients with CML commencing imatinib (2001-2018) was conducted across two sites. Prescribing patterns, tolerability outcomes, and survival and molecular response were evaluated. 86 patients received 89 imatinib treatments. Dose modifications were frequently observed (12-month rate of 58%). At last follow-up, 62 patients (5-year rate of 55%) had permanently discontinued imatinib treatment, of which 44 switched to another TKI (5-year rate of 46%). Within 3 months of starting imatinib, 43% (95% CI, 32%-53%) of patients experienced imatinib-related grade ≥3 adverse drug reactions (ADRs). Higher comorbidity score, lower body weight, higher imatinib starting dose, and Middle Eastern or North African ancestry were associated with a higher risk of grade ≥3 ADR occurrence on multivariable analysis (MVA). Estimated overall survival and event-free survival rates at 3 years were 97% (95% CI, 92%-100%) and 81% (95% CI, 72%-92%), respectively. Cumulative incidence of major molecular response (MMR) at 3 years was 63% (95% CI, 50%-73%). On MVA, imatinib starting dose, ELTS score, BCR-ABL1 transcript type, pre-existing pulmonary disease, and potential drug-drug interactions were predictive of MMR. In conclusion, imatinib induced deep molecular responses that translated to good survival outcomes in a real-world setting, but was associated with a higher incidence of ADRs, dose modifications and treatment discontinuations than in clinical trials.

Cytochromes P450 2C8 and 3A Catalyze the Metabolic Activation of the Tyrosine Kinase Inhibitor Masitinib

Masitinib is a small molecule tyrosine kinase inhibitor under investigation for the treatment of amyotrophic lateral sclerosis, mastocytosis, and COVID-19. Hepatotoxicity has been reported in some patients while taking masitinib. The liver injury is thought to involve hepatic metabolism of masitinib by cytochrome P450 (P450) enzymes to form chemically reactive, potentially toxic metabolites. The goal of the current investigation was to determine the P450 enzymes involved in the metabolic activation of masitinib in vitro. In initial studies, masitinib (30 μM) was incubated with pooled human liver microsomes in the presence of NADPH and potassium cyanide to trap reactive iminium ion metabolites as cyano adducts. Masitinib metabolites and cyano adducts were analyzed using reversed-phase liquid chromatography-tandem mass spectrometry. The primary active metabolite, N-desmethyl masitinib (M485), and several oxygenated metabolites were detected along with four reactive metabolite cyano adducts (MCN510, MCN524, MCN526, and MCN538). To determine which P450 enzymes were involved in metabolite formation, reaction phenotyping experiments were conducted by incubation of masitinib (2 μM) with a panel of recombinant human P450 enzymes and by incubation of masitinib with human liver microsomes in the presence of P450-selective chemical inhibitors. In addition, enzyme kinetic assays were conducted to determine the relative kinetic parameters (apparent K_m and V_max) of masitinib metabolism and cyano adduct formation. Integrated analysis of the results from these experiments indicates that masitinib metabolic activation is catalyzed primarily by P450 3A4 and 2C8, with minor contributions from P450 3A5 and 2D6. These findings provide further insight into the pathways involved in the generation of reactive, potentially toxic metabolites of masitinib. Future studies are needed to evaluate the impact of masitinib metabolism on the toxicity of the drug in vivo.

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.

Pharmacogenetics of Drugs Used in the Treatment of Cancers

Pharmacogenomics is based on the understanding of the individual differences in drug use, the response to drug therapy (efficacy and toxicity), and the mechanisms underlying variable drug responses. The identification of DNA variants which markedly contribute to inter-individual variations in drug responses would improve the efficacy of treatments and decrease the rate of the adverse side effects of drugs. This review focuses only on the impact of polymorphisms within drug-metabolizing enzymes on drug responses. Anticancer drugs usually have a very narrow therapeutic index; therefore, it is very important to use appropriate doses in order to achieve the maximum benefits without putting the patient at risk of life-threatening toxicities. However, the adjustment of the appropriate dose is not so easy, due to the inheritance of specific polymorphisms in the genes encoding the target proteins and drug-metabolizing enzymes. This review presents just a few examples of such polymorphisms and their impact on the response to therapy.

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 (C_ss,min ).

RESULTS

The PBPK model of imatinib demonstrated excellent predictive performance in describing pharmacokinetics and the attained C_ss,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 C_ss,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.

Pharmacogenomics of Impaired Tyrosine Kinase Inhibitor Response: Lessons Learned From Chronic Myelogenous Leukemia

The use of small molecules became one key cornerstone of targeted anti-cancer therapy. Among them, tyrosine kinase inhibitors (TKIs) are especially important, as they were the first molecules to proof the concept of targeted anti-cancer treatment. Since 2001, TKIs can be successfully used to treat chronic myelogenous leukemia (CML). CML is a hematologic neoplasm, predominantly caused by reciprocal translocation t(9;22)(q34;q11) leading to formation of the so-called BCR-ABL1 fusion gene. By binding to the BCR-ABL1 kinase and inhibition of downstream target phosphorylation, TKIs, such as imatinib or nilotinib, can be used as single agents to treat CML patients resulting in 80 % 10-year survival rates. However, treatment failure can be observed in 20-25 % of CML patients occurring either dependent or independent from the BCR-ABL1 kinase. Here, we review approved TKIs that are indicated for the treatment of CML, their side effects and limitations. We point out mechanisms of TKI resistance focusing either on BCR-ABL1-dependent mechanisms by summarizing the clinically observed BCR-ABL1-mutations and their implications on TKI binding, as well as on BCR-ABL1-independent mechanisms of resistances. For the latter, we discuss potential mechanisms, among them cytochrome P450 implications, drug efflux transporter variants and expression, microRNA deregulation, as well as the role of alternative signaling pathways. Further, we give insights on how TKI resistance could be analyzed and what could be learned from studying TKI resistance in CML in vitro.

Quantification of eight hematological tyrosine kinase inhibitors in both plasma and whole blood by a validated LC-MS/MS method

Therapeutic drug monitoring (TDM) of tyrosine kinase inhibitors (TKIs) in cancer therapy offers the potential to improve treatment efficacy while minimizing toxicity. Therefore, a high-throughput, sensitive LC-MS/MS method was developed and validated, to be used for personalized treatment of hematologic malignancies. The assay allows the simultaneous quantification in plasma (EDTA and heparin) and whole blood of eight TKIs, including bosutinib, dasatinib, gilteritinib, ibrutinib, imatinib, midostaurin, nilotinib and ponatinib, which are used in the treatment of chronic and acute myeloid leukemia (CML, AML) and chronic lymphocytic leukemia (CLL). The procedure involves simple protein precipitation of 50 μL of sample, a 4-min chromatographic separation by applying gradient elution on a standard reverse phase column, and tandem mass spectrometric detection. The method was successfully validated based on international guidelines in terms of calibration curves, precision (within-run CV 0.74-16.4%; between-run CV 1.65-17.8%), accuracy (within-run bias 0.07-19.8%; between-run bias 0.05 to -17.6%), carry-over (max 19.4%, for ponatinib), selectivity, matrix-effects, recovery (ranging from 61 to 128%), stability (only issues observed for ibrutinib) and dilution integrity. Furthermore, the accuracy of the method was demonstrated by analyzing external quality controls, with a maximum bias of -11.3%. Assay applicability was demonstrated by analyzing authentic plasma and whole blood samples in order to derive blood-plasma ratios and the variation thereof. The latter are important to allow possible blood-plasma conversion when envisaging possible future implementation of TDM via dried blood microsampling. The presented method can be applied in clinical practice for performing TDM of TKIs in plasma and whole blood samples.

Disease-drug and drug-drug interaction in COVID-19: Risk and assessment

COVID-19 is announced as a global pandemic in 2020. Its mortality and morbidity rate are rapidly increasing, with limited medications. The emergent outbreak of COVID-19 prompted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) keeps spreading. In this infection, a patient's immune response plays pivotal role in the pathogenesis. This inflammatory factor was shown by its mediators that, in severe cases, reach the cytokine at peaks. Hyperinflammatory state may sparks significant imbalances in transporters and drug metabolic machinery, and subsequent alteration of drug pharmacokinetics may result in unexpected therapeutic response. The present scenario has accounted for the requirement for therapeutic opportunities to relive and overcome this pandemic. Despite the diminishing developments of COVID-19, there is no drug still approved to have significant effects with no side effect on the treatment for COVID-19 patients. Based on the evidence, many antiviral and anti-inflammatory drugs have been authorized by the Food and Drug Administration (FDA) to treat the COVID-19 patients even though not knowing the possible drug-drug interactions (DDI). Remdesivir, favipiravir, and molnupiravir are deemed the most hopeful antiviral agents by improving infected patient’s health. Dexamethasone is the first known steroid medicine that saved the lives of seriously ill patients. Some oligopeptides and proteins have also been using. The current review summarizes medication updates to treat COVID-19 patients in an inflammatory state and their interaction with drug transporters and drug-metabolizing enzymes. It gives an opinion on the potential DDI that may permit the individualization of these drugs, thereby enhancing the safety and efficacy.

The effect of grape seed and green tea extracts on the pharmacokinetics of imatinib and its main metabolite, N-desmethyl imatinib, in rats

BACKGROUND

Imatinib is mainly metabolized by CYP3A4 and to a lesser extent by other isoenzymes, with N-desmethyl imatinib being its major equipotent metabolite. Being a CYP3A4 substrate, imatinib co-administration with CYP3A4 modulators would change its pharmacokinetic profile. The cancer chemoprevention potential and anticancer efficacy of many herbal products such as grape seed (GS) and green tea (GT) extracts had led to an increase in their concomitant use with anticancer agents. GS and GT extracts were demonstrated to be potent inhibitors of CYP3A4. The aim of this study is to investigate the effect of standardized GS and/or GT extracts at two different doses on the pharmacokinetics of imatinib and its metabolite, N-desmethyl imatinib, in SD-rats.

METHODS

Standardized GS and/or GT extracts were administered orally once daily for 21 days, at low (l) and high (h) doses, 50 and 100 mg/kg, respectively, before the administration of a single intragastric dose of imatinib. Plasma samples were collected and analyzed for imatinib and N-desmethyl imatinib concentrations using LC-MS/MS method, then their non-compartmental pharmacokinetic parameters were determined.

RESULTS

h-GS dose significantly decreased imatinib's Cmax and the [Formula: see text] by 61.1 and 72.2%, respectively. Similar effects on N-desmethyl imatinib's exposure were observed as well, in addition to a significant increase in its clearance by 3.7-fold. l-GT caused a significant decrease in imatinib's Cmax and [Formula: see text] by 53.6 and 63.5%, respectively, with more significant effects on N-desmethyl imatinib's exposure, which exhibited a significant decrease by 79.2 and 81.1%, respectively. h-GT showed similar effects as those of l-GT on the kinetics of imatinib and its metabolite. However, when these extracts were co-administered at low doses, no significant effects were shown on the pharmacokinetics of imatinib and its metabolite. Nevertheless, increasing the dose caused a significant decrease in Cmax of N-desmethyl imatinib by 71.5%.

CONCLUSIONS

These results demonstrated that the pharmacokinetics of imatinib and N-desmethyl imatinib had been significantly affected by GS and/or GT extracts, which could be partially explained by the inhibition of CYP3A-mediated metabolism. However, the involvement of other kinetic pathways such as other isoenzymes, efflux and uptake transporters could be involved and should be characterized.

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 (k_i,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 k_i 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.

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.

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport: Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.

Interaction between phytotherapy and oral anticancer agents: prospective study and literature review

Cancer is becoming more prevalent in elderly patient. Due to polypharmacy, older adults with cancer are predisposed to drug-drug interactions. There is also an increasing interest in the use of complementary and alternative medicine (CAM). Thirty to seventy percent of patients with cancer have used CAM. Through pharmaceutical counseling sessions, we can provide advices on herb-drug interactions (HDI). All the patients seen in pharmaceutical counseling sessions were prospectively included. Information was collected during these sessions: prescribed medication (oral anticancer agents (OAA) and other drugs), CAM (phytotherapy especially), and use of over-the-counter (OTC) drugs. If pharmacist considered an interaction or an intervention clinically relevant, the oncologist was notified. Then, a literature review was realized to identify the potential HDI (no interactions, precautions for use, contraindication). Among 201 pharmacist counseling sessions, it resulted in 104 interventions related to 46 HDI, 28 drug-drug interactions and 30 others (wrong dosage, omission…). To determine HDI, we review 73 medicinal plants which are used by our patients with cancer and 31 OAA. A total of 1829 recommendations were formulated about 59 (75%) medical plants and their interaction with an OAA. Herb-drug interactions should not be ignored by healthcare providers in their management of cancer patients in daily practice.

The impact of azole antifungal drugs on imatinib metabolism in human liver microsomes

1. Imatinib is widely used for the treatment of hematologic malignancies. It is common that imatinib is clinically co-prescribed with azole antifungal agents since these patients are more prone to invasive antifungal infection. The present study was to investigate the effects of azole antifungal drugs, including ketoconazole, fluconazole, voriconazole, itraconazole and posaconazole on imatinib metabolism. 2. The main metabolites, 1-OH midazolam and N-desmethyl imatinib, were determined in the absence and in the presence of various levels of ketoconazole, fluconazole, voriconazole, itraconazole and posaconazole. The relevant assay was also performed to screen mechanism-based inhibitors (MBI). 3.   The inhibition ability of 1-OH midazolam formation from midazolam based on IC₅₀ values was ketoconazole (0.09 µM)>itraconazole (0.31 µM)> posaconazole (0.68 µM)>voriconazole (2.10 µM) > fluconazole (8.90 µM). Similarly, the rank order of inhibitory effects on formation of N-desmethyl imatinib from imatinib was ketoconazole (4.58 µM)>itraconazole (17.45 µM)> posaconazole (31.02 µM)> voriconazole (367.9 µM) >fluconazole (1.11 mM). Posaconazole and itraconazole displayed evidence of MBI. Additionally, imatinib was also shown as a MBI of CYP3A with IC₅₀ value of 5.40 µM against the midazolam. 4. The significant difference in IC₅₀ values of midazolam and imatinib inhibited by azole antifungal agents was observed. The role of CYP2C8 in imatinib metabolism and imatinib autoinhibits CYP3A activity may explain this difference. Our findings suggest that the azole antifungal agents might have limited impacts on imatinib exposure by CYP3A activity.

Influence of CYP2C8 polymorphisms on imatinib steady-state trough level in chronic myeloid leukemia and gastrointestinal stromal tumor patients

Imatinib trough levels have been associated with its clinical effects. During chronic use of imatinib, CYP2C8 becomes an important metabolizing enzyme because of cytochrome P450 3A4 (CYP3A4) autoinhibition. Single nucleotide polymorphisms (SNPs) in CYP2C8 may affect imatinib trough levels. This study investigates the effect of common CYP2C8 polymorphisms [*1B (rs7909236), *1C (rs17110453), *3 (rs11572080 and rs10509681), and *4 (rs1058930)] on steady-state trough levels imatinib during chronic imatinib use in 43 patients with chronic myeloid leukemia or gastrointestinal stromal tumors. Standardized imatinib trough levels did not show a significant difference between wild-type and variant groups for any of the tested SNPs, but an association with age was found, with older patients having higher trough levels. This suggests that common CYP2C8 SNPs have no effect on the pharmacokinetics of imatinib.

Utility of physiologically based pharmacokinetic (PBPK) modeling in oncology drug development and its accuracy: a systematic review

PURPOSE

Physiologically based pharmacokinetic (PBPK) modeling, a mathematical modeling approach which uses a pharmacokinetic model to mimick human physiology to predict drug concentration-time profiles, has been used for the discover and development of drugs in various fields, including oncology, since 2000. There have been a few general review articles on the utilization of PBPK in the development of oncology drugs, but these do not include an evaluation of model prediction accuracy. We therefore conducted a systematic review to define the accuracy of PBPK model prediction and its utility throughout all the developmental phases of oncology drugs.

METHODS

A systematic search was performed in the PubMed, PubMed Central and Cochrane Library databases from 1980 to February 2017 for articles (1) written in English, (2) focused on oncology or antineoplastic or anticancer drugs, tumor or cancer or anticancer drugs listed in the U.S. National Institutes of Health and (3) involving a PBPK model. The absolute-average-folding-errors (AAFEs) of the area under the curve (AUC) between predicted and observed values in each article were calculated to assess model prediction accuracy.

RESULTS

Of the 2341 articles initially identified by our search of the databases, 40 were included in the review analysis. These articles reported on six types of studies, i.e. in vivo (n = 4), first-in-human (n = 5), phase II/III clinical trials (n = 9), organ impairment (n = 3), pediatrics (n = 4) and drug-drug interactions (n = 15). AAFEs of the predicted AUC for all groups of studies were within 1.3-fold of each other despite variations in experimental methodologies.

CONCLUSION

PBPK modeling is a potential tool which can be effectively applied throughout all phases of oncology drug development. The number of experimental animals and human participants enrolled in the studies can be reduced using PBPK modeling and PBPK-population-PK modeling. The limited number of publications of unsuccessful model application to date may contribute to bias toward the usefulness of modeling.

Pharmacogenetics and Pharmacogenomics of Targeted Therapeutics in Chronic Myeloid Leukemia

The advent of targeted therapeutics has greatly improved outcomes of chronic myeloid leukemia (CML) patients. Despite increased efficacy and better clinical responses over cytotoxic chemotherapies, many patients receiving targeted drugs exhibit a poor initial response, develop drug resistance, or undergo relapse after initial success. This inter-individual variation in response has heightened the interest in studying pharmacogenetics and pharmacogenomics (PGx) of cancer drugs. In this review, we discuss the influence of various germline and somatic factors on targeted drug response in CML. Specifically, we examine the role of genetic variants in drug metabolism genes, i.e. CYP3A family genes, and drug transporters, i.e. ABC and SLC family genes. Additionally, we focus on acquired somatic variations in BCR-ABL1, and the potential role played by additional downstream signaling pathways, in conferring resistance to targeted drugs in CML. This review highlights the importance of PGx of targeted therapeutics and its potential application to improving treatment decisions and patient outcomes.

Pharmacogenetics and the treatment of chronic myeloid leukemia: how relevant clinically? An update

Despite the excellent efficacy and improved clinical responses obtained with imatinib mesylate (IM), development of resistance in a significant proportion of chronic myeloid leukemia (CML) patients on IM therapy have emerged as a challenging problem in clinical practice. Resistance to imatinib can be due to heterogeneous array of factors involving BCR/ABL-dependent and BCR/ABL-independent pathways. Although BCR/ABL mutation is the major contributory factor for IM resistance, reduced bio-availability of IM in leukemic cells is also an important pharmacokinetic factor that contributes to development of resistance to IM in CML patients. The contribution of polymorphisms of the pharmacogenes in relation to IM disposition and treatment outcomes have been studied by various research groups in numerous population cohorts. However, the conclusions arising from these studies have been highly inconsistent. This review encompasses an updated insight into the impact of pharmacogenetic variability on treatment response of IM in CML patients.

Pharmacogenetics of drug transporters in modulating imatinib disposition and treatment outcomes in chronic myeloid leukemia & gastrointestinal stromal tumor patients

The use of imatinib in the treatment of BCR-ABL-positive chronic myeloid leukemia and gastrointestinal stromal tumors has significantly improved survival outcomes in patients afflicted by these malignancies. However, a substantial proportion of imatinib-treated patients still experience treatment failure. Suboptimal concentrations of imatinib have been postulated to contribute at least partially to the development of resistance against imatinib. Indeed, variations in the genes encoding drug transporters have been reported to markedly influence imatinib disposition and treatment outcomes in various populations. This review aims to consolidate and critically assess the studies conducted to date which have investigated the influence of pharmacogenetic variants in drug transporters on the disposition of imatinib and treatment outcomes in Asians and other populations.

Role of gemfibrozil as an inhibitor of CYP2C8 and membrane transporters

INTRODUCTION

Cytochrome P450 (CYP) 2C8 is a drug metabolizing enzyme of major importance. The lipid-lowering drug gemfibrozil has been identified as a strong inhibitor of CYP2C8 in vivo. This effect is due to mechanism-based inhibition of CYP2C8 by gemfibrozil 1-O-β-glucuronide. In vivo, gemfibrozil is a fairly selective CYP2C8 inhibitor, which lacks significant inhibitory effect on other CYP enzymes. Gemfibrozil can, however, have a smaller but clinically meaningful inhibitory effect on membrane transporters, such as organic anion transporting polypeptide 1B1 and organic anion transporter 3. Areas covered: This review describes the inhibitory effects of gemfibrozil on CYP enzymes and membrane transporters. The clinical drug interactions caused by gemfibrozil and the different mechanisms contributing to the interactions are reviewed in detail. Expert opinion: Gemfibrozil is a useful probe inhibitor of CYP2C8 in vivo, but its effect on membrane transporters has to be taken into account in study design and interpretation. Moreover, gemfibrozil could be used to boost the pharmacokinetics of CYP2C8 substrate drugs. Identification of gemfibrozil 1-O-β-glucuronide as a potent mechanism-based inhibitor of CYP2C8 has led to recognition of glucuronide metabolites as perpetrators of drug-drug interactions. Recently, also acyl glucuronide metabolites of clopidogrel and deleobuvir have been shown to strongly inhibit CYP2C8.

Role of Cytochrome P450 2C8 in Drug Metabolism and Interactions

During the last 10-15 years, cytochrome P450 (CYP) 2C8 has emerged as an important drug-metabolizing enzyme. CYP2C8 is highly expressed in human liver and is known to metabolize more than 100 drugs. CYP2C8 substrate drugs include amodiaquine, cerivastatin, dasabuvir, enzalutamide, imatinib, loperamide, montelukast, paclitaxel, pioglitazone, repaglinide, and rosiglitazone, and the number is increasing. Similarly, many drugs have been identified as CYP2C8 inhibitors or inducers. In vivo, already a small dose of gemfibrozil, i.e., 10% of its therapeutic dose, is a strong, irreversible inhibitor of CYP2C8. Interestingly, recent findings indicate that the acyl-β-glucuronides of gemfibrozil and clopidogrel cause metabolism-dependent inactivation of CYP2C8, leading to a strong potential for drug interactions. Also several other glucuronide metabolites interact with CYP2C8 as substrates or inhibitors, suggesting that an interplay between CYP2C8 and glucuronides is common. Lack of fully selective and safe probe substrates, inhibitors, and inducers challenges execution and interpretation of drug-drug interaction studies in humans. Apart from drug-drug interactions, some CYP2C8 genetic variants are associated with altered CYP2C8 activity and exhibit significant interethnic frequency differences. Herein, we review the current knowledge on substrates, inhibitors, inducers, and pharmacogenetics of CYP2C8, as well as its role in clinically relevant drug interactions. In addition, implications for selection of CYP2C8 marker and perpetrator drugs to investigate CYP2C8-mediated drug metabolism and interactions in preclinical and clinical studies are discussed.

Human hepatocyte assessment of imatinib drug-drug interactions - complexities in clinical translation

AIM

Inducers and inhibitors of CYP3A, such as ritonavir and efavirenz, may be used as part of the highly active antiretroviral therapy (HAART) to treat HIV patients. HIV patients with chronic myeloid leukemia or gastrointestinal stromal tumour may need imatinib, a CYP3A4 substrate with known exposure response-relationships. Administration of imatinib to patients on ritonavir or efavirenz may result in altered imatinib exposure leading to increased toxicity or failure of therapy, respectively. We used primary human hepatocyte cultures to evaluate the magnitude of interaction between imatinib and ritonavir/efavirenz.

METHODS

Hepatocytes were pre-treated with vehicle, ritonavir, ketoconazole, efavirenz or rifampicin, and the metabolism of imatinib was characterized over time. Concentrations of imatinib and metabolite were quantitated in combined lysate and medium, using LC-MS.

RESULTS

The predicted changes in imatinib CLoral (95% CI) with ketoconazole, ritonavir, rifampicin and efavirenz were 4.0-fold (0, 9.2) lower, 2.8-fold (0.04, 5.5) lower, 2.9-fold (2.2, 3.5) higher and 2.0-fold (0.42, 3.5) higher, respectively. These predictions were in good agreement with clinical single dose drug-drug interaction studies, but not with reports of imatinib interactions at steady-state. Alterations in metabolism were similar after acute or chronic imatinib exposure.

CONCLUSIONS

In vitro human hepatocytes predicted increased clearance of imatinib with inducers and decreased clearance with inhibitors of CYP enzymes. The impact of HAART on imatinib may depend on whether it is being initiated or has already been dosed chronically in patients. Therapeutic drug monitoring may have a role in optimizing imatinib therapy in this patient population.

Impact of CYP2C8*3 polymorphism on in vitro metabolism of imatinib to N-desmethyl imatinib

1. Imatinib is metabolized to N-desmethyl imatinib by CYPs 3A4 and 2C8. The effect of CYP2C8*3 genotype on N-desmethyl imatinib formation was unknown. 2. We examined imatinib N-demethylation in human liver microsomes (HLMs) genotyped for CYP2C8*3, in CYP2C8*3/*3 pooled HLMs and in recombinant CYP2C8 and CYP3A4 enzymes. Effects of CYP-selective inhibitors on N-demethylation were also determined. 3. A single-enzyme Michaelis-Menten model with autoinhibition best fitted CYP2C8*1/*1 HLM (n = 5) and recombinant CYP2C8 kinetic data (median ± SD Ki = 139 ± 61 µM and 149 µM, respectively). Recombinant CYP3A4 showed two-site enzyme kinetics with no autoinhibition. Three of four CYP2C8*1/*3 HLMs showed single-enzyme kinetics with no autoinhibition. Binding affinity was higher in CYP2C8*1/*3 than CYP2C8*1/*1 HLM (median ± SD Km = 6 ± 2 versus 11 ± 2 µM, P=0.04). CYP2C8*3/*3 (pooled HLM) also showed high binding affinity (Km = 4 µM) and single-enzyme weak autoinhibition (Ki = 449 µM) kinetics. CYP2C8 inhibitors reduced HLM N-demethylation by 47-75%, compared to 0-30% for CYP3A4 inhibitors. 4. In conclusion, CYP2C8*3 is a gain-of-function polymorphism for imatinib N-demethylation, which appears to be mainly mediated by CYP2C8 and not CYP3A4 in vitro in HLM.

Variability in bioavailability of small molecular tyrosine kinase inhibitors

Small molecular tyrosine kinase inhibitors (smTKIs) are in the centre of the very quickly expanding area of personalized chemotherapy and oral applicability thereof. The number of drugs in this class is rapidly growing, with twenty current approvals by both the European Medicines Agency (EMA) and the Food and Drug Administration (FDA). The drugs are, however, generally characterized by a poor oral, and thus variable, bioavailability. This results in significant variation in plasma levels and exposure. The cause is a complex interplay of factors, including poor aqueous solubility, issued permeability, membrane transport and enzymatic metabolism. Additionally, food and drug-drug interactions can play a significant role. The issues related with an impaired bioavailability generally receive little attention. To the best of our knowledge, this article is the first to provide an overview of the factors that determine the bioavailability of the smTKIs.

Investigating the contribution of CYP2J2 to ritonavir metabolism in vitro and in vivo

Ritonavir, an HIV protease inhibitor, is successfully used for the prevention and treatment of HIV infections. Ritonavir pharmacokinetics are complicated by inhibition, induction and pharmacogenetics of cytochrome P450 (CYP) enzymes mediating its clearance. This investigation revealed that CYP2J2, along with CYP3A4/5 and CYP2D6, efficiently metabolizes ritonavir, and to a CYP2J2-specific (minor) metabolite. Chemical inhibition of ritonavir metabolism, clearance, KI/kinact and abundance of CYP2J2 in liver microsomes were evaluated and then applied to an in vitro-in vivo static scaling model to estimate the contribution of each isozyme, as a function of CYP abundance, activity, and genotype. Disposition of the CYP2J2-specific metabolite was also evaluated in vivo. In plasma, metabolite abundance was well above previously reported levels with circulating concentrations measured at 2 μM for the main hydroxylisopropyl metabolite. Ritonavir and metabolite plasma profiles were simulated using Simcyp(®). A modest (2-6%) contribution of CYP2J2 to ritonavir clearance is predicted which increases to more than 20% in subjects carrying CYP2D6 poor metabolizer polymorphisms and CYP3A4 irreversible inhibition. These results indicate that minor drug metabolizing enzymes could become quantitatively important in RTV clearance if main metabolic pathways are impeded.

Structural identification of imatinib cyanide adducts by mass spectrometry and elucidation of bioactivation pathway

RATIONALE

Recent publications have reported that imatinib forms cyanide and methoxylamine adducts in vitro but without detail structural identification. The current work reports the identification of seven cyanide adducts that elucidate the bioactivation pathways and may provide hints for observed clinical adverse effects of the drug.

METHODS

Imatinib was incubated with human liver microsomal proteins in the presence of a NADPH-regeneration system and the trapping agents reduced GSH, potassium cyanide and methoxylamine. Samples were analyzed by high-performance liquid chromatography (HPLC) coupled with a LTQ-Orbitrap data collection system. Chemical structures were determined and/or postulated based on data-dependent high-resolution tandem mass spectrometric (MS(n)) exact mass measurements in both positive and negative scan modes, as well as in combination with hydrogen-deuterium exchange (HDX).

RESULTS

GSH and methoxylamine conjugates were either not detected or were in insufficient quantities for characterization. However, seven cyanide conjugates were identified, indicating that the piperazine and p-toluidine partial structures in imatinib can become bioactivated and subsequently trapped by the nucleophile cyanide ion. The reactive intermediates were postulated as imine and imine-carbonyl conjugate (α,β-unsaturated) structures on the piperazine ring, and imine-methide on the p-toluidine partial structure.

CONCLUSIONS

Chemical structures of seven cyanide adducts of imatinib have been identified or proposed based on high-resolution MS/MS data. Mechanisms for the formation of the conjugates were also proposed. The findings may help to understand the mechanism of hepatotoxicity of imatinib in humans.

Are drug labels static or dynamic?

Understanding drug metabolism is essential for identifying drug-drug interactions (DDIs). As new data concerning a drug's pharmacokinetics arise, updates to drug labels and administration procedures should rapidly follow. However, the US Food and Drug Administration (FDA) has inconsistently updated drug labels, based on new research findings (i.e., in peer-reviewed publications). In this Commentary, we highlight recent findings on the metabolism of imatinib and argue for a more stringent protocol for updating drug labels.

The effect of apigenin on pharmacokinetics of imatinib and its metabolite N-desmethyl imatinib in rats

The purpose of this study was to determine the effect of apigenin on the pharmacokinetics of imatinib and N-desmethyl imatinib in rats. Healthy male SD rats were randomly divided into four groups: A group (the control group), B group (the long-term administration of 165 mg/kg apigenin for 15 days), C group (a single dose of 165 mg/kg apigenin), and D group (a single dose of 252 mg/kg apigenin). The serum concentrations of imatinib and N-desmethyl imatinib were measured by HPLC, and pharmacokinetic parameters were calculated using DAS 3.0 software. The parameters of AUC_(0−t), AUC_(0−∞), T_max, V_z/F, and CL_z/F for imatinib in group B were different from those in group A (P < 0.05). Besides, MRT_(0−t) and MRT_(0−∞) in groups C and D differed distinctly from those in group A as well. The parameters of AUC_(0−t) and C_max for N-desmethyl imatinib in group C were significantly lower than those in group A (P < 0.05); however, compared with groups B and D, the magnitude of effect was modest. Those results indicated that apigenin in the short-term study inhibited the metabolism of imatinib and its metabolite N-desmethyl imatinib, while in the long-term study the metabolism could be accelerated.