17 research outputs found

    PRECLINICAL AND CLINICAL DEVELOPMENT OF THE LIPOPHILIC CAMPTOTHECIN ANALOGUE AR-67

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    AR-67 is a lipophilic third generation camptothecin analogue, currently under early stage clinical trials. It acts by targeting Topoisomerase 1 (Top1), a nuclear enzyme essential for DNA replication and transcription and is present in two forms, the pharmacologically active lipophilic lactone and the charged carboxylate. In oncology patients participating in a phase I clinical trial, AR-67 lactone was the predominant species in plasma. Similarly to other camptothecins, the identified dose-limiting toxicities for AR-67 were neutropenia, thrombocytopenia and fatigue. In addition, in vitro metabolism studies indicated AR-67 lactone as a substrate for CYP3A4/5 as well as the UGT1A7 and UGT1A8 enzymes localizing in the liver and the gut. Numerous studies have demonstrated the over-expression of transporters in certain tumor types. Here, the effect of interactions between AR-67 and efflux or uptake transporters on the antitumor efficacy of AR-67 in vitro was studied. We showed that BCRP and MDR1 overexpression confers resistance to AR-67. Moreover, we demonstrated the therapeutic superiority of protracted dosing over more intense dosing regimens of AR-67 using xenografts models. Our studies indicated the schedule-dependent expression of Top1 and the preferential partitioning of AR-67 in the tumor tissue. We reason that these are factors that need to be taken into consideration when designing dosing schedules aiming to maximize efficacy. As most cytotoxic drugs, AR-67 has a narrow therapeutic window. Thus, it is essential to identify the variables influencing exposure to this camptothecin analogue. A thorough compartmental pharmacokinetic analysis was performed on the patient data obtained in a phase 1 clinical trial on AR-67. Moreover, sources of intersubject variability associated with obtaining pharmacokinetic parameter estimates were identified and a population covariate pharmacokinetic model was developed. In conclusion, the drug development of AR-67 is a work in process. Findings presented above provide an insight on the factors contributing to its efficacy and toxicity when given to cancer patients

    Combination Effects of Docetaxel and Doxorubicin in Hormone-Refractory Prostate Cancer Cells

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    Combination effects of docetaxel (DOC) and doxorubicin (DOX) were investigated in prostate cancer cells (PC3 and DU145). Combination indices (CIs) were determined using the unified theory in various concentrations and mixing ratios (synergy: CI \u3c 0.9, additivity: 0.9 \u3c CI \u3c 1.1, and antagonism: CI \u3e 1.1). DOC showed a biphasic cytotoxicity pattern with the half maximal inhibitory concentration (IC50) at the picomolar range for PC3 (0.598 nM) and DU145 (0.469 nM), following 72 h drug exposure. The IC50s of DOX were 908 nM and 343 nM for PC3 and DU145, respectively. Strong synergy was seen when PC3 was treated with DOC at concentrations lower than its IC50 values (0.125~0.5 nM) plus DOX (2~8 times IC50). Equipotent drug combination treatments (7 × 7) revealed that the DOC/DOX combination leads to high synergy and effective cell death only in a narrow concentration range in DU145. This study provides a convenient method to predict multiple drug combination effects by the estimated CI values as well as cell viability data. The proposed DOC/DOX mixing ratios can be used to design combination drug cocktails or delivery systems to improve chemotherapy for cancer patients

    Quantification of anandamide, oleoylethanolamide and palmitoylethanolamide in rodent brain tissue using high performance liquid chromatography–electrospray mass spectroscopy

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    AbstractReported concentrations for endocannabinoids and related lipids in biological tissues can vary greatly; therefore, methods used to quantify these compounds need to be validated. This report describes a method to quantify anandamide (AEA), oleoylethanolamide (OEA) and palmitoylethanolamide (PEA) from rodent brain tissue. Analytes were extracted using acetonitrile without further sample clean up, resolved on a C18 reverse-phase column using a gradient mobile phase and detected using electrospray ionization in positive selected ion monitoring mode on a single quadrupole mass spectrometer. The method produced high recovery rates for AEA, OEA and PEA, ranging from 98.1% to 106.2%, 98.5% to 102.2% and 85.4% to 89.5%, respectively. The method resulted in adequate sensitivity with a lower limit of quantification for AEA, OEA and PEA of 1.4ng/mL, 0.6ng/mL and 0.5ng/mL, respectively. The method was reproducible as intraday and interday accuracies and precisions were under 15%. This method was suitable for quantifying AEA, OEA and PEA from rat brain following pharmacological inhibition of fatty acid amide hydrolase

    Acupressure on the extra 1 acupoint: The effect on bispectral index, serum melatonin, plasma beta-endorphin, and stress

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    BACKGROUND: Acupressure on the “extra 1” point decreases bispectral index (BIS) values and stress. METHODS: We investigated the BIS, melatonin, beta-endorphin, and verbal stress score values before, after 10 min of acupressure application on the extra 1 point, on a sham point, after no acupressure, and 1 h after completion of each intervention in 12 volunteers. RESULTS: The BIS and verbal stress score values were decreased after acupressure on the extra 1 point (P = 0.0001 and P = 0.008, respectively), but melatonin and beta-endorphin did not change. CONCLUSION: Acupressure on the extra 1 point has no effect on melatonin and beta-endorphin levels

    Interaction of Commonly Used Oral Molecular Excipients with P-glycoprotein.

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    P-glycoprotein (P-gp) plays a critical role in drug oral bioavailability, and modulation of this transporter can alter the safety and/or efficacy profile of substrate drugs. Individual oral molecular excipients that inhibit P-gp function have been considered a mechanism for improving drug absorption, but a systematic evaluation of the interaction of excipients with P-gp is critical for informed selection of optimal formulations of proprietary and generic drug products. A library of 123 oral molecular excipients was screened for their ability to inhibit P-gp in two orthogonal cell-based assays. β-Cyclodextrin and light green SF yellowish were identified as modest inhibitors of P-gp with IC50 values of 168 μM (95% CI, 118-251 μM) and 204 μM (95% CI, 5.9-1745 μM), respectively. The lack of effect of most of the tested excipients on P-gp transport provides a wide selection of excipients for inclusion in oral formulations with minimal risk of influencing the oral bioavailability of P-gp substrates

    Mechanistic modeling of drug products applied to the skin: A workshop summary report

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    Abstract The development of a generic drug product involves demonstrating that there is no significant difference in the rate and extent to which the active ingredient becomes available at the site of action, relative to the reference listed drug product. This remains challenging for many locally acting topical dermatological products because measuring the concentration of the active ingredient at the site of action in the skin may not be straightforward, and, in most instances, there are no established relationships between skin and plasma pharmacokinetic profiles. In recent years, the Office of Generic Drugs of the US Food and Drug Administration (FDA) established scientific research programs with the goal of enhancing patient access to high quality, affordable topical dermatological generics. A key strategy of these research programs was to leverage modeling and simulation methodologies that accelerate the development of these generics by facilitating alternative bioequivalence approaches for dermatological drug products. This report summarizes relevant insights and discussions from a 2021 FDA public workshop titled “Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches,” which illustrated how mechanistic modeling and simulation approaches can be utilized (and have been used) to inform generic drug product development and regulatory decisions during the assessment of generic drug applications submitted to the FDA

    Diffusion modelling of percutaneous absorption kinetics. Predicting urinary excretion from in vitro skin permeation tests (IVPT) for an infinite dose

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    In this work, we developed a number of generalised skin diffusion based pharmacokinetic models to relate published in vivo urinary excretion data to matching experimentally generated in vitro human skin permeation test (IVPT) data for a series of topically applied salicylate esters. A simplified linear in vivo model was found to inadequately describe the time course of urinary excretion over the entire sampling period. We represented the skin barrier as both a one layer (stratum corneum) and a two-layer (stratum corneum with viable epidermis) diffusion model and convoluted their Laplace solutions with that for a single exponential disposition phase to describe the urinary excretion profiles in the Laplace domain. We also derived asymptotic approximations for the model and estimated the conditions under which they could be used. We then sought to develop in vitro - in vivo relationships (IVIVR) for topically applied methyl, ethyl and glycol salicylates using our experimental IVPT data and the literature urinary excretion data. Good linear IVIVRs for ethyl and glycol salicylates were obtained, but the IVIVR for methyl salicylate was poor, perhaps because of topical stimulation of local skin blood flow by methyl salicylate. The ratio of the hydrated to dehydrated skin permeation for all salicylate esters was the same in both the IVPT and in vivo studies. A diffusion based one compartment pharmacokinetic model was also developed to describe the urinary excretion of solutes after removal of topical products and to compare the methyl salicylate skin permeation for five different body sites. The work presented here is consistent with the development of skin IVIVRs, but suggests that different skin conditions, application sites and local skin effects may affect model predictions
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