Oneeb Majid

Pharmacokinetics and Safety of Ketorolac Following Single Intranasal and Intramuscular Administration in Healthy Volunteers

Ketorolac was administered to 15 healthy volunteers in a phase 1, single‐dose, crossover, randomized study. Subjects received open‐label randomized 15‐ and 30‐mg intramuscular (IM) ketorolac and blinded randomized 15‐ and 30‐mg intranasal (IN) ketorolac. The IN ketorolac was well tolerated; the only nasal symptoms were some instances of mild irritation. The IN ketorolac was rapidly and well absorbed (median tmax, 0.50–0.75 hours), and the half‐life was approximately 5 to 6 hours, values that were similar to those following IM administration. Relative bioavailability of IN compared to IM administration at the same doses was approximately 67% to 75%. Dose proportionality was noted between the 15‐ and 30‐mg IN and IM dose levels. Thus, IN ketorolac offers a therapeutic alternative to IM administration and may provide benefits in the clinical setting.

Simultaneous determination of plasma prednisolone, prednisone, and cortisol levels by high-performance liquid chromatography.

Recipients of organ transplants remain particularly dependent on prednisolone as part of their maintenance immunosuppression. Despite this, the pharmacokinetics of prednisolone have never been fully characterized in these patients, and consequently dosing remains empirical. Accurate monitoring of prednisolone, its primary metabolite prednisone, and endogenous cortisol suppression in such patients may provide a means of improving the clinical outcome by adjusting for variability in prednisolone pharmacokinetics and pharmacodynamics. Measurement of endogenous cortisol may provide an independent marker of prednisolone pharmacodynamics. A simple isocratic reverse-phase high-performance liquid chromatography procedure, using betamethasone as an internal standard, was developed to quantify plasma prednisolone, prednisone, and cortisol simultaneously. The steroids were extracted from 0.5 mL plasma with 3 mL (1:1 v/v) ethyl acetate/tert-methyl butyl ether and 0.1 mL phosphoric acid, washed in 0.1 mol/L NaOH before a final drying step and reconstitution in mobile phase for injection. Separation was achieved using a Supelcosil LC-18-DB, 150 × 4.6-mm, 5-&mgr;m particle size, reverse-phase column attached to a Newguard 15 × 3-mm, RP8 guard column maintained at 25°C, with ultraviolet detector set at 254 nm. The mobile phase consisted of 16% isopropanol in water containing 0.1% trifluoroacetic acid, set at a flow rate of 1.2 mL/min. The assay was linear up to 1,002 &mgr;g/L for prednisolone, 982 &mgr;g/L for prednisone, and 545 &mgr;g/L for cortisol. Mean intra-assay and interassay imprecision levels were 6.0% and 7.2%, respectively, for prednisolone, 5.8% and 7.2% for prednisone, and 5.6% and 7.9% for cortisol. Intra-assay inaccuracy was <7% of nominal values for prednisolone, prednisone, and cortisol. The lower limit of quantification was 7 &mgr;g/L for prednisolone and prednisone and 10 &mgr;g/L for cortisol. Corticosteroid recoveries were 73%, 74%, and 90% for prednisolone, prednisone, and cortisol, respectively. The authors describe a robust, inexpensive, and simple method suitable for therapeutic drug monitoring or pharmacokinetic studies of prednisolone; it may also be used to measure the suppression of endogenous cortisol production.

Optimal Design for Multiresponse Pharmacokinetic–Pharmacodynamic Models – Dealing with Unbalanced Designs

This paper addresses the problem of determining D-optimal designs for multiresponse pharmacokinetic–pharmacodynamic (PKPD) experiments where data on each response variable can be collected at different times. Most previous multiresponse model optimal design applications have considered the case where all response variables are measured at the same time points. However in practice it may not be possible to have all responses measured at the same sampling times. We propose an optimal design method to take into account the unbalanced nature of the problem. The method developed was applied to a PKPD problem that involved describing the time course of drug plasma concentrations, heart rate and mean arterial blood pressure for both a fixed effects and mixed effects regression model. Additionally a simulation study was carried out in NONMEM for one such population optimal design problem.

Structural identifiability analysis and reparameterisation (parameter reduction) of a cardiovascular feedback model

Structural identifiability should be considered when developing mathematical models. A globally or at least locally identifiable model has to be obtained in order to have some chance of obtaining unique parameter estimates when real data are available. An indicator of structural unidentifiability may be that some unknown parameter estimates are found to be not well determined from parameter estimation of a model. An example is discussed in this paper to illustrate the procedures involved when such situations arise. Problems with parameter estimation were observed for a PKPD model for an α1A/1L-adrenoceptor partial agonist developed for the treatment of stress urinary incontinence The regulation of the side effects of the increased peripheral resistance, induced by the constriction of the blood vessels, was modelled by adapting a previous cardiovascular nonlinear PKPD model proposed by Franchetau and co-workers. Structural identifiability analysis confirmed that the model was unidentifiable. The model was then reparameterised (parameter list reduction) to obtain a globally identifiable model. Simulation studies confirm the superiority of the reduced parameterisation with respect to parameter estimation. The simulation study also confirms the models behave indistinguishably with respect to the input-output behaviour. The example demonstrates the importance of recognising an unidentifiable model and illustrates step by step identifiability analysis, reparameterisation and validation of reparameterised model against the original model.

Population pharmacometric analyses of eribulin in patients with locally advanced or metastatic breast cancer previously treated with anthracyclines and taxanes

Pharmacometric investigation of eribulin was undertaken in patients with metastatic breast cancer (MBC) and other advanced solid tumors. A population pharmacokinetic (PK) model used data combined from seven phase 1 studies (advanced solid tumors; n = 129), and one phase 2 (MBC; n = 211), and one phase 3 study (MBC; n = 173). Phase 3 data were also used in a PK/pharmacodynamic (PD) model of efficacy and tumor response (sum of longest diameters of target lesions). All analyses used NONMEM 7.2. Eribulin PK, described by a dose‐independent, three‐compartment model with allometric relationship for body weight, was similar for all tumor types. Inter‐individual variability (IIV) was 52% for both exposure and clearance. Liver function markers (albumin, alkaline phosphatase, bilirubin) significantly influenced eribulin PK (7.3% of IIV in clearance). Tumor shrinkage correlated with eribulin exposure; a 36% decrease in tumor size from baseline was modeled at week 36. No patient/disease factors significantly predicted eribulins effect on tumor size. At week 6, a decrease in tumor size was associated with longer survival than an increase (P = .0055), suggesting survival may relate indirectly to eribulin exposure. These pharmacometric analyses provide a detailed overview of eribulin exposure–efficacy relationships to inform physicians treating patients with MBC.

Immunosuppression, eotaxin and the diagnostic changes in eosinophils that precede early acute heart allograft rejection

Peripheral blood eosinophil counts (EOS) are undetectable in 40% blood samples sent for routine haematology at Papworth Hospital during the first 3 months after heart transplantation (HTx). Increases in EOS usually precede the development of allograft rejection by a median of 4 days. We compared the effects of cyclosporin (dose and total blood concentration), prednisolone (dose and both total and unbound plasma concentrations) and azathioprine, as well as plasma concentrations of the CCR-3 chemokines, eotaxin and RANTES, on changes in EOS in 47 consecutive HTx recipients, with a median follow-up of 90 (IQR 85-95) days. Multivariate analysis confirmed the independent association between both prednisolone dose (P<0.0001) and eotaxin (P<0.0001) and changes in EOS. The plasma eotaxin concentration was, in turn, most closely associated with the cyclosporin dose (P<0.001) and plasma prednisolone concentration (P=0.022). The blood cyclosporin concentration (P=0.028), EOS (P=0.012) and prednisolone dose (P=0.015) were all independently associated with the risk of treated acute rejection. When prednisolone pharmacokinetic parameters were substituted for the prednisolone dose in this multivariate model, only the pharmacokinetic parameter retained a significant association with the risk of rejection. Changes in EOS preceding cardiac allograft rejection are directly associated with plasma eotaxin concentrations and indirectly with prednisolone dosage. Cyclosporin may also indirectly influence these changes by inhibiting eotaxin production. EOS, prednisolone dose and blood cyclosporin concentrations were independently associated with the risk of acute rejection. The total and unbound fractions of prednisolone in plasma appear to be even more closely related to rejection but are difficult to measure. Monitoring EOS, as a surrogate measure of prednisolone immunosuppression, may be more cost-effective for controlling rejection than conventional cyclosporin monitoring in the first 6 weeks after HTx.