SUMMARYAlthough no randomized studies have demonstrated a positive impact of therapeutic drug monitoring (TDM) on clinical outcome in epilepsy, evidence from nonrandomized studies and everyday clinical experience does indicate that measuring serum concentrations of old and new generation antiepileptic drugs (AEDs) can have a valuable role in guiding patient management provided that concentrations are measured with a clear indication and are interpreted critically, taking into account the whole clinical context. Situations in which AED measurements are most likely to be of benefit include (1) when a person has attained the desired clinical outcome, to establish an individual therapeutic concentration which can be used at subsequent times to assess potential causes for a change in drug response; (2) as an aid in the diagnosis of clinical toxicity; (3) to assess compliance, particularly in patients with uncontrolled seizures or breakthrough seizures; (4) to guide dosage adjustment in situations associated with increased pharmacokinetic variability (e.g., children, the elderly, patients with associated diseases, drug formulation changes); (5) when a potentially important pharmacokinetic change is anticipated (e.g., in pregnancy, or when an interacting drug is added or removed); (6) to guide dose adjustments for AEDs with dose-dependent pharmacokinetics, particularly phenytoin.

The aim of the present review is to discuss the potential value of therapeutic drug monitoring (TDM) of the newer antiepileptic drugs (AEDs) felbamate, gabapentin, lamotrigine, levetiracetam, oxcarbazepine, tiagabine, topiramate, vigabatrin, and zonisamide. Studies of the relationship between serum concentrations and clinical efficacy of these drugs are reviewed, and the potential value of TDM of the drugs is discussed based on their pharmacokinetic properties and mode of action. Analytical methods for the determination of the serum concentrations of these drugs are also briefly described. There are only some prospective data on the serum concentration-effect relationships, and few studies have been designed primarily to study these relationships. As TDM is not widely practiced for the newer AEDs, there are no generally accepted target ranges for any of these drugs, and for most a wide range in serum concentration is associated with clinical efficacy. Furthermore, a considerable overlap in drug concentrations related to toxicity and nonresponse is reported. Nevertheless, the current tentative target ranges for felbamate, gabapentin, lamotrigine, levetiracetam, oxcarbazepine (10-hydroxy-carbazepine metabolite), tiagabine, topiramate, vigabatrin, and zonisamide are 125 to 250 micromol/L, 70 to 120 micromol/L, 10 to 60 micromol/L, 35 to 120 micromol/L, 50 to 140 micomol/L, 50 to 250 nmol/L, 15 to 60 micromol/L, 6 to 278 micromol/L, and 45 to 180 micromol/L, respectively. Further systematic studies designed specifically to evaluate concentration-effect relationships of the new AEDs are urgently needed. Although routine monitoring in general cannot be recommended at present, measurements of some of the drugs is undoubtedly of help with individualization of treatment in selected cases in a particular clinical setting.

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As small molecule drugs become harder to develop and less cost effective for patient use, efficient strategies for their property improvement become increasingly important to global health initiatives. Improvements in the physical properties of Active Pharmaceutical Ingredients (APIs), without changes in the covalent chemistry, have long been possible through the application of binary component solids. This was first achieved through the use of pharmaceutical salts, within the last 10-15years with cocrystals and more recently coamorphous systems have also been consciously applied to this problem. In order to rationally discover the best multicomponent phase for drug development, intermolecular interactions need to be considered at all stages of the process. This review highlights the current thinking in this area and the state of the art in: pharmaceutical multicomponent phase design, the intermolecular interactions in these phases, the implications of these interactions on the material properties and the pharmacokinetics in a patient.

A new tripodal tris(hydroxypyridinone) bifunctional chelator for gallium allows easy production of (68)Ga-labelled proteins rapidly under mild conditions in high yields at exceptionally high specific activity and low concentration.

PurposeThe human sodium/iodide symporter (hNIS) is a well-established target in thyroid disease and reporter gene imaging using gamma emitters 123I-iodide, 131I-iodide and 99mTc-pertechnetate. However, no PET imaging agent is routinely available. The aim of this study was to prepare and evaluate 18F-labelled tetrafluoroborate ([18F]TFB) for PET imaging of hNIS.Methods[18F]TFB was prepared by isotopic exchange of BF4− with [18F]fluoride in hot hydrochloric acid and purified using an alumina column. Its identity, purity and stability in serum were determined by HPLC, thin-layer chromatography (TLC) and mass spectrometry. Its interaction with NIS was assessed in vitro using FRTL-5 rat thyroid cells, with and without stimulation by thyroid-stimulating hormone (TSH), in the presence and absence of perchlorate. Biodistribution and PET imaging studies were performed using BALB/c mice, with and without perchlorate inhibition.Results[18F]TFB was readily prepared with specific activity of 10 GBq/mg. It showed rapid accumulation in FRTL-5 cells that was stimulated by TSH and inhibited by perchlorate, and rapid specific accumulation in vivo in thyroid (SUV = 72 after 1 h) and stomach that was inhibited 95% by perchlorate.Conclusion[18F]TFB is an easily prepared PET imaging agent for rodent NIS and should be evaluated for hNIS PET imaging in humans.Electronic supplementary materialThe online version of this article (doi:10.1007/s00259-010-1523-0) contains supplementary material, which is available to authorized users.

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To better understand the molecular mechanisms underpinning physiological variation in human populations, metabolic phenotyping approaches are increasingly being applied to studies involving hundreds and thousands of biofluid samples. Hyphenated ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) has become a fundamental tool for this purpose. However, the seemingly inevitable need to analyze large studies in multiple analytical batches for UPLC-MS analysis poses a challenge to data quality which has been recognized in the field. Herein, we describe in detail a fit-for-purpose UPLC-MS platform, method set, and sample analysis workflow, capable of sustained analysis on an industrial scale and allowing batch-free operation for large studies. Using complementary reversed-phase chromatography (RPC) and hydrophilic interaction liquid chromatography (HILIC) together with high resolution orthogonal acceleration time-of-flight mass spectrometry (oaTOF-MS), exceptional measurement precision is exemplified with independent epidemiological sample sets of approximately 650 and 1000 participant samples. Evaluation of molecular reference targets in repeated injections of pooled quality control (QC) samples distributed throughout each experiment demonstrates a mean retention time relative standard deviation (RSD) of <0.3% across all assays in both studies and a mean peak area RSD of <15% in the raw data. To more globally assess the quality of the profiling data, untargeted feature extraction was performed followed by data filtration according to feature intensity response to QC sample dilution. Analysis of the remaining features within the repeated QC sample measurements demonstrated median peak area RSD values of <20% for the RPC assays and <25% for the HILIC assays. These values represent the quality of the raw data, as no normalization or feature-specific intensity correction was applied. While the data in each experiment was acquired in a single continuous batch, instances of minor time-dependent intensity drift were observed, highlighting the utility of data correction techniques despite reducing the dependency on them for generating high quality data. These results demonstrate that the platform and methodology presented herein is fit-for-use in large scale metabolic phenotyping studies, challenging the assertion that such screening is inherently limited by batch effects. Details of the pipeline used to generate high quality raw data and mitigate the need for batch correction are provided.