Development and validation of an HPLC-UV method for quantification of elvitegravir and two other new antiretrovirals, dolutegravir and rilpivirine, in the plasma of HIV-positive patients.

Therapeutic drug monitoring may be crucial in selected clinical conditions for the management of HIV infection. In recent years, new antiretrovirals have been introduced and in particular elvitegravir (EVG) is now recommended for first-line and simplification treatment as well as dolutegravir (DTG) and rilpivirine (RPV). The aim of this study was to develop and validate a high-performance liquid chromatography-ultraviolet (HPLC-UV) method for determining EVG and new antiretrovirals DTG and RPV in human plasma. Solid-phase extraction was applied to a 600 µL plasma sample. Chromatographic separation of the three drugs and internal standard was achieved with a gradient of acetonitrile and phosphate buffer on a C18 reverse-phase analytical column with a 20 min analytical run time. EVG and DTG were detected at 265 nm and RPV at 290 nm. Mean intra- and inter-day precisions were < 10%; the mean accuracy was <15%. Extraction recovery ranged between 105 and 82% for the drugs analyzed. Calibration curves were optimized according to the expected ranges of drug concentrations in patients; the coefficient of determination was >0.997 for all drugs. This method allows for monitoring EVG, DTG and RPV in the plasma of HIV-positive patients using HPLC-UV.

Background qualitative analysis of the European Reference Life Cycle Database (ELCD) energy datasets - part I: fuel datasets.

INTRODUCTION: The aim of this study is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) fuel datasets. CASE DESCRIPTION: The revision is based on the data quality indicators described by the ILCD Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. DISCUSSION AND EVALUATION: Results show that ELCD fuel datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the fuel-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. CONCLUSIONS: Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD fuel datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall DQR of databases.

Method applied to the background analysis of energy data to be considered for the European Reference Life Cycle Database (ELCD).

Under the framework of the European Platform on Life Cycle Assessment, the European Reference Life-Cycle Database (ELCD - developed by the Joint Research Centre of the European Commission), provides core Life Cycle Inventory (LCI) data from front-running EU-level business associations and other sources. The ELCD contains energy-related data on power and fuels. This study describes the methods to be used for the quality analysis of energy data for European markets (available in third-party LC databases and from authoritative sources) that are, or could be, used in the context of the ELCD. The methodology was developed and tested on the energy datasets most relevant for the EU context, derived from GaBi (the reference database used to derive datasets for the ELCD), Ecoinvent, E3 and Gemis. The criteria for the database selection were based on the availability of EU-related data, the inclusion of comprehensive datasets on energy products and services, and the general approval of the LCA community. The proposed approach was based on the quality indicators developed within the International Reference Life Cycle Data System (ILCD) Handbook, further refined to facilitate their use in the analysis of energy systems. The overall Data Quality Rating (DQR) of the energy datasets can be calculated by summing up the quality rating (ranging from 1 to 5, where 1 represents very good, and 5 very poor quality) of each of the quality criteria indicators, divided by the total number of indicators considered. The quality of each dataset can be estimated for each indicator, and then compared with the different databases/sources. The results can be used to highlight the weaknesses of each dataset and can be used to guide further improvements to enhance the data quality with regard to the established criteria. This paper describes the application of the methodology to two exemplary datasets, in order to show the potential of the methodological approach. The analysis helps LCA practitioners to evaluate the usefulness of the ELCD datasets for their purposes, and dataset developers and reviewers to derive information that will help improve the overall DQR of databases.

Background qualitative analysis of the European reference life cycle database (ELCD) energy datasets - part II: electricity datasets.

The aim of this paper is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) electricity datasets. The revision is based on the data quality indicators described by the International Life Cycle Data system (ILCD) Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. Results show that ELCD electricity datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the electricity-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD electricity datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall Data Quality Requirements of databases.