UT analytical chemistry education activities at EcoBalt 2018 Conference

On Oct 26, 2018, Ivo Leito gave a presentation titled “Analytical chemistry education activities at University of Tartu” at the EcoBalt 2018 conference in Vilnius, Lithuania.

The presentation contains information about the online courses LC-MS Method Validation and Estimation of Measurement Uncertainty in Chemical Analysis, as well as the recently published tutorial reviews (Validation I, Validation II, LoD I, LoD II) that form the basis of the LC-MS Method Validation course.

The presentation also addresses the international master’s programmes Applied Measurement Science and Excellence in Analytical Chemistry at the University of Tartu.

The last part of the talk is devoted to the Eurachem 2018 General Assembly and Workshop that will take place in Tartu on May 20-21, 2018. The topic of the workshop is “Validation of targeted and non-targeted methods of analysis”.

 

Is it possible to use data below the limit of quantitation in pharmacokinetic studies?

Results below the limit of quantification (BLQ) are generally not reported or reported without explicit numbers, leaving pharmacokinetic (PK) and pharmacodynamic (PD) studies wishing for more information to improve their model parameters. But the laboratory cannot release actual values BLQ since the quality of that data has never been assessed.

Possible solutions to this unfortunate situation were investigated in a recent perspective article led by our group and published in Bioanalysis. The article titled: “Utilization of data below the analytical limit of quantitation in pharmacokinetic analysis and modelling: promoting interdisciplinary debate”, expanse the so far used statistical salvage of information, by an experimental addition to investigate the quality of data BLQ.

By directing this article towards the pharmacometrician, the analytical scientist and the regulatory personnel, we hope to encourage an inter-disciplinary discussion to improve the situation by finding ways to use BLQ data in PK/PD studies, in order to enhance the quality of the obtained pharmacokinetic models. Several ways were proposed for moving forward, in particular improving/modifying method validation guidelines for enabling to use BLQ data and leaving the decision regarding whether and how to incorporate the BLQ data into a PK/PD model to the data analyst and not the analytical chemist.

Comparative validation of amperometric and optical dissolved oxygen sensors

A comprehensive comparative validation for two different types of dissolved oxygen (DO) analyzers, amperometric and optical, together with estimation of measurement uncertainty is presented in the recently published article I. Helm, G. Karina, L. Jalukse, T. Pagano, I. Leito, Environmental Monitoring and Assessment 2018, 190, 313.

A number of performance characteristics were evaluated including drift, intermediate precision, accuracy of temperature compensation, accuracy of reading (under different measurement conditions), linearity, flow dependence of the reading, repeatability (reading stability), and matrix effects of dissolved salts. The matrix effects on readings in real samples were evaluated by analyzing the dependence of the reading on salt concentration (at saturation concentration of DO). The analyzers were also assessed in DO measurements of a number of natural waters. The uncertainty contributions of the main influencing parameters were estimated under different experimental conditions. It was found that the uncertainties of results for both analyzers are quite similar but the contributions of the uncertainty sources are different.

The results imply that the optical analyzer might not be as robust as is commonly assumed, however, it has better reading stability, lower stirring speed dependence, and typically requires less maintenance. On the other hand, the amperometric analyzer has a faster response and wider linear range.

(Photo by Lauri Jalukse: measurements of dissolved oxygen concentration with amperometric and optical analyzers at Jordan spring, Karksi-Nuia, Estonia)

 

Dissolved Oxygen Measurement Training in Uruguay

Irja_Helm_Conducting_Dissolved_Oxygen_Measurement_Training_in_UruguayDuring Jun 12-16, 2017 research fellow Irja Helm from University of Tartu, Institute of Chemistry is conducting a training session on high-accuracy dissolved oxygen measurement in Montevideo (Uruguay). The local organiser of the training is LATU (Laboratorio Tecnológico del Uruguay). There are 8 participants in the training, from Uruguay, Argentina, Ecuador and Peru.

The training is centered around the high-accuracy Winkler titration method of dissolved oxygen concentration measurement that Irja developed during her PhD study: I. Helm, L. Jalukse, I. Leito “A highly accurate method for determination of dissolved oxygen: Gravimetric Winkler method” Analytica Chimica Acta 2012, 741, 21–31. The training is interesting in the sense that most of it is carried out in laboratory, where participants do measurements hands-on. The experimental setup was assembled jointly by LATU and by Irja. The practical orientation is well in line with the main purpose of the training – to introduce the high-accuracy Winkler method to the reference laboratories in the participant countries.

The training is organised in the framework of the project „Regional Quality Infrastructure Fund for Biodiversity and Climate Protection in Latin America and the Caribbean“ (VH-No.: 95094) coordinated by PTB (Germany).

(Photo: Irja Helm, on the left, together with training participants in laboratory)

 

Metrology in chemistry in a nutshell

Random_and_Systematic_Effects_TimelineIn a recent edition of the premier journal devoted to quality and metrology in chemistry Accreditation and Quality Assurance Ivo Leito has attempted to express in very simple terms the essence of Metrology in Chemistry. In the article Accred. Qual. Assur. 2015, 20, 229–231 he arrived at three main recommendations:

1. Whenever possible, comparisons with reference values should be carried out. The reference values can be realized in different ways: Certified reference materials (CRMs), Laboratory reference materials (LRMs), Measurements with reference methods, etc.

2. Data on stable samples should be collected over long time periods (e.g. as the X chart), in order to evaluate as many sources of variability in the analysis method, as possible. The longer the time period, the more systematic effects will become random and thus easier to evaluate (more on this topic can be found in a recent review on bias).

3. “Do not stop there!”, meaning that the above mentioned activities should run in a lab on a continuous basis.

As a conclusion, it can be said that constant improvement is the key to reliable analytical results.