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An author’s perspective: Piotr J. Rudzki on graphical evaluation of unmatched incurred sample reanalysis

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To help provide insight into the recent article published in Bioanalysis: Extended 3D and 4D cumulative plots for evaluation of unmatched incurred sample reanalysis, we spoke with author Piotr Rudzki, Head of Pharmacokinetics at Pharmaceutical Research Institute (Warsaw, Poland). Piotr explains why he felt this was an important area for bioanalysis and worthy of publication. With 14 years of experience in the field including 8 as a research team manager, his work has been recently focused on graphical evaluation of unmatched incurred sample reanalysis.

“In 2003 I graduated from the Medical University of Warsaw (Poland) with a Master’s degree in Pharmacy (organic synthesis). Shortly after, I joined the Pharmacology Department (currently Pharmacokinetics Department) team at Pharmaceutical Research Institute (Warsaw, Poland). In 2009 I received PhD in pharmacy for application of LC–MS in bioanalysis and bioavailability study of a drug candidate. I have also graduated from 1 year courses on chemical metrology at the Faculty of Chemistry, University of Warsaw (Poland) and on research project management at Kozminski University (Warsaw, Poland). My primary research interests are reliability of bioanalytical methods (especially LC–MS for small molecules) and bioequivalence. Currently, as the Head of the Pharmacokinetics Department at Pharmaceutical Research Institute, I am responsible for team development, project sourcing and management, study designs, study reports approval, GLP-compliance, etc.

Before the start of the interview I would like to thank Bioanalysis Zone for the invitation. I would like also to acknowledge my colleagues for their support and inspirational environment.”

1. What inspired your research on incurred sample reanalysis (ISR)?
This test is a final proof of bioanalytical method reliability. Since the fundamental paper by M.L. Rocci et al. [1] many important papers dealt with ISR including: the European Bioanalysis Forum recommendations [2], the special feature issue of Bioanalysis [3] and a review by J.W. Findlay and M.M Kelley [4]. However, until our recent paper [5], a graphical presentation of ISR data has been neglected. When working on that paper, we developed two more concepts. Firstly, the regulatory ISR sample size recommendations seem to be ill-matched to the acceptance criteria. Thus, we have proposed adjusted ISR sample size calculation [6]. The second concept – inspired by A. Tan et al. [7] – was to develop a graphical tool for investigation of unmatched reanalyses in passed ISR tests.

2. What impact would you like to see as a result of your publication?
I would like to see our concept help in everyday laboratory practice. The tabulated ISR data is difficult to interpret, especially for studies with a large number of samples. Thus, 3D or 4D (cumulative or inverse cumulative) plots could help to find the solution of unmatched reanalyses. The plots may be used for in-study data monitoring and for post-study data inspection. To ease application of our concept, we have developed a free on-line unmatched ISR tool. In some cases our plots may even match J.W. Tukey’s quote: “The greatest value of a picture is when it forces us to notice what we never expected to see.” It would be great if our paper inspires further research on the visual or statistical evaluation of ISR.

3. What are the next steps for your research on bioanalytical method reliability?
First of all, to investigate the ISR sample size as there is no need to analyze so many samples. It has been a few years since the implementation of ISR in EMA bioanalytical method validation guideline. Now is a good time to sum up the experience of the bioanalytical community and reconsider regulatory recommendations.

I admire the confidence interval concept developed by Polish mathematician J. Spława-Neyman in 1937. It is simple and informative. We have used it in all our bioanalytical stability studies for over 10 years [8], so we can now sum up our observations.

Improved mathematical tools and new visualization ideas can examine a method’s reliability faster and more efficiently. I am curious to see whether in the next 5 years we will have novel regulatory recommendations aimed at time-saving and cost-efficient bioanalysis.

4. Are there any researchers or areas that you are watching at the moment, and any you think we should be keeping an eye on?
I like papers by Aimin Tan, because they challenge current methodology. I am also following my friend, Joanna Giebułtowicz, in her bridging of cloud-point extraction with LC–MS. We should keep an eye on bioanalysis of saliva due to non-invasive sample withdrawal. Bioequivalence of oral drugs is well defined, but for locally applied drugs there is an unmet need for novel methodologies.

5. Do you have any advice for anyone who may be interested in working in this field?
Build an interdisciplinary research team including members from both inside and outside your lab. Include academics without previous experience in bioanalysis. They ask a lot of questions and some of them may be very inspiring. They also help to adapt solutions developed in other scientific areas.

Piotr’s paper is available through Bioanalysis: Rudzki PJ, Kaza M, Biecek P. Extended 3D and 4D cumulative plots for evaluation of unmatched incurred sample reanalysis. Bioanalysis. doi:10.4155/bio-2017-0210 (2018) (Epub ahead of print).

Click here for more ‘An author’s perspective’ interviews.

References:

  1. Rocci ML, Devanarayan V, Haughey DB and Jardieu P. Confirmatory Reanalysis of Incurred Bioanalytical Samples. The AAPS Journal 9(3), Article 40 (2007)
  2. Timmerman P, Luedtke S, van Amsterdam P, Brudny-Kloeppel M and Lausecker B. Incurred sample reproducibility: views and recommendations by the European Bioanalysis Forum. Bioanalysis 1(6), 1049–1056(2009)
  3. Booth B. Special Focus: Incurred Sample Reanalysis – Foreword. Bioanalysis 3(9), 927–928(2011)
  4. Findlay JWA and Kelley MM. ISR: background, evolution and implementation, with specific consideration for ligand-binding assays. Bioanalysis 6(3), 393–402(2014)
  5. Rudzki PJ, Biecek P and Kaza M. Comprehensive graphical presentation of data from incurred sample reanalysis. Bioanalysis 9(12), 947–956(2017)
  6. Rudzki PJ, Buś-Kwaśnik K and Kaza M. Incurred sample reanalysis: adjusted procedure for sample size calculation. Bioanalysis 9(21), 1717–1724(2017)
  7. Tan A, Gagnon-Carignan S, Lachance S, Boudreau N, Lévesque A and Massé R. Beyond successful ISR: case-by-case investigations for unmatched reassay results when ISR passed. Bioanalysis 3(9), 1031–1038(2011)
  8. Rudzki PJ and Leś A. Application of confidence intervals to bioanalytical method validation – drug stability in biological matrix testing. Acta Pol Pharm 65(6), 743–747(2008)
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