Thomas M. Polasek

2.4k total citations
69 papers, 1.6k citations indexed

About

Thomas M. Polasek is a scholar working on Pharmacology, Pediatrics, Perinatology and Child Health and Oncology. According to data from OpenAlex, Thomas M. Polasek has authored 69 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Pharmacology, 23 papers in Pediatrics, Perinatology and Child Health and 13 papers in Oncology. Recurrent topics in Thomas M. Polasek's work include Pharmacogenetics and Drug Metabolism (38 papers), Pharmaceutical studies and practices (14 papers) and Statistical Methods in Clinical Trials (13 papers). Thomas M. Polasek is often cited by papers focused on Pharmacogenetics and Drug Metabolism (38 papers), Pharmaceutical studies and practices (14 papers) and Statistical Methods in Clinical Trials (13 papers). Thomas M. Polasek collaborates with scholars based in Australia, United States and United Kingdom. Thomas M. Polasek's co-authors include John O. Miners, Matthew Doogue, Andrew Rowland, Amin Rostami‐Hodjegan, Michael J. Sorich, David J. Elliot, Michael D. Wiese, Benjamin C. Lewis, Frank Lin and Andrew J. McLachlan and has published in prestigious journals such as Gastroenterology, Journal of Pharmacology and Experimental Therapeutics and Frontiers in Immunology.

In The Last Decade

Thomas M. Polasek

66 papers receiving 1.6k citations

Peers

Thomas M. Polasek
Thomas Kerbusch Netherlands
Jack Cook United States
S-M Huang United States
Christina L. Aquilante United States
Shitalben Patel United States
Ji‐Hong Shon South Korea
Caroline Samer Switzerland
Jonatan D. Lindh Sweden
K Rowland‐Yeo United Kingdom
Yoseph Caraco Israel
Thomas Kerbusch Netherlands
Thomas M. Polasek
Citations per year, relative to Thomas M. Polasek Thomas M. Polasek (= 1×) peers Thomas Kerbusch

Countries citing papers authored by Thomas M. Polasek

Since Specialization
Citations

This map shows the geographic impact of Thomas M. Polasek's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Thomas M. Polasek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas M. Polasek more than expected).

Fields of papers citing papers by Thomas M. Polasek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas M. Polasek. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Thomas M. Polasek. The network helps show where Thomas M. Polasek may publish in the future.

Co-authorship network of co-authors of Thomas M. Polasek

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas M. Polasek. A scholar is included among the top collaborators of Thomas M. Polasek based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Thomas M. Polasek. Thomas M. Polasek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Stocker, Sophie L. & Thomas M. Polasek. (2025). Using pharmacogenomics to personalise drug therapy: which drugs, when and how. Australian Prescriber. 48(3). 82–86. 1 indexed citations
2.
Zhao, Lijun, et al.. (2024). Efficacy and safety of pharmacogenomic-guided antidepressant prescribing in patients with depression: an umbrella review and updated meta-analysis. Frontiers in Psychiatry. 15. 1276410–1276410. 7 indexed citations
3.
Polasek, Thomas M., Chad Bousman, Amin Rostami‐Hodjegan, et al.. (2024). Virtual twins for model‐informed precision dosing of clozapine in patients with treatment‐resistant schizophrenia. CPT Pharmacometrics & Systems Pharmacology. 13(3). 424–436. 5 indexed citations
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Polasek, Thomas M., et al.. (2023). EP63 FIRST IN HUMAN TRIAL OF IMU-856, AN ORALLY AVAILABLE REGULATOR OF BARRIER FUNCTION FOR THE TREATMENT OF CELIAC DISEASE. Gastroenterology. 164(6). S–1204. 2 indexed citations
8.
Polasek, Thomas M.. (2023). Virtual twin for healthcare management. Frontiers in Digital Health. 5. 1246659–1246659. 3 indexed citations
9.
Polasek, Thomas M. & Virna Schuck. (2023). Improving the Efficiency of Clinical Pharmacology Studies. Clinical Pharmacology in Drug Development. 12(8). 771–774. 2 indexed citations
10.
Miners, John O., Thomas M. Polasek, Julie-Ann Hulin, Andrew Rowland, & Robyn Meech. (2023). Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance. Pharmacology & Therapeutics. 248. 108459–108459. 29 indexed citations
11.
Achour, Brahim, Pauline Gosselin, Jean Terrier, et al.. (2022). Liquid Biopsy for Patient Characterization in Cardiovascular Disease: Verification against Markers of Cytochrome P450 and P‐Glycoprotein Activities. Clinical Pharmacology & Therapeutics. 111(6). 1268–1277. 22 indexed citations
12.
Polasek, Thomas M., Chad Bousman, Amin Rostami‐Hodjegan, et al.. (2022). Delineating gene–environment effects using virtual twins of patients treated with clozapine. CPT Pharmacometrics & Systems Pharmacology. 12(2). 168–179. 11 indexed citations
13.
Darwich, Adam S., Thomas M. Polasek, Jeffrey K Aronson, et al.. (2020). Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy. The Annual Review of Pharmacology and Toxicology. 61(1). 225–245. 109 indexed citations
14.
Polasek, Thomas M., Amin Rostami‐Hodjegan, Dong‐Seok Yim, et al.. (2019). What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing. The AAPS Journal. 21(2). 17–17. 24 indexed citations
15.
Rowland, Andrew, Madelé van Dyk, Ashley M. Hopkins, et al.. (2018). Physiologically Based Pharmacokinetic Modeling to Identify Physiological and Molecular Characteristics Driving Variability in Drug Exposure. Clinical Pharmacology & Therapeutics. 104(6). 1219–1228. 30 indexed citations
16.
Rowland, Andrew, et al.. (2014). Inhibition of human drug-metabolising cytochrome P450 and UDP-glucuronosyltransferase enzyme activities in vitro by uremic toxins. European Journal of Clinical Pharmacology. 70(9). 1097–1106. 61 indexed citations
17.
Sorich, Michael J., Thomas M. Polasek, & Michael D. Wiese. (2013). Challenges and Limitations in the Interpretation of Systematic Reviews: Making Sense of Clopidogrel and CYP2C19 Pharmacogenetics. Clinical Pharmacology & Therapeutics. 94(3). 376–382. 21 indexed citations
18.
Lin, Frank, Stephen M. Anthony, Thomas M. Polasek, Guy Tsafnat, & Matthew Doogue. (2011). BICEPP: an example-based statistical text mining method for predicting the binary characteristics of drugs. BMC Bioinformatics. 12(1). 112–112. 4 indexed citations
19.
Polasek, Thomas M., et al.. (2009). In vitro-in vivo extrapolation of zolpidem as a perpetrator of metabolic interactions involving CYP3A. European Journal of Clinical Pharmacology. 66(3). 275–283. 15 indexed citations
20.
Polasek, Thomas M. & John O. Miners. (2006). Quantitative prediction of macrolide drug-drug interaction potential from in vitro studies using testosterone as the human cytochrome P4503A substrate. European Journal of Clinical Pharmacology. 62(3). 203–208. 67 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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