Jeremy Hing

971 total citations
16 papers, 764 citations indexed

About

Jeremy Hing is a scholar working on Oncology, Pharmacology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Jeremy Hing has authored 16 papers receiving a total of 764 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Oncology, 3 papers in Pharmacology and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Jeremy Hing's work include Statistical Methods in Clinical Trials (3 papers), Analytical Chemistry and Chromatography (2 papers) and Anesthesia and Pain Management (2 papers). Jeremy Hing is often cited by papers focused on Statistical Methods in Clinical Trials (3 papers), Analytical Chemistry and Chromatography (2 papers) and Anesthesia and Pain Management (2 papers). Jeremy Hing collaborates with scholars based in United States, United Kingdom and France. Jeremy Hing's co-authors include Peter M. C. Wright, Juan José Pérez Ruixo, Dennis Greenslade, Wojciech Krzyżański, Martin Griffin, Ian Shaw, Simon Baudouin, A. Gascoigne, R. Bullock and Nick Hayes and has published in prestigious journals such as Journal of Clinical Oncology, Anesthesiology and Clinical Pharmacology & Therapeutics.

In The Last Decade

Jeremy Hing

16 papers receiving 754 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jeremy Hing United States 10 227 158 153 138 112 16 764
Zhangzhe Peng China 22 487 2.1× 129 0.8× 294 1.9× 152 1.1× 39 0.3× 79 1.3k
Kostas Stylianou Greece 19 215 0.9× 71 0.4× 144 0.9× 137 1.0× 41 0.4× 77 1.0k
Ufuk Usta Türkiye 14 129 0.6× 171 1.1× 147 1.0× 122 0.9× 19 0.2× 68 637
Zhaoqing Du China 16 302 1.3× 82 0.5× 182 1.2× 253 1.8× 14 0.1× 38 886
Anja Urbschat Germany 17 202 0.9× 71 0.4× 127 0.8× 145 1.1× 39 0.3× 34 808
Fred Alexander United States 17 162 0.7× 125 0.8× 145 0.9× 200 1.4× 79 0.7× 47 880
Sieglinde Kofler Germany 13 174 0.8× 80 0.5× 70 0.5× 248 1.8× 48 0.4× 17 921
Jing Lin China 18 313 1.4× 205 1.3× 219 1.4× 167 1.2× 23 0.2× 73 1.3k
Masaki Imanishi Japan 17 249 1.1× 166 1.1× 184 1.2× 106 0.8× 26 0.2× 64 934

Countries citing papers authored by Jeremy Hing

Since Specialization
Citations

This map shows the geographic impact of Jeremy Hing'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 Jeremy Hing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeremy Hing more than expected).

Fields of papers citing papers by Jeremy Hing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeremy Hing. 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 Jeremy Hing. The network helps show where Jeremy Hing may publish in the future.

Co-authorship network of co-authors of Jeremy Hing

This figure shows the co-authorship network connecting the top 25 collaborators of Jeremy Hing. A scholar is included among the top collaborators of Jeremy Hing 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 Jeremy Hing. Jeremy Hing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Jain, Lokesh, Anne Chain, Daniel Tatosian, et al.. (2019). Pharmacokinetic–pharmacodynamic (dipeptidyl peptidase‐4 inhibition) model to support dose rationale in diabetes patients, including those with renal impairment, for once‐weekly administered omarigliptin. British Journal of Clinical Pharmacology. 85(12). 2759–2771. 7 indexed citations
2.
Li, Jianguo, Mark Lovern, Michelle Green, et al.. (2018). Ceftazidime‐Avibactam Population Pharmacokinetic Modeling and Pharmacodynamic Target Attainment Across Adult Indications and Patient Subgroups. Clinical and Translational Science. 12(2). 151–163. 77 indexed citations
3.
Raddad, Eyas, et al.. (2017). Population Pharmacokinetic and Pharmacodynamic Modeling of LY2510924 in Patients With Advanced Cancer. CPT Pharmacometrics & Systems Pharmacology. 6(9). 614–624. 4 indexed citations
4.
Tanis, Keith Q., Jeremy Hing, Jared Lunceford, et al.. (2016). An accessible pharmacodynamic transcriptional biomarker for notch target engagement. Clinical Pharmacology & Therapeutics. 99(4). 370–380. 4 indexed citations
5.
Hopkins, Seth C., et al.. (2015). Pharmacokinetics and Exposure-Response Relationships of Dasotraline in the Treatment of Attention-Deficit/Hyperactivity Disorder in Adults. Clinical Drug Investigation. 36(2). 137–146. 24 indexed citations
6.
Krop, Ian E., Tim Demuth, Tina Guthrie, et al.. (2012). Phase I Pharmacologic and Pharmacodynamic Study of the Gamma Secretase (Notch) Inhibitor MK-0752 in Adult Patients With Advanced Solid Tumors. Journal of Clinical Oncology. 30(19). 2307–2313. 251 indexed citations
7.
Blackman, Samuel C., Joel A. Klappenbach, Radha Railkar, et al.. (2009). Abstract B41: Identification of a time- and dose-responsive transcriptional signature of Notch pathway inhibition in plucked human hair follicles following exposure to the gamma-secretase inhibitor MK-0752. Molecular Cancer Therapeutics. 8(12_Supplement). B41–B41. 3 indexed citations
8.
Ruixo, Juan José Pérez, Wojciech Krzyżański, & Jeremy Hing. (2008). Pharmacodynamic Analysis of Recombinant Human Erythropoietin Effect on Reticulocyte Production Rate and Age Distribution in Healthy Subjects. Clinical Pharmacokinetics. 47(6). 399–415. 41 indexed citations
9.
Hing, Jeremy, Juan José Pérez Ruixo, Kim Stuyckens, et al.. (2007). Mechanism-based Pharmacokinetic/Pharmacodynamic Meta-analysis of Trabectedin (ET-743, Yondelis) Induced Neutropenia. Clinical Pharmacology & Therapeutics. 83(1). 130–143. 35 indexed citations
10.
Hing, Jeremy, Vladimir Piotrovsky, Hui C. Kimko, H. Robert Brashear, & Qinying Zhao. (2005). Pharmacokinetic simulation for switching from galantamine immediate-release to extended-release formulation. Current Medical Research and Opinion. 21(4). 483–487. 11 indexed citations
11.
Hing, Jeremy, et al.. (2002). Distinguishing animal subsets in toxicokinetic studies: comparison of non‐linear mixed effects modelling with non‐compartmental methods. Journal of Applied Toxicology. 22(6). 437–443. 4 indexed citations
12.
Batchelor, Anna, R. Bullock, A. Gascoigne, et al.. (2001). Peri-operative risk factors for acute lung injury after elective oesophagectomy. British Journal of Anaesthesia. 86(5). 633–638. 139 indexed citations
13.
Hing, Jeremy, et al.. (2001). Analysis of Toxicokinetic Data Using NONMEM: Impact of Quantification Limit and Replacement Strategies for Censored Data. Journal of Pharmacokinetics and Pharmacodynamics. 28(5). 465–479. 41 indexed citations
14.
Hing, Jeremy, et al.. (2001). Is Mixed Effects Modeling or Naïve Pooled Data Analysis Preferred for the Interpretation of Single Sample per Subject Toxicokinetic Data?. Journal of Pharmacokinetics and Pharmacodynamics. 28(2). 193–210. 21 indexed citations
15.
Caldwell, James E., Tom Heier, Peter M. C. Wright, et al.. (2000). Temperature-dependent Pharmacokinetics and Pharmacodynamics of Vecuronium. Anesthesiology. 92(1). 84–84. 94 indexed citations
16.
Wright, Peter M. C., B. J. Pollard, Jean M. Scott, et al.. (1999). Antagonism of rapacuronium using edrophonium or neostigmine: pharmacodynamics and pharmacokinetics. British Journal of Anaesthesia. 83(5). 727–733. 8 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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