Sandra A. G. Visser

2.3k total citations
73 papers, 1.7k citations indexed

About

Sandra A. G. Visser is a scholar working on Molecular Biology, Computational Theory and Mathematics and Physiology. According to data from OpenAlex, Sandra A. G. Visser has authored 73 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 15 papers in Computational Theory and Mathematics and 14 papers in Physiology. Recurrent topics in Sandra A. G. Visser's work include Computational Drug Discovery Methods (15 papers), Statistical Methods in Clinical Trials (13 papers) and Cardiac electrophysiology and arrhythmias (10 papers). Sandra A. G. Visser is often cited by papers focused on Computational Drug Discovery Methods (15 papers), Statistical Methods in Clinical Trials (13 papers) and Cardiac electrophysiology and arrhythmias (10 papers). Sandra A. G. Visser collaborates with scholars based in United States, Netherlands and Sweden. Sandra A. G. Visser's co-authors include Meindert Danhof, Piet H. van der Graaf, Thomas Kerbusch, L. A. Peletier, Tjerk Bueters, Alexander Staab, Gianni Marone, R.A. Voskuyl, Daniël M. Jonker and Ahmad Al‐Saffar and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Pharmacology and Experimental Therapeutics and British Journal of Pharmacology.

In The Last Decade

Sandra A. G. Visser

70 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sandra A. G. Visser United States	24	540	313	282	224	206	73	1.7k
Bart A. Ploeger Netherlands	26	630 1.2×	223 0.7×	166 0.6×	498 2.2×	145 0.7×	67	2.3k
Sandeep Dutta United States	30	365 0.7×	179 0.6×	140 0.5×	474 2.1×	100 0.5×	139	2.8k
Brian Corrigan United States	23	303 0.6×	173 0.6×	377 1.3×	184 0.8×	299 1.5×	69	2.1k
Piet H. van der Graaf Netherlands	32	1.7k 3.2×	653 2.1×	262 0.9×	518 2.3×	283 1.4×	149	3.8k
Klaus Romero United States	23	463 0.9×	119 0.4×	164 0.6×	87 0.4×	99 0.5×	80	1.7k
Richard Peck United Kingdom	25	295 0.5×	105 0.3×	203 0.7×	176 0.8×	167 0.8×	64	1.5k
Rasmus Jansson‐Löfmark Sweden	26	466 0.9×	119 0.4×	135 0.5×	161 0.7×	45 0.2×	81	2.1k
Vangelis G. Manolopoulos Greece	28	1.2k 2.2×	133 0.4×	421 1.5×	727 3.2×	66 0.3×	135	3.2k
Debra C. DuBois United States	31	950 1.8×	132 0.4×	606 2.1×	299 1.3×	34 0.2×	116	2.8k
J. G. Coen van Hasselt Netherlands	29	509 0.9×	108 0.3×	76 0.3×	183 0.8×	118 0.6×	115	2.6k

Countries citing papers authored by Sandra A. G. Visser

Since Specialization

Citations

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

Fields of papers citing papers by Sandra A. G. Visser

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sandra A. G. Visser. 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 Sandra A. G. Visser. The network helps show where Sandra A. G. Visser may publish in the future.

Co-authorship network of co-authors of Sandra A. G. Visser

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Goulooze, Sebastiaan C., Morris Muliaditan, Alejandro Mantero, et al.. (2025). Tutorial on Conditional Simulations With a Tumor Size‐Overall Survival Model to Support Oncology Drug Development. CPT Pharmacometrics & Systems Pharmacology. 14(4). 640–650. 1 indexed citations

Struemper, Herbert, Chetan Rathi, Morris Muliaditan, et al.. (2025). Development of a Joint Tumor Size–Overall Survival Modeling and Simulation Framework Supporting Oncology Development Decision‐Making. CPT Pharmacometrics & Systems Pharmacology. 14(6). 1006–1017. 1 indexed citations

Jewell, Roxanne C., Richard J. Mills, Colm Farrell, & Sandra A. G. Visser. (2024). Belantamab mafodotin concentration–QTc relationships in patients with relapsed or refractory multiple myeloma from the DREAMM‐1 and ‐2 studies. British Journal of Clinical Pharmacology. 90(10). 2571–2581. 1 indexed citations

Weber, Benjamin, et al.. (2024). How debunking biases in research and development decisions could lead to more equitable healthcare?. Clinical and Translational Science. 17(7). e13880–e13880. 1 indexed citations

McCabe, Michael T., Geraldine Ferron‐Brady, Paul Martin, et al.. (2024). Momelotinib: Mechanism of action, clinical, and translational science. Clinical and Translational Science. 17(8). e70018–e70018. 5 indexed citations

Ferron‐Brady, Geraldine, et al.. (2023). Building an adaptive dose simulation framework to aid dose and schedule selection. CPT Pharmacometrics & Systems Pharmacology. 12(11). 1602–1618. 2 indexed citations

Visser, Sandra A. G. & Tjerk Bueters. (2017). Assessment of translational risk in drug research: Role of biomarker classification and mechanism-based PKPD concepts. European Journal of Pharmaceutical Sciences. 109. S72–S77. 5 indexed citations

Cabal, Antonio, Khamir Mehta, David Ross, et al.. (2016). Preclinical Experimental and Mathematical Approaches for Assessing Effective Doses of Inhaled Drugs, Using Mometasone to Support Human Dose Predictions. Journal of Aerosol Medicine and Pulmonary Drug Delivery. 29(4). 362–377. 17 indexed citations

Gotta, Verena, Frank Cools, Karel Van Ammel, et al.. (2016). Application of a systems pharmacology model for translational prediction of hERG ‐mediated QT c prolongation. Pharmacology Research & Perspectives. 4(6). e00270–e00270. 12 indexed citations

10.

Kam, Pieter‐Jan de, Annelieke C. Kruithof, Jacobus Burggraaf, et al.. (2015). A PK-PD model-based assessment of sugammadex effects on coagulation parameters. European Journal of Pharmaceutical Sciences. 84. 9–17. 3 indexed citations

11.

Luo, Lei, et al.. (2013). In Vivo and Ex Vivo Inhibition of Spinal Nerve Ligation-Induced Ectopic Activity by Sodium Channel Blockers Correlate to In Vitro Inhibition of NaV1.7 and Clinical Efficacy: A Pharmacokinetic-Pharmacodynamic Translational Approach. Pharmaceutical Research. 30(5). 1409–1422. 6 indexed citations

12.

Bueters, Tjerk, Bart A. Ploeger, & Sandra A. G. Visser. (2013). The virtue of translational PKPD modeling in drug discovery: selecting the right clinical candidate while sparing animal lives. Drug Discovery Today. 18(17-18). 853–862. 33 indexed citations

13.

Janson, Juliette, Susanna Eketjäll, Karin Tunblad, et al.. (2013). Population PKPD Modeling of BACE1 Inhibitor-Induced Reduction in Aβ Levels In Vivo and Correlation to In Vitro Potency in Primary Cortical Neurons from Mouse and Guinea Pig. Pharmaceutical Research. 31(3). 670–683. 7 indexed citations

14.

Parkinson, Joanna, Sandra A. G. Visser, Philip Jarvis, et al.. (2013). Translational pharmacokinetic–pharmacodynamic modeling of QTc effects in dog and human. Journal of Pharmacological and Toxicological Methods. 68(3). 357–366. 35 indexed citations

15.

Wang, Fuhua, Tomas Klason, Olof Gissberg, et al.. (2012). Decreased axonal transport rates in the Tg2576 APP transgenic mouse: improvement with the gamma‐secretase inhibitor MRK‐560 as detected by manganese‐enhanced MRI. European Journal of Neuroscience. 36(9). 3165–3172. 24 indexed citations

16.

Visser, Sandra A. G., et al.. (2011). Using pharmacokinetic modeling to determine the effect of drug and food on gastrointestinal transit in dogs. Journal of Pharmacological and Toxicological Methods. 64(1). 42–52. 21 indexed citations

17.

Visser, Sandra A. G., Dymphy Huntjens, Piet H. van der Graaf, L. A. Peletier, & Meindert Danhof. (2003). Mechanism-Based Modeling of the Pharmacodynamic Interaction of Alphaxalone and Midazolam in Rats. Journal of Pharmacology and Experimental Therapeutics. 307(2). 765–775. 11 indexed citations

18.

Visser, Sandra A. G., et al.. (2003). Dose-Dependent EEG Effects of Zolpidem Provide Evidence for GABAA Receptor Subtype Selectivity in Vivo. Journal of Pharmacology and Experimental Therapeutics. 304(3). 1251–1257. 20 indexed citations

19.

Visser, Sandra A. G., et al.. (2002). Neuroactive Steroids Differ in Potency but Not in Intrinsic Efficacy at the GABAA Receptor in Vivo. Journal of Pharmacology and Experimental Therapeutics. 303(2). 616–626. 16 indexed citations

20.

Visser, Sandra A. G., et al.. (2000). High-performance liquid chromatography of the neuroactive steroids alphaxalone and pregnanolone in plasma using dansyl hydrazine as fluorescent label: application to a pharmacokinetic-pharmacodynamic study in rats. Journal of Chromatography B Biomedical Sciences and Applications. 745(2). 357–363. 28 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.

Explore authors with similar magnitude of impact