Tamara J. van Steeg

406 total citations
20 papers, 294 citations indexed

About

Tamara J. van Steeg is a scholar working on Molecular Biology, Pharmacology and Oncology. According to data from OpenAlex, Tamara J. van Steeg has authored 20 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Pharmacology and 6 papers in Oncology. Recurrent topics in Tamara J. van Steeg's work include Drug Transport and Resistance Mechanisms (5 papers), Antibiotics Pharmacokinetics and Efficacy (4 papers) and Receptor Mechanisms and Signaling (3 papers). Tamara J. van Steeg is often cited by papers focused on Drug Transport and Resistance Mechanisms (5 papers), Antibiotics Pharmacokinetics and Efficacy (4 papers) and Receptor Mechanisms and Signaling (3 papers). Tamara J. van Steeg collaborates with scholars based in Netherlands, United States and United Kingdom. Tamara J. van Steeg's co-authors include Elizabeth C. M. de Lange, Meindert Danhof, Paulien Ravenstijn, Piet H. van der Graaf, Hannah M. Jones, Jan Berkhout, Alison Betts, Lindsay B. Avery, Jan Freijer and Joke A. Bouwstra and has published in prestigious journals such as Journal of Controlled Release, Antimicrobial Agents and Chemotherapy and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Tamara J. van Steeg

17 papers receiving 275 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tamara J. van Steeg Netherlands	10	98	67	62	53	45	20	294
Y. Tanaka Japan	12	110 1.1×	31 0.5×	71 1.1×	37 0.7×	16 0.4×	34	487
Xia Hao Sweden	9	236 2.4×	30 0.4×	45 0.7×	24 0.5×	57 1.3×	21	579
Alessio Moriconi Italy	11	147 1.5×	29 0.4×	85 1.4×	120 2.3×	68 1.5×	21	465
David Paul India	14	233 2.4×	30 0.4×	92 1.5×	79 1.5×	29 0.6×	31	506
Jenny Tobin United States	7	152 1.6×	14 0.2×	32 0.5×	23 0.4×	22 0.5×	14	551
Whei‐Mei Wu United States	13	148 1.5×	25 0.4×	41 0.7×	16 0.3×	39 0.9×	20	398
Jens Lamerz Switzerland	17	293 3.0×	43 0.6×	123 2.0×	20 0.4×	16 0.4×	26	503
Ashutosh A. Kulkarni United States	11	193 2.0×	15 0.2×	127 2.0×	11 0.2×	23 0.5×	19	414
Vivaswath S. Ayyar United States	13	177 1.8×	19 0.3×	103 1.7×	48 0.9×	9 0.2×	22	486
Brooke M. Katzman United States	12	186 1.9×	45 0.7×	78 1.3×	55 1.0×	13 0.3×	26	406

Countries citing papers authored by Tamara J. van Steeg

Since Specialization

Citations

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

Fields of papers citing papers by Tamara J. van Steeg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tamara J. van Steeg. 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 Tamara J. van Steeg. The network helps show where Tamara J. van Steeg may publish in the future.

Co-authorship network of co-authors of Tamara J. van Steeg

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

All Works

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20 of 20 papers shown

DeJongh, Joost, Elaine Cadogan, Michael A. Davies, et al.. (2025). Defining preclinical efficacy with the DNAPK inhibitor AZD7648 in combination with olaparib: a minimal systems pharmacokinetic–pharmacodynamic model. Journal of Pharmacokinetics and Pharmacodynamics. 52(2). 17–17.

Man, Robert A. de, Nassim Kamar, Joep de Bruijne, et al.. (2025). Development of a ribavirin dosing regimen in transplant recipients with chronic hepatitis E virus infection: a population pharmacokinetic and -dynamic model. Journal of Antimicrobial Chemotherapy. 80(8). 2158–2168.

Muliaditan, Morris, Tamara J. van Steeg, Lindsay B. Avery, et al.. (2025). Translational minimal physiologically based pharmacokinetic model for transferrin receptor-mediated brain delivery of antibodies. mAbs. 17(1). 2515414–2515414. 1 indexed citations

Berkhout, Jan, et al.. (2024). A model‐based approach using GSK3772847, an anti‐interleukin‐33 receptor monoclonal antibody, as a showcase to predict SC administration PK and free target dynamics based on PK and total target measurements after IV administration. CPT Pharmacometrics & Systems Pharmacology. 14(1). 17–27.

Berends, Sophie E., Tamara J. van Steeg, Maurice J. Ahsman, et al.. (2019). Tumor necrosis factor-mediated disposition of infliximab in ulcerative colitis patients. Journal of Pharmacokinetics and Pharmacodynamics. 46(6). 543–551. 11 indexed citations

Steeg, Tamara J. van, Maurice J. Ahsman, Maria S. Michener, et al.. (2018). Extending a Systems Model of the APP Pathway: Separation of β- and γ-Secretase Sequential Cleavage Steps of APP. Journal of Pharmacology and Experimental Therapeutics. 365(3). 507–518. 13 indexed citations

Betts, Alison, Tamara J. van Steeg, Piet H. van der Graaf, et al.. (2018). Linear pharmacokinetic parameters for monoclonal antibodies are similar within a species and across different pharmacological targets: A comparison between human, cynomolgus monkey and hFcRn Tg32 transgenic mouse using a population-modeling approach. mAbs. 10(5). 751–764. 71 indexed citations

Goto, Akihiko, Yoshihiko Tagawa, Sho Sato, et al.. (2017). Influence of body composition on disposition of the highly fat distributed compound as analysed by physiologically based pharmacokinetic (PBPK) modeling and simulation. Biopharmaceutics & Drug Disposition. 38(9). 543–552. 1 indexed citations

Goto, Akihiko, Yoshihiko Tagawa, Sho Sato, et al.. (2017). Impact of acute fat mobilisation on the pharmacokinetics of the highly fat distributed compound TAK‐357, investigated by physiologically based pharmacokinetic (PBPK) modeling and simulation. Biopharmaceutics & Drug Disposition. 38(6). 373–380. 2 indexed citations

10.

Steeg, Tamara J. van, et al.. (2016). The application of mathematical modelling to the design of bispecific monoclonal antibodies. mAbs. 8(3). 585–592. 13 indexed citations

11.

Steeg, Tamara J. van, Maria S. Michener, Mary J. Savage, et al.. (2016). Systems Pharmacology Analysis of the Amyloid Cascade after β-Secretase Inhibition Enables the Identification of an Aβ42 Oligomer Pool. Journal of Pharmacology and Experimental Therapeutics. 357(1). 205–216. 7 indexed citations

12.

Steeg, Tamara J. van, et al.. (2009). Influence of Plasma Protein Binding on Pharmacodynamics: Estimation of In Vivo Receptor Affinities of β Blockers Using a New Mechanism-Based PK–PD Modelling Approach. Journal of Pharmaceutical Sciences. 98(10). 3816–3828. 15 indexed citations

13.

Steeg, Tamara J. van, et al.. (2009). Effect of altered AGP plasma binding on heart rate changes by S(−)‐propranolol in rats using mechanism‐based estimations of in vivo receptor affinity (KB,vivo). Journal of Pharmaceutical Sciences. 99(5). 2511–2520. 5 indexed citations

14.

Benson, Neil, Joost de Jongh, Hannah M. Jones, et al.. (2009). Pharmacokinetic-Pharmacodynamic Modeling of Alpha Interferon Response Induced by a Toll-Like 7 Receptor Agonist in Mice. Antimicrobial Agents and Chemotherapy. 54(3). 1179–1185. 10 indexed citations

15.

Steeg, Tamara J. van, Jan Freijer, Meindert Danhof, & Elizabeth C. M. de Lange. (2007). Pharmacokinetic‐pharmacodynamic modelling ofS(−)‐atenolol in rats: reduction of isoprenaline‐induced tachycardia as a continuous pharmacodynamic endpoint. British Journal of Pharmacology. 151(3). 356–366. 19 indexed citations

16.

Steeg, Tamara J. van, Jan Freijer, Meindert Danhof, & Elizabeth C. M. de Lange. (2007). Mechanism-Based Pharmacodynamic Modeling of S(–)-Atenolol: Estimation of in Vivo Affinity for the β1-Adrenoceptor with an Agonist-Antagonist Interaction Model. Journal of Pharmacology and Experimental Therapeutics. 324(3). 1234–1242. 5 indexed citations

17.

Steeg, Tamara J. van, Elke H. J. Krekels, Meindert Danhof, & Elizabeth C. M. de Lange. (2007). Reproducible and time-dependent modification of serum protein binding in Wistar Kyoto rats. Journal of Pharmacological and Toxicological Methods. 56(1). 72–78. 4 indexed citations

18.

Steeg, Tamara J. van, et al.. (2005). Cutaneous side-effects of transdermal iontophoresis with and without surfactant pretreatment: a single-blinded, randomized controlled trial. British Journal of Dermatology. 153(2). 404–412. 25 indexed citations

19.

Lange, Elizabeth C. M. de, et al.. (2005). Toward the prediction of CNS drug-effect profiles in physiological and pathological conditions using microdialysis and mechanism-based pharmacokinetic-pharmacodynamic modeling. The AAPS Journal. 7(3). E532–E543. 67 indexed citations

20.

Steeg, Tamara J. van, Hendrik van den Bussche, Hugo Maas, et al.. (2004). Transdermal iontophoretic delivery of apomorphine in patients improved by surfactant formulation pretreatment. Journal of Controlled Release. 101(1-3). 199–208. 25 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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