Cornelius Cilliers

1.0k total citations · 1 hit paper
17 papers, 762 citations indexed

About

Cornelius Cilliers is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Cornelius Cilliers has authored 17 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 10 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Molecular Biology. Recurrent topics in Cornelius Cilliers's work include Monoclonal and Polyclonal Antibodies Research (9 papers), HER2/EGFR in Cancer Research (6 papers) and CAR-T cell therapy research (4 papers). Cornelius Cilliers is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (9 papers), HER2/EGFR in Cancer Research (6 papers) and CAR-T cell therapy research (4 papers). Cornelius Cilliers collaborates with scholars based in United States, South Africa and Netherlands. Cornelius Cilliers's co-authors include Greg M. Thurber, Ian Nessler, Jennifer J. Linderman, Melissa L. Johnson, Minal Barve, James G. Christensen, Joshua K. Sabari, Karen Velastegui, Richard C. Chao and Igor I. Rybkin and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Journal of Pharmaceutical Sciences.

In The Last Decade

Cornelius Cilliers

17 papers receiving 745 citations

Hit Papers

First-in-Human Phase I/IB Dose-Finding Study of Adagrasib... 2022 2026 2023 2024 2022 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cornelius Cilliers United States 11 475 347 295 150 91 17 762
Alexander H. Staudacher Australia 15 443 0.9× 355 1.0× 225 0.8× 141 0.9× 75 0.8× 33 780
Anzhelika Vorobyeva Sweden 20 499 1.1× 799 2.3× 330 1.1× 122 0.8× 67 0.7× 73 1.0k
Hitomi Sudo Japan 17 235 0.5× 289 0.8× 246 0.8× 167 1.1× 51 0.6× 56 766
Sébastien Gouard France 18 259 0.5× 450 1.3× 159 0.5× 178 1.2× 52 0.6× 37 758
Erasmus Poku United States 14 302 0.6× 419 1.2× 156 0.5× 97 0.6× 107 1.2× 33 660
Joshua Z. Drago United States 9 742 1.6× 454 1.3× 356 1.2× 255 1.7× 80 0.9× 28 1.1k
Kelly M. Flagella United States 7 569 1.2× 489 1.4× 287 1.0× 50 0.3× 49 0.5× 7 792
Conrad Chan Canada 16 261 0.5× 504 1.5× 213 0.7× 158 1.1× 82 0.9× 32 772
Leslie Wetzel United States 7 459 1.0× 297 0.9× 188 0.6× 83 0.6× 95 1.0× 11 661
Vania Kenanova United States 15 271 0.6× 675 1.9× 360 1.2× 78 0.5× 57 0.6× 20 862

Countries citing papers authored by Cornelius Cilliers

Since Specialization
Citations

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

Fields of papers citing papers by Cornelius Cilliers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cornelius Cilliers

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

All Works

17 of 17 papers shown
1.
Cilliers, Cornelius, Eleanor Howgate, Hannah M. Jones, Lisa Rahbæk, & Jonathan Q. Tran. (2024). Clinical and Physiologically Based Pharmacokinetic Model Evaluations of Adagrasib Drug–Drug Interactions. Clinical Pharmacology & Therapeutics. 117(3). 732–741. 1 indexed citations
2.
Rahbæk, Lisa, Cornelius Cilliers, Christopher J. Wegerski, et al.. (2024). Absorption, single-dose and steady-state metabolism, excretion, and pharmacokinetics of adagrasib, a KRASG12C inhibitor. Cancer Chemotherapy and Pharmacology. 95(1). 7–7. 2 indexed citations
3.
Khera, Eshita, Michael D. Smith, Michelle L. Ganno, et al.. (2022). Pharmacokinetics and Pharmacodynamics of TAK-164 Antibody Drug Conjugate Coadministered with Unconjugated Antibody. The AAPS Journal. 24(6). 107–107. 5 indexed citations
4.
Cilliers, Cornelius, Dolf Odendaal, Marshall Heradien, et al.. (2022). Diagnostic performance of dobutamine stress echocardiography: A South African experience. South African Medical Journal. 112(6). 433–436. 1 indexed citations
5.
Ou, Sai‐Hong Ignatius, Pasi A. Jänne, Ticiana Leal, et al.. (2022). First-in-Human Phase I/IB Dose-Finding Study of Adagrasib (MRTX849) in Patients With Advanced KRASG12C Solid Tumors (KRYSTAL-1). Journal of Clinical Oncology. 40(23). 2530–2538. 206 indexed citations breakdown →
6.
Rybkin, Igor I., Alexander I. Spira, K. Papadopoulos, et al.. (2021). 99O_PR KRYSTAL-1: Activity and preliminary pharmacodynamic (PD) analysis of adagrasib (MRTX849) in patients (Pts) with advanced non–small cell lung cancer (NSCLC) harboring KRASG12C mutation. Journal of Thoracic Oncology. 16(4). S751–S752. 58 indexed citations
7.
Cilliers, Cornelius, et al.. (2020). An Agent-Based Systems Pharmacology Model of the Antibody-Drug Conjugate Kadcyla to Predict Efficacy of Different Dosing Regimens. The AAPS Journal. 22(2). 29–29. 20 indexed citations
8.
Khera, Eshita, Cornelius Cilliers, Michael D. Smith, et al.. (2020). Quantifying ADC bystander payload penetration with cellular resolution using pharmacodynamic mapping. Neoplasia. 23(2). 210–221. 39 indexed citations
9.
Nessler, Ian, Cornelius Cilliers, & Greg M. Thurber. (2020). Practical Guide for Quantification of In Vivo Degradation Rates for Therapeutic Proteins with Single-Cell Resolution Using Fluorescence Ratio Imaging. Pharmaceutics. 12(2). 132–132. 6 indexed citations
10.
Bartelink, Imke H., Ella F. Jones, Sheerin Shahidi-Latham, et al.. (2018). Tumor Drug Penetration Measurements Could Be the Neglected Piece of the Personalized Cancer Treatment Puzzle. Clinical Pharmacology & Therapeutics. 106(1). 148–163. 63 indexed citations
11.
Cilliers, Cornelius, et al.. (2017). Improved Tumor Penetration and Single-Cell Targeting of Antibody–Drug Conjugates Increases Anticancer Efficacy and Host Survival. Cancer Research. 78(3). 758–768. 84 indexed citations
12.
Cilliers, Cornelius, et al.. (2017). Tracking Antibody Distribution with Near-Infrared Fluorescent Dyes: Impact of Dye Structure and Degree of Labeling on Plasma Clearance. Molecular Pharmaceutics. 14(5). 1623–1633. 90 indexed citations
13.
Khera, Eshita, Cornelius Cilliers, Sumit Bhatnagar, & Greg M. Thurber. (2017). Computational transport analysis of antibody-drug conjugate bystander effects and payload tumoral distribution: implications for therapy. Molecular Systems Design & Engineering. 3(1). 73–88. 46 indexed citations
15.
Cilliers, Cornelius, et al.. (2015). Residualization Rates of Near-Infrared Dyes for the Rational Design of Molecular Imaging Agents. Molecular Imaging and Biology. 17(6). 757–762. 27 indexed citations
16.
Bhatnagar, Sumit, et al.. (2014). Multichannel Imaging to Quantify Four Classes of Pharmacokinetic Distribution in Tumors. Journal of Pharmaceutical Sciences. 103(10). 3276–3286. 22 indexed citations
17.
Lugt, J J van der, et al.. (1995). The diagnosis of Wesselsbron disease in a new-born lamb by immunohistochemical staining of viral antigen.. PubMed. 62(2). 143–6. 4 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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