Vijay Peddareddigari

2.8k total citations · 1 hit paper
18 papers, 1.2k citations indexed

About

Vijay Peddareddigari is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Vijay Peddareddigari has authored 18 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 10 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in Vijay Peddareddigari's work include CAR-T cell therapy research (6 papers), Biosimilars and Bioanalytical Methods (4 papers) and Fibroblast Growth Factor Research (3 papers). Vijay Peddareddigari is often cited by papers focused on CAR-T cell therapy research (6 papers), Biosimilars and Bioanalytical Methods (4 papers) and Fibroblast Growth Factor Research (3 papers). Vijay Peddareddigari collaborates with scholars based in United States, United Kingdom and Spain. Vijay Peddareddigari's co-authors include Raymond N. DuBois, Dingzhi Wang, Jeffrey R. Infante, Leslie A. Fecher, Douglas J. DeMarini, Gerald S. Falchook, Johanna C. Bendell, Wells A. Messersmith, Michael S. Gordon and Shannon R. Morris and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Cancer Research.

In The Last Decade

Vijay Peddareddigari

18 papers receiving 1.1k citations

Hit Papers

Safety, pharmacokinetic, pharmacodynamic, and efficacy da... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vijay Peddareddigari United States 11 714 600 183 170 149 18 1.2k
Giorgia Migliardi Italy 18 515 0.7× 719 1.2× 352 1.9× 277 1.6× 171 1.1× 28 1.3k
Gregory Friberg United States 18 504 0.7× 722 1.2× 318 1.7× 269 1.6× 83 0.6× 35 1.2k
Marion T. Weigel Germany 16 481 0.7× 338 0.6× 119 0.7× 275 1.6× 118 0.8× 27 1.1k
Chris Womack United Kingdom 16 595 0.8× 594 1.0× 282 1.5× 205 1.2× 132 0.9× 34 1.2k
Mónica Musteanu Spain 14 415 0.6× 552 0.9× 149 0.8× 181 1.1× 107 0.7× 32 972
Alexander C. Klimowicz Canada 23 821 1.1× 653 1.1× 188 1.0× 280 1.6× 182 1.2× 56 1.5k
Suso Platero United States 11 615 0.9× 441 0.7× 301 1.6× 309 1.8× 178 1.2× 22 1.1k
Christopher Ruel United States 18 468 0.7× 536 0.9× 309 1.7× 131 0.8× 74 0.5× 47 1.0k
Carles Barceló Spain 10 640 0.9× 616 1.0× 136 0.7× 300 1.8× 53 0.4× 17 1.2k
Arturo Loaiza‐Bonilla United States 13 287 0.4× 523 0.9× 238 1.3× 262 1.5× 156 1.0× 62 960

Countries citing papers authored by Vijay Peddareddigari

Since Specialization
Citations

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

Fields of papers citing papers by Vijay Peddareddigari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vijay Peddareddigari

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

All Works

18 of 18 papers shown
1.
Tholouli, Eleni, Wendy Osborne, Carlos Bachier, et al.. (2020). 890MO Phase I Alexander study of AUTO3, the first CD19/22 dual targeting CAR.T cell, with pembrolizumab in patients with relapsed/refractory (r/r) DLBCL. Annals of Oncology. 31. S651–S651. 4 indexed citations
2.
Popat, Rakesh, Sonja Zweegman, Jim Cavet, et al.. (2019). Phase 1 First-in-Human Study of AUTO2, the First Chimeric Antigen Receptor (CAR) T Cell Targeting APRIL for Patients with Relapsed/Refractory Multiple Myeloma (RRMM). Blood. 134(Supplement_1). 3112–3112. 45 indexed citations
7.
Chaplan, Sandra R., Zuleima Aguilar, Dennis M. Fisher, et al.. (2015). Abstract CT309: Rapid evaluation of a novel small molecule cMet tyrosine kinase inhibitor in healthy subjects. Cancer Research. 75(15_Supplement). CT309–CT309. 2 indexed citations
8.
Tabernero, Josep, Rastislav Bahleda, Rodrigo Dienstmann, et al.. (2015). Phase I Dose-Escalation Study of JNJ-42756493, an Oral Pan–Fibroblast Growth Factor Receptor Inhibitor, in Patients With Advanced Solid Tumors. Journal of Clinical Oncology. 33(30). 3401–3408. 299 indexed citations
9.
Dienstmann, Rodrigo, Rastilav Bahleda, Bárbara Adamo, et al.. (2014). Abstract CT325: First in human study of JNJ-42756493, a potent pan fibroblast growth factor receptor (FGFR) inhibitor in patients with advanced solid tumors. Cancer Research. 74(19_Supplement). CT325–CT325. 21 indexed citations
10.
Bahleda, Rastislav, Rodrigo Dienstmann, Bárbara Adamo, et al.. (2014). Phase 1 study of JNJ-42756493, a pan-fibroblast growth factor receptor (FGFR) inhibitor, in patients with advanced solid tumors.. Journal of Clinical Oncology. 32(15_suppl). 2501–2501. 34 indexed citations
11.
Parikh, Sameer A., Christopher A. French, Brian A. Costello, et al.. (2013). NUT Midline Carcinoma: An Aggressive Intrathoracic Neoplasm. Journal of Thoracic Oncology. 8(10). 1335–1338. 34 indexed citations
12.
Infante, Jeffrey R., Leslie A. Fecher, Gerald S. Falchook, et al.. (2012). Safety, pharmacokinetic, pharmacodynamic, and efficacy data for the oral MEK inhibitor trametinib: a phase 1 dose-escalation trial. The Lancet Oncology. 13(8). 773–781. 424 indexed citations breakdown →
13.
Chakravarti, Nitin, Vijay Peddareddigari, Carla L. Warneke, et al.. (2012). Differential Expression of the G-Protein–Coupled Formyl Peptide Receptor in Melanoma Associates With Aggressive Phenotype. American Journal of Dermatopathology. 35(2). 184–190. 20 indexed citations
14.
Gan, Hui, Noelia Nebot, J.C. Soria, et al.. (2012). 613 Pharmacokinetics/pharmacodynamics (PK/PD) of GSK2256098, a Focal Adhesion Kinase (FAK) Inhibitor, in Patients with Advanced Solid Tumors. European Journal of Cancer. 48. 189–189. 3 indexed citations
15.
Soria, Jean‐Charles, Ruth Plummer, Malcolm Ranson, et al.. (2012). 610 Loss of the Tumor Suppressor Merlin as a Potential Predictive Biomarker of Clinical Activity for the Oral, Focal Adhesion Kinase (FAK) Inhibitor GSK2256098 in Pts with Recurrent Mesothelioma. European Journal of Cancer. 48. 188–188. 7 indexed citations
16.
Messersmith, Wells A., Gerald S. Falchook, Leslie A. Fecher, et al.. (2011). Clinical activity of the oral MEK1/MEK2 inhibitor GSK1120212 in pancreatic and colorectal cancer.. Journal of Clinical Oncology. 29(4_suppl). 246–246. 8 indexed citations
17.
Gordon, M.S., J. R. Infante, W. Messersmith, et al.. (2010). 373 The oral MEK1/MEK2 inhibitor, GSK1120212, effectively inhibits the MAPK pathway: pharmacokinetic, pharmacodynamic, and clinical response relationship. European Journal of Cancer Supplements. 8(7). 118–118. 1 indexed citations
18.
Peddareddigari, Vijay, Dingzhi Wang, & Raymond N. DuBois. (2010). The Tumor Microenvironment in Colorectal Carcinogenesis. Cancer Microenvironment. 3(1). 149–166. 182 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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