Ajit Dash

2.2k total citations · 1 hit paper
38 papers, 1.8k citations indexed

About

Ajit Dash is a scholar working on Immunology, Hepatology and Epidemiology. According to data from OpenAlex, Ajit Dash has authored 38 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Immunology, 11 papers in Hepatology and 9 papers in Epidemiology. Recurrent topics in Ajit Dash's work include Liver physiology and pathology (6 papers), Liver Disease Diagnosis and Treatment (6 papers) and IL-33, ST2, and ILC Pathways (6 papers). Ajit Dash is often cited by papers focused on Liver physiology and pathology (6 papers), Liver Disease Diagnosis and Treatment (6 papers) and IL-33, ST2, and ILC Pathways (6 papers). Ajit Dash collaborates with scholars based in United States, United Kingdom and Germany. Ajit Dash's co-authors include Mark B. Pepys, Brian R. Wamhoff, M B Pepys, E. A. Munn, A. Feinstein, Ryan E. Feaver, Aviva Petrie, Thelma C. Fletcher, Banumathi K. Cole and Neil Richardson and has published in prestigious journals such as Nature, The Lancet and The Journal of Immunology.

In The Last Decade

Ajit Dash

36 papers receiving 1.6k citations

Hit Papers

Astegolimab (anti-ST2) efficacy and safety in adults with... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ajit Dash United States 21 486 360 360 350 301 38 1.8k
Christina Wu United States 26 736 1.5× 174 0.5× 561 1.6× 268 0.8× 222 0.7× 64 2.0k
G P Jahreis United States 21 796 1.6× 228 0.6× 482 1.3× 298 0.9× 252 0.8× 29 2.0k
Steven D. Carson United States 30 965 2.0× 119 0.3× 406 1.1× 243 0.7× 431 1.4× 96 2.9k
Christophe Desterke France 27 881 1.8× 123 0.3× 270 0.8× 589 1.7× 409 1.4× 138 2.6k
Takanori Sakaguchi Japan 28 748 1.5× 129 0.4× 348 1.0× 314 0.9× 890 3.0× 125 2.6k
Jan Heidemann Germany 29 751 1.5× 113 0.3× 763 2.1× 448 1.3× 544 1.8× 65 2.5k
Cathal Harmon Ireland 15 461 0.9× 152 0.4× 823 2.3× 374 1.1× 170 0.6× 21 1.8k
Владимир Субботин United States 35 1.0k 2.1× 204 0.6× 951 2.6× 499 1.4× 1.1k 3.7× 108 3.4k
Pedro Majano Spain 31 734 1.5× 152 0.4× 361 1.0× 1.1k 3.1× 446 1.5× 59 2.8k
Susumu Miyata Japan 20 890 1.8× 145 0.4× 431 1.2× 196 0.6× 247 0.8× 29 2.2k

Countries citing papers authored by Ajit Dash

Since Specialization
Citations

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

Fields of papers citing papers by Ajit Dash

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ajit Dash

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

All Works

20 of 20 papers shown
1.
Zhang, Wenhui, Dorothy Cheung, Alice Fong, et al.. (2025). Safety, Pharmacokinetics, and Immunogenicity of Astegolimab, an Anti‐ST2 Monoclonal Antibody, in Randomized, Phase I Clinical Studies. Clinical and Translational Science. 18(10). e70338–e70338.
2.
Kelsen, Steven G., Marcus Maurer, Michael R. Waters, et al.. (2025). Safety and tolerability of astegolimab, an anti-ST2 monoclonal antibody: a narrative review. Respiratory Research. 26(1). 302–302.
3.
Yoshida, Kenta, et al.. (2024). Simulation‐based evaluation of personalized dosing approaches for anti‐FGFR/KLB bispecific antibody fazpilodemab. CPT Pharmacometrics & Systems Pharmacology. 13(4). 544–550. 4 indexed citations
4.
Zhang, Wenhui, Dorothy Cheung, Alice Fong, et al.. (2024). Pharmacokinetics (PK) of the anti-ST2 monoclonal antibody, astegolimab. PA2987–PA2987. 2 indexed citations
5.
Mansfield, John, Annemarie Lekkerkerker, Yehong Wang, et al.. (2023). Dose escalation randomised study of efmarodocokin alfa in healthy volunteers and patients with ulcerative colitis. Gut. 72(8). 1451–1461. 13 indexed citations
6.
Maurer, Marcus, Dorothy Cheung, Xiaoying Yang, et al.. (2022). Phase 2 randomized clinical trial of astegolimab in patients with moderate to severe atopic dermatitis. Journal of Allergy and Clinical Immunology. 150(6). 1517–1524. 43 indexed citations
7.
Dash, Ajit, Jill Fredrickson, Nicholas Lewin‐Koh, et al.. (2022). Fibroblast growth factor receptor 1/Klothoβ agonist BFKB8488A improves lipids and liver health markers in patients with diabetes or NAFLD: A phase 1b randomized trial. Hepatology. 78(3). 847–862. 24 indexed citations
8.
Kelsen, Steven G., Ioana Agache, Weily Soong, et al.. (2021). Astegolimab (anti-ST2) efficacy and safety in adults with severe asthma: A randomized clinical trial. Journal of Allergy and Clinical Immunology. 148(3). 790–798. 195 indexed citations breakdown →
10.
Dash, Ajit, Robert A. Figler, Svetlana Marukian, et al.. (2016). Pharmacotoxicology of clinically-relevant concentrations of obeticholic acid in an organotypic human hepatocyte system. Toxicology in Vitro. 39. 93–103. 29 indexed citations
11.
Chapman, Kimberly A., Maria Sol Collado, Robert A. Figler, et al.. (2015). Recapitulation of metabolic defects in a model of propionic acidemia using patient-derived primary hepatocytes. Molecular Genetics and Metabolism. 117(3). 355–362. 13 indexed citations
12.
Terelius, Ylva, Robert A. Figler, Svetlana Marukian, et al.. (2015). Transcriptional profiling suggests that Nevirapine and Ritonavir cause drug induced liver injury through distinct mechanisms in primary human hepatocytes. Chemico-Biological Interactions. 255. 31–44. 27 indexed citations
13.
Dash, Ajit, Michael B. Simmers, Tye Deering, et al.. (2013). Hemodynamic flow improves rat hepatocyte morphology, function, and metabolic activity in vitro. American Journal of Physiology-Cell Physiology. 304(11). C1053–C1063. 91 indexed citations
14.
Dash, Ajit, Brett R. Blackman, & Brian R. Wamhoff. (2012). Organotypic systems in drug metabolism and toxicity: challenges and opportunities. Expert Opinion on Drug Metabolism & Toxicology. 8(8). 999–1014. 16 indexed citations
15.
Domanský, Karel, et al.. (2009). Perfused multiwell plate for 3D liver tissue engineering. Lab on a Chip. 10(1). 51–58. 8 indexed citations
16.
Dash, Ajit, W. R. Inman, Keith Hoffmaster, et al.. (2009). Liver tissue engineering in the evaluation of drug safety. Expert Opinion on Drug Metabolism & Toxicology. 5(10). 1159–1174. 127 indexed citations
17.
Pepys, Mark B., et al.. (1978). Comparative clinical study of protein SAP (amyloid P component) and C-reactive protein in serum.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 32(1). 119–24. 166 indexed citations
18.
Pepys, M B, Ajit Dash, & M. J. Ashley. (1977). Isolation of C-reactive protein by affinity chromatography.. PubMed. 30(1). 32–7. 73 indexed citations
19.
Pepys, Mark B., et al.. (1977). Isolation and study of murine C3.. PubMed. 33(4). 491–9. 31 indexed citations
20.
Pepys, Mark B., Mark Wansbrough‐Jones, Ajit Dash, et al.. (1976). Complement in the Induction of IgA and IgE Antibody Production. The Journal of Immunology. 116(6). 1746–1746. 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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