Michael Dodds

2.1k total citations
51 papers, 1.2k citations indexed

About

Michael Dodds is a scholar working on Oncology, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Michael Dodds has authored 51 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 12 papers in Molecular Biology and 7 papers in Infectious Diseases. Recurrent topics in Michael Dodds's work include Monoclonal and Polyclonal Antibodies Research (5 papers), Anesthesia and Sedative Agents (5 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Michael Dodds is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (5 papers), Anesthesia and Sedative Agents (5 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Michael Dodds collaborates with scholars based in United States, United Kingdom and Australia. Michael Dodds's co-authors include Korean J Child, D.J. Twissell, Brittany N. Davis, Paolo Vicini, J. P. Currie, R. D. Foord, Morwenna Muir, Andrew C. Hooker, Philip S. Stewart and Simon P. Langdon and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Cancer Research.

In The Last Decade

Michael Dodds

48 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Dodds United States 22 288 234 125 121 116 51 1.2k
Manuel Román Spain 25 228 0.8× 287 1.2× 177 1.4× 34 0.3× 196 1.7× 116 1.9k
Sunita J. Shukla United States 19 586 2.0× 214 0.9× 64 0.5× 52 0.4× 68 0.6× 31 1.7k
J Brugmans Belgium 18 176 0.6× 137 0.6× 130 1.0× 119 1.0× 159 1.4× 44 1.3k
Kensuke Kobayashi Japan 19 271 0.9× 129 0.6× 353 2.8× 33 0.3× 23 0.2× 80 1.2k
Kazuhisa Furuhama Japan 19 264 0.9× 113 0.5× 178 1.4× 142 1.2× 139 1.2× 144 1.4k
Vijay Batra United States 17 216 0.8× 204 0.9× 146 1.2× 45 0.4× 222 1.9× 45 1.3k
Dirk Meijer Netherlands 23 493 1.7× 676 2.9× 316 2.5× 20 0.2× 114 1.0× 71 1.9k
Leonid Kagan United States 24 468 1.6× 235 1.0× 147 1.2× 11 0.1× 115 1.0× 87 1.6k
Marc B. Bailie United States 17 476 1.7× 147 0.6× 143 1.1× 42 0.3× 151 1.3× 44 2.0k
Matthew W. Davis United States 19 407 1.4× 73 0.3× 364 2.9× 35 0.3× 101 0.9× 56 1.3k

Countries citing papers authored by Michael Dodds

Since Specialization
Citations

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

Fields of papers citing papers by Michael Dodds

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Dodds

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Dodds. A scholar is included among the top collaborators of Michael Dodds 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 Michael Dodds. Michael Dodds 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.
Siemers, Eric, Gopalan Sethuraman, Karen Sundell, et al.. (2025). INTERCEPT-AD, a phase 1 study of intravenous sabirnetug in participants with mild cognitive impairment or mild dementia due to Alzheimer's disease. The Journal of Prevention of Alzheimer s Disease. 12(1). 100005–100005. 4 indexed citations
2.
3.
Filosto, Simone, Manoj Chiney, Francesca Milletti, et al.. (2024). Investigating the Influence of Covariates on Axicabtagene Ciloleucel (axi-cel) Kinetics in Patients with Non-Hodgkin’s Lymphoma. Clinical Pharmacokinetics. 63(9). 1283–1299. 2 indexed citations
4.
5.
Li, Kan, Michael Dodds, Rachel L. Spreng, et al.. (2023). A tool for evaluating heterogeneity in avidity of polyclonal antibodies. Frontiers in Immunology. 14. 1049673–1049673. 4 indexed citations
6.
Hellgren, Fredrika, Alberto Cagigi, Sebastian Ols, et al.. (2023). Unmodified rabies mRNA vaccine elicits high cross-neutralizing antibody titers and diverse B cell memory responses. Nature Communications. 14(1). 3713–3713. 36 indexed citations
7.
Dodds, Michael, Yuan Xiong, Samer Mouksassi, et al.. (2021). Model‐informed drug repurposing: A pharmacometric approach to novel pathogen preparedness, response and retrospection. British Journal of Clinical Pharmacology. 87(9). 3388–3397. 9 indexed citations
8.
9.
Patel, Kashyap, Michael Dodds, António Gonçalves, et al.. (2020). Using in silico viral kinetic models to guide therapeutic strategies during a pandemic: An example in SARS‐CoV‐2. British Journal of Clinical Pharmacology. 87(9). 3425–3438. 3 indexed citations
10.
Zemouri, Charifa, Nicholas S. Jakubovics, Wim Crielaard, et al.. (2019). Resistance and resilience to experimental gingivitis: a systematic scoping review. BMC Oral Health. 19(1). 212–212. 18 indexed citations
11.
Alvarez‐Núñez, Fernando, Vincent Chow, Dominick Daurio, et al.. (2015). Utilizing Physiologically Based Pharmacokinetic Modeling to Inform Formulation and Clinical Development for a Compound with pH-Dependent Solubility. Journal of Pharmaceutical Sciences. 104(4). 1522–1532. 14 indexed citations
12.
Davda, Jasmine, et al.. (2014). A model-based meta-analysis of monoclonal antibody pharmacokinetics to guide optimal first-in-human study design. mAbs. 6(4). 1094–1102. 36 indexed citations
13.
Sims, Andrew H., Annelien J.M. Zweemer, Yoko Nagumo, et al.. (2012). Defining the molecular response to trastuzumab, pertuzumab and combination therapy in ovarian cancer. British Journal of Cancer. 106(11). 1779–1789. 38 indexed citations
14.
Faratian, Dana, Annelien J.M. Zweemer, Yoko Nagumo, et al.. (2011). Trastuzumab and Pertuzumab Produce Changes in Morphology and Estrogen Receptor Signaling in Ovarian Cancer Xenografts Revealing New Treatment Strategies. Clinical Cancer Research. 17(13). 4451–4461. 44 indexed citations
15.
Dodds, Michael, Klaus Stensgaard Frederiksen, Kresten Skak, et al.. (2008). Immune activation in advanced cancer patients treated with recombinant IL-21: multianalyte profiling of serum proteins. Cancer Immunology Immunotherapy. 58(6). 843–854. 21 indexed citations
16.
Guichard, Sylvie M., Janet S. Macpherson, Morwenna Muir, et al.. (2008). Gene expression predicts differential capecitabine metabolism, impacting on both pharmacokinetics and antitumour activity. European Journal of Cancer. 44(2). 310–317. 14 indexed citations
17.
Krudys, Kevin, et al.. (2005). Integrated model of hepatic and peripheral glucose regulation for estimation of endogenous glucose production during the hot IVGTT. American Journal of Physiology-Endocrinology and Metabolism. 288(5). E1038–E1046. 22 indexed citations
18.
Guichard, Sylvie M., R. W. Else, Benjamin D. Zeitlin, et al.. (2005). Anti-tumour activity in non-small cell lung cancer models and toxicity profiles for novel ruthenium(II) based organo-metallic compounds. Biochemical Pharmacology. 71(4). 408–415. 71 indexed citations
19.
Dodds, Michael & Paolo Vicini. (2004). Assessing Convergence of Markov Chain Monte Carlo Simulations in Hierarchical Bayesian Models for Population Pharmacokinetics. Annals of Biomedical Engineering. 32(9). 1300–1313. 14 indexed citations
20.
Hooker, Andrew C., Marco Foracchia, Michael Dodds, & Paolo Vicini. (2003). An Evaluation of Population D-Optimal Designs Via Pharmacokinetic Simulations. Annals of Biomedical Engineering. 31(1). 98–111. 22 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

Breakdown of academic impact, for papers by Manuel Román Breakdown of academic impact, for papers by Sunita J. Shukla Breakdown of academic impact, for papers by J Brugmans Breakdown of academic impact, for papers by Kensuke Kobayashi Breakdown of academic impact, for papers by Kazuhisa Furuhama Breakdown of academic impact, for papers by Vijay Batra Breakdown of academic impact, for papers by Dirk Meijer Breakdown of academic impact, for papers by Leonid Kagan Breakdown of academic impact, for papers by Marc B. Bailie Breakdown of academic impact, for papers by Matthew W. Davis
Rankless by CCL
2026