Michael Vicchiarelli

682 total citations
17 papers, 349 citations indexed

About

Michael Vicchiarelli is a scholar working on Pharmacology, Epidemiology and Molecular Biology. According to data from OpenAlex, Michael Vicchiarelli has authored 17 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Pharmacology, 7 papers in Epidemiology and 6 papers in Molecular Biology. Recurrent topics in Michael Vicchiarelli's work include Antibiotic Resistance in Bacteria (6 papers), Antibiotics Pharmacokinetics and Efficacy (6 papers) and Tuberculosis Research and Epidemiology (2 papers). Michael Vicchiarelli is often cited by papers focused on Antibiotic Resistance in Bacteria (6 papers), Antibiotics Pharmacokinetics and Efficacy (6 papers) and Tuberculosis Research and Epidemiology (2 papers). Michael Vicchiarelli collaborates with scholars based in United States and Colombia. Michael Vicchiarelli's co-authors include Layton H. Smith, Arianna Mangravita-Novo, Brock Brown, Eduard Sergienko, George L. Drusano, Arnold Louie, Russell Dahl, Michael S. Maynard, Li Yang and Nicholas D. P. Cosford and has published in prestigious journals such as Journal of Medicinal Chemistry, Antimicrobial Agents and Chemotherapy and Frontiers in Pharmacology.

In The Last Decade

Michael Vicchiarelli

15 papers receiving 345 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 Vicchiarelli United States 10 121 67 64 61 57 17 349
Thomas Kenney United States 12 136 1.1× 61 0.9× 64 1.0× 84 1.4× 24 0.4× 22 437
Seema Husain United States 12 219 1.8× 27 0.4× 152 2.4× 42 0.7× 20 0.4× 21 511
Sara Paccosi Italy 14 132 1.1× 20 0.3× 84 1.3× 20 0.3× 17 0.3× 28 433
Lidong Liu China 9 172 1.4× 24 0.4× 58 0.9× 44 0.7× 8 0.1× 12 319
Li Zha United States 11 329 2.7× 122 1.8× 18 0.3× 15 0.2× 18 0.3× 21 523
Yu‐Ning Juan Taiwan 9 108 0.9× 29 0.4× 31 0.5× 16 0.3× 14 0.2× 11 245
Óscar H. Martínez-Costa Spain 14 324 2.7× 72 1.1× 36 0.6× 15 0.2× 39 0.7× 28 514
Hongbo Xu China 12 272 2.2× 47 0.7× 68 1.1× 9 0.1× 11 0.2× 31 540
Lauren Wu United States 10 150 1.2× 13 0.2× 127 2.0× 37 0.6× 9 0.2× 11 397

Countries citing papers authored by Michael Vicchiarelli

Since Specialization
Citations

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

Fields of papers citing papers by Michael Vicchiarelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Vicchiarelli

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Vicchiarelli. A scholar is included among the top collaborators of Michael Vicchiarelli 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 Vicchiarelli. Michael Vicchiarelli 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.
Jiao, Yuanyuan, Jun Yan, Dhruvitkumar S. Sutaria, et al.. (2024). Population pharmacokinetics and humanized dosage regimens matching the peak, area, trough, and range of amikacin plasma concentrations in immune-competent murine bloodstream and lung infection models. Antimicrobial Agents and Chemotherapy. 68(3). e0139423–e0139423.
2.
Heine, Henry S., Bret K. Purcell, A. R. Chase, et al.. (2024). Evaluation of a potent LpxC inhibitor for post-exposure prophylaxis treatment of antibiotic-resistant Burkholderia pseudomallei in a murine infection model. Antimicrobial Agents and Chemotherapy. 69(1). e0129524–e0129524.
3.
Jiao, Yuanyuan, Jun Yan, Michael Vicchiarelli, et al.. (2023). Individual Components of Polymyxin B Modeled via Population Pharmacokinetics to Design Humanized Dosage Regimens for a Bloodstream and Lung Infection Model in Immune-Competent Mice. Antimicrobial Agents and Chemotherapy. 67(5). e0019723–e0019723. 5 indexed citations
4.
Drusano, George L., Robert A. Bonomo, Laura J. Rojas, et al.. (2021). Emergence of Resistance to Ceftazidime-Avibactam in a Pseudomonas aeruginosa Isolate Producing Derepressed bla PDC in a Hollow-Fiber Infection Model. Antimicrobial Agents and Chemotherapy. 65(6). 9 indexed citations
5.
Maynard, Michael S., George L. Drusano, Michael Vicchiarelli, et al.. (2021). Polymyxin B Pharmacodynamics in the Hollow-Fiber Infection Model: What You See May Not Be What You Get. Antimicrobial Agents and Chemotherapy. 65(8). e0185320–e0185320. 5 indexed citations
6.
Drusano, George L., Charles A. Scanga, Sarah Kim, et al.. (2020). Developing New Drugs for Mycobacterium tuberculosis Therapy: What Information Do We Get from Preclinical Animal Models?. Antimicrobial Agents and Chemotherapy. 64(12). 2 indexed citations
7.
Louie, Arnold, et al.. (2018). Determination of the Dynamically Linked Indices of Fosfomycin for Pseudomonas aeruginosa in the Hollow Fiber Infection Model. Antimicrobial Agents and Chemotherapy. 62(6). 21 indexed citations
8.
Drusano, George L., Michael Neely, Walter M. Yamada, et al.. (2018). The Combination of Fosfomycin plus Meropenem Is Synergistic for Pseudomonas aeruginosa PAO1 in a Hollow-Fiber Infection Model. Antimicrobial Agents and Chemotherapy. 62(12). 38 indexed citations
9.
Tao, Xun, Tae‐Hwan Kim, Michael Vicchiarelli, et al.. (2018). Clinical Regimens of Favipiravir Inhibit Zika Virus Replication in the Hollow-Fiber Infection Model. Antimicrobial Agents and Chemotherapy. 62(9). 23 indexed citations
10.
11.
Hershberger, Paul, Michael P. Hedrick, Satyamaheshwar Peddibhotla, et al.. (2013). Imidazole-derived agonists for the neurotensin 1 receptor. Bioorganic & Medicinal Chemistry Letters. 24(1). 262–267. 14 indexed citations
12.
Vicchiarelli, Michael, et al.. (2012). In Vivo Rapid Assessment of Compound Exposure (RACE) for Profiling the Pharmacokinetics of Novel Chemical Probes. PubMed. 4(4). 299–309. 5 indexed citations
13.
Dahl, Russell, Vandana Sharma, Mie Ichikawa, et al.. (2011). Potent, Selective, and Orally Available Benzoisothiazolone Phosphomannose Isomerase Inhibitors as Probes for Congenital Disorder of Glycosylation Ia. Journal of Medicinal Chemistry. 54(10). 3661–3668. 40 indexed citations
14.
Correa, Ricardo G., Daniela Divlianska, Satyamaheshwar Peddibhotla, et al.. (2011). Identification of Inhibitors of NOD1-Induced Nuclear Factor-κB Activation. ACS Medicinal Chemistry Letters. 2(10). 780–785. 47 indexed citations
15.
Heynen‐Genel, Susanne, Russell Dahl, Shenghua Shi, et al.. (2011). Screening for Selective Ligands for GPR55 - Antagonists. Europe PMC (PubMed Central). 23 indexed citations
16.
Peddibhotla, Satyamaheshwar, Ranxin Shi, Layton H. Smith, et al.. (2010). Inhibition of Protein Kinase C-Driven Nuclear Factor-κB Activation: Synthesis, Structure−Activity Relationship, and Pharmacological Profiling of Pathway Specific Benzimidazole Probe Molecules. Journal of Medicinal Chemistry. 53(12). 4793–4797. 16 indexed citations
17.
Dahl, Russell, Eduard Sergienko, Ying Su, et al.. (2009). Discovery and Validation of a Series of Aryl Sulfonamides as Selective Inhibitors of Tissue-Nonspecific Alkaline Phosphatase (TNAP). Journal of Medicinal Chemistry. 52(21). 6919–6925. 93 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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