Vaishali Dixit

796 total citations
18 papers, 579 citations indexed

About

Vaishali Dixit is a scholar working on Oncology, Molecular Biology and Pharmacology. According to data from OpenAlex, Vaishali Dixit has authored 18 papers receiving a total of 579 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 7 papers in Molecular Biology and 5 papers in Pharmacology. Recurrent topics in Vaishali Dixit's work include Drug Transport and Resistance Mechanisms (5 papers), Pharmacogenetics and Drug Metabolism (5 papers) and Advanced Breast Cancer Therapies (2 papers). Vaishali Dixit is often cited by papers focused on Drug Transport and Resistance Mechanisms (5 papers), Pharmacogenetics and Drug Metabolism (5 papers) and Advanced Breast Cancer Therapies (2 papers). Vaishali Dixit collaborates with scholars based in United States, United Kingdom and Japan. Vaishali Dixit's co-authors include Niresh Hariparsad, Jashvant D. Unadkat, Pankaj B. Desai, Kenneth E. Thummel, Fang Li, Jan Snoeys, Helen Tsao, Ming Zheng, Ann C. Collier and Dale Whittington and has published in prestigious journals such as Blood, The Journal of Immunology and Cancer Research.

In The Last Decade

Vaishali Dixit

17 papers receiving 568 citations

Peers

Vaishali Dixit
Rucha Sane United States
Justin D. Lutz United States
Mohamad Shebley United States
Takenori Niioka Japan
Sarah Shugarts United States
Aaron M. Moss United States
Poe‐Hirr Hsyu United States
Daniel A.J. Bow United States
Niresh Hariparsad United States
Rucha Sane United States
Vaishali Dixit
Citations per year, relative to Vaishali Dixit Vaishali Dixit (= 1×) peers Rucha Sane

Countries citing papers authored by Vaishali Dixit

Since Specialization
Citations

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

Fields of papers citing papers by Vaishali Dixit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vaishali Dixit

This figure shows the co-authorship network connecting the top 25 collaborators of Vaishali Dixit. A scholar is included among the top collaborators of Vaishali Dixit 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 Vaishali Dixit. Vaishali Dixit 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.
Kumar, Niyanta, Vaishali Dixit, Howard Burt, et al.. (2025). PBPK Modeling to Predict Clinical Drug–Drug Interaction and Impact of Hepatic Impairment for an ADC With the Payload Auristatin F‐Hydroxypropylamide. CPT Pharmacometrics & Systems Pharmacology. 14(10). 1661–1672.
2.
Dixit, Vaishali, et al.. (2024). Emerging strategies for synthesis of heterocyclic compounds enabled by titanium oxide nanoparticles as heterogeneous catalyst. Tetrahedron. 160. 134039–134039. 7 indexed citations
3.
Schalm, Stefanie S., Yogesh K. Chutake, Susanne B. Breitkopf, et al.. (2023). P464: PULSE DOSING OF POTENT AND SELECTIVE HETEROBIFUNCTIONAL MDM2 DEGRADER KT-253 DRIVES TUMOR REGRESSION AND DEMONSTRATES DIFFERENTIATED PHARMACOLOGY COMPARED TO P53/MDM2 SMALL MOLECULE INHIBITORS.. HemaSphere. 7(S3). e9022892–e9022892. 1 indexed citations
4.
Sullivan, Jeffrey, Crystal Brown, Michele Mayo, et al.. (2022). STAT3 degraders inhibit cellular activation, cytokine production, and Th17 development, resulting in inhibition of autoimmunity in the MOG-EAE model of CNS inflammation.. The Journal of Immunology. 208(Supplement_1). 60.07–60.07. 1 indexed citations
5.
Huang, Kang, Dinesh Chandra, Shannon McGrath, et al.. (2022). Pharmacologic Activation of STING in the Bladder Induces Potent Antitumor Immunity in Non-Muscle Invasive Murine Bladder Cancer.. PubMed. 21(6). 914–924. 13 indexed citations
6.
Dixit, Vaishali, Michele Mayo, Joyoti Dey, et al.. (2021). A First-in-Class STAT3 Degrader KT-333 in Development for Treatment of Hematologic Cancers. Blood. 138(Supplement 1). 1865–1865. 14 indexed citations
7.
8.
Plummer, Ruth, Nicola Cresti, Yvette Drew, et al.. (2020). First-in-human study of the PARP/tankyrase inhibitor E7449 in patients with advanced solid tumours and evaluation of a novel drug-response predictor. British Journal of Cancer. 123(4). 525–533. 57 indexed citations
9.
Heimbach, Tycho, Yuan Chen, Jun Chen, et al.. (2020). Physiologically‐Based Pharmacokinetic Modeling in Renal and Hepatic Impairment Populations: A Pharmaceutical Industry Perspective. Clinical Pharmacology & Therapeutics. 110(2). 297–310. 91 indexed citations
10.
Huang, Kuan‐Chun, Chi Zhang, Kun Yu, et al.. (2020). Abstract 592: Demonstration of E7766, a novel STING agonist, as a potent immunotherapy in BCG-insensitive non-muscle invasive bladder cancer models via intravesical administration. Cancer Research. 80(16_Supplement). 592–592. 7 indexed citations
11.
Taskar, Kunal S., Venkatesh Pilla Reddy, Howard Burt, et al.. (2019). Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations. Clinical Pharmacology & Therapeutics. 107(5). 1082–1115. 110 indexed citations
12.
Hao, Ming‐Hong, et al.. (2018). Celecoxib is a substrate of CYP2D6: Impact on celecoxib metabolism in individuals with CYP2C9*3 variants. Drug Metabolism and Pharmacokinetics. 33(5). 219–227. 21 indexed citations
13.
Kolber‐Simonds, Donna, Jiayi Wu, Utpal Majumder, et al.. (2018). Abstract 3961: Role for neuropilin1 in mode of action of chlorotoxin. Cancer Research. 78(13_Supplement). 3961–3961. 1 indexed citations
14.
Dixit, Vaishali, et al.. (2015). Application of Micropatterned Cocultured Hepatocytes to Evaluate the Inductive Potential and Degradation Rate of Major Xenobiotic Metabolizing Enzymes. Drug Metabolism and Disposition. 44(2). 250–261. 38 indexed citations
15.
O’Dowd, Hardwin, Dean Shannon, Vaishali Dixit, et al.. (2015). Discovery and Characterization of a Water-Soluble Prodrug of a Dual Inhibitor of Bacterial DNA Gyrase and Topoisomerase IV. ACS Medicinal Chemistry Letters. 6(7). 822–826. 19 indexed citations
16.
Dixit, Vaishali, et al.. (2013). Epilepsy - A Comprehensive Review. 2(12). 17 indexed citations
17.
Kirby, Brian, Ann C. Collier, Evan D. Kharasch, et al.. (2011). Complex Drug Interactions of HIV Protease Inhibitors 2: In Vivo Induction and In Vitro to In Vivo Correlation of Induction of Cytochrome P450 1A2, 2B6, and 2C9 by Ritonavir or Nelfinavir. Drug Metabolism and Disposition. 39(12). 2329–2337. 58 indexed citations
18.
Dixit, Vaishali, Niresh Hariparsad, Fang Li, et al.. (2007). Cytochrome P450 Enzymes and Transporters Induced by Anti-Human Immunodeficiency Virus Protease Inhibitors in Human Hepatocytes: Implications for Predicting Clinical Drug Interactions. Drug Metabolism and Disposition. 35(10). 1853–1859. 121 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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