Kosalaram Goteti

755 total citations
32 papers, 489 citations indexed

About

Kosalaram Goteti is a scholar working on Immunology, Pharmacology and Molecular Biology. According to data from OpenAlex, Kosalaram Goteti has authored 32 papers receiving a total of 489 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Immunology, 8 papers in Pharmacology and 7 papers in Molecular Biology. Recurrent topics in Kosalaram Goteti's work include Pharmacogenetics and Drug Metabolism (7 papers), Lung Cancer Treatments and Mutations (6 papers) and Cancer therapeutics and mechanisms (5 papers). Kosalaram Goteti is often cited by papers focused on Pharmacogenetics and Drug Metabolism (7 papers), Lung Cancer Treatments and Mutations (6 papers) and Cancer therapeutics and mechanisms (5 papers). Kosalaram Goteti collaborates with scholars based in United States, Germany and Switzerland. Kosalaram Goteti's co-authors include Iftekhar Mahmood, Christopher Banfield, C. Edwin Garner, Elena Peeva, Patrick Brassil, Elizabeth Kieras, Weidong Zhang, Karen Page, Matthew Scaramozza and Michael S. Vincent and has published in prestigious journals such as Cancer Research, Kidney International and Journal of Medicinal Chemistry.

In The Last Decade

Kosalaram Goteti

31 papers receiving 476 citations

Peers

Kosalaram Goteti
Anjaneya Chimalakonda United States
Raja Velagapudi United States
Tarundeep Kakkar United States
Parnian Zia‐Amirhosseini United States
Mukul Minocha United States
Shunji Matsuki Japan
Montserrat Briz Spain
Dennis A. Noe United States
Brian P. Monahan United States
Kourosh Parivar United States
Anjaneya Chimalakonda United States
Kosalaram Goteti
Citations per year, relative to Kosalaram Goteti Kosalaram Goteti (= 1×) peers Anjaneya Chimalakonda

Countries citing papers authored by Kosalaram Goteti

Since Specialization
Citations

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

Fields of papers citing papers by Kosalaram Goteti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kosalaram Goteti

This figure shows the co-authorship network connecting the top 25 collaborators of Kosalaram Goteti. A scholar is included among the top collaborators of Kosalaram Goteti 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 Kosalaram Goteti. Kosalaram Goteti 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
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Lü, Hong, Jatinder Kaur Mukker, Jayaprakasam Bolleddula, et al.. (2024). Asia‐inclusive drug development leveraging principles of ICH E5 and E17 guidelines: Case studies illustrating quantitative clinical pharmacology as a foundational enabler. Clinical and Translational Science. 17(10). e70050–e70050. 1 indexed citations
3.
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Gopalakrishnan, Sathej, Özkan Yalkinoglu, Hong Lü, et al.. (2024). Asia‐Inclusive Global Development of Enpatoran: Results of an Ethno‐Bridging Study, Intrinsic/Extrinsic Factor Assessments and Disease Trajectory Modeling to Inform Design of a Phase II Multiregional Clinical Trial. Clinical Pharmacology & Therapeutics. 115(6). 1346–1357. 13 indexed citations
5.
Sawant‐Basak, Aarti, Shweta Urva, Jatinder Kaur Mukker, et al.. (2024). Role of Clinical Pharmacology in Diversity and Inclusion in Global Drug Development: Current Practices and Industry Perspectives: White Paper. Clinical Pharmacology & Therapeutics. 116(4). 902–913. 2 indexed citations
6.
Goteti, Kosalaram, William R. Gillespie, Jonathan French, et al.. (2023). Model‐based meta‐analysis using latent variable modeling to set benchmarks for new treatments of systemic lupus erythematosus. CPT Pharmacometrics & Systems Pharmacology. 13(2). 281–295. 6 indexed citations
7.
Goteti, Kosalaram, Mindy Magee, Sven Mensing, et al.. (2023). Opportunities and Challenges of Disease Progression Modeling in Drug Development – An IQ Perspective. Clinical Pharmacology & Therapeutics. 114(2). 266–274. 5 indexed citations
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Nyberg, Joakim, Orestis Papasouliotis, Andreas Johne, et al.. (2022). Exposure–response analyses for the MET inhibitor tepotinib including patients in the pivotal VISION trial: support for dosage recommendations. Cancer Chemotherapy and Pharmacology. 90(1). 53–69. 8 indexed citations
10.
Munafo, Alain, et al.. (2021). Optimization of dose selection using multiple surrogates of toxicity as a continuous variable in phase I cancer trial. Contemporary Clinical Trials. 113. 106657–106657. 2 indexed citations
11.
Gale, Jeremy D., Steven A. Gilbert, Samuel S. Blumenthal, et al.. (2018). Effect of PF-04634817, an Oral CCR2/5 Chemokine Receptor Antagonist, on Albuminuria in Adults with Overt Diabetic Nephropathy. Kidney International Reports. 3(6). 1316–1327. 38 indexed citations
12.
Banfield, Christopher, Matthew Scaramozza, Weidong Zhang, et al.. (2017). The Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of a TYK2/JAK1 Inhibitor (PF‐06700841) in Healthy Subjects and Patients With Plaque Psoriasis. The Journal of Clinical Pharmacology. 58(4). 434–447. 71 indexed citations
13.
Mahmood, Iftekhar & Kosalaram Goteti. (2013). Prediction of Drug Concentration–Time Profiles in Children From Adults. American Journal of Therapeutics. 22(2). 132–140.
14.
Shapiro, Adam B., et al.. (2013). Improvement of the Pharmacokinetics and In Vivo Antibacterial Efficacy of a Novel Type IIa Topoisomerase Inhibitor by Formulation in Liposomes. Antimicrobial Agents and Chemotherapy. 57(10). 4816–4824. 5 indexed citations
15.
Mahmood, Iftekhar & Kosalaram Goteti. (2012). Prediction of drug concentration-time data in humans from animals: a comparison of three methods. Xenobiotica. 42(8). 756–765. 5 indexed citations
16.
Goteti, Kosalaram, C. Edwin Garner, & Iftekhar Mahmood. (2009). Prediction of Human Drug Clearance from Two Species: A Comparison of Several Allometric Methods. Journal of Pharmaceutical Sciences. 99(3). 1601–1613. 12 indexed citations
17.
Goteti, Kosalaram, C. Edwin Garner, Jing Dai, et al.. (2009). Preclinical pharmacokinetic/pharmacodynamic models to predict synergistic effects of co-administered anti-cancer agents. Cancer Chemotherapy and Pharmacology. 66(2). 245–254. 26 indexed citations
18.
Goteti, Kosalaram, Patrick Brassil, Steven S. Good, & C. Edwin Garner. (2008). Estimation of Human Drug Clearance Using Multiexponential Techniques. The Journal of Clinical Pharmacology. 48(10). 1226–1236. 18 indexed citations
19.
Goteti, Kosalaram, et al.. (2006). Perivascular Tissue Pharmacokinetics of Dipyridamole. Pharmaceutical Research. 23(4). 718–728. 5 indexed citations
20.
Masaki, Takahisa, Kosalaram Goteti, Christi M. Terry, et al.. (2006). Efficacy of local dipyridamole therapy in a porcine model of arteriovenous graft stenosis. Kidney International. 69(12). 2179–2185. 26 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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