Vijay Upreti

2.4k total citations · 1 hit paper
55 papers, 1.7k citations indexed

About

Vijay Upreti is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Vijay Upreti has authored 55 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Oncology, 16 papers in Molecular Biology and 10 papers in Immunology. Recurrent topics in Vijay Upreti's work include CAR-T cell therapy research (14 papers), Biosimilars and Bioanalytical Methods (9 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). Vijay Upreti is often cited by papers focused on CAR-T cell therapy research (14 papers), Biosimilars and Bioanalytical Methods (9 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). Vijay Upreti collaborates with scholars based in United States, Germany and Switzerland. Vijay Upreti's co-authors include Jan L. Wahlstrom, Natalie D. Eddington, Ming Zheng, Neil Parrott, Jan Snoeys, Tycho Heimbach, Yuan Chen, S D Hall, Christopher R. Gibson and Frank LaCreta and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Clinical Cancer Research.

In The Last Decade

Vijay Upreti

54 papers receiving 1.7k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Physiologically based pharmacokinetic modeling in drug discovery and development: A pharmaceutical industry perspective

2015 358 citations Yuan Chen, Vijay Upreti et al. Clinical Pharmacology & Therapeutics profile →

Peers

Countries citing papers authored by Vijay Upreti

Since Specialization

Citations

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

Fields of papers citing papers by Vijay Upreti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vijay Upreti

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	A novel Bayesian generative approach for estimating tumor dynamics from published studies 2024 ·CPT Pharmacometrics & Systems Pharmacology ·(unknown), (unknown), Jamie N. Connarn, (unknown), Vijay Upreti, Chih‐Wei Lin, Khamir Mehta	1
2	Considerations for Industry—Preparing for the FDA Model‐Informed Drug Development (MIDD) Paired Meeting Program 2024 ·Clinical Pharmacology & Therapeutics ·Gerald R. Galluppi, Malidi Ahamadi, (unknown), Nageshwar Budha, Ferdous Gheyas, Chi‐Chung Li, Yuan Chen, Anne‐Gaëlle Dosne, Niels Rode Kristensen, Mindy Magee, Mahesh N. Samtani, Vikram Sinha, Kunal S. Taskar, Vijay Upreti, Jianning Yang, Jack Cook	6
3	Predicting Clinical Pharmacokinetics/Pharmacodynamics and Impact of Organ Impairment on siRNA‐Based Therapeutics Using a Mechanistic Physiologically‐Based Pharmacokinetic‐Pharmacodynamic Model 2024 ·Clinical Pharmacology & Therapeutics ·Annie Lumen, (unknown), Sandeep Dutta, Vijay Upreti	4
4	An IQ Consortium Perspective on Best Practices for Bioanalytical and Immunogenicity Assessment Aspects of CAR‐T and TCR‐T Cellular Therapies Development 2023 ·Clinical Pharmacology & Therapeutics ·Jochem Gokemeijer, (unknown), K. OGASAWARA, (unknown), Vijay Upreti, Hardik Mody, Siddha Kasar, Venkata R. Vepachedu, Weifeng Xu, Swati Gupta, Edit Tarcsa, Robert Dodge, (unknown), Tong‐Yuan Yang, Sophie Tourdot, Vibha Jawa	2
5	Mechanistic Pharmacokinetic/Pharmacodynamic Modeling in Support of a Patient-Convenient, Longer Dosing Interval for Carfilzomib, a Covalent Inhibitor of the Proteasome 2023 ·Clinical Pharmacokinetics ·(unknown), Khamir Mehta, (unknown), (unknown), Vivek S. Chopra, Sandeep Dutta, Vijay Upreti	4
6	Immunogenicity assessment of AAV-based gene therapies: An IQ consortium industry white paper 2022 ·Molecular Therapy — Methods & Clinical Development ·Tong‐Yuan Yang, Manuela Braun, (unknown), Fraser McBlane, John Kamerud, Stephen DeWall, Edit Tarcsa, Xiaodong Fang, (unknown), Uma Kavita, Vijay Upreti, Swati Gupta, (unknown), (unknown), (unknown), Kay‐Gunnar Stubenrauch, (unknown), Cindy Q. Xia, Vibha Jawa	48
7	A Phase 1 First in Human (FIH) Study of AMG 701, an Anti-B-Cell Maturation Antigen (BCMA) Half-Life Extended (HLE) BiTE® (bispecific T-cell engager) Molecule, in Relapsed/Refractory (RR) Multiple Myeloma (MM) 2020 ·Blood ·Simon J. Harrison, Monique C. Minnema, Hans C. Lee, Andrew Spencer, Prashant Kapoor, Deepu Madduri, Jeremy T. Larsen, Sikander Ailawadhi, Jonathan L. Kaufman, Marc S. Raab, Parameswaran Hari, Shinsuke Iida, Ravi Vij, Faith E. Davies, Robin Lesley, Vijay Upreti, Zhao Yang, Anjali Sharma, Alex C. Minella, Suzanne Lentzsch	100
8	Safety, tolerability, and pharmacokinetics of anti-EGFRvIII antibody–drug conjugate AMG 595 in patients with recurrent malignant glioma expressing EGFRvIII 2019 ·Cancer Chemotherapy and Pharmacology ·Mark Rosenthal, Richard Curry, David A. Reardon, Erik Rasmussen, Vijay Upreti, Michael A. Damore, Haby Henary, John S. Hill, Timothy F. Cloughesy	45
9	Dose escalation results from a first-in-human, phase 1 study of glucocorticoid-induced TNF receptor–related protein agonist AMG 228 in patients with advanced solid tumors 2018 ·Journal for ImmunoTherapy of Cancer ·Ben Tran, Richard D. Carvajal, Aurélien Marabelle, Sandip Pravin Patel, Patricia LoRusso, Erik Rasmussen, Gloria Juan, Vijay Upreti, Courtney Beers, Gataree Ngarmchamnanrith, Patrick Schöffski	62
10	Bioequivalence of Saxagliptin/Metformin Immediate Release (IR) Fixed-Dose Combination Tablets and Single-Component Saxagliptin and Metformin IR Tablets in Healthy Adult Subjects 2013 ·Clinical Drug Investigation ·Vijay Upreti, (unknown), David W. Boulton, Ming Chang, Li Li, Angela Tang, (unknown), (unknown), Ernst U. Frevert, Frank LaCreta	15
11	Effect of famotidine on the pharmacokinetics of apixaban, an oral direct factor Xa inhibitor 2013 ·Clinical Pharmacology Advances and Applications ·Vijay Upreti, Song, Wang, (unknown), (unknown), (unknown), (unknown), (unknown)	35
12	Biowaiver Approach for Biopharmaceutics Classification System Class 3 Compound Metformin Hydrochloride Using In Silico Modeling 2012 ·Journal of Pharmaceutical Sciences ·John R. Crison, Peter Timmins, Anther Keung, Vijay Upreti, David W. Boulton, (unknown)	35
13	Effect of rifampicin on the pharmacokinetics and pharmacodynamics of saxagliptin, a dipeptidyl peptidase‐4 inhibitor, in healthy subjects 2011 ·British Journal of Clinical Pharmacology ·Vijay Upreti, David W. Boulton, Li Li, (unknown), Hong Su, Frank LaCreta, Chirag G. Patel	22
14	Mechanisms of MDMA (Ecstasy)-Induced Oxidative Stress, Mitochondrial Dysfunction, and Organ Damage 2010 ·Current Pharmaceutical Biotechnology ·Byoung‐Joon Song, Kwan–Hoon Moon, Vijay Upreti, Natalie D. Eddington, Insong J. Lee	52
15	Increased oxidative‐modifications of cytosolic proteins in 3,4‐methylenedioxymethamphetamine (MDMA, ecstasy)‐exposed rat liver 2010 ·PROTEOMICS ·Vijay Upreti, Kwan–Hoon Moon, Li‐Rong Yu, Insong J. Lee, Natalie D. Eddington, Xiaoying Ye, Timothy D. Veenstra, Byoung‐Joon Song	18
16	Mechanism of 3,4‐methylenedioxymethamphetamine (MDMA, ecstasy)‐mediated mitochondrial dysfunction in rat liver 2008 ·PROTEOMICS ·Kwan–Hoon Moon, Vijay Upreti, Li‐Rong Yu, Insong J. Lee, Xiaoying Ye, Natalie D. Eddington, Timothy D. Veenstra, Byoung‐Joon Song	51
17	Determination of endogenous glycosaminoglycans derived disaccharides in human plasma by HPLC: Validation and application in a clinical study 2005 ·Journal of Chromatography B ·Vijay Upreti, (unknown), Donna S. Cox, Natalie D. Eddington	13
18	Safety, Tolerability, and Pharmacokinetics of a Capsule Formulation of DRF‐1042, a Novel Camptothecin Analog, in Refractory Cancer Patients in a Bridging Phase I Study 2005 ·The Journal of Clinical Pharmacology ·(unknown), Raghunadharao Digumarti, Kasiram Katneni, Vijay Upreti, Rao N. V. S. Mamidi, Ramesh Mullangi, (unknown), (unknown), (unknown), (unknown), Nuggehally R. Srinivas	11
19	Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of an Orally Active Novel Camptothecin Analog, DRF‐1042, in Refractory Cancer Patients in a Phase I Dose Escalation Study 2004 ·The Journal of Clinical Pharmacology ·(unknown), Raghunadharao Digumarti, Rao N. V. S. Mamidi, Kasiram Katneni, Vijay Upreti, (unknown), (unknown), (unknown), (unknown), Swaminathan Subramaniam, Nuggehally R. Srinivas	12
20	Quantitative determination of DRF‐1042 in human plasma by HPLC: validation and application in clinical pharmacokinetics 2003 ·Biomedical Chromatography ·Vijay Upreti, Rao N. V. S. Mamidi, Kasiram Katneni, Nuggehally R. Srinivas	8

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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