Satjit Brar
Impact in
- Pharmacology top 2%
- Pharmacogenetics and Drug Metabolism
- Antibiotics Pharmacokinetics and Efficacy
- Statistics and Probability top 5%
- Statistical Methods in Clinical Trials
Papers in
- Oncology 6
- Polyomavirus and related diseases 3
- Cancer Immunotherapy and Biomarkers 2
- Viral-associated cancers and disorders 2
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- Pharmaceutical studies and practices 3
- Co-authors
- Julie Bullock (2 shared papers)Joseph A. Grillo (2 shared papers)Rajanikanth Madabushi (1 shared paper)Young‐Jin Moon (1 shared paper)Pengfei Song (1 shared paper)Eva Gil Berglund (1 shared paper)B Booth (1 shared paper)K S Reynolds (1 shared paper)
- Journals
- Clinical Pharmacology & Therapeutics (3 papers)CPT Pharmacometrics & Systems Pharmacology (2 papers)Journal of Neurotrauma (2 papers)Clinical Pharmacokinetics (1 paper)Molecular Cancer Therapeutics (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Satjit Brar
15 papers receiving 873 citations
Satjit Brar's Hit Papers
Peers
Comparison fields: 5 of 93
- Pharmacology 197
- Statistics and Probability 121
- Oncology 255
- Genetics 79
- Pharmaceutical Science 48
Countries citing papers authored by Satjit Brar
This map shows the geographic impact of Satjit Brar'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 Satjit Brar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satjit Brar more than expected).
Fields of papers citing papers by Satjit Brar
This network shows the impact of papers produced by Satjit Brar. 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 Satjit Brar. The network helps show where Satjit Brar may publish in the future.
Co-authors
The 25 scholars most cited alongside Satjit Brar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Applications of Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation During Regulatory Review Hit paper breakdown → | 2010 | 437 |
| 2 | 2011 | 125 | |
| 3 | 2012 | 111 | |
| 4 | 2019 | 65 | |
| 5 | 2019 | 36 | |
| 6 | 2017 | 32 | |
| 7 | 2021 | 24 | |
| 8 | 2017 | 16 | |
| 9 | 2013 | 16 | |
| 10 | 2021 | 16 | |
| 11 | 2022 | 9 | |
| 12 | 2013 | 6 | |
| 13 | 2009 | 5 | |
| 14 | Brain penetration of Cyclosporin A in traumatic brain injury patients: a pharmacokinetic analysis | 2006 | 1 |
| 15 | 2021 | 1 |
About Satjit Brar
Satjit Brar is a scholar working on Oncology, Pediatrics, Perinatology and Child Health, Economics and Econometrics, Genetics and Pathology and Forensic Medicine, having authored 15 papers that have together received 900 indexed citations. Recurring topics across this work include Polyomavirus and related diseases (3 papers), Lymphoma Diagnosis and Treatment (3 papers), Pharmaceutical studies and practices (3 papers), Cancer Immunotherapy and Biomarkers (2 papers), Viral-associated cancers and disorders (2 papers), Pharmaceutical Economics and Policy (2 papers), Statistical Methods in Clinical Trials (2 papers) and Chronic Lymphocytic Leukemia Research (2 papers). The work is most often cited by research in Pharmacology (197 citations), Statistics and Probability (121 citations), Oncology (255 citations), Genetics (79 citations) and Pharmaceutical Science (48 citations). Satjit Brar has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Julie Bullock, Joseph A. Grillo, Rajanikanth Madabushi, Young‐Jin Moon, Pengfei Song, Eva Gil Berglund, B Booth, K S Reynolds, Ping Zhao and Ta C. Wu. Their work appears in journals such as Clinical Pharmacology & Therapeutics, CPT Pharmacometrics & Systems Pharmacology, Journal of Neurotrauma, Clinical Pharmacokinetics and Molecular Cancer Therapeutics.
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.