Archana Khosa

806 total citations · 1 hit paper
9 papers, 516 citations indexed

About

Archana Khosa is a scholar working on Biomaterials, Pharmaceutical Science and Molecular Biology. According to data from OpenAlex, Archana Khosa has authored 9 papers receiving a total of 516 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Biomaterials, 4 papers in Pharmaceutical Science and 3 papers in Molecular Biology. Recurrent topics in Archana Khosa's work include Nanoparticle-Based Drug Delivery (5 papers), Advanced Drug Delivery Systems (3 papers) and Advancements in Transdermal Drug Delivery (2 papers). Archana Khosa is often cited by papers focused on Nanoparticle-Based Drug Delivery (5 papers), Advanced Drug Delivery Systems (3 papers) and Advancements in Transdermal Drug Delivery (2 papers). Archana Khosa collaborates with scholars based in India and United Arab Emirates. Archana Khosa's co-authors include Satish Reddi, Ranendra Narayan Saha, Sunil Kumar Dubey, Ranendra Narayan Saha, Gautam Singhvi, Vamshi Krishna Rapalli, Srividya Gorantla, Tejashree Waghule, Kowthavarapu Venkata Krishna and Saswata Banerjee and has published in prestigious journals such as Biomedicine & Pharmacotherapy, Methods in molecular biology and Journal of Liposome Research.

In The Last Decade

Archana Khosa

8 papers receiving 502 citations

Hit Papers

Nanostructured lipid carr... 2018 2026 2020 2023 2018 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Archana Khosa India 5 281 200 112 78 62 9 516
Satish Reddi India 6 285 1.0× 198 1.0× 105 0.9× 77 1.0× 55 0.9× 8 511
Nishika Yadav India 5 245 0.9× 200 1.0× 136 1.2× 88 1.1× 79 1.3× 6 532
Iti Chauhan India 8 363 1.3× 193 1.0× 119 1.1× 87 1.1× 46 0.7× 35 613
Neha Mallick India 9 266 0.9× 184 0.9× 139 1.2× 60 0.8× 58 0.9× 11 602
Jessy Shaji India 12 292 1.0× 158 0.8× 89 0.8× 53 0.7× 37 0.6× 38 511
Srinivas Reddy Jitta India 12 287 1.0× 194 1.0× 110 1.0× 77 1.0× 39 0.6× 17 578
Pedzisai A. Makoni South Africa 11 202 0.7× 148 0.7× 115 1.0× 64 0.8× 77 1.2× 17 514
Reza Mahjub Iran 16 258 0.9× 255 1.3× 112 1.0× 102 1.3× 111 1.8× 43 708
Shady A. Swidan Egypt 14 243 0.9× 141 0.7× 90 0.8× 52 0.7× 62 1.0× 29 527
Mona Qushawy Saudi Arabia 17 330 1.2× 170 0.8× 90 0.8× 73 0.9× 44 0.7× 33 628

Countries citing papers authored by Archana Khosa

Since Specialization
Citations

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

Fields of papers citing papers by Archana Khosa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Archana Khosa

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

All Works

9 of 9 papers shown
1.
Javed, Muhammad Aqib, et al.. (2024). Performance of MT-I spherical tokamak with upgraded power supplies. Radiation effects and defects in solids. 179(11-12). 1683–1696.
2.
Waghule, Tejashree, Vamshi Krishna Rapalli, Gautam Singhvi, et al.. (2020). Design of temozolomide-loaded proliposomes and lipid crystal nanoparticles with industrial feasible approaches: comparative assessment of drug loading, entrapment efficiency, and stability at plasma pH. Journal of Liposome Research. 31(2). 158–168. 44 indexed citations
3.
Khosa, Archana, Kowthavarapu Venkata Krishna, Sunil Kumar Dubey, & Ranendra Narayan Saha. (2019). Lipid Nanocarriers for Enhanced Delivery of Temozolomide to the Brain. Methods in molecular biology. 2059. 285–298. 13 indexed citations
4.
Khosa, Archana, Gautam Singhvi, Ranendra Narayan Saha, & Gaurav Gupta. (2018). Drug delivery to the CNS. Panminerva Medica. 60(4). 226–226. 4 indexed citations
5.
Khosa, Archana, et al.. (2018). Simple, Rapid and Sensitive UV Spectrophotometric Method for Determination of Temozolomide in Poly-ε-caprolactone Nanoparticles. Asian Journal of Chemistry. 30(4). 868–872. 3 indexed citations
6.
Khosa, Archana, Satish Reddi, & Ranendra Narayan Saha. (2018). Nanostructured lipid carriers for site-specific drug delivery. Biomedicine & Pharmacotherapy. 103. 598–613. 432 indexed citations breakdown →
7.
Khosa, Archana, Kowthavarapu Venkata Krishna, Ranendra Narayan Saha, Sunil Kumar Dubey, & Satish Reddi. (2018). A simplified and sensitive validated RP-HPLC method for determination of temozolomide in rat plasma and its application to a pharmacokinetic study. Journal of Liquid Chromatography & Related Technologies. 41(10). 692–697. 11 indexed citations
9.
Banerjee, Saswata, Gautam Singhvi, & Archana Khosa. (2017). In vitro Lipolysis: An Indispensable Tool for the Development of IVIVC of Lipid Based Drug Delivery Systems. Drug Delivery Letters. 7(3). 2 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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