Binodh DeSilva

3.6k total citations
60 papers, 1.8k citations indexed

About

Binodh DeSilva is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Binodh DeSilva has authored 60 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Immunology, 38 papers in Molecular Biology and 28 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Binodh DeSilva's work include Biosimilars and Bioanalytical Methods (45 papers), Monoclonal and Polyclonal Antibodies Research (28 papers) and Advanced Biosensing Techniques and Applications (20 papers). Binodh DeSilva is often cited by papers focused on Biosimilars and Bioanalytical Methods (45 papers), Monoclonal and Polyclonal Antibodies Research (28 papers) and Advanced Biosensing Techniques and Applications (20 papers). Binodh DeSilva collaborates with scholars based in United States, Germany and Sweden. Binodh DeSilva's co-authors include Marian Kelley, W. Smith, Masood N. Khan, I. Das, John W. A. Findlay, Gerald D. Nordblom, Ronald R. Bowsher, Russell Weiner, Benjamin Lee and Masood Mehmood Khan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Analytical Chemistry and Journal of Controlled Release.

In The Last Decade

Binodh DeSilva

60 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Binodh DeSilva United States 17 1.0k 957 669 205 198 60 1.8k
Chad Ray United States 14 558 0.5× 453 0.5× 208 0.3× 83 0.4× 143 0.7× 23 1.1k
Wendell C. Smith United States 10 591 0.6× 716 0.7× 511 0.8× 81 0.4× 178 0.9× 13 1.2k
Rob Webster United Kingdom 17 705 0.7× 270 0.3× 167 0.2× 65 0.3× 267 1.3× 26 2.1k
Leonid Kagan United States 24 468 0.5× 175 0.2× 185 0.3× 122 0.6× 235 1.2× 87 1.6k
Steve Elliott United States 24 845 0.8× 372 0.4× 282 0.4× 169 0.8× 294 1.5× 39 2.0k
Simon Parry United Kingdom 16 545 0.5× 400 0.4× 112 0.2× 103 0.5× 63 0.3× 29 981
Hélène Diemer France 25 938 0.9× 232 0.2× 280 0.4× 175 0.9× 178 0.9× 59 1.7k
Ziping Yang United States 21 944 0.9× 194 0.2× 218 0.3× 74 0.4× 455 2.3× 45 1.7k
James L. Weaver United States 23 530 0.5× 306 0.3× 91 0.1× 222 1.1× 231 1.2× 75 1.6k
Anthony J. Leathem United Kingdom 25 944 0.9× 431 0.5× 223 0.3× 29 0.1× 285 1.4× 53 1.7k

Countries citing papers authored by Binodh DeSilva

Since Specialization
Citations

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

Fields of papers citing papers by Binodh DeSilva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Binodh DeSilva

This figure shows the co-authorship network connecting the top 25 collaborators of Binodh DeSilva. A scholar is included among the top collaborators of Binodh DeSilva 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 Binodh DeSilva. Binodh DeSilva 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
1.
Hamuro, Lora, Giridhar Tirucherai, Akbar Nayeem, et al.. (2019). Evaluating a Multiscale Mechanistic Model of the Immune System to Predict Human Immunogenicity for a Biotherapeutic in Phase 1. The AAPS Journal. 21(5). 94–94. 14 indexed citations
2.
Myler, Heather, Boris Gorovits, Viswanath Devanarayan, et al.. (2019). Report on the AAPS Immunogenicity Guidance Forum. The AAPS Journal. 21(4). 55–55. 14 indexed citations
3.
Xu, Weifeng, Jennifer Cummings, Stephen M. Carl, et al.. (2018). Bead-extraction and heat-dissociation (BEHD): A novel way to overcome drug and matrix interference in immunogenicity testing. Journal of Immunological Methods. 462. 34–41. 14 indexed citations
4.
Liu, Rong, Shannon Chilewski, Uma Kavita, et al.. (2016). Accelerating Regulated Bioanalysis for Biotherapeutics: Case Examples Using a Microfluidic Ligand Binding Assay Platform. The AAPS Journal. 19(1). 82–91. 4 indexed citations
5.
Zhao, Yue, Guowen Liu, Lora Hamuro, et al.. (2015). Development and validation of a liquid chromatography tandem mass spectrometry assay for the quantitation of a protein therapeutic in cynomolgus monkey serum. Journal of Chromatography B. 988. 81–87. 8 indexed citations
6.
Dong, Huijin, et al.. (2015). Development of a Generic Anti-PEG Antibody Assay Using BioScale’s Acoustic Membrane MicroParticle Technology. The AAPS Journal. 17(6). 1511–1516. 16 indexed citations
7.
Chimalakonda, Anjaneya, et al.. (2015). Development and characterization of a free therapeutic ligand binding assay with assistance from kinetics modeling. Journal of Immunological Methods. 419. 18–24. 3 indexed citations
8.
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10.
Jiang, Hao, Jianing Zeng, Craig Titsch, et al.. (2013). Fully Validated LC-MS/MS Assay for the Simultaneous Quantitation of Coadministered Therapeutic Antibodies in Cynomolgus Monkey Serum. Analytical Chemistry. 85(20). 9859–9867. 64 indexed citations
11.
Lee, Ed, Michael Eschenberg, Kinnari Pandya, et al.. (2012). Specific Method Validation and Sample Analysis Approaches for Biocomparability Studies of Denosumab Addressing Method and Manufacture Site Changes. The AAPS Journal. 15(1). 70–77. 1 indexed citations
12.
Thway, Theingi M., et al.. (2011). Assessment of Incurred Sample Reanalysis for Macromolecules to Evaluate Bioanalytical Method Robustness: Effects from Imprecision. The AAPS Journal. 13(2). 291–298. 8 indexed citations
13.
14.
Ray, Chad, Lei Zhou, Jennifer Tsoi, et al.. (2010). A strategy for improving comparability across sites for ligand binding assays measuring therapeutic proteins. Journal of Pharmaceutical and Biomedical Analysis. 53(3). 729–734. 8 indexed citations
15.
Thway, Theingi M., et al.. (2008). Experimental and statistical approaches in method cross-validation to support pharmacokinetic decisions. Journal of Pharmaceutical and Biomedical Analysis. 49(3). 613–618. 13 indexed citations
16.
Kelley, Marian & Binodh DeSilva. (2007). Key elements of bioanalytical method validation for macromolecules. The AAPS Journal. 9(2). E156–E163. 107 indexed citations
17.
DeSilva, Binodh, Wendell C. Smith, Russell Weiner, et al.. (2003). Recommendations for the Bioanalytical Method Validation of Ligand-Binding Assays to Support Pharmacokinetic Assessments of Macromolecules. Pharmaceutical Research. 20(11). 1885–1900. 447 indexed citations
18.
DeSilva, Binodh & George S. Wilson. (2000). Synthesis of Bifunctional Antibodies for Immunoassays. Methods. 22(1). 33–43. 3 indexed citations
19.
Topp, Elizabeth M., et al.. (1998). Antibody transport in cultured tumor cell layers. Journal of Controlled Release. 53(1-3). 15–23. 10 indexed citations
20.
DeSilva, Binodh & George S. Wilson. (1995). Solid phase synthesis of bifunctional antibodies. Journal of Immunological Methods. 188(1). 9–19. 8 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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