Diane Ramsden

2.8k total citations · 1 hit paper
86 papers, 2.1k citations indexed

About

Diane Ramsden is a scholar working on Radiation, Oncology and Pharmacology. According to data from OpenAlex, Diane Ramsden has authored 86 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiation, 22 papers in Oncology and 20 papers in Pharmacology. Recurrent topics in Diane Ramsden's work include Radiation Detection and Scintillator Technologies (22 papers), Pharmacogenetics and Drug Metabolism (20 papers) and Drug Transport and Resistance Mechanisms (20 papers). Diane Ramsden is often cited by papers focused on Radiation Detection and Scintillator Technologies (22 papers), Pharmacogenetics and Drug Metabolism (20 papers) and Drug Transport and Resistance Mechanisms (20 papers). Diane Ramsden collaborates with scholars based in United Kingdom, United States and Japan. Diane Ramsden's co-authors include G. J. Boer, Gregory M. Flato, M. C. Reader, Andrew J. Weaver, Warren G. Lee, N. A. McFarlane, Ling-Jian Meng, Donald Tweedie, R Hoffenberg and Stuart Evans and has published in prestigious journals such as Gastroenterology, Antimicrobial Agents and Chemotherapy and International Journal of Pharmaceutics.

In The Last Decade

Diane Ramsden

78 papers receiving 1.9k 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.

The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

2000 523 citations Diane Ramsden et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Diane Ramsden	767	574	286	219	178	86	2.1k
You He	787 1.0×	1.3k 2.2×	636 2.2×	336 1.5×	41 0.2×	47	2.6k
Wolfgang Weiß	506 0.7×	296 0.5×	83 0.3×	69 0.3×	127 0.7×	132	3.0k
Yoshihisa Kato	136 0.2×	519 0.9×	255 0.9×	278 1.3×	12 0.1×	232	3.9k
Takao Iida	1.0k 1.3×	487 0.8×	49 0.2×	63 0.3×	419 2.4×	262	4.0k
J. D. Burton	150 0.2×	194 0.3×	41 0.1×	578 2.6×	36 0.2×	136	5.7k
Karl‐Heinz Schmidt	119 0.2×	172 0.3×	38 0.1×	157 0.7×	87 0.5×	107	2.0k
Hiroshi Ogawa	500 0.7×	376 0.7×	56 0.2×	30 0.1×	34 0.2×	134	3.9k
Richard Forbes	2.4k 3.2×	2.4k 4.2×	21 0.1×	87 0.4×	16 0.1×	146	5.1k
Kiyoshi Tanaka	146 0.2×	269 0.5×	45 0.2×	212 1.0×	17 0.1×	197	3.9k
Werner Schneider	320 0.4×	160 0.3×	78 0.3×	47 0.2×	76 0.4×	97	1.7k

Countries citing papers authored by Diane Ramsden

Since Specialization

Citations

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

Fields of papers citing papers by Diane Ramsden

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diane Ramsden

This figure shows the co-authorship network connecting the top 25 collaborators of Diane Ramsden. A scholar is included among the top collaborators of Diane Ramsden 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 Diane Ramsden. Diane Ramsden 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

Chothe, Paresh P., et al.. (2025). Advancing Predictions of Oral Drug Absorption, CYP3A4 Induction, and Transporter‐Mediated Interactions Using a Human Primary Intestinal 3D Model ( EpiIntestinal™ ). Clinical Pharmacology & Therapeutics. 118(6). 1499–1511.

Ferguson, Douglas, et al.. (2024). Assessing complex drug-drug interactions using the truvivotm hepatocyte model. Drug Metabolism and Pharmacokinetics. 55. 100866–100866. 1 indexed citations

Proia, Theresa A., Matthew Sung, Srinivas Mamidi, et al.. (2024). Quantitative evaluation of trastuzumab deruxtecan pharmacokinetics and pharmacodynamics in mouse models of varying degrees of HER2 expression. CPT Pharmacometrics & Systems Pharmacology. 13(6). 994–1005. 7 indexed citations

Aluri, Krishna, et al.. (2024). Aminobenzotriazole inhibits and induces several key drug metabolizing enzymes complicating its utility as a pan CYP inhibitor for reaction phenotyping. Clinical and Translational Science. 17(3). e13746–e13746. 3 indexed citations

Mulford, Darcy J., Diane Ramsden, Liming Zhang, et al.. (2023). Tiered approach to evaluate the CYP3A victim and perpetrator drug–drug interaction potential for vonoprazan using PBPK modeling and clinical data to inform labeling. CPT Pharmacometrics & Systems Pharmacology. 12(4). 532–544. 8 indexed citations

Chothe, Paresh P., Vikram Arya, Bhagwat Prasad, Diane Ramsden, & Kunal S. Taskar. (2023). Innovations, Opportunities, and Challenges for Predicting Alteration in Drug-Metabolizing Enzyme and Transporter Activity in Specific Populations. Drug Metabolism and Disposition. 51(12). 1547–1550. 3 indexed citations

Ramsden, Diane, et al.. (2022). Characterization of Correction Factors to Enable Assessment of Clinical Risk from In Vitro CYP3A4 Induction Data and Basic Drug-Drug Interaction Models. European Journal of Drug Metabolism and Pharmacokinetics. 47(4). 467–482. 11 indexed citations

Ramsden, Diane, et al.. (2021). Predictive In Vitro-In Vivo Extrapolation for Time Dependent Inhibition of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6 Using Pooled Human Hepatocytes, Human Liver Microsomes, and a Simple Mechanistic Static Model. Drug Metabolism and Disposition. 50(2). 114–127. 12 indexed citations

Kenny, Jane R., Diane Ramsden, David B. Buckley, et al.. (2018). Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidances from Regulatory Agencies: Focus on CYP3A4 mRNA In Vitro Response Thresholds, Variability, and Clinical Relevance. Drug Metabolism and Disposition. 46(9). 1285–1303. 43 indexed citations

10.

Hariparsad, Niresh, Diane Ramsden, Jairam Palamanda, et al.. (2017). Considerations from the IQ Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Focus on Downregulation, CYP2C Induction, and CYP2B6 Positive Control. Drug Metabolism and Disposition. 45(10). 1049–1059. 33 indexed citations

11.

Fahmi, Odette A., Mohamad Shebley, Jairam Palamanda, et al.. (2016). Evaluation of CYP2B6 Induction and Prediction of Clinical Drug–Drug Interactions: Considerations from the IQ Consortium Induction Working Group—An Industry Perspective. Drug Metabolism and Disposition. 44(10). 1720–1730. 38 indexed citations

12.

Sane, Rucha, et al.. (2015). Contribution of Major Metabolites toward Complex Drug-Drug Interactions of Deleobuvir: In Vitro Predictions and In Vivo Outcomes. Drug Metabolism and Disposition. 44(3). 466–475. 23 indexed citations

13.

Ramsden, Diane, Jin Zhou, & Donald Tweedie. (2015). Determination of a Degradation Constant for CYP3A4 by Direct Suppression of mRNA in a Novel Human Hepatocyte Model, HepatoPac. Drug Metabolism and Disposition. 43(9). 1307–1315. 39 indexed citations

14.

Ramsden, Diane, Donald Tweedie, Tom S. Chan, & Timothy S. Tracy. (2014). Altered CYP2C9 Activity Following Modulation of CYP3A4 Levels in Human Hepatocytes: an Example of Protein-Protein Interactions. Drug Metabolism and Disposition. 42(11). 1940–1946. 21 indexed citations

15.

Ramsden, Diane, et al.. (2013). Generating an In Vitro–In Vivo Correlation for Metabolism and Liver Enrichment of a Hepatitis C Virus Drug, Faldaprevir, Using a Rat Hepatocyte Model (HepatoPac). Drug Metabolism and Disposition. 42(3). 407–414. 20 indexed citations

16.

Ramsden, Diane, Donald Tweedie, Tom S. Chan, Mitchell E. Taub, & Yongmei Li. (2013). Bridging In Vitro and In Vivo Metabolism and Transport of Faldaprevir in Human Using a Novel Cocultured Human Hepatocyte System, HepatoPac. Drug Metabolism and Disposition. 42(3). 394–406. 56 indexed citations

17.

Ahlquist, James, J. A. Franklyn, Diane Ramsden, & Michael C. Sheppard. (1990). Regulation of α and thyrotrophin-β subunit mRNA levels by androgens in the female rat. Journal of Molecular Endocrinology. 5(1). 1–6. 9 indexed citations

18.

Ramsden, Diane, et al.. (1988). Ioxynil and 3,5,3′-triiodothyronine: comparison of binding to human plasma proteins. Toxicology Letters. 44(3). 281–287. 9 indexed citations

19.

Wood, Diana, Kevin Docherty, Diane Ramsden, K I J Shennan, & Michael C. Sheppard. (1987). Thyroid status affects the regulation of prolactin mRNA accumulation by tri-iodothyronine and thyrotrophin-releasing hormone in cultured rat anterior pituitary cells. Journal of Endocrinology. 115(3). 497–503. 8 indexed citations

20.

Ramsden, Diane. (1979). Direct comparisons of human and animal data for plutonium oxide inhalation.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 36(1). 88–9. 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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