Zhoumeng Lin

4.8k total citations · 1 hit paper
116 papers, 3.6k citations indexed

About

Zhoumeng Lin is a scholar working on Pharmacology, Food Science and Pollution. According to data from OpenAlex, Zhoumeng Lin has authored 116 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Pharmacology, 22 papers in Food Science and 19 papers in Pollution. Recurrent topics in Zhoumeng Lin's work include Antibiotics Pharmacokinetics and Efficacy (31 papers), Pesticide Residue Analysis and Safety (20 papers) and Nanoparticle-Based Drug Delivery (15 papers). Zhoumeng Lin is often cited by papers focused on Antibiotics Pharmacokinetics and Efficacy (31 papers), Pesticide Residue Analysis and Safety (20 papers) and Nanoparticle-Based Drug Delivery (15 papers). Zhoumeng Lin collaborates with scholars based in United States, China and Spain. Zhoumeng Lin's co-authors include Jim E. Riviere, Wei‐Chun Chou, Nancy A. Monteiro‐Riviere, Chunla He, Yi‐Hsien Cheng, Nikolay M. Filipov, Ronette Gehring, Qiran Chen, Wei‐Bing Xie and Celia A. Dodd and has published in prestigious journals such as Environmental Science & Technology, ACS Nano and Journal of Hazardous Materials.

In The Last Decade

Zhoumeng Lin

112 papers receiving 3.6k citations

Hit Papers

align trajectories

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.

Meta-Analysis of Nanoparticle Delivery to Tumors Using a Physiologically Based Pharmacokinetic Modeling and Simulation Approach

2020 230 citations Yi‐Hsien Cheng, Jim E. Riviere et al. ACS Nano profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhoumeng Lin United States	36	679	590	538	466	432	116	3.6k
Marion Ehrich United States	32	805 1.2×	363 0.6×	190 0.4×	222 0.5×	191 0.4×	176	3.4k
Xuemei Yang China	35	2.4k 3.6×	426 0.7×	245 0.5×	597 1.3×	341 0.8×	229	5.6k
Jong Min Kim South Korea	43	2.4k 3.5×	545 0.9×	172 0.3×	281 0.6×	556 1.3×	303	6.2k
Branislav Ruttkay-Nedecký Czechia	28	1.4k 2.1×	159 0.3×	215 0.4×	555 1.2×	763 1.8×	80	4.6k
Hao Wang China	38	1.3k 1.9×	224 0.4×	437 0.8×	571 1.2×	427 1.0×	214	4.1k
Qing Xia China	24	1.1k 1.6×	323 0.5×	354 0.7×	442 0.9×	132 0.3×	117	2.6k
Diana A. Averill‐Bates Canada	34	2.9k 4.3×	387 0.7×	230 0.4×	457 1.0×	297 0.7×	93	6.0k
Seppo Auriola Finland	49	3.4k 5.0×	451 0.8×	259 0.5×	442 0.9×	124 0.3×	240	8.5k
He Li China	31	839 1.2×	504 0.9×	109 0.2×	325 0.7×	226 0.5×	185	3.2k
An S. Tan New Zealand	20	1.8k 2.7×	233 0.4×	235 0.4×	467 1.0×	341 0.8×	29	4.3k

Countries citing papers authored by Zhoumeng Lin

Since Specialization

Citations

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

Fields of papers citing papers by Zhoumeng Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhoumeng Lin

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

Mi, Kun, et al.. (2025). Chemical risk assessment in food animals via physiologically based pharmacokinetic modeling − Part I: Veterinary drugs on human food safety assessment. Environment International. 197. 109339–109339. 9 indexed citations

Tell, Lisa A., et al.. (2025). An open-source interactive physiologically based pharmacokinetic model of tylosin in broiler chickens and laying hens. Toxicological Sciences. 205(2). 279–296. 1 indexed citations

Chou, Wei‐Chun, Alexa Canchola, Fan Zhang, & Zhoumeng Lin. (2025). Machine Learning and Artificial Intelligence in Nanomedicine. Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology. 17(4). e70027–e70027. 13 indexed citations

Pai, Amy Barton, Zhoumeng Lin, Heather H. Gustafson, et al.. (2025). Challenging Traditional ADME Assumptions for Physiologically Based Pharmacokinetic Models for Intravenous Administration of Iron–Carbohydrate Nanomedicines: Potential Utility of Gold Nanoparticle Models as a Roadmap. Clinical Pharmacokinetics. 64(10). 1477–1494.

Lin, Zhoumeng, et al.. (2025). Applications of PBPK Models to Predict Tissue Residues and Extralabel Withdrawal Times of Drugs in Food Animals: Perspectives from the Food Animal Residue Avoidance Databank (FARAD) Program. The AAPS Journal. 27(6). 153–153.

Guinn, Daphne, et al.. (2025). Application of Lactation Physiologically Based Pharmacokinetic Modeling to Predict Milk Exposure of Passively Diffused Drugs. The Journal of Clinical Pharmacology. 65(12). 1637–1649.

Canchola, Alexa, Kunpeng Chen, Chi‐Yun Chen, et al.. (2025). Meta-Analysis and Machine Learning Prediction of Protein Corona Composition across Nanoparticle Systems in Biological Media. ACS Nano. 19(43). 37633–37650. 4 indexed citations

Chen, Xinyue & Zhoumeng Lin. (2025). A Physiologically Based Pharmacokinetic Model of an Oral Tyrosine Kinase 2 Inhibitor Deucravacitinib in Healthy Adults. The Journal of Clinical Pharmacology. 65(8). 1011–1025.

Chen, Qiran, et al.. (2024). Residue depletion profiles and withdrawal intervals of florfenicol and its metabolite florfenicol amine in plasma and milk of lactating goats after repeated subcutaneous administrations. Regulatory Toxicology and Pharmacology. 153. 105707–105707. 1 indexed citations

10.

Lin, Zhoumeng, et al.. (2024). Informing the risk assessment related to lactation and drug exposure: A physiologically based pharmacokinetic lactation model for pregabalin. CPT Pharmacometrics & Systems Pharmacology. 13(11). 1953–1966. 2 indexed citations

11.

Chou, Wei‐Chun & Zhoumeng Lin. (2023). Impact of protein coronas on nanoparticle interactions with tissues and targeted delivery. Current Opinion in Biotechnology. 85. 103046–103046. 24 indexed citations

12.

Ensley, Steve, Zhoumeng Lin, Michael D. Kleinhenz, et al.. (2023). Pharmacokinetics, Milk Residues, and Toxicological Evaluation of a Single High Dose of Meloxicam Administered at 30 mg/kg per os to Lactating Dairy Cattle. Veterinary Sciences. 10(4). 301–301. 5 indexed citations

13.

Schmidt, Stephan, Valvanera Vozmediano, Rodrigo Cristofoletti, et al.. (2023). Requirements, expectations, challenges and opportunities associated with training the next generation of pharmacometricians. CPT Pharmacometrics & Systems Pharmacology. 12(7). 883–888. 4 indexed citations

14.

Li, Miao, Ronald E. Baynes, Lisa A. Tell, et al.. (2020). Physiological parameter values for physiologically based pharmacokinetic models in food‐producing animals. Part III: Sheep and goat. Journal of Veterinary Pharmacology and Therapeutics. 44(4). 456–477. 23 indexed citations

15.

Lin, Zhoumeng, Miao Li, Lisa A. Tell, et al.. (2020). Physiological parameter values for physiologically based pharmacokinetic models in food‐producing animals. Part I: Cattle and swine. Journal of Veterinary Pharmacology and Therapeutics. 43(5). 385–420. 36 indexed citations

16.

Li, Miao, Locke A. Karriker, Larry W. Wulf, et al.. (2019). An integrated experimental and physiologically based pharmacokinetic modeling study of penicillin G in heavy sows. Journal of Veterinary Pharmacology and Therapeutics. 42(4). 461–475. 13 indexed citations

17.

Bach, Jonathan F., et al.. (2018). Bioavailability of suppository acetaminophen in healthy and hospitalized ill dogs. Journal of Veterinary Pharmacology and Therapeutics. 41(5). 652–658. 6 indexed citations

18.

Cheng, Yi‐Hsien, Jim E. Riviere, Nancy A. Monteiro‐Riviere, & Zhoumeng Lin. (2018). Probabilistic risk assessment of gold nanoparticles after intravenous administration by integrating in vitro and in vivo toxicity with physiologically based pharmacokinetic modeling. Nanotoxicology. 12(5). 453–469. 31 indexed citations

19.

Lin, Zhoumeng, Joan D. Rowe, Mengjie Li, et al.. (2016). Estimation of tulathromycin depletion in plasma and milk after subcutaneous injection in lactating goats using a nonlinear mixed-effects pharmacokinetic modeling approach. BMC Veterinary Research. 12(1). 258–258. 15 indexed citations

20.

Monteiro‐Riviere, Nancy A., M. Teresa Ortega, Kyoungju Choi, et al.. (2015). Comparative In Vitro Cytotoxicity of 20 Potential Food Ingredients in Canine Liver, Kidney, Bone Marrow-Derived Mesenchymal Stem Cells, and Enterocyte-like Cells. 1(4). 276–288. 3 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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