Chuang Lu

3.1k total citations · 1 hit paper
56 papers, 2.3k citations indexed

About

Chuang Lu is a scholar working on Pharmacology, Oncology and Molecular Biology. According to data from OpenAlex, Chuang Lu has authored 56 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Pharmacology, 27 papers in Oncology and 18 papers in Molecular Biology. Recurrent topics in Chuang Lu's work include Pharmacogenetics and Drug Metabolism (30 papers), Drug Transport and Resistance Mechanisms (25 papers) and Computational Drug Discovery Methods (5 papers). Chuang Lu is often cited by papers focused on Pharmacogenetics and Drug Metabolism (30 papers), Drug Transport and Resistance Mechanisms (25 papers) and Computational Drug Discovery Methods (5 papers). Chuang Lu collaborates with scholars based in United States, China and Japan. Chuang Lu's co-authors include Xiaomei Zhuang, Albert P. Li, Xinxin Ding, Donglu Zhang, Gang Luo, Liang‐Shang Gan, Gerald T. Miwa, Vinita Uttamsingh, Suresh K. Balani and Li Di and has published in prestigious journals such as Cancer Research, Scientific Reports and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Chuang Lu

55 papers receiving 2.2k 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.

PBPK modeling and simulation in drug research and development

2016 291 citations Xiaomei Zhuang, Chuang Lu Acta Pharmaceutica Sinica B profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chuang Lu United States	23	1.1k	748	659	305	250	56	2.3k
Dermot F. McGinnity United Kingdom	23	1.1k 1.0×	801 1.1×	693 1.1×	352 1.2×	152 0.6×	41	2.1k
Jane R. Kenny United States	24	996 0.9×	707 0.9×	442 0.7×	237 0.8×	192 0.8×	58	1.8k
Jean‐Charles Gautier France	27	1.2k 1.1×	646 0.9×	852 1.3×	140 0.5×	209 0.8×	60	2.8k
Michael Sinz United States	29	1.6k 1.5×	1.1k 1.4×	636 1.0×	303 1.0×	394 1.6×	72	2.8k
Liang‐Shang Gan United States	25	759 0.7×	953 1.3×	843 1.3×	223 0.7×	379 1.5×	43	2.4k
Donald Tweedie United States	24	834 0.8×	568 0.8×	499 0.8×	158 0.5×	230 0.9×	49	1.6k
Ruth Hyland United Kingdom	24	1.5k 1.4×	734 1.0×	639 1.0×	301 1.0×	289 1.2×	31	2.5k
Robert L. Walsky United States	25	1.8k 1.6×	927 1.2×	666 1.0×	370 1.2×	279 1.1×	35	2.7k
Miki Katoh Japan	31	1.2k 1.1×	949 1.3×	827 1.3×	181 0.6×	469 1.9×	86	2.5k
Thierry Lavé Switzerland	35	1.3k 1.2×	1.1k 1.5×	682 1.0×	485 1.6×	364 1.5×	68	3.0k

Countries citing papers authored by Chuang Lu

Since Specialization

Citations

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

Fields of papers citing papers by Chuang Lu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chuang Lu

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

Daniels, Matthew H., David Brennan, Brian Johnston, et al.. (2024). Abstract PR003: DHX9 inhibition as a novel therapeutic for ovarian and breast cancer with loss-of-function mutations in the DNA damage repair genes BRCA1 or BRCA2. Cancer Research. 84(1_Supplement). PR003–PR003.

Zhou, Xiaofei, Yuexian Li, Lawrence H. Cohen, et al.. (2020). Biotransformation Pathways and Metabolite Profiles of Oral [14C]Alisertib (MLN8237), an Investigational Aurora A Kinase Inhibitor, in Patients with Advanced Solid Tumors. Drug Metabolism and Disposition. 48(3). 217–229. 13 indexed citations

Weidolf, Lars, Thomas Andersson, Joel P. Bercu, et al.. (2019). Qualification of impurities based on metabolite data. Regulatory Toxicology and Pharmacology. 110. 104524–104524. 12 indexed citations

Dong, Jiajia, Olajide E. Olaleye, Rongrong Jiang, et al.. (2018). Glycyrrhizin has a high likelihood to be a victim of drug–drug interactions mediated by hepatic organic anion‐transporting polypeptide 1B1/1B3. British Journal of Pharmacology. 175(17). 3486–3503. 21 indexed citations

Zhang, Zhiyuan, Xin Wang, Dan Liŭ, et al.. (2017). Development and validation of an LC‐MS/MS method for the determination of a novel thienoquinolin urea transporter inhibitor PU‐48 in rat plasma and its application to a pharmacokinetic study. Biomedical Chromatography. 32(4). 4 indexed citations

Qi, Huimin, Xin Wang, Pu Zhang, et al.. (2017). Effects of functional CYP2C8,CYP2C9,CYP3A5,and ABCB1 genetic variants on the pharmacokinetics of insulin sensitizer pioglitazone in Chinese Han individuals. Pharmacogenetics and Genomics. 27(4). 125–134. 4 indexed citations

Zhuang, Xiaomei & Chuang Lu. (2016). PBPK modeling and simulation in drug research and development. Acta Pharmaceutica Sinica B. 6(5). 430–440. 291 indexed citations breakdown →

Wang, Xin, Jian Li, Zhiyun Meng, et al.. (2015). Quantitative and qualitative analysis of the novel antitumor 1,3,4-oxadiazole derivative (GLB) and its metabolites using HPLC-UV and UPLC-QTOF-MS. Scientific Reports. 5(1). 11906–11906. 4 indexed citations

Liu, Fei, Xiaomei Zhuang, Cuiping Yang, et al.. (2014). Characterization of preclinicalin vitroandin vivoADME properties and prediction of human PK using a physiologically based pharmacokinetic model for YQA‐14, a new dopamine D₃receptor antagonist candidate for treatment of drug addiction. Biopharmaceutics & Drug Disposition. 35(5). 296–307. 17 indexed citations

10.

Zhuang, Xiaomei, et al.. (2013). Identification and Characterization of Psoralen and Isopsoralen as Potent CYP1A2 Reversible and Time-Dependent Inhibitors in Human and Rat Preclinical Studies. Drug Metabolism and Disposition. 41(11). 1914–1922. 37 indexed citations

11.

Lu, Chuang, et al.. (2010). Enzyme inhibition in drug discovery and development : the good and the bad. Wiley eBooks. 20 indexed citations

12.

Lu, Chuang, Suresh K. Balani, Mark G. Qian, et al.. (2009). Quantitative Prediction and Clinical Observation of a CYP3A Inhibitor-Based Drug-Drug Interactions with MLN3897, a Potent C-C Chemokine Receptor-1 Antagonist. Journal of Pharmacology and Experimental Therapeutics. 332(2). 562–568. 10 indexed citations

13.

Grimm, Scott, Heidi J. Einolf, Kan He, et al.. (2009). The Conduct of in Vitro Studies to Address Time-Dependent Inhibition of Drug-Metabolizing Enzymes: A Perspective of the Pharmaceutical Research and Manufacturers of America. Drug Metabolism and Disposition. 37(7). 1355–1370. 224 indexed citations

14.

Lu, Chuang, et al.. (2008). Prediction of Pharmacokinetic Drug-Drug Interactions Using Human Hepatocyte Suspension in Plasma and Cytochrome P450 Phenotypic Data. III. In Vitro-in Vivo Correlation with Fluconazole. Drug Metabolism and Disposition. 36(7). 1261–1266. 33 indexed citations

15.

Lu, Chuang, Ping Li, Richard Gallegos, et al.. (2006). Comparison of Intrinsic Clearance in Liver Microsomes and Hepatocytes from Rats and Humans: Evaluation of Free Fraction and Uptake in Hepatocytes. Drug Metabolism and Disposition. 34(9). 1600–1605. 117 indexed citations

16.

Lu, Chuang, Richard Gallegos, Ping Li, et al.. (2006). INVESTIGATION OF DRUG-DRUG INTERACTION POTENTIAL OF BORTEZOMIB IN VIVO IN FEMALE SPRAGUE-DAWLEY RATS AND IN VITRO IN HUMAN LIVER MICROSOMES. Drug Metabolism and Disposition. 34(4). 702–708. 28 indexed citations

17.

Uttamsingh, Vinita, Chuang Lu, Gerald T. Miwa, & Liang‐Shang Gan. (2005). RELATIVE CONTRIBUTIONS OF THE FIVE MAJOR HUMAN CYTOCHROMES P450, 1A2, 2C9, 2C19, 2D6, AND 3A4, TO THE HEPATIC METABOLISM OF THE PROTEASOME INHIBITOR BORTEZOMIB. Drug Metabolism and Disposition. 33(11). 1723–1728. 109 indexed citations

18.

Lu, Chuang, et al.. (2005). Validation of a high‐throughput absorption, distribution, metabolism, and excretion (ADME) system and results for 60 literature compounds. Rapid Communications in Mass Spectrometry. 19(9). 1191–1199. 12 indexed citations

19.

Shitara, Yoshihisa, Albert P. Li, Yukio Kato, et al.. (2003). Function of Uptake Transporters for Taurocholate and Estradiol 17β-D-Glucuronide in Cryopreserved Human Hepatocytes. Drug Metabolism and Pharmacokinetics. 18(1). 33–41. 86 indexed citations

20.

Lu, Chuang, et al.. (1996). Synthesis of optically pure chrysobactin and immunoassay development. BioMetals. 9(4). 377–83. 9 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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