Philippe Jacqmin

2.1k total citations · 1 hit paper
57 papers, 1.5k citations indexed

About

Philippe Jacqmin is a scholar working on Pediatrics, Perinatology and Child Health, Hematology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Philippe Jacqmin has authored 57 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Pediatrics, Perinatology and Child Health, 13 papers in Hematology and 10 papers in Cellular and Molecular Neuroscience. Recurrent topics in Philippe Jacqmin's work include Neuroscience and Neuropharmacology Research (9 papers), Autoimmune and Inflammatory Disorders Research (7 papers) and Immune Cell Function and Interaction (7 papers). Philippe Jacqmin is often cited by papers focused on Neuroscience and Neuropharmacology Research (9 papers), Autoimmune and Inflammatory Disorders Research (7 papers) and Immune Cell Function and Interaction (7 papers). Philippe Jacqmin collaborates with scholars based in Belgium, United States and United Kingdom. Philippe Jacqmin's co-authors include Eric Snoeck, Ronald Gieschke, Cristina de Min, Jean‐Louis Steimer, G Lapeyre, Armel Stockis, Maria Ballabio, Fabrizio De Benedetti, Alexei A. Grom and Lynn McFadyen and has published in prestigious journals such as New England Journal of Medicine, Blood and Antimicrobial Agents and Chemotherapy.

In The Last Decade

Philippe Jacqmin

55 papers receiving 1.5k 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.

Emapalumab in Children with Primary Hemophagocytic Lymphohistiocytosis

2020 311 citations Fabrizio De Benedetti, Alexei A. Grom et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Philippe Jacqmin Belgium	20	413	398	321	253	242	57	1.5k
Nidal Al‐Huniti United States	21	140 0.3×	144 0.4×	95 0.3×	226 0.9×	280 1.2×	72	1.4k
Cyril Mamotte Australia	26	404 1.0×	136 0.3×	302 0.9×	798 3.2×	157 0.6×	67	3.4k
Manuel Román Spain	25	455 1.1×	59 0.1×	158 0.5×	228 0.9×	287 1.2×	116	1.9k
Stefaan Rossenu Belgium	19	185 0.4×	126 0.3×	111 0.3×	153 0.6×	117 0.5×	35	976
Rik de Greef United States	22	240 0.6×	80 0.2×	100 0.3×	234 0.9×	721 3.0×	65	1.7k
DR Mould United States	7	132 0.3×	74 0.2×	117 0.4×	240 0.9×	225 0.9×	7	1.5k
Young‐A Heo New Zealand	20	163 0.4×	83 0.2×	245 0.8×	561 2.2×	218 0.9×	53	1.8k
Malcolm Boyce United Kingdom	29	363 0.9×	139 0.3×	40 0.1×	468 1.8×	396 1.6×	107	2.4k
Ann M. Moyer United States	24	219 0.5×	77 0.2×	68 0.2×	541 2.1×	311 1.3×	109	2.1k
Nicolas von Ahsen Germany	31	117 0.3×	337 0.8×	119 0.4×	825 3.3×	386 1.6×	89	2.8k

Countries citing papers authored by Philippe Jacqmin

Since Specialization

Citations

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

Fields of papers citing papers by Philippe Jacqmin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philippe Jacqmin

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

Jacqmin, Philippe, Yuki Iwaki, Mathieu Le Gars, et al.. (2023). Mechanistic modeling projections of antibody persistence after homologous booster regimens of COVID‐19 vaccine Ad26.COV2.S in humans. CPT Pharmacometrics & Systems Pharmacology. 12(10). 1485–1498. 4 indexed citations

Benedetti, Fabrizio De, Alexei A. Grom, Paul Brogan, et al.. (2023). Efficacy and safety of emapalumab in macrophage activation syndrome. Annals of the Rheumatic Diseases. 82(6). 857–865. 67 indexed citations

Choy, Ernest, Iain B. McInnes, Kathy de Graaf, et al.. (2019). Efficacy and safety of NI-0101, an anti-toll-like receptor 4 monoclonal antibody, in patients with rheumatoid arthritis after inadequate response to methotrexate: a phase II study. Annals of the Rheumatic Diseases. 79(3). 316–323. 58 indexed citations

Manso-Silván, Maria A., et al.. (2017). Population pharmacokinetic evaluation of ADV6209, an innovative oral solution of midazolam containing cyclodextrin. European Journal of Pharmaceutical Sciences. 114. 46–54. 20 indexed citations

Harrold, John M., Philippe Jacqmin, Per Olsson, et al.. (2014). Translational Modeling to Identify Human Dosing of Filgrastim to Improve Overall Survival (OS) in Acute Radiation Syndrome (ARS). Blood. 124(21). 690–690.

Delattre, Isabelle, Flora T. Musuamba, Philippe Jacqmin, et al.. (2012). Population pharmacokinetics of four β-lactams in critically ill septic patients comedicated with amikacin. Clinical Biochemistry. 45(10-11). 780–786. 26 indexed citations

Chan, Phylinda L. S., Philippe Jacqmin, Marc Lavielle, Lynn McFadyen, & B.C. Weatherley. (2010). The use of the SAEM algorithm in MONOLIX software for estimation of population pharmacokinetic-pharmacodynamic-viral dynamics parameters of maraviroc in asymptomatic HIV subjects. Journal of Pharmacokinetics and Pharmacodynamics. 38(1). 41–61. 61 indexed citations

Jacqmin, Philippe, Lynn McFadyen, & Janet R. Wade. (2010). Basic PK/PD principles of drug effects in circular/proliferative systems for disease modelling. Journal of Pharmacokinetics and Pharmacodynamics. 37(2). 157–177. 14 indexed citations

Jacqmin, Philippe, et al.. (2009). Pharmacokinetic/Pharmacodynamic Modeling of Psychomotor Impairment Induced by Oral Clonazepam in Healthy Volunteers. Therapeutic Drug Monitoring. 31(5). 566–574. 9 indexed citations

10.

Olsson, Per, Philippe Jacqmin, & Juan José Pérez Ruixo. (2007). Population Pharmacokinetics Meta-Analysis of Recombinant Human Erythropoietin in Healthy Subjects. Clinical Pharmacokinetics. 46(2). 159–173. 36 indexed citations

11.

Pigeolet, Etienne, et al.. (2007). Population Pharmacokinetics of??Levetiracetam in Japanese and??Western Adults. Clinical Pharmacokinetics. 46(6). 503–512. 49 indexed citations

12.

Jacqmin, Philippe, Eric Snoeck, E.A. van Schaick, et al.. (2006). Modelling Response Time Profiles in the Absence of Drug Concentrations: Definition and Performance Evaluation of the K–PD Model. Journal of Pharmacokinetics and Pharmacodynamics. 34(1). 57–85. 141 indexed citations

13.

Pillai, Goonaseelan, Ronald Gieschke, Timothy Goggin, et al.. (2004). A semimechanistic and mechanistic population PK–PD model for biomarker response to ibandronate, a new bisphosphonate for the treatment of osteoporosis. British Journal of Clinical Pharmacology. 58(6). 618–631. 72 indexed citations

14.

Snoeck, Eric, Philippe Jacqmin, A. Van Peer, et al.. (1997). Population analysis of the non linear red blood cell partitioning and the concentration‐effect relationship of draflazine following various infusion rates. British Journal of Clinical Pharmacology. 43(6). 603–612. 5 indexed citations

15.

Snoeck, Eric, Philippe Jacqmin, R. Lins, et al.. (1997). Population analysis of the non-linear red blood cell partitioning of draflazine following various infusion durations. European Journal of Clinical Pharmacology. 53(1). 57–63. 2 indexed citations

16.

Snoeck, Eric, Philippe Jacqmin, A. Van Peer, et al.. (1996). The implications of non‐linear red blood cell partitioning for the pharmacokinetics and pharmacodynamics of the nucleoside transport inhibitor draflazine. British Journal of Clinical Pharmacology. 42(5). 605–613. 9 indexed citations

17.

Mahieu, Paul, A. Hassoun, Roger Vanbinst, Philippe Jacqmin, & Michel Lesne. (1987). Flunitrazepam Acute Intoxication - Comparative Pharmacokinetic and Clinical Follow-up. Digital Access to Libraries. 29. 107–107. 1 indexed citations

18.

Trouvin, Jean‐Hugues, Philippe Jacqmin, Claude Rouch, Michel Lesne, & C. Jacquot. (1987). Benzodiazepine receptors are involved in tabernanthine-induced tremor: in vitro and in vivo evidence. European Journal of Pharmacology. 140(3). 303–309. 27 indexed citations

19.

Frenckell, R. von, et al.. (1987). Comparison of Sublingual and Oral Prazepam in Normal Subjects. Neuropsychobiology. 18(2). 77–82. 4 indexed citations

20.

Jacqmin, Philippe, et al.. (1986). Modulation of ligands binding to the benzodiazepine receptor by an endogenous inhibitor (GABA-modulin) and bicuculline.. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 17(4). 657–63. 1 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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