Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Naji, M.
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Huang, W.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (9/9 displayed)

  • 2024Suspended micro thermometer for anisotropic thermal transport measurements3citations
  • 2024Activation of peracetic acid by a magnetic biochar-ferrospinel AFe2O4 (A = Cu, Co, or Mn) nanocomposite for the degradation of carbamazepine − a comparative and mechanistic study15citations
  • 2022Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors.6citations
  • 2020Hybrid organic–metal oxide multilayer channel transistors with high operational stability56citations
  • 2017Multiferroic Bi2FeCrO6 based p-i-n heterojunction photovoltaic devices59citations
  • 2015Epitaxial Bi2FeCrO6 Multiferroic Thin Film as a New Visible Light Absorbing Photocathode Material84citations
  • 2006ZnCdSe-ZnSe cladded quantum dots using photoassisted microwave plasma enhanced metalorganic chemical vapor deposition for lasers and electroluminescent phosphorscitations
  • 2006ZnCdSe-ZnSe cladded quantum dots using Photoassisted Microwave Plasma (PMP) enhanced metalorganic chemical vapor deposition for lasers and electroluminescent phosphorscitations
  • 2005Selective fluorescence detection of divalent and trivalent metal ions with functionalized lipid membranes19citations

Places of action

Chart of shared publication
Nigro, A.
1 / 5 shared
Zardo, I.
1 / 4 shared
Kaur, Y.
1 / 1 shared
Koch, D. M.
1 / 1 shared
Raciti, G.
1 / 1 shared
Paul, T.
1 / 4 shared
Sojo-Gordillo, J. M.
1 / 1 shared
De Vito, G.
1 / 3 shared
Swami, R.
1 / 2 shared
Calame, M.
1 / 2 shared
Swinkels, M. Y.
1 / 1 shared
Kamali, M.
1 / 1 shared
Appels, L.
1 / 1 shared
Xue, Y.
1 / 1 shared
Dewil, R.
1 / 6 shared
Kakavandi, B.
1 / 1 shared
Costa, Mev
1 / 7 shared
Thompson, Ip
1 / 1 shared
Stader, F.
1 / 1 shared
Chan, P.
1 / 1 shared
Li, L.
1 / 90 shared
Cs, Shemesh
1 / 1 shared
Kl, Gill
1 / 1 shared
Hm, Jones
1 / 1 shared
Rossato, G.
1 / 1 shared
Wu, B.
1 / 5 shared
Chen, Y.
1 / 71 shared
Jy, Jin
1 / 1 shared
Chanu, P.
1 / 1 shared
Tsetseris, L.
1 / 6 shared
Faber, H.
1 / 7 shared
Lin, Y.
1 / 24 shared
Zhang, Q.
1 / 19 shared
Khim, D.
1 / 2 shared
Patsalas, P.
1 / 13 shared
Anthopoulos, T.
1 / 8 shared
Pliatsikas, N.
1 / 5 shared
Seitkhan, A.
1 / 3 shared
Hastas, N.
1 / 2 shared
Zhang, X.
1 / 65 shared
Bradley, D.
1 / 5 shared
Li, W.
1 / 48 shared
Nechache, R.
2 / 5 shared
Rosei, F.
2 / 25 shared
Benetti, D.
1 / 4 shared
Harnagea, C.
1 / 4 shared
Chaker, M.
1 / 2 shared
Li, S.
1 / 57 shared
Serpone, N.
1 / 1 shared
Alotaibi, B.
1 / 1 shared
Mi, Z.
1 / 1 shared
Ayers, J.
2 / 2 shared
Jain, F.
2 / 2 shared
Papadimitrakopoulos, F.
2 / 2 shared
Rodriguez, A.
2 / 6 shared
Vitti, L.
1 / 1 shared
Li, R.
2 / 25 shared
Yarlagadda, Prasad Kdv
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Shelnutt, Ja
1 / 1 shared
Gopalan, As
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Jacobs, Hk
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Pincus, Jl
1 / 1 shared
Song, Y.
1 / 14 shared
Sasaki, Dy
1 / 1 shared
Chart of publication period
2024
2022
2020
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2015
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2005

Co-Authors (by relevance)

  • Nigro, A.
  • Zardo, I.
  • Kaur, Y.
  • Koch, D. M.
  • Raciti, G.
  • Paul, T.
  • Sojo-Gordillo, J. M.
  • De Vito, G.
  • Swami, R.
  • Calame, M.
  • Swinkels, M. Y.
  • Kamali, M.
  • Appels, L.
  • Xue, Y.
  • Dewil, R.
  • Kakavandi, B.
  • Costa, Mev
  • Thompson, Ip
  • Stader, F.
  • Chan, P.
  • Li, L.
  • Cs, Shemesh
  • Kl, Gill
  • Hm, Jones
  • Rossato, G.
  • Wu, B.
  • Chen, Y.
  • Jy, Jin
  • Chanu, P.
  • Tsetseris, L.
  • Faber, H.
  • Lin, Y.
  • Zhang, Q.
  • Khim, D.
  • Patsalas, P.
  • Anthopoulos, T.
  • Pliatsikas, N.
  • Seitkhan, A.
  • Hastas, N.
  • Zhang, X.
  • Bradley, D.
  • Li, W.
  • Nechache, R.
  • Rosei, F.
  • Benetti, D.
  • Harnagea, C.
  • Chaker, M.
  • Li, S.
  • Serpone, N.
  • Alotaibi, B.
  • Mi, Z.
  • Ayers, J.
  • Jain, F.
  • Papadimitrakopoulos, F.
  • Rodriguez, A.
  • Vitti, L.
  • Li, R.
  • Yarlagadda, Prasad Kdv
  • Shelnutt, Ja
  • Gopalan, As
  • Jacobs, Hk
  • Pincus, Jl
  • Song, Y.
  • Sasaki, Dy
OrganizationsLocationPeople

article

Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors.

  • Huang, W.
  • Stader, F.
  • Chan, P.
  • Li, L.
  • Cs, Shemesh
  • Kl, Gill
  • Hm, Jones
  • Rossato, G.
  • Wu, B.
  • Chen, Y.
  • Jy, Jin
  • Chanu, P.
Abstract

<b>Background:</b> Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients. <b>Objective:</b> To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations. <b>Methods:</b> A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both <i>in vitro</i> data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old. <b>Results:</b> Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including C<sub>min</sub>, C<sub>max</sub>, and AUC<sub>tau</sub> were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults. <b>Conclusion:</b> The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.

Topics
  • phase
  • simulation