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A supervised machine-learning approach for the efficient development of a multi method (LC-MS) for a large number of drugs and subsets thereof: focus on oral antitumor agents.
Kehl, Niklas; Gessner, Arne; Maas, Renke; Fromm, Martin F; Taudte, R Verena.
Affiliation
  • Kehl N; Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Gessner A; Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Maas R; Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Fromm MF; FAU NeW - Research Center for New Bioactive Compounds, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Taudte RV; Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Clin Chem Lab Med ; 62(2): 293-302, 2024 Jan 26.
Article in En | MEDLINE | ID: mdl-37606251
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Antineoplastic Agents Type of study: Guideline Limits: Humans Language: En Journal: Clin Chem Lab Med Journal subject: QUIMICA CLINICA / TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2024 Document type: Article Affiliation country: Germany Country of publication: Germany
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Antineoplastic Agents Type of study: Guideline Limits: Humans Language: En Journal: Clin Chem Lab Med Journal subject: QUIMICA CLINICA / TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2024 Document type: Article Affiliation country: Germany Country of publication: Germany