Results 201 to 210 of about 96,194 (242)
From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling. [PDF]
Wang H, Arulraj T, Ippolito A, Popel AS.
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This study presents a single‐cell atlas of pseudomyxoma peritonei spanning primary and paired metastatic lesions. Distinct epithelial substates, stromal remodeling, immune exclusion, lipid metabolic reprogramming, and a candidate angiogenic network were identified in metastatic lesions.
Xi Li +14 more
wiley +1 more source
Selenium Nanoparticles Selectively Target KRAS G13D to Inhibit Colorectal Cancer
The mechanisms of SeNPs therapy in cancer treatment, encompass three parallel actions: (1) seleno‐amino acids, key metabolites, upregulate GPX2 expression, thereby inhibiting tumor metastasis via the GPX2‐HIF1α‐VEGF signaling pathway; (2) selenite (SeO32−), an inorganic metabolite, forms hydrogen bonds with amino acid residues 13–17 of the KRAS G13D ...
Xiaoting Liu +13 more
wiley +1 more source
Coupling quantitative systems pharmacology modelling to machine learning and artificial intelligence for drug development: its <i>pAIns</i> and <i>gAIns</i>. [PDF]
Folguera-Blasco N +8 more
europepmc +1 more source
Eliciting the antitumor immune response with a conditionally activated PD-L1 targeting antibody analyzed with a quantitative systems pharmacology model. [PDF]
Ippolito A +5 more
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Quantitative Systems Pharmacology
Handbook of Experimental PharmacologyHaya Majid, null Nidhi
exaly +3 more sources
Quantitative systems pharmacology: a promising approach for translational pharmacology
Drug Discovery Today: Technologies, 2016Biopharmaceutical companies have increasingly been exploring Quantitative Systems Pharmacology (QSP) as a potential avenue to address current challenges in drug development. In this paper, we discuss the application of QSP modeling approaches to address challenges in the translational of preclinical findings to the clinic, a high risk area of drug ...
K, Gadkar +3 more
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