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Role of three-dimensional cell culture in therapeutics and diagnostics: an updated review

Drug development and testing are a tedious and expensive process with a high degree of uncertainty in the clinical success and preclinical validation of manufactured therapeutic agents. Currently, to understand the drug action, disease mechanism, and drug testing, most therapeutic drug manufacturers...

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Detalles Bibliográficos
Autores principales: Biju, Tina Sara, Priya, Veeraraghavan Vishnu, Francis, Arul Prakash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10042111/
https://www.ncbi.nlm.nih.gov/pubmed/36971997
http://dx.doi.org/10.1007/s13346-023-01327-6
Descripción
Sumario:Drug development and testing are a tedious and expensive process with a high degree of uncertainty in the clinical success and preclinical validation of manufactured therapeutic agents. Currently, to understand the drug action, disease mechanism, and drug testing, most therapeutic drug manufacturers use 2D cell culture models to validate the drug action. However, there are many uncertainties and limitations with the conventional use of 2D (monolayer) cell culture models for drug testing that are primarily attributed due to poor mimicking of cellular mechanisms, disturbance in environmental interaction, and changes in structural morphology. To overcome such odds and difficulties in the preclinical validation of therapeutic medications, newer in vivo drug testing cell culture models with higher screening efficiencies are required. One such promising and advanced cell culture model reported recently is the “three-dimensional cell culture model.” The 3D cell culture models are reported to show evident benefits over conventional 2D cell models. This review article outlines and describes the current advancement in cell culture models, their types, significance in high-throughput screening, limitations, applications in drug toxicity screening, and preclinical testing methodologies to predict in vivo efficacy. GRAPHICAL ABSTRACT: [Image: see text]