| کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن | 
|---|---|---|---|---|
| 8410166 | 1545114 | 2017 | 10 صفحه PDF | دانلود رایگان | 
عنوان انگلیسی مقاله ISI
												Emerging technologies for prediction of drug candidate efficacy in the preclinical pipeline
												
											ترجمه فارسی عنوان
													فن آوری های جدید برای پیش بینی اثربخشی داروی مصرفی در خط لوله پیشخوان 
													
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																																												موضوعات مرتبط
												
													علوم زیستی و بیوفناوری
													بیوشیمی، ژنتیک و زیست شناسی مولکولی
													بیوتکنولوژی یا زیستفناوری
												
											چکیده انگلیسی
												The pharmaceutical industry is tackling increasingly complex multifactorial diseases, resulting in increases in research & development (R&D) costs and reductions in the success rates for drug candidates during Phase 2 and 3 clinical trials, with a lack of efficacy being the primary reason for drug candidate failure. This implies that the predictive power of current preclinical assays for drug candidate efficacy is suboptimal and, therefore, that alternatives should be developed. Here, I review emerging in vitro, imaging, and in silico technologies and discuss their potential contribution to drug efficacy assessment. Importantly, these technologies are complimentary and can be bundled into the preclinical platform. In particular, patient-on-a-chip recapitulates both human genetics and physiology. The response of a patient-on-a-chip to drug candidate treatment is monitored with light-sheet fluorescent microscopy and fed into the image-analysis pipeline to reconstruct an image-based systems-level model for disease pathophysiology and drug candidate mode of action. Thus, such models could be useful tools for assessing drug candidate efficacy and safety in humans.
											ناشر
												Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Drug Discovery Today - Volume 22, Issue 11, November 2017, Pages 1598-1603
											Journal: Drug Discovery Today - Volume 22, Issue 11, November 2017, Pages 1598-1603
نویسندگان
												Denis Menshykau, 
											