Per definition, rare diseases affect only a small number of subjects within a given population. Taken together however, they represent a considerable medical burden, which remains poorly addressed in terms of treatment. Compared to other diseases, obstacles to the development of therapies for rare diseases include less extensive physiopathology knowledge, limited number of patients to test treatments, and poor commercial interest from the industry. Recently, advances in high-throughput and high-content screening (HTS and HCS) have been fostered by the development of specific routines that use robot- and computer-assisted technologies to automatize tasks, allowing screening of a large number of compounds in a short period of time, using experimental model of diseases. These approaches are particularly relevant for drug repositioning in rare disease, which restricts the search to compounds that have already been tested in humans, thereby reducing the need for extensive preclinical tests. In the future, these same tools, combined with computational modeling and artificial neural network analyses, may also be used to predict individual clinical responses to drugs in a personalized medicine approach

High-content drug screening for rare diseases / Bellomo, F.; Medina, D; De Leo, E.; Panarella, A.; Emma, F.. - In: JOURNAL OF INHERITED METABOLIC DISEASE. - ISSN 1573-2665. - 73:3(2017), pp. 449-455. [10.1007/s10545-017-0055-1]

High-content drug screening for rare diseases

Medina D
Co-primo
;
2017

Abstract

Per definition, rare diseases affect only a small number of subjects within a given population. Taken together however, they represent a considerable medical burden, which remains poorly addressed in terms of treatment. Compared to other diseases, obstacles to the development of therapies for rare diseases include less extensive physiopathology knowledge, limited number of patients to test treatments, and poor commercial interest from the industry. Recently, advances in high-throughput and high-content screening (HTS and HCS) have been fostered by the development of specific routines that use robot- and computer-assisted technologies to automatize tasks, allowing screening of a large number of compounds in a short period of time, using experimental model of diseases. These approaches are particularly relevant for drug repositioning in rare disease, which restricts the search to compounds that have already been tested in humans, thereby reducing the need for extensive preclinical tests. In the future, these same tools, combined with computational modeling and artificial neural network analyses, may also be used to predict individual clinical responses to drugs in a personalized medicine approach
2017
High-content drug screening for rare diseases / Bellomo, F.; Medina, D; De Leo, E.; Panarella, A.; Emma, F.. - In: JOURNAL OF INHERITED METABOLIC DISEASE. - ISSN 1573-2665. - 73:3(2017), pp. 449-455. [10.1007/s10545-017-0055-1]
File in questo prodotto:
File Dimensione Formato  
Bellomo_JIMD.pdf

accesso aperto

Tipologia: Versione Editoriale (PDF)
Licenza: Accesso privato/ristretto
Dimensione 647.9 kB
Formato Adobe PDF
647.9 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/752831
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 28
  • ???jsp.display-item.citation.isi??? 27
social impact