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• W2896683815 abstract "Amyotrophic lateral sclerosis (ALS) is a rapid adult-onset neurodegenerative disorder characterised by the progressive loss of upper and lower motor neurons. Current treatment options are limited for ALS, with very modest effects on survival. Therefore, there is a unmet need for novel therapeutics to treat ALS. Areas covered: This review highlights the many diverse high-throughput screening platforms that have been implemented in ALS drug discovery. The authors discuss cell free assays including in silico and protein interaction models. The review also covers classical in vitro cell studies and new cell technologies, such as patient derived cell lines. Finally, the review looks at novel in vivo models and their use in high-throughput ALS drug discovery Expert opinion: Greater use of patient-derived in vitro cell models and development of better animal models of ALS will improve translation of lead compounds into clinic. Furthermore, AI technology is being developed to digest and interpret obtained data and to make 'hidden knowledge' usable to researchers. As a result, AI will improve target selection for high-throughput drug screening (HTDS) and aid lead compound optimisation. Furthermore, with greater genetic characterisation of ALS patients recruited to clinical trials, AI may help identify responsive genetic subtypes of patients from clinical trials." @default.
• W2896683815 created "2018-10-26" @default.
• W2896683815 creator A5000029365 @default.
• W2896683815 creator A5038737585 @default.
• W2896683815 date "2018-10-13" @default.
• W2896683815 modified "2023-10-17" @default.
• W2896683815 title "High-throughput drug screens for amyotrophic lateral sclerosis drug discovery" @default.
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• W2896683815 doi "https://doi.org/10.1080/17460441.2018.1533953" @default.
• W2896683815 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30317895" @default.
• W2896683815 hasPublicationYear "2018" @default.
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