| Literature DB >> 30317895 |
Alexander McGown1, Matthew John Stopford1.
Abstract
INTRODUCTION: 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.Entities:
Keywords: Amyotrophic lateral sclerosis (ALS); drug discovery; high-throughput drug screening (HTDS)
Mesh:
Year: 2018 PMID: 30317895 DOI: 10.1080/17460441.2018.1533953
Source DB: PubMed Journal: Expert Opin Drug Discov ISSN: 1746-0441 Impact factor: 6.098