piperacillin, amphotericin B, and doxycycline (Liu et al. 2020). Every drug candi-

date listed was supported with scientific literature for reference.

Tools and platforms enhanced with the aid of network-based approaches and AI

allow researchers to come up with candidate drugs more efficiently while scanning

through massive data sets simultaneously. In addition, the outcomes of these

analyses and methods are considered to have higher potential. This is due to the

integration of more stringent variables within each search and wider data coverage.

Connections are also more reliable as data sets mostly include validated experimen-

tal findings. Figure 5.3 provides some of the popular databases, tools, and platforms

that can be used for DR.

5.3.3

Examples of DR for Genetic Diseases

5.3.3.1 Alzheimer’s Disease

AD is an age-related neurodegenerative disease (Alzheimer disease 2021). The

development of this disease is irreversible and progressive, causing slow disruption

to the thought process, memory, and motor performance, typically after age

65 (Alzheimer disease 2021). About 75% of AD cases are believed to be sporadic,

with no history of the disorder in their family and 25% are from familial inheritance

(Alzheimer disease 2021). The progression of AD is complex and not fully under-

stood. From what it is known, the disease manifests by an accumulation of abnormal

amounts of amyloid proteins and tau proteins in the brain, affecting neuronal

function, therefore resulting in a progressive loss of brain function (Tackenberg

et al. 2020).

In the context of DR, numerous literature and computational approaches are

preferred. A study conducted by Zhang et al. has reported 244 genetic variations,

14 epigenetic modifications, 98 proteins, and 86 metabolites associated with AD by

analysing “omics” data comprising genomics, epigenomics, proteomics, and

metabolomics data from the GWAS Catalogue, PubMed, and HMDB databases

(Zhang et al. 2016). Subsequently, DrugBank and Therapeutic Target Database

(TTD) were used for drug-target data extraction. With an in-house developed anti-

AD ranking algorithm, two best candidates for drug target (i.e., CD33 and migration

inhibitory factor (MIF)/CD74 receptors) and seven potential existing drug

repurposing candidates were found (Zhang et al. 2016). CD33 leads to the

impairment of microglia-mediated clearance of Aβ, resulting in an accumulation of

amyloid plaques in the brain (Jiang et al. 2014). Hence, an anti-CD33 inhibitor like

gemtuzumab ozogamicin, which was first approved in 2000 for CD33-positive acute

myeloid leukaemia, now holds a significant therapeutic potential for AD (Zhang

et al. 2016; Jiang et al. 2014).

5.3.3.2 Cystic Fibrosis

CF is an autosomal recessive and hereditary disease that affects the lungs and

digestive system (Delavan et al. 2018; De Boeck et al. 2017). It is life-threatening

and affects more than 70,000 individuals worldwide, primarily Caucasians (About

5

Genomic Approaches for Drug Repositioning

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