*2.3.6.1 Network-based cluster approaches*

These kinds of approaches have been proposed in order to determine the mechanism/relationships between the drug and the disease or the drug and the target/ receptor. The biological interaction pattern in our human body has a characteristic network. The entities such as disease, drug and the protein share similar kind of interaction pattern in the network-based cluster approaches. This approach has been incorporated to develop various kinds of modules using the network topology-based cluster algorithms such as cliques/clusters/groups, subnetworks. They portray relationships or pattern of interaction between drug-drug, disease, target/receptors. The overlapping clusters cannot be detected by CLIQUE, OPTICS, DBSCAN and STING [20]. These modules are most commonly used network-based cluster approaches. Examples of repurposed drugs using network approach are atomoxetine indicated for Parkinson's disease and repurposed for attention deficit

hyperactivity disorder (ADHD), etanercept indicated for rheumatoid arthritis and repurposed for asthma [3].

### *2.3.6.2 Network-based propagation approaches*

These approaches have been categorized as another important approach under network strategies. They can be classified in two types: local and global approach. The information under this approach circulates from node (source) to all the nodes which are networked to each other and followed by subnetwork nodes [19].

Many studies have stated that these techniques are really being helpful and providing some useful results in obtaining interaction patterns/relationships between the drug—target/receptor, gene, disease. Local propagation procures small/fewer amount of data from the database and displays improper results. In opposing to this global approach gathers all of the data from database/network and make correct predictions. Currently, researchers are working on global approach for drug repurposing/repositioning [1, 19].

#### *2.3.7 Genetic association*

Genome-wide association studies (GWAS) has been widely used to determine the genetic alterations in whole genome which contribute to specific diseases and provides the pathophysiology of various diseases. The data obtained from the GWAS helps to identify novel targets which contributes to the specific diseases can provide repositioning of several drugs. Human Genome Project has already been completed and vast amount of data is available for specific diseases. So, there is a huge opportunity for various drugs that could be repositioned and provide beneficial outcome. However, the data available from GWAS does not provide exact pathophysiological mechanism and the available data is not appropriate due to the gene variant. As, there many still thousands of genes hidden which is yet to be discovered and these hidden genes may be contributing largely behind pathophysiology of various diseases [1].

#### *2.3.8 Signature-based repurposing*

Signature inversion method is defined as the approaches which screens the inverse relationships/interaction pattern of drug and the disease by correlating the gene expression information between the drug-disease. As defined this method utilizes the expression of genes to discover off-target mechanisms as well as novel pathophysiological mechanisms related to diseases. One of the prime advantages of these approaches is that they identify unique/novel mechanisms of action for drugs. Additionally, unlike knowledge-based methods that use the databases to predict the mechanism or action of drugs, more molecular- and/or genetic-level mechanisms are involved in signature-based repurposing methods [1].

#### *2.3.9 Text mining (data mining) and semantic approach*

The data available in the literature contains large and varied amount of information/data for all the drugs in the database as well as for the diseases (including orphan/rare diseases) which are commonly occurred in individuals. Through these data one can potentially predict the new indications of existing drugs via text mining approach. Gene ontology/biological ontology allows us to correlate the available information and analyze all the biological data from different databases. One such

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*Drug Repurposing and Orphan Disease Therapeutics DOI: http://dx.doi.org/10.5772/intechopen.91941*

repurposed for pancreatic neuroendocrine tumors [3].

repurposed for hyperkinesis in children (ADHD) [3].

examples of repurposed drugs described in **Table 2**.

drug repurposing were 30% [23].

be 5 in 10,000 [1, 22].

example of repurposed drug is Everolimus indicated for immunosuppressant and

**3. Drug repurposing/repositioning for orphan diseases/disorders**

Semantic inference incorporates techniques like topic modeling which utilizes different databases for the discovery of repurposing of existing drugs. Example of repurposed drug was amphetamine which was indicated for CNS stimulant and

Approximately 7000 rare diseases are currently present in the world and more than 95% among these lack therapeutic agents approved by US-FDA [1]. The concept behind orphan disease might be many yet they have a single key point which is common that is the disease affects a minor part of the population. The definition of orphan diseases differs in different countries. In US, orphan disease is the one affecting fewer than 2 lakh people, in Japan the disease should affect fewer than 50,000 people to be called as orphan disease and in Europe the prevalence should

It is very challenging to develop new drugs for the treatment of rare diseases because the number of patients suffering from these diseases are very limited and are distributed over a vast geographical area. Another issue is of high variability among these diseases, influenced mostly by genetic factors. Financially, the development and subsequent production of these drugs is not viable for the pharmaceutical companies therefore drug repurposing for orphan diseases is a good option [22]. The patients requiring immediate treatment also do not have the luxury of more time at their disposal therefore a new strategy is needed so that the drugs are made available faster and cheaper to these patients. The pathology and various biochemical pathways of many orphan diseases are not very well known. Computational techniques will be a helpful option in the case where the underlying mechanism of the disease is not well understood. The advancement of the huge scale genomic sequencing project may lead to the understanding of the genetic variations that may be the cause of these diseases and it may lead to possibility of repurposing the drugs which are targeting the concerned protein [1]. There are few

The approved drugs have already undergone intense testing like the safety studies, bioavailability studies and PK/PD studies and therefore drug repurposing leads to significant cost cutting and faster development [22]. Hence, this is an attractive prospect for the pharmaceutical industry as well. A total of 51 new medications reaching the market in 2009, the drugs which came to the market via the strategy of

There are particular regulations designed to promote the research into orphan diseases and these rules could give market exclusiveness in circumstances repurposed agents cannot be protected by the patent. The Orphan Drug Act (ODA; 1983) was introduced for the first time which reflected the issues regarding the economics of drug development for orphan disease and how it was unfavorable. FDA has licensed about 360 agents for rare diseases since 1983 as compared to less than 50 agents before 1983 [24]. US legislation provides for faster FDA approval, tax incentives and funding support for research in orphan diseases. Market protection is also one of the incentives in which a generic form is not allowed to come to the market for 7 years. Tax concession, waiving of the regulatory fees are also the incentives which are provided. Similar legislation has been implemented in Singapore, Japan, Europe and Australia after the success of ODA, with each jurisdiction having a little bit of difference in the definition of the indication and the incentives to be provided [1].

*Drug Repurposing - Hypothesis, Molecular Aspects and Therapeutic Applications*

repurposed for asthma [3].

posing/repositioning [1, 19].

ology of various diseases [1].

*2.3.8 Signature-based repurposing*

*2.3.7 Genetic association*

nodes [19].

*2.3.6.2 Network-based propagation approaches*

hyperactivity disorder (ADHD), etanercept indicated for rheumatoid arthritis and

These approaches have been categorized as another important approach under network strategies. They can be classified in two types: local and global approach. The information under this approach circulates from node (source) to all the nodes which are networked to each other and followed by subnetwork

Many studies have stated that these techniques are really being helpful and providing some useful results in obtaining interaction patterns/relationships between the drug—target/receptor, gene, disease. Local propagation procures small/fewer amount of data from the database and displays improper results. In opposing to this global approach gathers all of the data from database/network and make correct predictions. Currently, researchers are working on global approach for drug repur-

Genome-wide association studies (GWAS) has been widely used to determine the genetic alterations in whole genome which contribute to specific diseases and provides the pathophysiology of various diseases. The data obtained from the GWAS helps to identify novel targets which contributes to the specific diseases can provide repositioning of several drugs. Human Genome Project has already been completed and vast amount of data is available for specific diseases. So, there is a huge opportunity for various drugs that could be repositioned and provide beneficial outcome. However, the data available from GWAS does not provide exact pathophysiological mechanism and the available data is not appropriate due to the gene variant. As, there many still thousands of genes hidden which is yet to be discovered and these hidden genes may be contributing largely behind pathophysi-

Signature inversion method is defined as the approaches which screens the inverse relationships/interaction pattern of drug and the disease by correlating the gene expression information between the drug-disease. As defined this method utilizes the expression of genes to discover off-target mechanisms as well as novel pathophysiological mechanisms related to diseases. One of the prime advantages of these approaches is that they identify unique/novel mechanisms of action for drugs. Additionally, unlike knowledge-based methods that use the databases to predict the mechanism or action of drugs, more molecular- and/or genetic-level mechanisms

The data available in the literature contains large and varied amount of information/data for all the drugs in the database as well as for the diseases (including orphan/rare diseases) which are commonly occurred in individuals. Through these data one can potentially predict the new indications of existing drugs via text mining approach. Gene ontology/biological ontology allows us to correlate the available information and analyze all the biological data from different databases. One such

are involved in signature-based repurposing methods [1].

*2.3.9 Text mining (data mining) and semantic approach*

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example of repurposed drug is Everolimus indicated for immunosuppressant and repurposed for pancreatic neuroendocrine tumors [3].

Semantic inference incorporates techniques like topic modeling which utilizes different databases for the discovery of repurposing of existing drugs. Example of repurposed drug was amphetamine which was indicated for CNS stimulant and repurposed for hyperkinesis in children (ADHD) [3].
