scholarly journals Synthetic Repurposing of Drugs in Hypertension: a Datamining Method Based on Association Rules and a Novel Discrete Algorithm

2020 ◽  
Author(s):  
Yosef Masoudi-Sobhanzadeh ◽  
Ali Masoudi-Nejad
Keyword(s):  
Drug Development ◽  
Association Rules ◽  
State Of The Art ◽  
Medical Condition ◽  
Drug Repurposing ◽  
Development Projects ◽  
Mining Method ◽  
Treatment Plans ◽  
Low Dosage ◽  
Statistical Criteria

Abstract Background Drug repurposing aims to detect the new benefits of the existing drugs and to reduce the spent time and cost of the drug development projects. Although synthetic repurposing of drugs may be more useful than single repurposing in terms of reducing toxicity and enhancing efficacy, the researchers have not taken it into account. To address the issue, a novel datamining method is introduced and applied to the repositioning of drugs in hypertension (HT), which is a serious medical condition and therefore needs to be dealt with effectively through making some improved treatment plans to help cure it. Results a novel two-step data mining method, which is based on the If-Then association rules and a novel discrete optimization algorithm, is proposed and applied to the synthetic repurposing of drugs in HT. The required data are extracted from DruhBank, KEGG, and DrugR+ databases. The outcomes presented that the proposed method outperforms the other state-of-the-art approaches in terms of different statistical criteria. In contrast to the previously proposed methods which failed to discover a list for some datasets, our method managed to suggest a combination of drugs for all the datasets. Conclusion The proposed synthetic method may revive some failed drug development projects and be a suitable plan for curing orphan and rare diseases due to using a low dosage of medicines. It is also essential to use some efficient computational methods to produce better results.

scholarly journals Synthetic Repurposing of Drugs in Hypertension: a Datamining Method Based on Association Rules and a Novel Discrete Algorithm

2020 ◽  
Author(s):  
Yosef Masoudi-Sobhanzadeh ◽  
Ali Masoudi-Nejad
Keyword(s):  
Drug Development ◽  
Association Rules ◽  
State Of The Art ◽  
Drug Repurposing ◽  
Development Projects ◽  
Synthetic Method ◽  
Mining Method ◽  
Efficient Treatment ◽  
Treatment Plans ◽  
Statistical Criteria

Abstract Background: Drug repurposing aims to detect new benefits of the existing drugs and to reduce the time and cost of drug development projects. Although synthetic repurposing of drugs may be more useful than single repurposing in terms of reducing toxicity and enhancing efficacy, the researchers have not taken it into account. To address the issue, a novel datamining method is introduced and applied to the repositioning of drugs in hypertension (HT). This disease is a complex one and needs to efficient treatment plans to cure it better.Methods: A novel two-step data mining method, which is based on the If-Then association rules and a novel discrete optimization algorithm, is proposed and applied to the synthetic repurposing of drugs in HT. The required data are extracted from DruhBank, KEGG, and DrugR+ databases. Results: The outcomes presented that the proposed method outperforms other state-of-the-art approaches in terms of different statistical criteria. Since different methods failed to discover the list for some datasets, our method could suggest a combination of drugs for all the datasets. Conclusion: Due to using a minimum dosage of medicines, the synthetic method may revive some failed drug development projects and maybe a suitable plan for curing orphan and rare diseases. Also, to achieve better outcomes, it is essential to use efficient computational methods.

Old Drugs with New Tricks; Paradigm in Drug Development Pipeline for Alzheimer’s Disease

2020 ◽  
Vol 20 ◽  
Author(s):  
Tanay Dalvi ◽  
Bhaskar Dewangan ◽  
Rudradip Das ◽  
Jyoti Rani ◽  
Suchita Dattatray Shinde ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Development ◽  
Molecular Targets ◽  
Drug Repurposing ◽  
Phase Iii ◽  
Complex Nature ◽  
New Drug ◽  
Development Pipeline ◽  
Old Drugs

: The most common reason behind dementia is Alzheimer’s disease (AD) and it is predicted to be the third lifethreatening disease apart from stroke and cancer for the geriatric population. Till now only four drugs are available in the market for symptomatic relief. The complex nature of disease pathophysiology and lack of concrete evidences of molecular targets are the major hurdles for developing new drug to treat AD. The the rate of attrition of many advanced drugs at clinical stages, makes the de novo discovery process very expensive. Alternatively, Drug Repurposing (DR) is an attractive tool to develop drugs for AD in a less tedious and economic way. Therefore, continuous efforts are being made to develop a new drug for AD by repursing old drugs through screening and data mining. For example, the survey in the drug pipeline for Phase III clinical trials (till February 2019) which has 27 candidates, and around half of the number are drugs which have already been approved for other indications. Although in the past the drug repurposing process for AD has been reviewed in the context of disease areas, molecular targets, there is no systematic review of repurposed drugs for AD from the recent drug development pipeline (2019-2020). In this manuscript, we are reviewing the clinical candidates for AD with emphasis on their development history including molecular targets and the relevance of the target for AD.

scholarly journals Drug Repurposing Opportunities in Pancreatic Ductal Adenocarcinoma

2021 ◽  
Vol 14 (3) ◽  
pp. 280
Author(s):  
Rita Rebelo ◽  
Bárbara Polónia ◽  
Lúcio Lara Santos ◽  
M. Helena Vasconcelos ◽  
Cristina P. R. Xavier
Keyword(s):  
Clinical Trials ◽  
Drug Development ◽  
Pancreatic Ductal Adenocarcinoma ◽  
De Novo ◽  
Drug Repurposing ◽  
Metastatic Tumor ◽  
Therapeutic Options ◽  
Ductal Adenocarcinoma ◽  
Clinical Indication ◽  
Novel Treatments

Pancreatic ductal adenocarcinoma (PDAC) is considered one of the deadliest tumors worldwide. The diagnosis is often possible only in the latter stages of the disease, with patients already presenting an advanced or metastatic tumor. It is also one of the cancers with poorest prognosis, presenting a five-year survival rate of around 5%. Treatment of PDAC is still a major challenge, with cytotoxic chemotherapy remaining the basis of systemic therapy. However, no major advances have been made recently, and therapeutic options are limited and highly toxic. Thus, novel therapeutic options are urgently needed. Drug repurposing is a strategy for the development of novel treatments using approved or investigational drugs outside the scope of the original clinical indication. Since repurposed drugs have already completed several stages of the drug development process, a broad range of data is already available. Thus, when compared with de novo drug development, drug repurposing is time-efficient, inexpensive and has less risk of failure in future clinical trials. Several repurposing candidates have been investigated in the past years for the treatment of PDAC, as single agents or in combination with conventional chemotherapy. This review gives an overview of the main drugs that have been investigated as repurposing candidates, for the potential treatment of PDAC, in preclinical studies and clinical trials.

State of the Art Lecture: Erythropoietin receptor: application in drug development

1995 ◽  
Vol 10 (supp2) ◽  
pp. 28-34 ◽  
Author(s):  
L. K. Jolliffe ◽  
S. A. Middleton ◽  
F. P. Barbone ◽  
D. L. Johnson ◽  
F. J. McMahon ◽  
...  
Keyword(s):  
Drug Development ◽  
State Of The Art ◽  
Erythropoietin Receptor

scholarly journals Repurposing as a strategy for the discovery of new anti-leishmanials: the-state-of-the-art

Parasitology ◽  
2017 ◽  
Vol 145 (2) ◽  
pp. 219-236 ◽  
Author(s):  
REBECCA L. CHARLTON ◽  
BARTIRA ROSSI-BERGMANN ◽  
PAUL W. DENNY ◽  
PATRICK G. STEEL
Keyword(s):  
State Of The Art ◽  
Drug Repurposing ◽  
Tropical Disease ◽  
Neglected Tropical Disease ◽  
Current State ◽  
Disability Adjusted Life ◽  
Life Years ◽  
Vector Borne ◽  
Faster Development ◽  
New Treatments

SUMMARYLeishmaniasis is a vector-borne neglected tropical disease caused by protozoan parasites of the genus Leishmania for which there is a paucity of effective viable non-toxic drugs. There are 1·3 million new cases each year causing considerable socio-economic hardship, best measured in 2·4 million disability adjusted life years, with greatest impact on the poorest communities, which means that desperately needed new antileishmanial treatments have to be both affordable and accessible. Established medicines with cheaper and faster development times may hold the cure for this neglected tropical disease. This concept of using old drugs for new diseases may not be novel but, with the ambitious target of controlling or eradicating tropical diseases by 2020, this strategy is still an important one. In this review, we will explore the current state-of-the-art of drug repurposing strategies in the search for new treatments for leishmaniasis.

scholarly journals MINING ESSENTIAL RULES USING FREQUENT CLOSED ITEMSETS LATTICE

2009 ◽  
Vol 12 (11) ◽  
pp. 49-56
Author(s):  
Bac Hoai Le ◽  
Bay Dinh Vo
Keyword(s):  
Association Rules ◽  
Frequent Itemsets ◽  
Suitable Method ◽  
Mining Method ◽  
Parent Child Relationship ◽  
Left Hand ◽  
Child Relationship ◽  
Closed Itemsets ◽  
The Cost ◽  
Parent Child

In traditional mining of association rules, finding all association rules from databases that satisfy minSup and minConf faces with some problems in case of the number of frequent itemsets is large. Thus, it is necessary to have a suitable method for mining fewer rules but they still embrace all rules of traditional mining method. One of the approaches that is the mining method of essential rules: it only keeps the rule that its left hand side is minimal and its right side is maximal (follow in parent-child relationship). In this paper, we propose a new algorithm for mining the essential rules from the frequent closed itemsets lattice to reduce the time of mining rules. We use the parent-child relationship in lattice to reduce the cost of considering parent-child relationship and lead to reduce the time of mining rules.

Requirements Engineering for Courseware Development

2011 ◽  
pp. 170-188 ◽  
Author(s):  
Ines Grützner ◽  
Barbara Paech
Keyword(s):  
Requirements Engineering ◽  
State Of The Art ◽  
Comprehensive Analysis ◽  
Further Education ◽  
The State ◽  
Requirements Specification ◽  
Development Projects ◽  
Learning Context ◽  
Active Involvement ◽  
The Web

Technology-enabled learning using the Web and the computer and courseware, in particular, is becoming more and more important as an addition, extension, or replacement of traditional further education measures. This chapter introduces the challenges and possible solutions for requirements engineering (RE) in courseware development projects. First the state-of-the-art in courseware requirements engineering is analyzed and confronted with the most important challenges. Then the IntView methodology is described as one solution for these challenges. The main features of IntView RE are: support of all roles from all views on courseware RE; focus on the audience supported by active involvement of audience representatives in all activities; comprehensive analysis of the sociotechnical environment of the audience and the courseware as well as of the courseware learning context; coverage of all software RE activities; and development of an explicit requirements specification documentation.

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