Rare genetic diseases: update on diagnosis, treatment and online resources

Pogue, Robert; Cavalcanti, Denise Pontes; Shanker, Shreya; Andrade, Rosângela Vieira de; Aguiar, Lana Ribeiro; Carvalho, Juliana Lott; Costa, Fabrício F.

doi:10.1016/j.drudis.2017.11.002

Cited by 66 publications

(52 citation statements)

References 70 publications

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“…Besides, this method maybe a suitable therapy plan for treating orphans or diseases because developing an efficient drug is costly and time-consuming and therefore not affordable for drug companies [59]. Another discovered medication for managing the HT is Dapiprazole which is an alpha-blocker agent.…”

Section: -Discussionmentioning

confidence: 99%

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

Masoudi-Sobhanzadeh

Masoudi‐Nejad²

2020

Preprint

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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.

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Section: -Discussionmentioning

confidence: 99%

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

Masoudi-Sobhanzadeh

Masoudi‐Nejad²

2020

Preprint

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show abstract

“…Besides, our method may be a suitable therapy choice for treating orphans or diseases, in which developing an efficient drug is not affordable for drug companies because of the huge volume of cost and time (62). Another discovered medication for managing the HT is Dapiprazole which is an alpha-blocker agent.…”

Section: -Discussionmentioning

confidence: 99%

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

Masoudi-Sobhanzadeh

Masoudi‐Nejad²

2020

Preprint

View full text Add to dashboard Cite

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.

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“…Gathering real-world data on any sequelae may therefore be the only available method of learning about effectiveness and side effects, and therefore of ameliorating vulnerability (see for example (Lipworth 2019)). As noted above, similar considerations may be applied to research involving children, or on research into rare or 'orphan' diseases, for which sweeps of large datasets may provide otherwise unavailable insights into prevalence, aetiology, and possible treatment (Costa 2014;Pogue et al 2018;Austin and Gadhia 2017). However, for some problems that need to be addressed with this notion, see (Halfmann et al 2017).…”

Section: Group Harmsmentioning

confidence: 99%

An Ethics Framework for Big Data in Health and Research

Xafis

Schaefer

Labude

et al. 2019

ABR

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Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and Policy-relevant Ethics in Singapore (SHAPES) Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts. It also describes a set of substantive and procedural values that can be weighed up in addressing these concerns, and a step-by-step process for identifying, considering, and resolving the ethical issues arising from big data uses in health and research. This Framework is subsequently applied in the papers published in this Special Issue. These papers each address one of six domains where big data is currently employed: openness in big data and data repositories, precision medicine and big data, real-world data to generate evidence about healthcare interventions, AIassisted decision-making in healthcare, public-private partnerships in healthcare and research, and cross-sectoral big data.

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Rare genetic diseases: update on diagnosis, treatment and online resources

Cited by 66 publications

References 70 publications

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

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

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

An Ethics Framework for Big Data in Health and Research

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