Dataset Information

Drug repositioning in pulmonary arterial hypertension: challenges and opportunities.

ABSTRACT: Despite many advances in medical therapy for pulmonary arterial hypertension (PAH) over the past 20 years, long-term survival is still poor. Novel therapies which target the underlying pathology of PAH and which could be added to current vasodilatory therapies to halt disease progression and potentially reverse pulmonary vascular remodeling are highly sought after. Given the high attrition rates, substantial costs, and slow pace of new drug development, repositioning of "old" drugs is increasingly becoming an attractive path to identify novel treatment options, especially for a rare disease such as PAH. We here summarize the limitations of current PAH therapy, the general concept of repurposing and repositioning, success stories of approved repositioned drugs in PAH as well as novel repositioned drugs that show promise in preclinical models of pulmonary hypertension (PH) and are currently tested in clinical trials. We furthermore discuss various data-driven as well as experimental approaches currently used to identify repurposed drug candidates and review challenges for the "repositioning community" with regards to funding and patent and regulatory considerations, and to illustrate opportunities for collaborative solutions for drug repositioning relevant to PAH.

SUBMITTER: Grinnan D

PROVIDER: S-EPMC6852366 | biostudies-literature | 2019 Jan-Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Drug repositioning in pulmonary arterial hypertension: challenges and opportunities.

Grinnan Daniel D Trankle Cory C Andruska Adam A Bloom Bruce B Spiekerkoetter Edda E

Pulmonary circulation 20190101 1

Despite many advances in medical therapy for pulmonary arterial hypertension (PAH) over the past 20 years, long-term survival is still poor. Novel therapies which target the underlying pathology of PAH and which could be added to current vasodilatory therapies to halt disease progression and potentially reverse pulmonary vascular remodeling are highly sought after. Given the high attrition rates, substantial costs, and slow pace of new drug development, repositioning of "old" drugs is increasing ...[more]

PMID: 30729869

Similar Datasets

Project description:Current research and development approaches to drug discovery have become less fruitful and more costly. One alternative paradigm is that of drug repositioning. Many marketed examples of repositioned drugs have been identified through serendipitous or rational observations, highlighting the need for more systematic methodologies to tackle the problem. Systems level approaches have the potential to enable the development of novel methods to understand the action of therapeutic compounds, but requires an integrative approach to biological data. Integrated networks can facilitate systems level analyses by combining multiple sources of evidence to provide a rich description of drugs, their targets and their interactions. Classically, such networks can be mined manually where a skilled person is able to identify portions of the graph (semantic subgraphs) that are indicative of relationships between drugs and highlight possible repositioning opportunities. However, this approach is not scalable. Automated approaches are required to systematically mine integrated networks for these subgraphs and bring them to the attention of the user. We introduce a formal framework for the definition of integrated networks and their associated semantic subgraphs for drug interaction analysis and describe DReSMin, an algorithm for mining semantically-rich networks for occurrences of a given semantic subgraph. This algorithm allows instances of complex semantic subgraphs that contain data about putative drug repositioning opportunities to be identified in a computationally tractable fashion, scaling close to linearly with network data. We demonstrate the utility of our approach by mining an integrated drug interaction network built from 11 sources. This work identified and ranked 9,643,061 putative drug-target interactions, showing a strong correlation between highly scored associations and those supported by literature. We discuss the 20 top ranked associations in more detail, of which 14 are novel and 6 are supported by the literature. We also show that our approach better prioritizes known drug-target interactions, than other state-of-the art approaches for predicting such interactions.

Dataset Information

Drug repositioning in pulmonary arterial hypertension: challenges and opportunities.

Publications

Drug repositioning in pulmonary arterial hypertension: challenges and opportunities.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets