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An integrative approach using real-world data to identify alternative therapeutic uses of existing drugs.

ABSTRACT: Different computational approaches are employed to efficiently identify novel repositioning possibilities utilizing different sources of information and algorithms. It is critical to propose high-valued candidate-repositioning possibilities before conducting lengthy in vivo validation studies that consume significant resources. Here we report a novel multi-methodological approach to identify opportunities for drug repositioning. We performed analyses of real-world data (RWD) acquired from the United States Food and Drug Administration's Adverse Event Reporting System (FAERS) and the claims database maintained by the Japan Medical Data Center (JMDC). These analyses were followed by cross-validation through bioinformatics analyses of gene expression data. Inverse associations revealed using disproportionality analysis (DPA) and sequence symmetry analysis (SSA) were used to detect potential drug-repositioning signals. To evaluate the validity of the approach, we conducted a feasibility study to identify marketed drugs with the potential for treating inflammatory bowel disease (IBD). Primary analyses of the FAERS and JMDC claims databases identified psycholeptics such as haloperidol, diazepam, and hydroxyzine as candidates that may improve the treatment of IBD. To further investigate the mechanistic relevance between hit compounds and disease pathology, we conducted bioinformatics analyses of the associations of the gene expression profiles of these compounds with disease. We identified common biological features among genes differentially expressed with or without compound treatment as well as disease-perturbation data available from open sources, which strengthened the mechanistic rationale of our initial findings. We further identified pathways such as cytokine signaling that are influenced by these drugs. These pathways are relevant to pathologies and can serve as alternative targets of therapy. Integrative analysis of RWD such as those available from adverse-event databases, claims databases, and transcriptome analyses represent an effective approach that adds value to efficiently identifying potential novel therapeutic opportunities.

SUBMITTER: Hosomi K

PROVIDER: S-EPMC6177143 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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An integrative approach using real-world data to identify alternative therapeutic uses of existing drugs.

Hosomi Kouichi K Fujimoto Mai M Ushio Kazutaka K Mao Lili L Kato Juran J Takada Mitsutaka M

PloS one 20181009 10

Different computational approaches are employed to efficiently identify novel repositioning possibilities utilizing different sources of information and algorithms. It is critical to propose high-valued candidate-repositioning possibilities before conducting lengthy in vivo validation studies that consume significant resources. Here we report a novel multi-methodological approach to identify opportunities for drug repositioning. We performed analyses of real-world data (RWD) acquired from the Un ...[more]

PMID: 30300381

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Project description:BackgroundPre-travel consultation and chemoprophylaxis measures for malaria are a key component in the prevention of imported malaria in travelers. In this study we report a predictive tool for assessing personalized malaria risk in travelers based on the analysis of electronic medical records from travel consultations. The tool aims to guide physicians in the recommendation of appropriate prophylaxis prior to their trip. We also provide best-practice recommendations for pre-processing noisy and highly sparse real world evidence data.MethodsWe leveraged a large EMR dataset, containing demographic information about travelers and their destination. The data has been previously preprocessed using various strategies to handle missing and unbalanced data. We compared multiple machine learning approaches to assess the risk of malaria acquisition in travelers during their travels. Additionally, a feature importance analysis was performed using SHAP (SHapley Additive Explanations) values to identify patterns associated with malaria risk.ResultsOur study revealed that our XGB models achieved high predictive capacity (AUC >0.80). The most significant features predicting malaria infection during travel included travel destinations with low malaria risk, vaccination history, number of countries visited, age, and trip duration. Remarkably, we were able to obtain a reduced model with only five features. When comparing this model with a population of travelers recommended for malaria chemoprophylaxis, we observed that it was deemed necessary in only 40% of these travelers. This suggests that 60% received chemoprophylaxis despite having a low personalized risk of malaria.ConclusionWe have developed an algorithmic tool that utilizes a concise survey to generate a personalized travel risk assessment, effectively minimizing the prescription of unnecessary malaria chemoprophylaxis. Through the identification of patterns linked to predictions, our model significantly enhances the efficacy of pre-travel consultations.

Project description:BackgroundFinding new therapeutic uses for existing medicines could lead to safe, affordable and timely new treatment options for patients with high medical needs. However, due to a lack of economic incentives, pharmaceutical developers are rarely interested to invest in research with approved medicines, especially when they are out of basic patent or regulatory protection. Consequently, potential new uses for these medicines are mainly studied in independent clinical trials initiated and led by researchers from academia, research institutes, or collaborative groups. Yet, additional financial support is needed to conduct expensive phase III clinical trials to confirm the results from exploratory research.MethodsIn this study, scientific and grey literature was searched to identify and evaluate new mechanisms for funding clinical trials with repurposed medicines. Semi-structured interviews were conducted with 16 European stakeholders with expertise in clinical research, funding mechanisms and/or drug repurposing between November 2018 and February 2019 to consider the future perspectives of applying new funding mechanisms.ResultsTraditional grant funding awarded by government and philanthropic organisations or companies is well known and widely implemented in all research fields. In contrast, only little research has focused on the application potential of newer mechanisms to fund independent clinical research, such as social impact bonds, crowdfunding or public-private partnerships. Interviewees stated that there is a substantial need for additional financial support in health research, especially in areas where there is limited commercial interest. However, the implementation of new funding mechanisms is facing several practical and financial challenges, such as a lack of expertise and guidelines, high transaction costs and difficulties to measure health outcomes. Furthermore, interviewees highlighted the need for increased collaboration and centralisation at a European and international level to make clinical research more efficient and reduce the need for additional funding.ConclusionsNew funding mechanisms to support clinical research may become more important in the future but the unresolved issues identified in the current study warrant further exploration.

Dataset Information

An integrative approach using real-world data to identify alternative therapeutic uses of existing drugs.

Publications

An integrative approach using real-world data to identify alternative therapeutic uses of existing drugs.

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