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A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19.

ABSTRACT: Biomedical information mining is increasingly recognized as a promising technique to accelerate drug discovery and development. Especially, integrative approaches which mine data from several (open) data sources have become more attractive with the increasing possibilities to programmatically access data through Application Programming Interfaces (APIs). The use of open data in conjunction with free, platform-independent analytic tools provides the additional advantage of flexibility, re-usability, and transparency. Here, we present a strategy for performing ligand-based in silico drug repurposing with the analytics platform KNIME. We demonstrate the usefulness of the developed workflow on the basis of two different use cases: a rare disease (here: Glucose Transporter Type 1 (GLUT-1) deficiency), and a new disease (here: COVID 19). The workflow includes a targeted download of data through web services, data curation, detection of enriched structural patterns, as well as substructure searches in DrugBank and a recently deposited data set of antiviral drugs provided by Chemical Abstracts Service. Developed workflows, tutorials with detailed step-by-step instructions, and the information gained by the analysis of data for GLUT-1 deficiency syndrome and COVID-19 are made freely available to the scientific community. The provided framework can be reused by researchers for other in silico drug repurposing projects, and it should serve as a valuable teaching resource for conveying integrative data mining strategies.

SUBMITTER: Tuerkova A

PROVIDER: S-EPMC7686838 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Legislative incentives enacted in Europe through the Regulation (EC) No. 141/2000 to incentivize orphan drug development have over the last 12 years constituted a powerful impetus toward R&D directed at the rare diseases population. However, despite therapeutic promises contained in these projects and significant economic impact linked to burgeoning R&D expenditures, the affordability and value of OMPs has become a topic of health policy debate in Europe fueled by the perception that OMPs have high acquisition costs, and by misconceptions around pricing dynamics and rare-diseases business models. In order to maintain sustainable patient access to new and innovative therapies, it is essential to address these misconceptions, and to ensure the successful continuation of a dynamic OMPs R&D within rare-diseases public health policy. Misconceptions abound regarding the pricing of rare diseases drugs and reflect a poor appreciation of the R&D model and the affordability and value of OMPs. Simulation of potential financial returns of small medium sized rare diseases companies focusing on high priced drugs show that their economic returns are likely to be close to their cost of capital. Research in rare diseases is a challenging endeavour characterised by high fixed costs in which companies accrue substantial costs for several years before potentially generating returns from the fruits of their investments. Although heavily dependent upon R&D capabilities of each individual company or R&D organization, continuous flow of R&D financial investment should allow industry to increasingly include efficiencies in research and development in cost considerations to its customers. Industry should also pro-actively work on facilitating development of a specific value based pricing approach to help understanding what constitute value in rare diseases. Policy makers must reward innovation based upon unmet need and patient outcome. Broader understanding by clinicians, the public, and policy makers of the complexity of clinical programs to deliver OMPs to market is required to better comprehend the decisions needed and made by industry. In parallel, an overt effort to consider the impact of public policies on R&D investments is key to enable policy makers to better reconcile the incentives provided by public policy decisions and companies investments decisions in a more positive manner.

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A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19.

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