CloudScreen

The proposed project focuses on the implementation of a next-generation “one-stop shop” computational platform for drug repositioning and re-targeting in precision medicine. Compared to existing computational approaches, the platform:
(a) Integrates and analyzes both 1D (genome, transcriptome, proteome, metabolome) and 3D data (molecular design and computational chemistry), rather than being limited to 1D data.
(b) Minimizes confounding errors in data mining, integration, and analysis, promoting unbiased decision-making by combining artificial and human intelligence capabilities, including:
(i) data mining services,
(ii) collaboration support services, and
(iii) decision support services.
(c) Offers dynamic updating capabilities and extends text-based services, including patents and ethical/legal considerations.
(d) Serves as a one-stop shop tool for predicting and assessing the efficacy and toxicity of repurposed molecules for new indications.

Specific objectives of the project include:
(a) the development of the next-generation CloudScreen platform, and
(b) the validation of the platform using a pilot case study of a marketed drug. This case study will utilize clearly defined data to demonstrate CloudScreen’s functionality in diverse collaboration and decision-making settings, covering heterogeneous data types and sources, thereby addressing the full spectrum of requirements for potential drug repositioning.

To this end, the efficacy and toxicity of sitagliptin will be assessed through:

• 3D cell-based and isogenic lines using mechanism-based assays and phenotypic screening,
• Functional assays,
• ADME-Tox studies (human liver microsomes, in vitro pharmacokinetic/pharmacodynamic profiling), and
• Pharmacogenomic analyses.