The proposed Demonstrator Project Swiss Pediatric Data Warehouse - SwissPedDW is based on the vision of the submitting Consortium to optimise and individualise dosing schemes for children, based on the analysis of clinical, pharmacokinetics (PK) and omics Data. SwissPedDW will provide the required infrastructure to reach this goal. SwissPedDW builds on the infrastructure established in our SPHN Infrastructure Development Project SwissPK cdw - Swiss PharmacoKinetics clinical data warehouse (2019/2020). SwissPK cdw is a modular platform for the centralised storage, management, including quality assurance, exploration and analysis of pseudonymised paediatric clinical Data. It is implemented in Leonhard Med, one of the Swiss BioMedIT nodes. SwissPK cdw follows FAIR principles and the SPHN guidelines. Data flows were established to SwissPK cdw from the University Children's Hospital Zurich (KiSpi), the University Children's Hospital Basel (UKBB) and the University of Basel (UB). The clinical and research primary interests of SwissPK cdw are to provide a centralised platform for patient Data and their analysis within the framework of SPHN/PHRT, SwissPedNet and SwissPedDose towards optimising and individualising dosing schemes for paediatric patients, based on drug plasma concentration measurements obtained in routine clinical care and prospective clinical studies. SwissPK cdw is a unique central Data source for drug plasma concentration measurements in Switzerland. Only few such Databases exist worldwide. The main weakness of SwissPK cdw in its current form is the low number of participating hospitals. SwissPK cdw should furthermore be expanded for the storage, management, quality assurance and analysis of omics Data, as omics Data are indispensable for the intended uses of SwissPK cdw . The infrastructure-related goals of the Demonstrator Project SwissPedDW are: to establish data flows from all Swiss University Children's Hospitals to the SwissPK cdw platform to implement the RDF data format in SwissPK cdw (Data were transferred and stored in csv format so far) to establish the infrastructure for omics Data within SwissPK cdw (whole genome sequencing, WGS, metabolomics) by generating, storing, managing and quality-assuring a pilot set of omics Data to define Data semantics and set up Data flows with the hospitals for the provision of routine and prospective PK-related Data and of biosamples for omics analysis to define strategies in collaboration with other SPHN/PHRT projects for the sustainable management of patient Data, in particular omics Data to provide a national platform for the central storage, management and quality assurance and analysis of Data from paediatric centres to generate sustainable and interoperable Metadata and agreement forms for Data access and use which will be published in Metadata repositories for optimising the findability, accessibility and reusability of the stored Data and to define policies for the access to the Data/Metadata for other SPHN/PHRT projects The clinical goals of the Demonstrator Project SwissPedDW are: to provide a national platform for the analysis of clinical and omics Data of children to optimise / individualise dosing schemes for children, in collaboration with SwissPedNet/SwissPedDose, based on real-world Data stored, managed, quality-assured and analysed within SwissPK cdw . The readiness of the tested elements shall be demonstrated by data flows from all Swiss University Children's Hospitals to SwissPK cdw and BioMedIT initiation of the re-evaluation/definition together with SwissPedNet and SwissPedDose of dosing schemes for gentamicin, voriconazole and busulfan, based on our recent SwissPK cdw -related studies and on additional routine Data provided by the hospitals onboarded during the proposed Demonstrator project. To the best of our knowledge, SwissPedDW , based on SwissPK cdw , would be unique as a central infrastructure for the storage, management, quality assurance and analysis of clinical and omics Data, all within the highly secure BioMedIT network of SPHN/PHRT. Our centralised approach has the potential to reduce redundancies and inconsistencies in multi-centric Data-driven projects. It enables complex multi-centric Data analyses where Data need to be combined for analysis, such as population PK analyses in our project. A relevant prerequisite for the success of our infrastructure is the confidence of the Data-providing parties in the FAIR management and provider-controlled use of the Data.