The evaluation of new medicines for rare diseases (RD) including rare paediatric RDs is challenging for several reasons, among which are the small patient sample sizes, heterogeneity of patients and diseases and heterogeneity in disease knowledge. Due to these difficulties, access to effective treatments and the number of treatment options are often limited in RDs. INVENTS aims to provide clinical trial trialists, researchers and regulators with a global framework encompassing methods, workflows and evidence assessment tools to be implemented in orphan and paediatric drug development. Our ambition is to significantly improve the evaluation of evidence and regulatory decision-making through the development and validation of: refined longitudinal model-based diseases trajectories and treatment effect, improved extrapolation models, in silico trials (e.g., virtual patient cohorts), optimised model-based clinical trial designs and evidence synthesis methods. These will be evaluated through simulation studies and tested on extensive data from a range of use cases provided by our industrial partners Roche and Novartis and Real World data (RWD) from RD registry. The INVENTS framework will improve consistency and efficiency of the drug evaluation process for RD by augmenting clinical evidence without compromising its scientific integrity and providing regulators assessment credibility criteria. At the end of this 5 years project, the European industry will be able to exploit novel and improved clinical trial designs, in silico trials and RWD analysis approaches supporting drug development in RD. The European Medicine Agency and European national regulators (including Health Technology Assessment bodies) will be supplied with a general framework allowing better informed decision-making. Most importantly, RD patients will benefit from an increased and faster access to efficacious and safe treatments.

Context: Data users (i.e., researchers, innovators, regulation agencies and policy-makers) need high-quality data. In HealthData@EU, data holders are expected to make their datasets available for secondary use, providing a notion of their quality and utility and the maturity of their data quality procedures. In article 56 in the HealthData@EU proposed regulation, this notion would take the form of a label. Goal: Overall, QUANTUM aims at developing and implementing a label mechanism that could be ideally adopted in the future HealthData@EU. Methods: QUANTUM builds on 5 technical work packages (WP). WP1 conceptualises and provides technical specifications for a data quality, utility, and maturity label. WP2 designs and tests, at small-scale, the label. WP3 implements the labelling mechanism in a number of data holders. WP4 engages the data quality users’ community; and, WP5 outreaches other interested parties, including other initiatives building HealthData@EU. Expected results: a) A common concept of datasets Quality and Utility and Data holders’ Maturity; b) Technical specifications for the label (Deliverable D1.1. and D1.2); c) A conformance checking tool that yields the label (D2.1); d) An implementation report of the label mechanism (D3.1); e) Recommendations for a large-scale implementation of the QUANTUM label mechanism (D3.2); and, f) The QUANTUM Exchange Platform and Academy (D4.2 and D4.3) as instruments for capacity building. Consortium: For this purpose, 27 beneficiaries, 5 affiliated entities and 3 associated partners. The composition of the Consortium seeks to reflect the different roles and institutions in the governance of the HealthData@EU; virtually consider all types of data and science of interest; and gather the expertise of previous outstanding projects in the domain