The Friends of Cancer Research Real World Data (RWD) Collaboration Pilot 2.0: Methodological Recommendations from Oncology Case Studies

INTRODUCTION:The Innovative Medicines Initiative, IMI-GetReal project aimed to explore incorporation of robust methods for real-world data (RWD) collection and synthesis earlier in the medicines development process, both by pharmaceutical companies and healthcare decision makers. The focus was on the potential use of RWD, alone or in combination with randomized controlled trials (RCTs), to demonstrate effectiveness of new interventions. Four case studies were conducted in multiple disease areas to examine methods for predicting drug effectiveness and the perspectives of different stakeholders on these methods. This study aimed to identify practical obstacles in accessing and using RWD and RCT data for effectiveness research conducted as part of these case studies.METHODS:Qualitative content analysis was conducted to identify and characterize key issues relating to accessing and analysing study data from external sources, both RWD and RCTs.RESULTS:Accessing RWD from registries proved difficult due to multiple reasons, including: complex and non-transparent application procedures, resistance from registry owners to discuss applications and datasets not being research-ready within project timeframes. There were also issues with the RWD eventually accessed, including a lack of individual participant data (IPD) and incomplete data. Where access to IPD from RCTs was obtainable, there were restrictions imposed on how it could be used. For example, it could not be used to target analysis on an individual product, but rather explore methodologies for data synthesis in a product-anonymised setting. This condition encouraged additional data sharing by other stakeholders.CONCLUSIONS:Despite the collaborative, multi-stakeholder nature of IMI-GetReal and proper disclosures with data owners, access to data proved challenging. Such barriers to data accessibility can delay effectiveness research, restrict opportunities for the development of methods incorporating RWD and diminish the potential use of RWD in decision making. Where data is intended to be used for this purpose, sufficient attention should be paid to these potential barriers.

Download Full-text

YAMATO: Yet-another more advanced top-level ontology

Applied Ontology ◽

10.3233/ao-210257 ◽

2021 ◽

pp. 1-22

Author(s):

Riichiro Mizoguchi ◽

Stefano Borgo

Keyword(s):

Case Studies ◽

Real World ◽

Modern Society ◽

Real World Data ◽

World Data ◽

The World ◽

Philosophical Contribution

yamato sharply distinguishes itself from other existing upper ontologies in the following respects. (1) Most importantly, yamato is designed with both engineering and philosophical minds. (2) yamato is based on a sophisticated theory of roles, given that the world is full of roles. (3) yamato has a tenable theory of functions which helps to deal with artifacts effectively. (4) Information is a ‘content-bearing’ entity and it differs significantly from the entities that philosophers have traditionally discussed. Taking into account the modern society in which a flood of information occurs, yamato has a sophisticated theory of informational objects (representations). (5) Quality and quantity are carefully organized for the sake of greater interoperability of real-world data. (6) The philosophical contribution of yamato includes a theory of objects, processes, and events. Those features are illustrated with several case studies. These features lead to the intensive application of yamato in some domains such as biomedicine and learning engineering.

Download Full-text