For collecting and processing RWD, ONCOVALUE introduces automated and standardized methods as part of standard clinical routines. The project is first focusing on developing practices through set use cases, developing and testing a structured real-time data collection pathway for breast cancer and non-small cell lung cancer (NSCLC), with plans to widen horizons in the near future to additional cancer types.
First versions of guidelines and standard operating procedures (SOPs) have been developed for the collection, processing and basic analytics of structured data. The documents can be used by other cancer centres that aim at building fully structured data collection practices into their clinical routines. In structured EMRs, data elements that are available in a structured format have been evaluated and novel documentation templates implemented to increase the availability of structured data. The templates will help both the clinicians to document relevant data consistently and ensure that all necessary RWD is documented for later utilization.
The project is developing a “future-proof” HTA-framework, which will provide guidance for using RWD-based HTAs, utilizing both structured and unstructured data. To accomplish this, the HTA recommendations related to the acceptance of RWE have been comprehensively explored.
Developing and validating AI models requires annotated image and text data. For medical images, annotated imaging data has been prepared using a tool developed within the project to streamline annotation. This data is used for the development of AI algorithms for automatic disease progression quantification. For clinical report data, the capabilities of the Clinical Data Collector (CDC)-tool to automatically identify and extract structured data from unstructured medical notes have been explored. Next, text data will also be annotated to further develop natural language processing (NLP) models for data structuring. For this purpose, a text annotation training has been created, simultaneously launching the Knowledge Hub which will serve as an integral centre of excellence, hosting the trainings developed in the project to share the gained knowledge from the project.
The solutions developed within the ONCOVALUE project will be validated in cancer hospitals. This will be executed by performing pilot studies, which will validate the guidelines and SOPs developed for the collection and processing of structured RWD, the hybrid RWD-based HTA-framework and the AI-tools developed for the automatic extraction of structured information from unstructured data. To execute this, two pilot studies have been designed, one in the breast cancer setting and one in lung cancer, and a validation process handbook for both studies created.
ONCOVALUE is aiming to develop a RWD source for federated analysis by HTA and regulatory bodies across Europe, containing harmonized and curated data. Eventually, we aim to display data from the participating hospitals into a federated dashboard. There are many advantages in federated analysis: it enables bigger sample size, more variation in patients and also variation across the clinical centres and countries that are needed for value-based HTA decisions.
