Real‐world data for precision cancer medicine—A European perspective

Abstract

Leveraging real‐world data (RWD) for drug access is necessary to overcome a key challenge of modern precision oncology: tackling numerous low‐prevalence oncogenic mutations across cancers. Withholding a potentially active medication in patients with rare mutations for the sake of control chemotherapy or “best” supportive care is neither practicable nor ethically justifiable anymore, particularly as RWD could meanwhile be used instead, according to scientific principles outlined by the US Food and Drug Administration, European Medicines Agency and other stakeholders. However, practical implementation varies, with occasionally opposite recommendations based on the same evidence in different countries. In the face of growing need for precision drugs, more transparency of evaluation, a priori availability of guidance for the academia and industry, as well as a harmonized framework for health technology assessment across the European Union (EU) are imperative. These could in turn trigger infrastructural changes in national and pan‐European registries, cancer management guidelines (e.g., frequency of routine radiologic restaging, inclusion of patient‐reported outcomes), and the health data space, to ensure conformity with declared standards and facilitate extraction of RWD sets (including patient‐level data) suitable for approval and pricing with minimal effort. For an EU‐wide unification of precision cancer medicine, collective negotiation of drug supply contracts and funding solidarity would additionally be required to handle the financial burden. According to experience from pivotal European programs, off‐label use could potentially also be harmonized across EU‐states to accelerate availability of novel drugs, streamline collection of valuable RWD, and mitigate related costs through wider partnerships with pharmaceutical companies.

A data management system for precision medicine

“…Medical data science projects increase in complexity due to the evaluation of different biomarkers, either separately or in numerous combinations (13,14). While clinical trials in conventional medicine often limit their criteria by exclusion of potential comorbidities, precision medicine aims to include real-world data as relevant cases of human disease (15)(16)(17)(18). Statistical analyses combining collections of real-world data (19,20) and clinical trial recordings (21) challenges the prerequisites for medical data management systems (medical DMSs; MedDMSs).…”

The future of collaborative precision oncology approaches in sub-Saharan Africa: learnings from around the globe

“…One example is the LANTERN project, a multi-center observational clinical trial involving five institutions from different European countries, which seeks to employ advanced machine learning (ML) and artificial intelligence (AI) to develop predictive models for lung cancer diagnosis and predictive individual-specific treatments (27). This leveraging of RWD and RWE can not only guide treatment decisions but also support regulatory decisionmaking by national and EU-wide bodies (28).…”

Implementation of precision medicine in healthcare—A European perspective

“…The term RWD refers to health data that are collected during the course of disease, including treatment and outcome data [45]. These may be derived from individual patient records or registry‐based studies and may also include data collected via health apps or by wearables [46, 47].…”