Menu Back to Poster-Presentations-Details

SP02-33: Augmenting Randomized Control Trials with Real World Data to Improve Clinical Decision Making and Outcomes Within Oncology

Poster Presenter

Bhavika Parikh

Student
Ernest Mario School of Pharmacy, Rutgers University
United States

Objectives

A literature search was conducted to evaluate RWD and RWE in oncology to monitor post-market safety, identify adverse events, and develop guidelines for use in clinical practice in order to enhance clinical trial designs to generate new treatment approaches leading to drug repurposing and approval.

Method

A literature analysis was performed using PubMed, MedLine, FDA.gov, and clinicaltrials.gov evaluating clinical studies and case reports published from 2013 to 2020. PubMed MeSH search terms included: “real world evidence oncology,” “real world data,” “oncology,” “NSCLC real world evidence.” Co-authors: Krishna Rana and Apoorva Vasireddy

Results

Our search yielded 19 published papers; a mix of review and primary articles were studied looking at the use of RWE/RWD in the fields of oncology. The potential of RWD to supplement evidence from randomized controlled trials (RCTs) may be especially relevant in oncology where it is estimated that <5% of patients with cancer are enrolled. Several Big Pharma companies such as Novartis, Pfizer, Eli Lilly and Company, and Amgen have used RWE to release new oncology drugs such as Ramucirumab and Ceritinib. While reviewing these, we were able to identify seven drugs that utilized RWD in different scenarios including orphan drug application, indication expansion, and more. RWE helps companies lower healthcare costs by increasing the possibility of drug repurposing and approval. A few limitations of RWE include lack of standard, disconnected data sources, HIPAA/informed consent issues, and no established process for data merging or analytics. However, a number of third-party organizations have begun using RWE in oncology to evaluate health economic outcomes and supplement post marketing data for new and current FDA approvals, primarily in breast cancers, lung cancers, and leukemias.

Conclusion

RWD and RWE try to look at the effect of drugs under normal, everyday conditions in order to discover prospective benefits or risks based on study designs and analyses from various studies. Therefore, they may be used for accelerated approvals in oncology by being beneficial in providing additional data for post market surveillance and other information related to patient outcomes. There are examples of several pharmaceutical companies that support the use of RWE to submit applications to the FDA. The FDA has published guidances on the use of RWD in supporting and expediting the approval of new therapeutic oncology indications, thus saving pharmaceutical companies potentially large amounts of resources while possibly lowering costs for traditional drug development. With appropriate implementation, RWD and RWE can help fill evidence gaps about the performance of oncology products used in a real-world setting, while also expanding their indications for regulatory evaluations.