Real-world evidence and product development: Opportunities, challenges and risk mitigation
| Autor: | Célia Bouharati, Virendra Rambiritch, Sumanth Karamchand, Robert J. Chilton, Rory Leisegang, Poobalan Naidoo, Nadina Jose |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Disease
Review Article 030204 cardiovascular system & hematology Routine clinical practice 03 medical and health sciences 0302 clinical medicine Product lifecycle Medicine Electronic Health Records Humans 030212 general & internal medicine Product (category theory) Risk management Cost Reduction business.industry SARS-CoV-2 COVID-19 Reproducibility of Results General Medicine Systematic error Real-world data Clinical trial Risk analysis (engineering) Data quality New product development business Risk assessment Delivery of Health Care |
| Zdroj: | Wiener Klinische Wochenschrift |
| ISSN: | 1613-7671 0043-5325 |
| Popis: | Summary Real-world evidence (RWE) is derived from real-world data (RWD) sources including electronic health records, claims data, registries (disease, product) and pragmatic clinical trials. The importance of RWE derived from RWD has been once again demonstrated during the coronavirus disease 2019 (COVID-19) pandemic, as it can improve patient care by complementing information obtained from traditional clinical trial programs. Additionally, RWE can generate insights into disease mechanisms, epidemiology, patient flows in and out of healthcare systems, and drivers and barriers to optimal clinical care in real-world settings. Identifying unmet medical needs is crucial as it often can inform which investigational new drugs enter clinical trial testing, and RWE studies from hospital settings have contributed substantial progress here. RWE can also optimize the design of clinical studies, inform benefit risk assessments and use networks of pragmatic studies to help with clinical trial feasibilities and eventual trial initiation. The challenges of RWD include data quality, reproducibility and accuracy which may affect validity. RWD and RWE must be fit for purpose and one must be cognizant of inherent biases. |
| Databáze: | OpenAIRE |
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