Real world evidence is gaining importance in pharmaceutical and life science industries for decision making related to product development, clinical research and post-ing studies. It provides insights from real patient experience outside traditional clinical research settings.
Role Of Real World Evidence In Drug Development And Clinical Research
During drug development, real world evidence plays a vital role in understanding disease progression, variability in patient response, dosing patterns and adherence to medications in real world settings. This helps pharmaceutical companies design optimal clinical trials with refined inclusion criteria and endpoints more relevant to patients.
RWE from electronic health records supplements traditional clinical trial findings with insights on patient subgroups that may benefit more from a therapy. It also provides insights on long term safety and effectiveness of drugs in broader and more diverse patient populations than clinical trials. This helps identify new potential uses and fine tune product labeling.
Role of Pharmaceutical and Life Sciences Real World Evidence in Posting Studies and Outcomes Research
Posting surveillance using real world data sources is crucial for monitoring safety and gathering insights on effectiveness, adherence and risk mitigation strategies over extended time periods in large patient populations.
RWE supports comparative effectiveness research among existing treatment options. This provides physicians and patients clarity on relative benefits, safety profiles and adherence patterns of different treatments for making informed decisions.
Challenges And Limitations Of Real World Evidence
While real world evidence provides important insights, there are certain limitations and biases inherent due to its observational nature. Lack of randomization, standard protocols and controls pose challenges to establishing causal relationships.
Differences in data collection practices and coding across healthcare systems also impact data quality and interoperability. Bias from missing or inconsistent data points require statistical adjustments in analyses.
Additionally, findings from real world evidence may not always generalize well to broader patient populations as the study samples are still not fully representative. Unmeasured confounding factors also limit interpretation.
Addressing Quality And Regulatory Acceptance Of Pharmaceutical And Life Sciences Real World Evidence
Pharmaceutical and life sciences companies are working on strategies to address above challenges and strengthen regulatory acceptance of real world evidence. Initiatives include standardizing data definitions, improving data quality and ensuring representativeness through larger and more diverse datasets.
Developing analytic methodologies to minimize biases through multivariate analyses, propensity score matching and active surveillance are key focus areas. Engaging regulators proactively in evidence generation process also helps establish trustworthiness.
Overall, with advancement in data analytics and stringent methodological practices, real world evidence is expected to play a bigger role complementing traditional clinical research in future. It will enable more informed and personalized decision making in pharma and life sciences.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
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