AI Article Synopsis
- Most new drug approvals rely on large randomized clinical trials (RCTs), but results can vary even among similar trials, making it hard to apply findings broadly.
- There is a gap between conclusions drawn from RCTs and those based on real-world data (RWD), which reflects actual patient experiences outside of controlled settings.
- The use of real-world evidence (RWE) from RWD, especially when enhanced by artificial intelligence, is gaining traction in haematology and could help support regulatory decisions alongside traditional trial data.
Article Abstract
Most new drug approvals are based on data from large randomized clinical trials (RCTs). However, there are sometimes contradictory conclusions from seemingly similar trials and generalizability of conclusions from these trials is limited. These considerations explain, in part, the gap between conclusions from data of RCTs and those from registries termed real world data (RWD). Recently, real-world evidence (RWE) from RWD processed by artificial intelligence has received increasing attention. We describe the potential of using RWD in haematology concluding RWE from RWD may complement data from RCTs to support regulatory decisions.
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| http://dx.doi.org/10.1016/j.beha.2024.101536 | DOI Listing |
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