Multi-drug attribution is deciding which drug, or drugs, in a combination regimen most likely caused an adverse event. Combination therapy is the norm in oncology: FOLFOX, carboplatin with pemetrexed, a checkpoint inhibitor with chemotherapy, an antibody-drug conjugate. When diarrhea, a falling neutrophil count or rising liver enzymes appear, each drug in the regimen is a candidate, and so are the disease and the patient's other medications. The call matters beyond the visit: attribution recorded during a trial feeds SAE narratives, expedited safety reports, signal detection and, at approval, the warnings and monitoring on the drug's label. Burna AI assesses every drug in the regimen separately with the WHO-UMC and Kramer methods and shows the reasoning for each, so the investigator decides with the evidence in front of them.
More on multi drug attribution.
- How does Burna AI compute adverse event attribution?
- What are the WHO-UMC causality categories and the Kramer algorithm?
- What is dechallenge and rechallenge?
- Which oncology regimens does Burna AI cover?
- Can Burna AI grade single-agent trials too?
- How does Burna AI handle protocols where the trial drug profile is sensitive sponsor IP?