Case Study: Oncology
The oncology team was doing everything right.
They were running investigator and nurse interviews across multiple studies. The science was strong. The questions were sharp. The stakes were high.
Then the transcripts started coming in.
Drug names appeared multiple ways. Biomarkers were spelled inconsistently. Protocol shorthand shifted from interview to interview. In adverse event discussions, even small variations required review.
The team recognized the risk immediately.
In oncology research, inconsistency does not just slow analysis. It introduces uncertainty. They needed a way to bring structure to fast-moving, complex conversations without disrupting active studies.
When precision determines insight
What Changed
Wordibly partnered with the team mid-stream. Together, we developed a study-specific oncology glossary based on protocol language and how investigators actually spoke during interviews.
The glossary and adverse event expectations were integrated into the project workflow before transcription continued. Quality reviewers applied the same standards across all files, ensuring consistency as interviews progressed.
The work did not slow down. It became more controlled.
The Result
Terminology stabilized across studies. Clarification questions decreased. Analysis moved forward with greater confidence in transcript accuracy.
Why It Mattered
In oncology research, insight depends on precision. Structured, human-led transcription protected consistency where automation had introduced risk.
The Result
Symptom timelines were clearer. Safety language was consistent. Caregiver and clinician perspectives were captured as stated, without distortion.
Why It Mattered
In rare disease research, accuracy protects trust. Human transcription supported reliable review and reporting where automation introduced risk.