It's the use of AI across clinical data work and the wider processes around a trial, from coding and data checks to study setup and startup. It draws on more than the data a study produces, pulling in sources like electronic health records and wearables that sit outside any single trial but can inform it. People stay in charge, reviewing what the AI produces. In Viedoc, this starts with medical coding today, with more in development.

Across clinical trials, AI tends to be used for improved productivity, pattern recognition, and automated workflows. In Viedoc, AI-assisted medical coding is available now. AI-assisted study build, patient onboarding, and the ability to ask questions of your study data are in development. Further capabilities, like proactive risk signals, are also in early development.

Auto-coding matches a reported term, such as a medication or an adverse event, to a standard dictionary code automatically. In Viedoc Coder, the WHODrug Koda integration codes medication terms this way, and a coder confirms each one.

Yes. Viedoc Coder uses AI through the WHODrug Koda integration, for medication coding.

No. AI suggests a code, and the coder reviews it, approves it, or changes it. The coder keeps the final call, and their judgment decides every code.

The suggestions come from WHODrug Koda, built by the Uppsala Monitoring Centre, which runs the WHODrug dictionary, so they draw on a trusted source. A coder still reviews and confirms every code, so a person stands behind the accuracy of each one.

AI-assisted coding suggests a code for a person to review and confirm. Autonomous coding would apply codes on its own, without that review. Viedoc's coding is AI-assisted, so a coder approves every code before it's applied.

No. We never use your data to train public models.

No. Viedoc runs on open standards and an open API, so you can export your data and connect other systems whenever you need to.

No. It works inside the existing Viedoc Coder workflow, with no setup and no extra cost.