AI, Synthetic Data and the Development Pipeline: Why Animal Health May Have the Edge

Synthetic data enriches clinical datasets and simulates alternative scientific scenarios through computer-generated subject data, synthetic placebo groups, digital twins, and more. Combined with AI across target identification, trial design, and sample size modeling, a new toolkit is emerging that could shorten the time from idea to decision, and animal health may be better placed than human pharma to use it.

• AI-driven target identification, trial design, and exploration of inclusion criteria
• Synthetic placebo groups, digital twins, and enriching underpowered datasets
• Real-world evidence and PIMS data as a development input
• Addressing small, fragmented datasets in guiding product development decisions
• Replacing, reducing and refining animal use through computational approaches