Discovery through perturbation: taking causality into your own hands 

Increasingly sophisticated human cell-based models are expanding the scope and relevance of wet lab experiments, with the most scalable systems best poised to leverage emerging AI methods that power the likes of ChatGPT. But companies looking to capitalize on this trend must navigate trade-offs in their choices of experimental and computational models.

Target discovery campaigns that start with experiments in human cells, organoids or tissue models can establish cause-and-effect relationships from the start, and give researchers control over input variables, such how samples are processed, and outputs such as signal density. Starting with observational patient data, by contrast, ensures patient-relevance but offers far less control...