Is the science actually as good as the deck says?

A scientist who reads the data the way your reviewers will, and a strategist who knows what to do next.

I spend my days inside the primary literature and the raw analysis, not the summary slide. My research applies functional connectivity analysis and machine-learning classification to subcortical signals in epilepsy, asking a hard question: when does a brain signal actually distinguish one clinical phenotype from another, and when is it noise dressed as insight. That work is published in Neurology, Brain Imaging and Behavior, and Epilepsia, with a fourth manuscript in preparation.

The same discipline carries across the development arc. I hold candidate markers to a validation standard, I look for the leakage and overfitting that inflate a classifier, and I separate the technically adequate from the clinically overstated. Twenty-five years across sponsor and CRO, at Merck, CSL Behring, IQVIA, and Syneos, means I read the science with an eye on what a board, a regulator, and a market will each need to see, and I can translate that judgment into an evidence plan, a launch strategy, or a study that will actually run.