Grad students test commercialization skills, teamwork in JAX-sponsored case competition

You could think of the Yale Healthcare Case Competition, sponsored by The Jackson Laboratory, as the medical version of TV’s "Shark Tank," played on a scientific stage.

Fourteen teams of graduate students from Columbia, MIT, UConn and Yale were challenged to present the best business proposal for commercializing a novel diagnostic test for childhood pneumonia.

They each gave a 10-minute PowerPoint presentation on their market analysis, financial projections and commercialization strategy to a panel of “investors” — judges from academia and industry — at Yale’s School of Management on Feb. 27.

Judges Andrey Antov and Yu Hui Rogers from the Jackson Laboratory
Judges Andrey Antov and Yu Hui Rogers from the Jackson Laboratory.

The best presentations were so compelling that the five finalists were invited to showcase their proposals April 20 at The Jackson Laboratory for Genomic Medicine in Farmington, Conn., where a JAX audience voted for the best of the best.

UConn’s four-person team, dubbed Clinomics Consulting, won the showcase, but all of the five finalist teams — a mix of MBA, Ph.D., MPH and medical students — took home a cash prize and valuable lessons about how to take a new technology into the healthcare marketplace and work successfully on an interdisciplinary team.

The theme of the competition, next-generation sequencing, was suggested by JAX Professor George Weinstock, Ph.D., Evnin family chair and director of microbial genetics at JAX Genomic Medicine. He is a global expert in the microbiome, the vast collection of microbes that live in our bodies and influence health and disease.

Weinstock’s lab is researching potential new diagnostic tests for infectious diseases based on next-generation sequencing technology, which can provide a fast read-out of an organism’s entire DNA, or genome. So-called metagenomic tests could identify multiple pathogens — viruses, bacteria and fungi — in a person’s tissue or fluid sample, yielding faster, more precise and more comprehensive disease diagnoses.