Daniel D. McKinnon founded Gamow Labs after his first son, Owen, died from undiagnosed alveolar capillary dysplasia. Traditional NICU sequencing failed to locate the causative mutation, forcing the family into emergency ECMO and eventual loss. The tragedy revealed a bottleneck in expert interpretation of whole‑genome data, prompting McKinnon to build his own analysis pipeline. He leveraged open‑source tools and cloud computing to accelerate analysis.

Using a custom AI model, McKinnon re‑analyzed his son’s genome and identified a 91‑kilobase deletion that reduced expression of the FOXF1 enhancer, confirming the genetic cause. He then applied the same system to 66 rare‑disease cases left unsolved by clinical labs, achieving 100% detection of known causal variants and uncovering two previously unknown diagnoses. The pipeline also prioritized variant pathogenicity scoring, reducing manual review time.

McKinnon’s early results suggest AI‑driven interpretation can democratize NICU genomics, cutting costs and shortening diagnostic timelines. By targeting a population with high genetic disease prevalence, Gamow Labs aims to prove the model’s scalability before expanding to broader precision‑medicine applications. Initial funding came from personal savings and a small angel round, underscoring innovation.