Jan 2, 2019, 12:41 AM ET

a16z Podcast | Revisiting the Gene

Genomic applications will rest on a foundational sequencing layer characterized by rapid, reliable, and low-cost data acquisition.
Costs for interpreting genomic data are projected to increase by 100 to 1,000 times relative to acquisition expenses.
Computational models are planned to guide variant interpretation teams regarding molecular and cellular effects and to predict outcomes for the 9.4% of currently unknown mutations.
Diagnostic metrics for predictive models will be prospectively tracked and audited to ensure value.
Dynamic DNA-based applications theoretically enable disease detection associated with immune changes.
Post-launch learning mechanisms are expected to improve accuracy over time, reducing the likelihood of errors after initial AI-based diagnostic deployment.
A new diagnostic approach aims to capture a fraction of the 35 million unscreened individuals, potentially creating a clinical trial one to two orders of magnitude larger than previous announcements.
Payment models will likely expand to include life insurance companies and hospital closed systems, though these methods remain in early development stages.
The healthcare system is forecasted to undergo a permanent transformation in its conceptualization of disease.