Genome sequencing costs have plunged from $100 million in 2001 to under $200 today, but analyzing the data remains expensive and slow. In this episode, Lucas and Luna explore how quantum computing is starting to change the economics of genomics — specifically the computational bottleneck of variant calling and alignment. They walk through a real example: how a single human genome generates 200 gigabytes of raw data, and how quantum algorithms could reduce analysis time from hours to minutes at a fraction of the energy cost. They also discuss partnerships between quantum hardware startups and genome centers, the role of hybrid classical-quantum workflows, and why this matters for personalized medicine timelines. Plus, a brief note on why this show remains ad-free and how listeners can support it.

#QuantumComputing #Genomics #GenomeSequencing #Bioinformatics #PersonalizedMedicine #DrugDiscovery #HealthcareTech #BusinessAndTechnology #FexingoBusiness #BusinessPodcast #QuantumAlgorithms #VariantCalling #DNA #Illumina #IONQ #Rigetti #Deloitte #HypeCycle

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