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 Speaker Profile

Ph.D., CEO, Switchpoint Bio

Biography
Samuel Myllykangas focuses on translating advances in immune epigenetics and genomics into practical tools that help researchers and pharmaceutical teams better understand how the immune system drives disease. His work centers on making immune system state measurable from a simple blood sample and turning this insight into a scalable data layer for research and drug development. Earlier in his career, Samuel worked in leadership roles in specialty genetics at Quest Diagnostics and was a founder of Blueprint Genetics, a global rare disease diagnostics company. Throughout his career, he has operated at the intersection of genomics, immunology, and precision medicine, with a long-standing interest in turning complex biology into actionable insight that can improve how disease is studied and ultimately prevented.


Talk
Making the Immune System Measurable at Scale
Most human diseases are influenced by immune system behavior that we have not been able to measure in practice. Immune epigenetics represents a new measurable data layer that can help researchers and drug developers better understand disease biology, patient variability, and how immune regulation shapes health over time.


AI and Data Sciences Showcase:
Switchpoint Bio

Switchpoint Bio is building a new biological data layer based on immune epigenetics, enabling immune system state to be measured from a simple blood sample. The company works with research and pharmaceutical partners to translate this insight into practical applications for understanding disease and patient variability.

 Session Abstract – PMWC 2026 Silicon Valley

Showcase Track S1 - March 4 11.00 A.M.-5.00 P.M.,Showcase Track S1 - March 5 9.00 A.M.-5.00 P.M.,Showcase Track S1 - March 6 9.15 A.M.-11.30 A.M.


The PMWC 2026 AI Company Showcase will provide a 15-30 minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.

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