Inside the Minds of Other Biotech & Life Sciences CEO & Founders

• •applying machine learning to make sense of vast genomic data
• •quantitatively tracking human performance improvements
• •integrating phenotypic information with genomic data for understanding
• •bridging machine learning and biomedical data disciplines
• •overcoming internal self-doubt and being authentic

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• •reducing disease to single variables is 'asinine'
• •extreme burden of 24/7/365 operational requirements for living organsNew
• •tech and health tech companies losing massive valuation and access to capital simultaneously
• •very few success stories to train machine learning models on in pharma
• •meat from cultured cells can come out mushy lacking firmness

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• •metrics alignment with cfo on profitability and roi, not just revenue growth
• •cost-effective for patients in the overall system
• •driving greater improvement in business processes
• •prediction of heart disease or alzheimer's in 10 years
• •measuring biomarkers for nutrition and mental cognition

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• •bridging the chasm - focusing on areas requiring expertise in two disparate disciplines
• •biomarker-forward strategy - validate biomarkers as predictive of clinical benefit to enable faster regulatory pathways for field, not just for gain's own developmentNew
• •expanding antigen targets (to cover more cancer types)
• •personal comfort level: people should wait until they are comfortable with genetic testing
• •first principle thinking - for measuring humans and closing the loop

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• •marketers not telling roi story clearly and quantitatively to skeptical stakeholders
• •not understanding the difference in omega quality
• •lack of payment innovation for one-time treatments
• •reliance on 'gut/experience driven' methods for decision making
• •leaky gut and compromised epithelial barrier

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