- Details
- Participants
- Notes
- Morgan Levine
- Aging
- Envision for Hope
- Technology
- Future
- Issues
- Upcoming
- Advice
- Trim Trials
- Resources
- Categories
Details
Podcast: Existential Hope Podcast
Episode: Morgan Levine On Aging and the Future
Participants
Morgan Levine
Morgan Levine
Notes
Morgan Levine
- Founding member of Altos Labs
- Former Yale Professor
- Epigenetic Researcher
- Specializes in molecular processes to understand the language of cells.
- Interested in determining how to differentiate healthy and unhealthy cells and, from that, decide whether it's possible to revert unhealthy cells into healthy ones.
Aging
- Biomarkers are good determiners if interventions are working.
- It's essential to determine if the biomarkers correspond to chronological age, and the difference has to be meaningful.
- Biomarkers also need to be reliable. The exact change should reflect a similar shift in chronological age. In addition, there can only be a little noise. +/- decades is too noisy.
- The science in this space is accelerating.
- Because things are moving so fast, she urges caution when seeing research that proves one thing or another. Ensure any research is independently verified.
Envision for Hope
- Morgan realized that she could help create the future.
- To do so, it has to be tools + imagination.
- Generally, she is optimistic because of:
- The increasing rate of discoveries in this space.
- The early signs that technology is transforming medicine, health outcomes, and altering people's life courses.
- In being optimistic, she believes you need to think about positive outcomes, only worry about the things in your control, and do the work to create a better future. Don't dwell on the negative scenarios.
- Eutrophic (?)
- The science will generate life-extension treatments.
- Prevent and reverse disease to a significant degree within ten years.
- Science should be able to 'turn back the clock by ten years in ten years. Thus, when you are your age now + 10 years, in ten years, I should feel the same age as I am now.
Technology
- Much of the technology around this space has to do with computational science.
- Using models, mathematics, and data science to compute the efficacy of interventions.
- But there are a lot of other factors that drive aging, including socioeconomic status. Solving some of those issues is also significant in making the population younger and healthier. We need to reduce aging in those populations that experience accelerated aging.
- In her labs and many others, there are multi-disciplinary teams, including biochemists and biologists, mathematicians, data scientists, and information theory professionals.
Future
- The future of the field is a continuation and expansion of data science and machine learning.
- More, better, and standardized computation tools and data formats are needed.
- Open Science data is a step forward and solving this would result in another acceleration. Organizations include:
Issues
- An issue with the field is the tendency only to publish positive outcomes in research papers. We need to see more of what doesn't work.
- Publishing only positive results creates an unintentional bias in the field.
Upcoming
- She is excited to join Altos full-time because there are no goals. It's in the model of Bell Labs to follow where your curiosity leads.
- It's a lot of basic science, and basic science with open-ended questions is where significant discoveries emerge. There's less discovery when people chase after one specific thing.
Advice
- The best advice she has ever heard and would pass on is don't let your current state dictate your future.
- Limit your exposure to naysayers and fight the impostor syndrome.
- Don't compare yourself to others.
Trim Trials
- There is some research which is claiming to have cracked the age reversal code.
- She warns this research is far from proven, but it may be on the right track. She doubts they are all the way there.
Resources
What is Life? by Edwin Schrodinger
AntiFragile: Things that Gain from Disorder by Nassim Nicholas Taleb a book she suggests on complexity.