Looking forward to the Superage games in New York on November 7th. Have been trying to keep fit. If in New York, ping me and we can meet. Still time to register: games.superage.com Also, any ideas from the crowd on what to do for the final week before?
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Our co-founder @RonjonNag at the American Society for Human Genetics conference in Montreal, discussing Agemica’s peptide research and Superbio.ai.
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How a small, focused team can beat OpenAI or Anthropic on a drug program:
Use the best available AI. Know a specific biological problem deeply. Run the experiments that settle it.
That is the opportunity we see for Agemica.
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Use the best available AI. Know a specific biological problem deeply. Run the experiments that settle it.
That is the opportunity we see for Agemica.
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The edge can be knowing which target matters, which assay is misleading, and when to kill a candidate.
A focused team can accumulate that judgment around one program while using tools developed across the AI industry.
Scientific depth compounds too.
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A focused team can accumulate that judgment around one program while using tools developed across the AI industry.
Scientific depth compounds too.
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For Agemica, the ambition is to reach a valuable drug candidate first in the area we choose.
We believe a concentrated team, decisive experiments and improving AI can outperform a larger organization on a specific program.
That is our bet as AI moves into biology.
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We believe a concentrated team, decisive experiments and improving AI can outperform a larger organization on a specific program.
That is our bet as AI moves into biology.
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Our co-founder @RonjonNag, just before taking the stage at EPPICON 2026.
He was there as both a founder and a funder: joining the aging panel, pitching Agemica, and discussing our research into a vaccine for aging.
Afterward, we caught up on the pitch, what comes next, and how ous idea without getting ahead of the science. As he puts it: “We’re in animal studies now.”
Before and after the talk, in his own words.
He was there as both a founder and a funder: joining the aging panel, pitching Agemica, and discussing our research into a vaccine for aging.
Afterward, we caught up on the pitch, what comes next, and how ous idea without getting ahead of the science. As he puts it: “We’re in animal studies now.”
Before and after the talk, in his own words.
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US cancer data put lifetime diagnosis risk at roughly 4 in 10.
Agemica is actively testing across 30 cancer types. A result in one cell model can be a fluke or a narrow effect; testing across models helps reveal where a combination keeps working.
We're very excited to share one ry soon.
Agemica is actively testing across 30 cancer types. A result in one cell model can be a fluke or a narrow effect; testing across models helps reveal where a combination keeps working.
We're very excited to share one ry soon.
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Four questions from Ronjon's talk at AI Insiders × Longevity during SF Tech Week:
1. Was this a trial or an observational study?
2. Did health outcomes improve, or did a biomarker move?
3. Could better health explain the association, rather than the other way around?
4. Was this ice?
Keep these in mind the next time a headline promises a longer life.
A promising signal can justify another experiment. Establishing that a treatment helps people takes further evidence. We want that distinction to remain clear as longevity research reaches more people.
1. Was this a trial or an observational study?
2. Did health outcomes improve, or did a biomarker move?
3. Could better health explain the association, rather than the other way around?
4. Was this ice?
Keep these in mind the next time a headline promises a longer life.
A promising signal can justify another experiment. Establishing that a treatment helps people takes further evidence. We want that distinction to remain clear as longevity research reaches more people.
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Agemica retweeted
Great to talk about Agemica and aging vaccines at the AI Insiders x Longevity Event - so many thanks for having me
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Agemica retweeted
Free Stanford lectures, open to all: Impact of AI on Critical Thinking in the Life Sciences
Oct 14, 10am PT: Can biomedical AI become dangerous? Oct 16, 5pm PT: Does the prediction survive the data? Oct 19, 5pm PT: Follow the money
Online live and Recorded. Register: stanford.zoom.us/meeting/regist…
Oct 14, 10am PT: Can biomedical AI become dangerous? Oct 16, 5pm PT: Does the prediction survive the data? Oct 19, 5pm PT: Follow the money
Online live and Recorded. Register: stanford.zoom.us/meeting/regist…
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Agemica doesn't build one drug for one disease.
Our platform looks for the biological mechanisms shared across cancer, aging, and age-related disease, then designs around those shared mechanisms instead of treating each condition in isolation.
The process runs in three steps:
(01) Decompose.
Break a disease down into the biological pathways actually driving it.
(02) Search.
Find existing, already safety-characterized drugs that act on those pathways. Agemica leans on FDA-approved and clinically tested compounds, so much of the safety and pharmacological data already exists.
(03) Rank.
Score the resulting combinations on predicted effectiveness, selectivity against healthy cells, and existing pharmacological evidence.
A separate track inside the same platform designs peptide and mRNA vaccine candidates, ranked on immunogenicity, selectivity, stability, and manufacturability.
Every prediction eventually gets tested, and the result feeds back into how future candidates are ranked. Prediction, test, result, re-rank, repeat.
Holding $AGE is a way to stay close to that loop as it moves forward.
More life.
Our platform looks for the biological mechanisms shared across cancer, aging, and age-related disease, then designs around those shared mechanisms instead of treating each condition in isolation.
The process runs in three steps:
(01) Decompose.
Break a disease down into the biological pathways actually driving it.
(02) Search.
Find existing, already safety-characterized drugs that act on those pathways. Agemica leans on FDA-approved and clinically tested compounds, so much of the safety and pharmacological data already exists.
(03) Rank.
Score the resulting combinations on predicted effectiveness, selectivity against healthy cells, and existing pharmacological evidence.
A separate track inside the same platform designs peptide and mRNA vaccine candidates, ranked on immunogenicity, selectivity, stability, and manufacturability.
Every prediction eventually gets tested, and the result feeds back into how future candidates are ranked. Prediction, test, result, re-rank, repeat.
Holding $AGE is a way to stay close to that loop as it moves forward.
More life.
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We raised money from the $AGE community through trading fees. You deserve to know exactly what that money is funding.
Agemica has officially commissioned a new pancreatic cancer study.
• 246 humanized mice
• 41 experimental groups
• 14 therapeutic agents, tested individually and in combinations
Here’s what that actually means:
What are we trying to find out?
Which combinations can control pancreatic tumor growth in a living animal, and what signs of harm appear alongside any benefit?
A combination can look promising in a computer prediction or a laboratory cell experiment and still disappoint in a living body. This study is intended to help us identify which candidates deserve further development.
How did we choose the candidates?
Our AI approach examines patterns of gene activity in cancer and compares them with the changes different drugs produce.
Think of cancer as disrupting several connected systems inside a cell. The approach looks for combinations that could address those disruptions together.
Our earlier laboratory work has shown activity in human cancer models outside a living body. The next question is whether that activity holds up under more complex biological conditions. Our research approach.
These mechanisms explain why combinations are worth investigating. They do not tell us in advance which combinations will work or be tolerable.
What does “humanized mice” mean?
The planned model uses mice carrying pancreatic tumor tissue derived from a patient, with human immune cells introduced into the mice.
That allows researchers to investigate treatment responses with human tumor tissue and components of a human immune system present. It remains an animal model, with limitations. About these models.
What will be measured?
• Tumor size, measured three times a week, to track whether growth slows or tumors shrink.
• Body weight, also measured three times a week, to help detect treatment-related problems.
• Daily observations of the animals’ condition.
• Blood measurements to assess toxicity.
• Measurements confirming the presence of human immune cells.
Tumor response and tolerability both matter. A treatment that affects a tumor but causes unacceptable harm may not justify advancing.
Where are we today?
The study has been commissioned. Results from this experiment are still to come.
This particular experiment evaluates pancreatic cancer drug combinations.
We’ll share positive results, negative results, inconclusive findings, and the limitations that affect how to interpret them.
Agemica has officially commissioned a new pancreatic cancer study.
• 246 humanized mice
• 41 experimental groups
• 14 therapeutic agents, tested individually and in combinations
Here’s what that actually means:
What are we trying to find out?
Which combinations can control pancreatic tumor growth in a living animal, and what signs of harm appear alongside any benefit?
A combination can look promising in a computer prediction or a laboratory cell experiment and still disappoint in a living body. This study is intended to help us identify which candidates deserve further development.
How did we choose the candidates?
Our AI approach examines patterns of gene activity in cancer and compares them with the changes different drugs produce.
Think of cancer as disrupting several connected systems inside a cell. The approach looks for combinations that could address those disruptions together.
Our earlier laboratory work has shown activity in human cancer models outside a living body. The next question is whether that activity holds up under more complex biological conditions. Our research approach.
These mechanisms explain why combinations are worth investigating. They do not tell us in advance which combinations will work or be tolerable.
What does “humanized mice” mean?
The planned model uses mice carrying pancreatic tumor tissue derived from a patient, with human immune cells introduced into the mice.
That allows researchers to investigate treatment responses with human tumor tissue and components of a human immune system present. It remains an animal model, with limitations. About these models.
What will be measured?
• Tumor size, measured three times a week, to track whether growth slows or tumors shrink.
• Body weight, also measured three times a week, to help detect treatment-related problems.
• Daily observations of the animals’ condition.
• Blood measurements to assess toxicity.
• Measurements confirming the presence of human immune cells.
Tumor response and tolerability both matter. A treatment that affects a tumor but causes unacceptable harm may not justify advancing.
Where are we today?
The study has been commissioned. Results from this experiment are still to come.
This particular experiment evaluates pancreatic cancer drug combinations.
We’ll share positive results, negative results, inconclusive findings, and the limitations that affect how to interpret them.
Introducing Agemica.
On our mission to solve aging.
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