IMPRINT

Thank you to @chanzuckerberg.bsky.social & @biohub.org for an inspiring AI x Immunology Affiliate Symposium in NYC.

We were excited to take part and for our CEO & co-founder @beckbrachman.bsky.social to present among other leaders driving the future of R&D and human health.

We were honored to have our CEO & Co-Founder, @beckbrachman.bsky.social, represent scientific innovation at the @cornelltech.bsky.social x Cornell Club–New York 'Era of AI' event, discussing how AI is transforming science and healthcare.

Exciting work coming out of the Cornell Tech HealthTech Hub!

Training data composition determines machine learning generalization and biological rule discovery - Nature Machine Intelligence Negative data composition critically shapes machine learning robustness in sequence-based biological tasks. Training data composition and its implications are investigated on biological rule discoveri...

A recent @natmachintell.nature.com paper by our cofounder-CTO @victorgreiff.bsky.social shows models trained on harder antibody binding tasks learned better, boosting antibody ML generation.

At IMPRINT, this mindset drives our push for robust AI-based mapping of adaptive immunity.

#Immunology #AI

A huge thank you to @mofollp.bsky.social and West End Labs for bringing together leaders across science, technology and business to push the boundaries of what’s possible in NYC!

#MoForum #MachineLearning #Immunology #AntibodyDiscovery #AIForScience

Our CEO & Co-Founder @beckbrachman.bsky.social spoke at @mofollp.bsky.social #MoForum in NYC on how AI/ML is reshaping immunology and the opportunities ahead for life sciences — alongside amazing innovators! 🧠

#MachineLearning #Immunology #AIForScience #AntibodyDiscovery

The importance of negative training data for robust antibody binding prediction - Nature Machine Intelligence Thoughtfully designed negative training datasets may hold the key to more robust machine learning models. Ursu et al. reveal how negative training data composition shapes antibody prediction models an...

At IMPRINT, this mindset drives our push for robust AI-based mapping of adaptive immunity.

News & Views feature: doi.org/10.1038/s422...

#MachineLearning #Immunology #AntibodyDiscovery #AIForScience

Training data composition determines machine learning generalization and biological rule discovery - Nature Machine Intelligence Negative data composition critically shapes machine learning robustness in sequence-based biological tasks. Training data composition and its implications are investigated on biological rule discoveri...

Models trained on harder antibody binding tasks learned deeper biological rules + generalized better.

New NatureMachIntel paper by CTO @victorgreiff.bsky.social shows training on hard negatives (weak vs strong binders) boosts antibody ML generalization.

Read the paper: doi.org/10.1038/s422...

@convergentresearch.bsky.social @beckbrachman.bsky.social

Earlier this year, Imprint came out of stealth on the TED Mainstage to share our vision:

What if the immune system holds the key to curing chronic diseases—and we just need the tools to read it?

We’re building those tools.
Our TED talk is now live 👉 go.ted.com/beckbrachman

Jobs — Imprint FRO Join our team—current openings at Imprint

ICMYI, we're also still accepting applications for the following roles:

🔹Experimental Director
🔹Scientist, Molecular Biology & Immunology
🔹Computational Immunologist / Machine Learning Scientist / Biostatistician

Full role descriptions here:
www.imprint.org/jobs

#biotech #hiring #nycjobs

IMPRINT is #hiring a COO to help shape our work at the intersection of #immunology, machine learning, and neuroscience! The COO will guide product strategy/development, build a community of users and partners, and scale Imprint from early-stage R&D to market readiness, entry, and growth.

Imprint, a Startup Born from Runway Program, Raises $15 Million Imprint, an organization founded through Cornell Tech's Runway program, announced it has raised over $15 million.

New: @cornelltech.bsky.social's article on IMPRINT’s journey from incubation to last week’s launch, w/ grant funding from the NYC Economic Development Corporation’s LifeSci Initiative. The crucial support offered by both of these organizations makes our work at IMPRINT possible.

Imprint Labs Launches to Pioneer "Forensic Immunology" For Chronic Disease Imprint has raised $15 million to decode the body's immune memory for understanding chronic diseases, such as long-COVID and psychiatric disorders.

📣Major thanks to @faylinphd.bsky.social at GEN News for this lovely piece on IMPRINT! It was a pleasure for our founders — @beckbrachman.bsky.social, @victorgreiff.bsky.social, and Raymond Alvarez — to speak about our mission and research, and being NYC's first FRO.

@convergentresearch.bsky.social

I could not be prouder to publicly announce IMPRINT, a pioneering new non-profit to decode the body's immune memory and uncover the causes of chronic diseases. I’m joined in this journey by a brilliant and dedicated team of scientists from Europe and N. America.

Excited to co-found and help lead @imprintlabs.bsky.social —a focused effort to decode the immune system’s memory through cutting-edge computation and experimentation. Grateful to be on this journey with an exceptional team.

Imprint FRO IMPRINT is developing tools to read and analyze immune memory signatures, providing a new approach to identify hidden causes of chronic disease.

Also: we’re #hiring! 🎊To learn more about Imprint and view open roles on our team, visit imprint.org.

🤝 If you are a clinical or computational research group interested in partnering with Imprint, please follow us for future updates and opportunities.

#Immunology #Biotech #BiotechResearch

IMPRINT is the first Focused Research Organization (FRO) in New York City. We are supported by Eric and Wendy Schmidt, Convergent Research, Peter Reinhart, and the New York City Economic Development Corporation.

@convergentresearch.bsky.social

With teams in Europe and North America, we are building experimental and machine learning tools to identify the hidden causes of and cures for chronic diseases that affect hundreds of millions of people worldwide.

The immune system is not just an army — it’s also an archive. IMPRINT aims to decode this archive using an innovative forensic immunology approach, enabling new diagnostics, treatments, and cures for conditions ranging from autoimmune disorders to mental illness.

Press Release May 2025 — Imprint FRO Imprint FRO launches with $15M in funding

🧵 Today, IMPRINT, a pioneering new nonprofit initiative, is announcing $15 million in philanthropic funding to advance our work to decode the body's immune memory and uncover the causes of chronic diseases.

#Immunology #Biotech #BiotechResearch

@convergentresearch.bsky.social

Imprint FRO IMPRINT is developing tools to read and analyze immune memory signatures, providing a new approach to identify hidden causes of chronic disease.

Beyond advancing impactful science, Imprint offers a unique culture as a Focused Research Organization (FRO).

FROs are non-profit, impact-driven moonshot initiatives, combining philanthropic support with startup-like agility to tackle humanity's biggest challenges.

Learn more about Imprint:

Imprint FRO IMPRINT is developing tools to read and analyze immune memory signatures, providing a new approach to identify hidden causes of chronic disease.

We're seeking passionate individuals for the following roles in NYC, Canada, and Europe:

🔹Experimental Director
🔹Scientist, Molecular Biology & Immunology
🔹Computational Immunologist / Machine Learning Scientist / Biostatistician

Full role descriptions here:
www.imprint.org/jobs

#hiring #nycjobs

Jobs — Imprint FRO Join our team—current openings at Imprint

Looking for a job in immunology or biotech research?
✨IMPRINT is #hiring! ✨

Join us to help revolutionize how we decode the body’s immune memory, uncover the causes of chronic diseases, and drive breakthroughs in autoimmunity and neuropsychiatric research.

#BiotechJobs #Immunology #sciencejobs

tldr:

3) Coordinated, large-scale research efforts connecting ML researchers, immunologists, structural biologists, disease experts, and others are needed to unlock the full potential for the field

tldr:

2) The field will benefit greatly from nascent efforts to create standardized datasets, problem specifications, and competitions

tldr:

1) We think advances in antigen specificity prediction will ultimately be possible by training models on the full diversity of available structural and non-structural datasets

@timodonnell.bsky.social @giulioisac.bsky.social @jlimenitakis.bsky.social Beck Brachman Raymond Alvarez @victorgreiff.bsky.social Convergent Research

It's an exciting moment for immune repertoire research! At the end of December in Cell Systems, we shared our perspective on recent advances in ML for immune repertoire interpretation: www.sciencedirect.com/science/arti...