President, @InSilicoMeds. Opinions are my own. Not investment or medical advice.
Joined August 2017
- Tweets103
- Following358
- Followers98
- Likes255
Alex Aliper retweeted
VAV1 was long considered “undruggable.”
Generative AI cracked it: Chemistry42 designed ISM9546, an oral molecular glue degrader that beat a reference degrader in colitis models.
Cracking the hallmarks of aging, one after another.
biopharmaapac.com/news/20/85…
Alex Aliper retweeted
Insilico’s SOTA models are finally available for everyone to try. For FREE! 🧪
No setup. No barriers. Just head to MMAI Playground and see what the models can do with your molecules.
playground.insilico.com
4 state-of-the-art drug discovery models. FREE to try. 🧪
Got compounds? Put them to the test.
💊 ADMET. Kinase selectivity. GPCR interactions. Synthetic chemistry.
Your compounds. Real-time predictions. Zero cost to try.
👉 playground.insilico.com
Alex Aliper retweeted
One of Day 2 highlights of #ARDD2026 was the tall by Kevin Duffin of Eli Lilly on the effects of Tirzepatide on aging clocks (make sure to check out poster #13 today).
Today, everyone is anticipating the Novo Nordisk presentation on Semaglutide. And I want to thank Andrew Adams and Lotte Bjerre Knudsen who opened the door last year.
This is the first ARDD when the clock data is presented - this is the new world!
Alex Aliper retweeted
FDA confirmed aging will be on its regulatory science agenda. ARPA-H has $144M building the endpoint framework. #ARDD2026 at Harvard was where that plan took shape. geneonline.com/ardd-2026-can…
Alex Aliper retweeted
LongevityBench, our new aging benchmark with @InSilicoMeds tests models on 17 tasks across clinical records, DNA methylation, transcriptomics, proteomics, and genetics. On several tasks, our compact LFMs outperformed every frontier model we evaluated.
What did it take to get there? @katerina_nasto, Liquid AI researcher, and our CTO Mathias Lechner (@mlech26l) talk through how the benchmark was built, why leakage-proof evaluation matters, and and how specialized models that run locally on sensitive patient data could help researchers move from prediction toward better hypotheses and experiments.
We're taking this work to the longevity research community next and will be presenting at @ARDD_Meeting this week. Reach out if you're attending and want to meet the team!
Blog and model: liquid.ai/blog/longevitybenc…
Paper: shorturl.at/qJZLO
Alex Aliper retweeted
Had a great time at the Lab of the Future Congress in Amsterdam 🇳🇱
I had the chance to share some of the latest work we’ve been doing at Insilico Medicine, including our latest Cell cover study on longevity, developed together with @liquidai 🧬, as well as our work benchmarking frontier models for drug discovery 🤖💊
Great conversations, great people, and lots of exciting ideas around the future of automated science 🚀
Thanks to everyone I met and spoke with during the conference! 🙌
Alex Aliper retweeted
This one is extremely important for me. The fact that now you can have absolute frontier class models in hard specialized domains such as healthcare and longevity, AND can run on your personal devices, is truly special.
The impact is huge, nothing is more important than our health and so glad that with our amazing partners at @InSilicoMeds we are unlocking new efficient frontiers in biology.
enjoy!
In a new article published today on the cover of @CellCellPress, we obtained Liquid Foundation Model instances that establish state-of-the-art performance on biological longevity tasks, outperforming the best frontier models such as Gemini-3.1-Pro, GPT-5, and Claude Opus.
In partnership with @InSilicoMeds, we built and released:
> A comprehensive eval suite of 17 biological longevity tasks (i.e., LongevityBench), to assess whether a general-purpose language model can interpret aging data spanning clinical records, DNA methylation, transcriptomics, plasma proteomics, and genetic evidence.
> LFM2-1.2B-Longevity and LFM2-2.6B-Longevity: two compact models specialized for interpreting structured aging data across these tasks.
These results are important! 🧵
Alex Aliper retweeted
In a new article published today on the cover of @CellCellPress, we obtained Liquid Foundation Model instances that establish state-of-the-art performance on biological longevity tasks, outperforming the best frontier models such as Gemini-3.1-Pro, GPT-5, and Claude Opus.
In partnership with @InSilicoMeds, we built and released:
> A comprehensive eval suite of 17 biological longevity tasks (i.e., LongevityBench), to assess whether a general-purpose language model can interpret aging data spanning clinical records, DNA methylation, transcriptomics, plasma proteomics, and genetic evidence.
> LFM2-1.2B-Longevity and LFM2-2.6B-Longevity: two compact models specialized for interpreting structured aging data across these tasks.
These results are important! 🧵
Alex Aliper retweeted
Recently, Alex Zhavoronkov, Founder and CEO of Insilico Medicine, attended the Nature Conference Redefining Healthcare in the Age of AI at the Sorbonne in Paris.
During his presentation, Alex reflected on his entrepreneurial journey, from founding Insilico Medicine in 2014 after recognizing the potential of deep learning, to establishing a sustainable AI-driven drug discovery model and advancing rentosertib into Phase III clinical development.
He also shared recent progress in generative AI-powered drug discovery, including findings from a Phase IIa study involving proteomic aging clocks and changes in biological age. Alex further discussed how biotechnology companies can balance commercial viability with the long-term goal of advancing aging research.
The findings discussed remain investigational and should not be considered medical or investment advice.
Alex Aliper retweeted
This tiny ion channel can kill an otherwise great drug. ❤️⚡
It’s called hERG.
A molecule may be potent, selective, and beautifully designed, but if it blocks hERG too strongly, it can disrupt the heart’s electrical rhythm.
That’s why hERG is one of the most important ADMET predictions. 🧪
The goal is simple: Find dangerous molecules as early as possible.
This is exactly the kind of task the InsilicoMMAI-4B-Chem-ADMET model is built for. 🤖
#insilicoSOTAFM
Alex Aliper retweeted
MMAI Gym paper is out, amazing work. arxiv.org/abs/2603.03517v2
Kudos to the team: @Max__Kuznetsov @zulfatmif @RimShayakhmetov @sumrexromanus @chem_logos @chemcensor @ThomasMM17 @eugenebabin!! 💪
Accepted to the #EMNLP2026 Industry Track 🎉
@InSilicoMeds built MMAI Gym for Science. @liquidai built the Liquid Foundation Model. We combined them.
400+ drug-discovery tasks. Chemistry-native tokens. SFT, then RL.
Not a bigger model. A better gym. 🏋️
#insilicoSOTAFM 🧵👇
Alex Aliper retweeted
GPT-6 Astra is the best frontier model for multi-step retrosynthesis. 🧪
In our DDD Benchmark, it outperformed every other frontier model we tested, coming remarkably close to specialist-level models for synthesis planning.
Our Rentosertib molecule, which showed an age-reversing effect across 6 aging clocks in Phase 2 clinical trials, also had to be synthesized somehow. 😅
And that’s exactly what we measure here: how well a model can predict synthetic routes for small molecules.
Great job @sama, @gdb 👏
#insilicoSOTAFM
Alex Aliper retweeted
Accepted to the #EMNLP2026 Industry Track 🎉
@InSilicoMeds built MMAI Gym for Science. @liquidai built the Liquid Foundation Model. We combined them.
400+ drug-discovery tasks. Chemistry-native tokens. SFT, then RL.
Not a bigger model. A better gym. 🏋️
#insilicoSOTAFM 🧵👇
Alex Aliper retweeted
Astra for antibody developability prediction:
GPT-6 Astra is now the best-performing frontier model for antibody developability prediction in our benchmark. 🧬
Finding an antibody that binds is only the beginning. Will it aggregate? Will it stay stable? Can it actually behave like a drug?
GPT-6 Astra predicts these developability properties better than the other frontier models we tested. 🤯
And yes, the interactive visualization showing how an antibody actually works was also built with Astra in about 1 hour.
This model looks seriously powerful.
Congrats @gbt @sama
#insilicoSOTAFM
Alex Aliper retweeted
Find benchmarking protocol details here: arxiv.org/abs/2608.18940, the new GPT-6 Astra results will be soon released at dddbench.insilico.com 2/2
Alex Aliper retweeted
I am happy to report that we just dosed our first patient in the pivotal Phase III trial. Please Wish Me Luck and Strong Sustained Efficacy! 🍀🤞
Alex Aliper retweeted
Congrats Alex and the @InSilicoMeds team!
Of the 43 patients in the trial, the clocks showed significant reductions in the predicted age 🧵
nytimes.com/2026/09/07/scien…
My dear friends, I am happy to report the publication of the most important paper in my life to date (we have several great papers coming out but this is very special). Tomorrow, I will present this paper for the first time at the Nature AI Healthcare in Paris and will post a longer post on this story and its broader implications for how to conduct clinical trials. Please read it and comment on it.
Many thanks to the great co-authors of the study and everyone who contributed. Many thanks to the many reviewers (friendly and unfriendly) for spending so much time and helping make it better.
Link in the comments.
Alex Aliper retweeted
The first drug in development (rentosertib, anti-fibrotic, designed with AI) to show slowing of proteomic aging clocks, 6 of 6, in a small trial @gladyshev_lab
@NatureBiotech @biogerontology @InSilicoMeds
nature.com/articles/s41587-0…
Alex Aliper retweeted
🧬 Rentosertib just turned back biological age in people.
⏱️ 6 aging clocks. 6 independent groups.
After 12 weeks, all 6 clocks read them 3 to 4 years younger.
🚀 The first AI-designed drug. The first clinical demonstration of 3–4 year biological age reversal.
The first experiment is done. 🔬 Now run your own with Insilico’s SOTA models.
#InsilicoSOTAFM