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DIMENSION

@_DimensionCap

Dimension is a multistage, research oriented, investment firm partnering with companies across the frontiers of science and compute

New York and San Francisco Katılım Haziran 2022
27 Takip Edilen3K Takipçiler
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DIMENSION
DIMENSION@_DimensionCap·
Reflecting on 2024: a category sweep of the Nobels, AI enabled clinical readouts, and the first trillion dollar pharma in sight. We stand on the shoulders of giants. Looking to 2025: This is just the beginning. Make no small plans.
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Zavain Dar
Zavain Dar@zavaindar·
Achira is building world models for the atomistic world As the frontier labs eat more and more of the human language world, the physical world is still entirely up for grabs. Come join us at Achira (a @_DimensionCap cofounded company) 🚀 achira.ai/careers/
Theofanis Karaletsos@Tkaraletsos

Hiring AI/ML talent at @achira_ai to build world models for molecules We're looking for scientists and research engineers who will join Achira's technical staff to join its mission to build microscopic world models. As large scale AI models have matured and revolutionized our ability to intervene on the digital world, we are increasingly racing towards physical AI as the next frontier. Achira builds foundation simulation models that will explictly model the microcosm on an atomistic level with a goal to deeply impact virtual chemistry in service of drug discovery and is marrying the best of deep learning/generative AI with physics, statistical mechanics, and quantum chemistry. If you're up for the challenge to build at the frontier, come join us. achira.ai/careers/

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Simon Barnett
Simon Barnett@SimonDBarnett·
I'm extremely excited to be partnering with @apoorva_mehta @olshav @LakshAithani as they build Abundance. Similar to @_DimensionCap itself, the team is focused on highly technical underwriting of emerging technologies, initially spanning the continuum of compute and the life sciences. We believe concentrated teams of technologies and taste-makers like those at Abundance, combined with frontier AI/ML tooling, can capture exceptional value. In Abundance's case, that's an agentic hedge fund laser-focused on leveraging deep technical domain experience overtop intelligent, data-driven capital allocation decisions in the public markets.
Apoorva Mehta@apoorva_mehta

x.com/i/article/2047…

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Zavain Dar
Zavain Dar@zavaindar·
it's been exhilarating being a day 0 investor & partner with @apoorva_mehta @LakshAithani and @olshav as they build ABUNDANCE. Agentic harnesses, next gen reasoning models, and an unabashed hunt for rapid iteration and dispassionate truth seeking will upend global markets -- starting with the deeply technical and often scientifically opaque (think: rvmd, sk hynix, and sndk over the last 24 months). work we've seen pioneered at ABUNDANCE has changed our thinking internally at @_DimensionCap and our view on how to invest and what to build for the coming decade the team is hiring for an extremely small number of three-sigma+ builers and polymaths. if that is you, you'll know how to get in touch
Apoorva Mehta@apoorva_mehta

x.com/i/article/2047…

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Viswa Colluru
Viswa Colluru@viswacolluru·
Pharma spent 30 years going biology-first. Enveda is built on the opposite bet. On @generalist with @mariodgabriele: why the chemistry 4 billion years of evolution has already selected for is still the best starting material we have ...and why that question is personal for me.
Mario Gabriele 🦊@mariogabriele

For decades, drug discovery has shifted away from nature and toward biology-first approaches. @viswacolluru believes that shift was a catastrophic mistake. His company, Enveda (@lifeschemistry), has raised over $500 million to build a “search engine for nature’s chemistry.” In our conversation, we explore: • Why the pharmaceutical industry abandoned nature (and why that was a massive mistake) • How Enveda built a system to decode unknown molecules in nature • The deeply personal story of his mother’s battle with leukemia and how it shaped his life’s work • Why old ideas, from immunotherapy to natural products, often hold the most latent potential • How Enveda developed 18 drug candidates for about $1 million each instead of $10-15 million • Enveda’s three leading drug candidates targeting eczema, obesity, and ulcerative colitis • Why first-in-class medicines capture the vast majority of returns in pharma • What competitive table tennis taught him about building companies Thank you to the partners who make this possible @brexHQ: The intelligent finance platform: brex.com/mario @ahrefs Brand Radar: Find your brand in AI results: ahrefs.com/generalist @withpersona: Trusted identity verification for any use case: withpersona.com/generalist (00:00) Introduction to Viswa Colluru (07:06) Early pull toward technology (14:24) Studying Biotechnology (24:23) Innovation vs. novelty (32:05) Joining Recursion (40:42) What launched Enveda (49:53) Chemistry-first approach (52:17) Raising $225K and investing $55K personally (56:04) Initial studies and targets (1:18:27) Enveda’s long-term vision (1:21:31) Book recommendation

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Zavain Dar
Zavain Dar@zavaindar·
alongside 3 wholly owned I&I assets currently in ph2 and ph1 studies, & 2 assets partnered with Sanofi rapidly approaching the clinic, Earendil presented 9 new onc programs at AACR last week. 3 of these programs are in IND enabling studies and all 9 should be in humans in the next 18 months the majority of these will be first in class. all of them have preclinical data suggesting best in class potential for their indication areas
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Zavain Dar@zavaindar

.@_DimensionCap has led, alongside DST Global and Hillhouse, $787M of new financings into Earendil Labs. The company uses cutting edge AI to redesign every joint of the discovery, design, manufacturing, and development process for new medicines, and is pioneering some of the most inventive research we’ve seen across the US and China. In terms of novel, orthogonal research: I’d describe this as the Deepseek of biotech. The company has multiple partnered and wholly owned assets entering or already in the clinic, and is building a burgeoning pipeline across I&I and onc .. pushing the boundaries of multispecific, multivalent, and next gen modalities. The team has publicly commented on pipeline, platform, and research partnerships with Sanofi, Wuxi and NVidia. I have to imagine: more to come. Finally, the company is led by famed UIUC/Tsinghua computer science professor, Jian Peng, and the original inventor of the class of PD-1/VEGF bispecifics, Zhenping Zhu. prnewswire.com/news-releases/…

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Zavain Dar
Zavain Dar@zavaindar·
.@_DimensionCap cofounded neolab Coefficient called out in Anthropic’s quest to impact the life sciences will be fun to watch the Anthropic and Coefficient teams double down on Coefficient’s build over the last year we’re still just at the very, very beginning
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Georgia Channing
Georgia Channing@cgeorgiaw·
the blogs that @tamarindbio write legitimately make it possible to understand the whole landscape from one article every other field needs this, and no other field has it
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Akshat Bubna
Akshat Bubna@akshat_b·
Pretty cool watching agents fully realize the dream of programmatic infra. Give your agent the gift of better primitives today, and see how much more they can get done!
Modal@modal

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Simon Barnett
Simon Barnett@SimonDBarnett·
An outstanding result, by any measure! I wrote about this compound, daraxonrasib, in 2024. research.dimensioncap.com/p/rmc-6236-a-c… We've only scratched the surface of small molecule pharmacology. This drug is a macrocyclic glue, and it achieved something spectacular. Let's keep going. :)
Anirban Maitra@Aiims1742

🚨🚨🚨 RASOLUTE-302 Ph3 is POSITIVE "Daraxonrasib demonstrated a median OS of 13.2 months versus 6.7 months for chemotherapy, with a hazard ratio of 0.40 (p < 0.0001)".... WOW! AMAZING news for patients with #PancreaticCancer The RAS Revolution is ON!! ir.revmed.com/news-releases/…

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Jacob Kimmel
Jacob Kimmel@jacobkimmel·
.@newlimit's first reprogramming medicines will enter the clinic in the coming years. we're recruiting a clinical leader to guide these trials for a new class of medicines intended to keep patients healthier, longer. reach out if you or a colleague are a good fit.
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Jacob Kimmel
Jacob Kimmel@jacobkimmel·
early this year @newlimit, we moved our 1st medicine into manufacturing. never would have guessed we'd be here 3 years ago. highlights: - +1 lead that rescues multiple hepatocyte functions - +19 hits that restore regulatory fxn in T cells - 2X discovery rate with multitask AI
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Simon Barnett
Simon Barnett@SimonDBarnett·
Galileo's similarity theory powered centuries of industrialization, but living cells broke it. In my newest essay, I argue that encoding this theory as an inductive bias is the only way to transform #bioprocess scaling from alchemy back into engineering.
Simon Barnett@SimonDBarnett

x.com/i/article/2038…

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Zavain Dar
Zavain Dar@zavaindar·
the first public sneak peek of data from @lifeschemistry's first clinical trials this is small early data, but has the potential to be: 1) clinically differentiated and meaningfully best in class 2) small molecule vs injectable 3) active in an all-patient population, including for non responders to IL-4/IL-13/STAT6 pathway
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Andrew Dunn@AndrewE_Dunn

Exclusive: Enveda's first clinical readout shows early promise for its lead eczema drug I talked with @viswacolluru on the ENV-294 data and next steps, including a Phase 2a readout expected in 2H26: endpoints.news/envedas-first-…

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Frank Gao
Frank Gao@ChemVagabond·
We gave AI agents varying freedom to optimize models for protein thermostability prediction. They beat a 15x larger reference model, matched Bayesian optimization. And we learned a hybrid approach may work even better. Blog: research.dimensioncap.com/p/the-melting-…
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Simon Barnett
Simon Barnett@SimonDBarnett·
Amazing work by @ChemVagabond! We @_DimensionCap tried our hands at autonomous research on protein thermostability - and learning a lot about agentic + Bayesian optimization along the way. Code + results + research blog below! 👇
Frank Gao@ChemVagabond

We gave AI agents varying freedom to optimize models for protein thermostability prediction. They beat a 15x larger reference model, matched Bayesian optimization. And we learned a hybrid approach may work even better. Blog: research.dimensioncap.com/p/the-melting-…

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