Reha Mathur

Thrilled to announce that I joined the investment team at @_DimensionCap! Excited to support founders at the intersection of biology and tech!

Exclusive: Clarissa Desjardins' newest biotech has put its first drug in the clinic + raised $40M more. Congruence also expects to put 2 more molecules into clinic in early 2027, seeing its platform driving its R&D efficiency: endpoints.news/congruence-sta…

Join the early team @CoefficientBio. We have an AI team that I’m incredibly proud of, and truly think is the most effective and exceptional technical team building in AI x bio. We're looking for people to: * Build and maintain robust AI systems to an exacting standard * Design and run experiments that let us iterate fast * Work on challenging scientific and engineering problems for human flourishing NYC-based (or willing to relocate). If you’re curious about what we’re building, reach out directly. If we don’t know each other yet, a great cold DM (or email: join@coefficientbio.com), or warm intro goes a long way.

I joined @_DimensionCap. I make $1-50m+ investments. Pre-seed to Public. Infra, horizontal apps, life sciences. I’m Nikhil. Our website is dimensioncap.com. My email is a combination of those.

@nikhilvnamburi @AGoulburn @zavaindar @nanli @hathwar607 @SimonDBarnett @bauer_lesavage its not every day you get to become ur friend's boss :) jk, nikhil is a phenomenal investor and an even better person, dimension is incredibly lucky to have him

@AGoulburn @zavaindar @nanli @RehaMathur @hathwar607 @SimonDBarnett @bauer_lesavage

at NeurIPS late this week alongside my @_DimensionCap teammates and many of our entrepreneurs. DM's are open if you're around!

Nikhil is one to watch. Rigorous thinker, analytical mind, true student of the game. Spend any time w him and you’re guaranteed to a) think better and b) laugh a lot. Onwards!

@EdReznik @flamholz I would love to come!

The rumors are true: there is a revival of the famous Harvard Systems Biology Theory Lunch in New York, co-organized by @flamholz and I. There is food. There is chalk. There is science. It's been fun. More to come, please reach out if you'd like to attend.

@davidkmyang they need to run the phase 2/3 in us and will need to develop med affairs/clin dev in the us. Few have the appetite and capital base to do so rn. The cost/benefit to build that out vs selling assets for sometimes significant upfronts is not as clear imo

Most people don't believe China will ever commercialize their own drugs but I think that's wildly incorrect. Reason for today's popular sentiment is (1) Chinese biopharma lacks global commercial capability today and (2) US will not allow it which substantially shrinks the market opportunity and thus uninteresting. But Chinese biotechs are already realizing they're leaving value on the table by selling assets at DC or Ph1, and are developing it internally until Ph2/3. Eventually they'll realize that there's even more value in simply launching the drug. The potential ban on licensing China assets will of course accelerate this trend. US will ultimately not allow Chinese biopharma to commercialize on its soil and indeed it's the giant market for pharma. But ex-US market is sufficiently meaningful to incentivize Chinese pharmas to launch + they may be allowed sell US rights. I've mentioned this before, but as China starts advancing first-in-class drugs, we likely end up seeing Europeans get access to valuable drugs that US does not, flipping the current dynamic. Get ready for global Chinese pharmas.

Excited to announce @_DimensionCap's partnership with @garydglick and the entire @Odyssey_Tx team on an oversubscribed Series D. They are moving ahead to an exciting chapter where the company will translate multiple programs out of a massively productive discovery platform. Odyssey brings together novel biology, cutting-edge research tooling, and most importantly of all, a seasoned leadership team who have brought many drugs to patients. Dimension continues to be believers in the productivity of discovery platforms and aims to partner with the best founders that want to build enduring companies in biotech. We are here to partner across all stages - from early company formation all the way through to IPO and beyond. Onwards!!

We've raised $8.6m to build leading AI tools for the biopharma industry! Our seed financing was led by @kleinerperkins and @_DimensionCap , with participation from @ACME, @CommaCapital, @Liquid2V, @notboringco, @AudaciousHQ, @Lux_Capital, and leaders in AI and biotechnology

Congrats on the launch of most recent @_DimensionCap co @Convokebio! @Atelfo @okaymaged and @VelagapudiVikas are an incredible team building an AI operating system for life science. From data ingestion, to clinical insights, to program tracking, Convoke allows customers to build AI native workflows for their most important projects.

a few months ago we @_DimensionCap quietly funded a team of 3 MIT computer scientists & mathematicians at the forefront of ML & physics+simulation for enzyme design. these. guys. are. cracked today they're stealthily building the early team. if you're world class, look below 👇

Deep Tech Software Engineer: voltaris.notion.site/software-engin…

Excited to introduce our newest team member, Sriram (“Rami”) Hathwar! 🚀 From winning the US Scripps National Spelling Bee, to enrolling in a Chemistry/Bio/CS curriculum at Princeton, to developing bioinformatics tools at a clinical stage biotech, Rami embodies the interdisciplinary culture of the firm and our founders. We’re fortunate to have his curiosity, drive, and passion for science and technology on the Dimension team and are certain that he will make an immediate impact in the community! Please be on the lookout for him out in the industry and make sure to get in touch @hathwar607. dimensioncap.com/people/rami-ha…

@joliegans do you think u see a shift now towards industry training researchers as well -- see retro bioscience phd program or quant researchers etc.

Could we ever run out of researchers? What happens if we do? I wrote a new piece outlining what I call the Researcher Fertility Rate (RFR) - we have more PhD students than ever, but those staying to become PIs themselves is shrinking rapidly. Just like the population crisis, we could see an inversion that irreversibly shows itself in decades. Why's this happening? I trace it back to Gen Z's cultural and economic nihilism. Some examples: >The average age for first NIH grant is now nearing 50. It was 35 in the 1980s. >Entry-level software engineers make $180K, postdocs make $56K. >"Oh... you're still in school?" We made pregnancy low-status. We're doing the same to research, marking it as either privilege or naiveté, especially to non-academics. Maybe you're asking - but what about industry research? What about research automation? How do we solve this? Answers in full piece below.

great to see Dimension backed axi.om and Dimension cofounded achira.ai both on @mariogabriele's The Future 50 list below!!

@JacobTref this is assuming that building the binder is the missing step in validating a target which isnt really true. imo the issue with these models is the binder models we have also can't address the targets that are hard to experimentally build binders for so we don't increase surface

As I understand this he means something like: pharma limits themselves by surface area, = intersection of 1) validated target, 2) big enough disease/pricing power Now with AI you can make binders galore, quickly -> gain confidence in new targets (#1) -> surface area expands

🤝Excited to partner with Tamarind @kavi_deniz to build towards an agentic AI protein designer. 🔁 Agentic protein optimization — Starting from a sequence, Biomni iteratively improves thermostability by orchestrating AlphaFold-2, ThermoMPNN, and reasoning over predictions and literature to suggest mutations. 🧠 Natural language control of tools like Boltz-2, Chai-1, and ImmuneBuilder. Learn more: biomni.stanford.edu/blog/tamarind-…

How Genentech/Prescient Design use AI to design 3-100x better antibodies Genentech uses lab in a loop as an iterative approach for designing antibodies by marrying generative machine learning models, property predictors and data from in vitro experimentation. Thread👇 The authors take 1,800 antibody binders to wet lab for four clinically-relevant targets (EGFR, IL-6, HER2, OSM), achieving 3-100x better binding from leads found through animal immunization and immune repertoire mining techniques.

Excited to announce our new product: AI Protein Design Copilot @tamarindbio has been the leading provider to use the top AI tools in computational protein engineering. Today we announce a completely new way to interface with computational molecular design. Available now!