Reha Mathur

biotech | @Princeton

[Reha Mathur @RehaMathur]

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

[Reha Mathur @RehaMathur]

@andrewpannu hey would love to see this!

[Andrew Dunn @AndrewE_Dunn]

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: https://t.co/pzxcnmKFBj

[Nathan C. Frey @nc_frey]

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: [email protected]), or warm intro goes a long way.

[Nikhil Namburi @nikhilvnamburi]

I joined @_DimensionCap.

I make $1-50m+ investments. Pre-seed to Public. Infra, horizontal apps, life sciences.

I’m Nikhil. Our website is https://t.co/07lUow3mNk. My email is a combination of those.

[Reha Mathur @RehaMathur]

@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

[Zavain Dar @zavaindar]

at NeurIPS late this week alongside my @_DimensionCap teammates and many of our entrepreneurs.

DM's are open if you're around!

[Proby Shandilya @ProbyShandilya]

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!

[Reha Mathur @RehaMathur]

@EdReznik @flamholz I would love to come!

[Reha Mathur @RehaMathur]

@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

[Nan Li @nanli]

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!!

[Convoke @Convokebio]

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

[Nan Li @nanli]

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.

[Zavain Dar @zavaindar]

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 👇

[Zavain Dar @zavaindar]

Deep Tech Software Engineer: https://t.co/KR5Nj2aC3W

[DIMENSION @_DimensionCap]

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.

https://t.co/BzBeJFtgDX

[Reha Mathur @RehaMathur]

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

[Zavain Dar @zavaindar]

great to see Dimension backed https://t.co/40xgMVmGMT and Dimension cofounded https://t.co/UuTySY80XZ both on @mariogabriele's The Future 50 list below!!

[Reha Mathur @RehaMathur]

@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

[Kexin Huang @KexinHuang5]

🤝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: https://t.co/tiQldKpVnq

[Deniz Kavi @kavi_deniz]

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.