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Dimension raises $500M second fund for investing at the intersection of tech and life sciences | TechCrunch

Dec 09, 2024 - techcrunch.com
Dimension Capital, a venture firm founded in 2022, successfully raised an oversubscribed $500 million fund, surpassing its $400 million target. The firm, which focuses on the intersection of life sciences and technology, has gained traction due to the growing interest in AI-driven drug discovery. Dimension's unique approach involves investing in companies where a significant portion of the team consists of computational biologists and AI experts working alongside traditional scientists. This strategy has attracted returning investors from its first fund and a select group of new investors, allowing Dimension to turn away many interested LPs.

Since its inception, Dimension has invested in about 20 companies, with a portfolio split between drug discovery and biopharma-supporting software and infrastructure. Notable investments include Chai Discovery and Enveda Biosciences, both of which leverage AI for drug development. Initially focused on early-stage investments, Dimension now adopts a stage-agnostic approach, writing checks from $1 million to over $30 million. The firm emphasizes the high caliber of entrepreneurs entering the life sciences and technology sector, highlighting their technical and scientific expertise.

Key takeaways:

  • Dimension Capital successfully raised an oversubscribed $500 million fund, exceeding its $400 million target, despite 2024 being a challenging year for raising capital.
  • The firm focuses on investing at the intersection of life sciences and technology, particularly in drug discovery using artificial intelligence.
  • Dimension Capital has a stage-agnostic investment approach, allowing them to invest in companies from inception to public stages, with check sizes ranging from $1 million to over $30 million.
  • Unlike traditional life sciences VCs, Dimension requires a significant portion of a biotech startup's team to be computational biologists, emphasizing the integration of AI and machine learning with traditional sciences.
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