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Chronicles

The story behind the story

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Hong Kong-based Insilico Medicine, which uses machine learning to identify potential drug targets, raised $35M from Prosperity7, bringing its Series D to $95M

Rita Liao / TechCrunch :

TechCrunch Rita Liao

Context & Ripple Effects

This $35M Prosperity7 check closed out Insilico Medicine's Series D at $95M — a mid-stage moment in what became a steady climb: a $110M Series E led by Value Partners at a $1B+ valuation followed in early 2025, then a Hong Kong IPO that raised $293M and opened 45% above its offer price.

The raise also landed in a category where machine-learning drug discovery was already drawing nine-figure private capital — insitro had pulled in a $143M Series B led by Andreessen Horowitz the same season — making target-identification AI one of the better-funded corners of biotech.

First-order effects

  • Insilico gains an extended Series D war chest to push its machine-learning-identified drug targets through development without returning to market on short notice.
  • Prosperity7 secures a position in a company whose later trajectory — a $1B+ valuation, a Hong Kong listing, and reported 2024 revenue above $85M — validated the entry price.

Second-order effects

  • Insilico's funding cadence pressured peers like insitro, which answered with a $400M round led by Canada Pension Plan months later, escalating the capital bar for ML-first discovery startups.
  • The Hong Kong listing route Insilico took gave China-operating AI drug developers a credible exit lane distinct from US exchanges, shaping where later rounds and IPOs in the sector priced.

Third-order effects

  • If the pattern holds, AI drug discovery consolidates around companies that can finance their own pipelines end-to-end — private rounds, public float, then pharma co-development deals like the up-to-$2.75B Eli Lilly collaboration with $115M upfront — rather than licensing targets out early.
  • Big pharma's willingness to pay nine-figure upfronts to AI-native discoverers points toward a structural split: incumbents buy pipeline optionality while the ML platforms capture the discovery layer of the value chain.

The trend: AI drug discovery is maturing from venture-funded target identification into publicly listed platform companies that monetize pipelines through large pharma co-development deals.