Insilico Medicine Funding History

Insilico Medicine uses generative AI for drug discovery. Its work spans target identification, molecule design and preclinical and clinical development.

Company Overview

Insilico Medicine logo

Insilico Medicine

  • Healthcare

Founded 2014 · Hong Kong

Official Website

Insilico Medicine Funding Timeline

  1. Announced Mar 13, 2025

    Series E

    US$110 million

    Insilico raised the round as it developed its AI drug discovery platform and advanced its pipeline of drug candidates.

    Led by Value Partners Group.

    Source · prnewswire.com ↗
  2. Announced Jun 6, 2022

    Series D

    US$60 million

    Insilico said the funds would expand its drug pipeline and help establish a laboratory that combined AI with robotics.

    Source · prnewswire.com ↗
  3. Announced Jun 22, 2021

    Series C

    US$255 million

    Insilico said it would use the proceeds to move therapeutic programs into human trials and start additional drug discovery projects.

    Led by Warburg Pincus.

    Source · prnewswire.com ↗

Insilico Medicine Founding Team

Alex Zhavoronkov founded Insilico Medicine to apply AI to questions in aging and drug discovery. His early work at the company used biological data to study disease mechanisms and identify potential drug targets.

Insilico Medicine Products

  • Pharma.AI

    Apply generative models to pharmaceutical research and drug discovery.

Insilico Medicine Company Development

Connecting Molecule Design to the Laboratory

Insilico joined its computational drug discovery work to an internal pipeline and announced plans for a robotics laboratory in 2022. The lab plans added an experimental step to a process that starts with identifying targets and designing molecules.

Insilico Medicine Competitive Landscape

Generating Molecules and Profiling Biology

Insilico’s Pharma.AI spans target identification and molecule design. Insitro emphasizes large-scale measurements of human biology that can teach models which targets are relevant to disease. Both bring computation into drug discovery, with different starting points for the experimental work.