# Thirty-seven crowded targets and the case for AstraZeneca's insitro deal

> Last week AstraZeneca announced a deal with insitro to discover new targets and treatments for MASH and cardiomyopathies, with $40 million upfront. I think improving the evidence behind target selection is a sensible place for pharma to invest.

URL: https://www.ch-healthtech.com/insights/crowded-targets-astrazeneca-insitro-deal
Markdown: https://www.ch-healthtech.com/insights/crowded-targets-astrazeneca-insitro-deal.md
Published: 2026-10-20
Updated: 2026-10-21
Author: Christian Hein
Tags: technology/artificial-intelligence, technology/machine-learning, activity/partnership-alliance, industry/large-pharma, function/pre-clinical-research, therapeutic_area/cardiovascular

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## TL;DR

Last week, AstraZeneca announced a deal with insitro to discover new targets and treatments for MASH and cardiomyopathies. insitro will receive $40 million upfront, with up to approximately $1.46 billion in potential milestone payments. I am deeply convinced that improving the evidence behind target selection is a sensible place for pharma to invest. Much of the industry keeps competing around familiar targets, so I think identifying new targets with convincing biological evidence is increasingly valuable.

Thirty-seven drug targets have more than 50 development programmes each, according to Daphne Koller. I haven't written about insitro here before, although I really liked its founder's August essay, "Drug Discovery Has No Magic Wands".

Much of the industry keeps competing around familiar targets. The growing competition from Chinese biotechs also includes substantial work on established targets and new combinations of them. I think that makes the ability to identify new targets with convincing biological evidence increasingly valuable.

Last week, AstraZeneca announced a deal with insitro to discover new targets and treatments for MASH and cardiomyopathies. insitro will receive $40 million upfront, with up to approximately $1.46 billion in potential milestone payments. According to the announcement, insitro combines human and cellular data with machine learning to investigate the biological causes of disease.

Both conditions are relevant choices for target expansion, as patients with the same diagnosis can have quite different underlying biology. The collaboration covers target discovery and advancing AZ-nominated targets through to development candidates. AstraZeneca will lead clinical development, regulatory work and commercialisation.

Koller's argument connects with what I wrote in August about Dario Amodei's prediction that AI could cure most diseases within five to ten years. There is still a great deal of human biology to understand, and establishing whether a treatment helps patients takes time. I am deeply convinced that improving the evidence behind target selection is a sensible place for pharma to invest.