ASHG 2026 · Biopharma

insitro, inc. at ASHG 2026

South San Francisco, California

insitro, inc. at ASHG 2026 in Montréal: 5 presentations (5 posters).

5
presentations on the program
1
Reviewers’ Choice abstracts

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OrganizationASHG 2026 Attendance
insitro, inc.
South San Francisco, California
2 Staff Data Scientist · 1 Statistical Geneticist · 1 Scientist I · 1 Scientist
Private company~260 people
insitro develops therapeutics and AI discovery platforms using causal human biology, machine learning, and multimodal human and cellular data. Its focus includes metabolic disease, neuroscience, and oncology.
insitro appointed Hideo Makimura as chief medical officer to lead its transition into a clinical-stage company.
insitro appointed Hideo Makimura as chief medical officer to lead its transition into a clinical-stage company.
2026-09 · source
insitro presented preclinical data showing its AI-discovered MASH drug candidate has anti-fibrotic effects beyond liver fat reduction.
2026-06 · source
insitro expanded its strategic collaboration with Bristol Myers Squibb to include two new ALS drug targets.
2026-03 · source
Source: company newsroom
Raised $400M Series C (Mar 2021)
Led by CPP Investments; the most recent disclosed funding round for the company. · 2021-03-15
“insitro today announced that it has raised $400 million in a Series C financing.”
Source: funding announcement
Poster
Wed Oct 21
2:30 pm
Multimodal imputation of regional adiposity reveals shared genetic architecture across fat depots and anthropometric traits
Complex Traits and Polygenic Disorders
Genome-wide association studyObesityMetabolic disorder
Poster
Thu Oct 22
4:15 pm
Genetics-guided phenotype imputation increases GWAS power without increasing sample size: age-related macular degeneration as a case study
Statistical Genetics and Genetic Epidemiology
Collaborators: Institute of Rheumatology, University of Oxford +1 more
Genome-wide association studyLarge-scale biobanksElectronic health recordsMethodology
Poster
Thu Oct 22
4:15 pm
ML-based MRI phenotyping of supraclavicular fat enables genetic discovery of human brown adipose tissue
Artificial Intelligence and Machine Learning
Deep learningGenome-wide association studyStatistical geneticsPhenotype
Poster
Thu Oct 22
4:15 pm
Poster
Fri Oct 23
2:30 pm
★ Reviewers’ Choice
Retinal Imaging AI augments association power for GWAS of age-related macular degeneration
Artificial Intelligence and Machine Learning
Collaborators: University College London
Artificial intelligenceComplex diseasesGenome-wide association studyMachine learning

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