insitro is a data-driven drug discovery and development company that leverages machine learning and high-throughput biology to transform the way medicines are created to help patients.

At insitro, we are rethinking the entire drug discovery process, from the perspective of machine learning, human genetics, and high-throughput, quantitative biology. Over the past five decades, we have seen the development of new medicines becoming increasingly more difficult and expensive, leaving many patients with significant unmet need. We’re embarking on a new approach to drug development – one that leverages machine learning and unique in vitro strategies for modeling disease state and designing new therapeutic interventions. We aim to eliminate key bottlenecks in traditional drug discovery, so we can help more people sooner and at a much lower cost to the patient and the healthcare industry.
 
We believe that by harnessing the power of technology to interrogate and measure human biology, we can have a major impact on many diseases. We invest heavily in cutting edge bioengineering technologies to enable the construction of large-scale, high-quality data sets that are designed specifically to drive machine learning methods. Our first application is to use human genetics, functional genomics, and machine learning to build a new generation of in vitro human cell-derived disease models whose response to perturbation is designed to be predictive of human clinical outcomes. 
 
This cannot be done without great people. We are bringing together an outstanding team of people whose expertise spans multiple disciplines - life sciences, machine learning, human genetics, engineering, and drug discovery - and building a unique culture where people from diverse backgrounds work as a single team towards a common goal. We offer opportunities to collaborative people with expertise in life science and computational science. Join us to help bring better health to more people, faster and cheaper.

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Canada Pension Plan Investment Board

Casdin Capital

Google Ventures

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Third Rock Ventures

Foresite Capital

Alexandria Venture Investments

HOF Capital

insitro

We’re excited to share significant progress in our science, advancing us towards our mission of bringing better drugs faster to patients who can benefit most with machine learning and data at scale. Featured in a new STAT article by Matthew Herper, insitro is proud to unveil the publication of three groundbreaking new research papers posted online. These papers cover our three core therapeutic areas - neuroscience, oncology, and metabolism - and highlight how our machine learning platform delivers novel insights across a broad range of biologies. Learn more about these noteworthy developments in the STAT story and explore further on our new website, www.insitro.com. #JPM24

Our CEO and founder Daphne Koller and insitro director of computational biology Angela Oliveira Pisco Pisco will join the AI & Data Sciences track on January 26 during #PMWC24. Daphne will give a keynote address titled, “Machine Learning for Therapeutic Discovery,” while Angela will join other industry leaders for a panel titled “Exploring the Power of AI and Data Sciences in Drug Discovery.” Don’t miss an exciting conversation around the role of #AI in #drugdiscovery and development. For the full agenda, visit the link here: https://lnkd.in/evyj5m3a

Since our inception more than five years ago, insitro has made significant strides toward unlocking transformative new medicines through our industry-leading machine learning platform and data at scale. We were proud to share our latest progress last week at the J.P. Morgan Healthcare Conference, including:  

1. In insitro’s #JPM24 corporate presentation, our CEO and founder Daphne Koller provided a snapshot of our ML-driven drug discovery platform and our rapidly emerging pipeline across our three therapeutic areas. 

2. We announced the appointment of Dr. S. Michael Rothenberg as chief medical officer. Most recently serving as VP of early oncology development and clinical research at Pfizer, Mike brings two decades of clinical care and drug development experience.

3. We published three new research papers, highlighting notable advances in #oncology, #ALS, and liver disease research –  
- Predicting patient stratification biomarkers from pathology images with ML
- Applying deep learning to interrogate the in vitro phenotypic consequences of ALS  genetics
- Improving genetic discovery for liver disease through multimodal #ML

Read our new research papers and other updates at https://lnkd.in/eUtMksuG. Stay tuned in 2024 as we continue to accelerate progress toward our mission.

insitro CEO and founder Daphne Koller joined fellow visionaries and leaders at the World Economic Forum Davos 2024 Annual Meeting this week, discussing advances in generative #AI models at the frontier of scientific research and its application. Watch the full panel below. #WEF24

We’re thrilled to share the recent publication of research aimed at leveraging #ML to expand the genetic landscape of MASLD. In our paper “Machine Learning Across Multiple Imaging and Biomarker Modalities in the UK Biobank Improves Genetic Discovery for Liver Fat Accumulation,” we leveraged ML to impute liver fat content across multiple imaging and biomarker-based modalities, followed by genome-wide association studies (GWAS), revealing novel insights into the genetic basis of liver fat accumulation. By further characterizing these GWAS associations, we demonstrated that a majority of the newly identified liver fat associations are likely clinically relevant to MASLD. Using advanced ML and imputation, we’ve enabled a series of large-scale GWASs in the UK Biobank to identify multiple genes that could potentially serve as therapeutic targets for MASLD.

Read our new paper: https://lnkd.in/gsCSUSWZ

Hari Somineni, Sumit Mukherjee, Ph.D., David (Didi) Amar, Jingwen Pei, Karl Guo, Dave Light, Kaitlin Flynn, Ph.D., Chris Probert, Tom Soare, Santhosh Satapati, Daphne Koller, David Lloyd, Colm O'Dushlaine

insitro Research Alert: #ALS is a devastating, genetically complex disease that makes the discovery of new medicines challenging. To address this challenge, insitro has built the world’s largest collection of ALS-related engineered cell lines and applied multimodal machine learning to uncover phenotypic consequences of genetic perturbations to identify potential therapeutic interventions. We are thrilled to be advancing this work in collaboration with our world class partners at BMS neuroscience. Read our recently published paper “Deep Learning Analysis on Images of iPSC-derived Motor Neurons Carrying fALS-genetics Reveals Disease-Relevant Phenotypes” to learn more about our approach and first-in-kind findings: https://lnkd.in/gDfaDSJz

Rahul Atmaramani, Tommaso Dreossi, Kevin Ford,  Lin Gan, Jana Mitchell, Shengjiang Tu, Jeevaa Velayutham, Haoyang Zeng, Michael Chickering, Tom Soare, Srinivasan Sivanandan, Ryan Conrad, Yujia Bao, Santiago Akle Serrano, Jonathan Liu, Stephanie Redmond, PhD, Syuan-Ming Guo, Patrick Conrad, Flora Yi, Nick Atkeson, difei xu, Aidan McMorrow, Emiliano Hergenreder, Mukund H., Ahmed Sandakli, Nitya Mittal, Liyuan Zhang, Aaron Topol, Brigham Hartley, Elaine (Higashi) Lam, Eva-Maria Tanzer (Krauel), Theofanis Karaletsos, Angela Oliveira Pisco, Ajamete Kaykas, Daphne Koller, Samuel Sances

New Research Alert: At insitro, we are deploying novel machine learning methods to better understand the complexities of cancer, a key step towards developing new and effective treatments. Our recently published paper, "Machine Learning-Enabled Prediction of Digital Biomarkers from Whole Slide Histopathology Images," details our approach to leveraging #ML and broad patient data to identify biomarkers that effectively stratify patients to enable the effective, targeted delivery of therapeutics and biomarker-informed design of new investigative medicines. https://lnkd.in/gNugZfKV

insitro is thrilled to announce the appointment of Dr. S. Michael Rothenberg as chief medical officer, marking a pivotal step forward as we advance our therapeutic programs towards the clinic. Dr. Rothenberg joins us from Pfizer, where he led a portfolio of early-phase oncology trials from first-in-human through proof-of-concept stages. With two decades of clinical care and drug development experience, he has worked across multiple therapeutic modalities, including small molecules, antibodies, antibody drug conjugates, bispecific engagers, and novel protein-engineered therapeutics, and he has made significant contributions to many first- and best-in-class medicines. Hear more from Mike in STAT: https://lnkd.in/gQnQKkE8

"We are incredibly excited to welcome Dr. Mike Rothenberg to our leadership team," said Daphne Koller, insitro CEO and founder. "Mike has an incredible track record of innovation in clinical trial design, developing and implementing data-driven strategies that have significantly accelerated the journey of bringing medicines to patients. He brings a deep understanding of genetics and multimodal data, and has used them to inform the design of biomarkers and improve clinical development. He will be a critical leader in achieving our mission of bringing better drugs faster to patients who can benefit most." Read our press release: https://lnkd.in/gEctsnpf

As we ring in 2024, insitro recommends NEJM AI as a pivotal resource in the New Year. We're excited to continue reading as insitro CEO and founder Daphne Koller and fellow members of the NEJM AI editorial board drive important and nuanced dialogue on AI's role in clinical development and patient care.

Are you coming to #JPM24? Be sure to check out our founder and CEO Daphne Koller on Monday, Jan. 8 at 3:30 p.m. PT for an update on our latest work and progress.

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Founder and CEO

Daphne Koller

Controller / Vice President, Finance

Allison Lai

VP Automation

Ben Miller

VP Metabolic Disease

David Lloyd

VP Integrated Assay Science

Ellen Berg

VP, Disease Modeling Systems & Arrayed Screening

Eugeni Vaisberg

Senior Vice-President Drug Discovery

Keith James

VP, Corporate Development and Strategy

Perry Palmedo

Vice President of Data Science and Machine Learning

Theofanis Karaletsos

SVP, Lab & Data Platform

Tom Stocky

Vikram Bajaj

Vijay Pande

Paul McCracken

Roger Perlmutter

Duane Valz

VP and General Counsel

Britt Huber

VP of People

Mary Rozenman

CFO and CBO

Chris Probert

Machine Learning Engineer

Francesco Paolo Casale

Data Scientist

Founder & CEO

Ajamete Kaykas

Zack Phillips

Staff Automation Engineer, Microscopy

Machine Learning Companies With Fewer Than 1000 Employees (Top 10K)

Therapeutics Companies With Fewer Than 1000 Employees (Top 10K)

Biotechnology Companies with Late Stage Venture Funding

United States Companies (Top 10K)

Insitro is an operator of a data-driven drug discovery and development company that utilizes machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients.

The company uses state-of-the-art technologies from bioengineering enabling it to generate high-throughput, functional genomic data sets and aligning them with patient data via novel machine learning methods, thereby building predictive models that can accelerate target selection and the design and development of effective therapeutics.

In 2018, Daphne Koller established Insitro in South San Francisco, California..

CPP Investments

Series C - Insitro

Andreessen Horowitz

Series B - Insitro

Series A - Insitro

Computer and Software Services and Scientific Services

South San Francisco

California

United States

North America

Insitro

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AI & drug discovery: A biotech CEO, a scientist, and a venture capitalist separate hype from reality

insitro Hires AI and Machine Learning Visionary, Emily Fox, Ph.D., as Senior Vice President of AI/ML

Leading Clinical Research Innovator, Amy Abernethy, M.D., Ph.D., Joins insitro Board of Directors

Alexandria Real Estate Equities, Inc. Announces Significant Early Renewal With insitro for a 6-Year Lease Extension at ...

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Insitro is a data-driven drug discovery company that aims to transform the way that drugs are discovered and delivered to patients.

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