Insitro
Active
DNA, Drug Development, Drug Discovery
Machine Learning

Business Overview

insitro is an exciting startup company that aims to take a new approach to drug development: one with big data and machine learning at its core. We plan to build on the ground-breaking innovations that have occurred in life sciences to develop large data sets that are designed from the start to allow machine learning to address fundamental bottlenecks in the drug development process. Our goal is to cure more people, sooner, and at a much lower cost. We are fortunate to have the strong support from the top investors in both biotech and tech: ARCH Ventures, Foresite Capital, A16Z, GV, and Third Rock Ventures. We are building a remarkable team that embodies a new type of culture, one based on a true partnership between scientists, engineers, and data scientists. Together we are working to define the problems, design experiments, analyze the data, and derive the insights that will lead us to new therapeutics. Join us, and help make a difference to patients!

Founded
February 2018
Employees
60
Business model
B2B
Offering type
Software
Funding stage
Series B
Total funding
$243 Million
Sectors
DNA, Drug Development, Drug Discovery, Healthcare, Next Generation Sequencing

Founders

Insitro
Daphne Koller
CEO
Serial Entrepreneur
AI Expert

Board Members and Advisors

Insitro
Vijay Pande
Board Member

Funding Rounds

Calculated as the average ratio between the current funding round amount raised and the previous funding round amount raised. Note that 'plus' rounds are summed together. i.e. Series A = Series A and Series A+.
Funding Growth Multiple
1.4x

Date Announced

Funding Round

Amount Raised

Investors

AI Technology Stack

AI Description

Powerful machine learning requires powerful data. Our data pipelines and automation infrastructure allow us to go beyond artisanal chemistry and biology, and rapidly generate massive amounts of high-quality data. This scale allows us to span much more of the diversity of human disease and potential therapies.

With massive amounts of high quality data, we then develop and deploy a variety of leading-edge machine learning methods. As witnessed in other industries, machine learning can make sense of vast amounts of high-dimensional data that are beyond human ability to interpret. Our machine learning models allow us to differentiate between cell states at much finer granularity and predict disease-relevant clinical traits.

AI employees
21
AI application
Vertical AI
AI types
Machine Learning
AI tools
Caffe, OpenCV, Pytorch, TensorFlow
Coding
C++, Python, R, Scala
Cloud provider
Amazon Web Services, Google Cloud AI

Similar Startups

STATUS
Active
STATUS
Active
STATUS
Acquired
STATUS
Active

Related Investors

TYPE
Family Office

INVESTMENTS

3

PORTFOLIO

3

TYPE
Private Equity

INVESTMENTS

3

PORTFOLIO

12

TYPE
Venture Capital
MIN CHEQUE
$0.25 M

INVESTMENTS

9

PORTFOLIO

6

TYPE
Venture Capital

INVESTMENTS

13

PORTFOLIO

10

CONFERENCE PRESENTATION

CONTACT

San Francisco
United States
279 East Grand Avenue

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