We are industrializing the discovery of new medicines.

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In Silico Discovery Meets Empirical Discovery

We Design

We explore our proprietary 1859 virtual library for a specific disease target and then design focused libraries of small molecules predicted to affect that target in a desired way.

We Build

We construct the focused libraries of small molecules for testing in a matter of weeks.

We Test

We screen focused libraries in a biochemical or cell based context at the pico-scale, with a few milliliters of materials.

We Learn

We discover the identity of the molecules that affected the disease target, and then leverage machine learning and AI to design new focused libraries predicted to produce even better discoveries.

You have a novel target?
We have a novel library.

We offer the ability to navigate chemical space unimpeded by the capital and time constraints of the status quo, giving our partners access to the right type of chemical matter from the start of a discovery program. We use both structure-based and ligand-based virtual screening methods to identify the right properties of the molecules needed to affect a particular disease target. Lastly, we offer the ability to screen our growing inventory of Training Set Libraries designed to tease out the types of molecules we should include in a subsequent library design.


Active Programs


Molecules per Week Screened

3 weeks

for New Library Build

4 mL

of Material per Screen


We are giving major pharmaceutical
partners unprecedented capabilities.

“…we are enthusiastic about the potential for 1859’s technology to enable miniaturized cell-based assays, ultra-high throughput screening, and rapid exploration of chemical space. The 1859 team has proven to be excellent partners.”

—Confidential Top 25 Pharma Partner

Interested in becoming an early access partner?

Interested in becoming an early access partner?

We are opening up our technology and capabilities to partners looking to join our revolution on upending the current paradigm for new medicine discovery.

Let's Partner
Chris standing up holding his daughter Elva

We are building the tools that will make the discovery of new medicines a data science.

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Who We Are.

We are a team of chemists, biologists, engineers, coders, and innovators.

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Johnny Koo Johnny Koo
Kerry Wilson Kerry Wilson
Pavel Chubukov Pavel Chubukov
Reo Yoo Reo Yoo
Yousif Slaiwa Yousif Slaiwa
Andrea Rothmeier Andrea Rothmeier
Brian Tenner Brian Tenner
Caroline Habib Caroline Habib
Corey Bretz Corey Bretz
Hannah Finnegan Hannah Finnegan
Nick Job Nick Job
Talon Mahosky Talon Mahosky
Jonathan Iaconelli Jonathan Iaconelli
Neil McAlpine Neil McAlpine
Phil Cistrone Phil Cistrone
Ryan Noorbehesht Ryan Noorbehesht
Shahed Kay Shahed Kay
Warren Wade Warren Wade
Alexandre Gillet Alexandre Gillet
Cassandra Chen Cassandra Chen
Nicholas Reed Nicholas Reed
Scott Sylliaasen Scott Sylliaasen
Sean Michael Sean Michael
Adam Bouzaffour Adam Bouzaffour
Danielle Gelsinger Danielle Gelsinger
David Milliken David Milliken
Jonathan Kirkland Jonathan Kirkland
Sara Tin Sara Tin
Alex Price Alex Price
Aparna Balarama Rao Aparna Balarama Rao
Jill Tee-Sy Jill Tee-Sy
Kyle Lawrence Kyle Lawrence
Monica Hilgeman Monica Hilgeman
Parth Shah Parth Shah
Austin Crinklaw Austin Crinklaw
Ingrid Barbosa Farias Ingrid Barbosa Farias
Jason Del Rio Jason Del Rio
Josh Wade Josh Wade
Sean Stromberg Sean Stromberg
Steve Brown Steve Brown
Andrea Bacconi Andrea Bacconi
Andrew MacConnell Andrew MacConnell
Austin Hallgren Austin Hallgren
Devon Cayer Devon Cayer
Jeff Noonan Jeff Noonan
Michael Nyman Michael Nyman
Nora Safabakhsh Nora Safabakhsh
Paula King Paula King
Ramesh Ramji Ramesh Ramji
David Holmes David Holmes
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