AI Case Study

University of the Philippines researchers are exploring making pesticides safer for consumption by analysing molecular chemistry using deep learning

University of the Philippines is working with Atomwise to analyse molecular chemistry using deep learning in an attempt to develop pesticides which are safer for human consumption.

Industry

Basic Materials

Agriculture

Project Overview

"To make pesticides safer, we simulate millions of compounds and identify the ones that target pests without causing toxicity in humans or other friendly species. Our technology allows us to investigate larger numbers of compounds via computer simulation and move human and environmental testing earlier into compound discovery, thereby letting us find better and safer compounds faster and more cheaply. We are working with Dr Marlon Manalo at the University of the Philippines, Los Baños, the premier institute in the Philippines focusing on agriculture, to integrate our predictive models into the pesticide development process. This work is supported by Grand Challenges Canada.

Atomwise’s software analyzes simulations of molecules, reducing the time researchers need to spend synthesizing and testing compounds. The company says it currently screens more than 10 million compounds each day. Atomwise’s AtomNet system uses deep learning algorithms to analyze molecules and predict how they might act in the human body, including their potential efficacy as medication, toxicity and side effects, at an earlier stage than in the traditional drug discovery process."

Reported Results

Research;Results not yet available

Technology

"Atomwise is focused on chemistry problems; specifically, using deep neural networks for structure-based drug design."

Function

R And D

Product Development

Background

"Pesticides cause an estimated 26 million poisoning cases and 220 thousand deaths annually."

Benefits

Data