Bayer partners with Google for quantum drug discovery

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Bayer signs a collaboration agreement that applies Google Cloud’s computing power to drug discovery.

The agreement sees Bayer leveraging Google Cloud’s Tensor Processing Units (TPUs). According to Google, its TPUs are custom-develop, application-specific circuits used to accelerate machine learning workloads. The TPUs are designed to minimize the time-to-accuracy when training large, complex network models.

The aim is to apply this computing power to accelerate and scale Bayer’s quantum chemistry calculations. This will involve quantum mechanics being applied to computer-aided drug discovery, enabling the in-silico modelling of biological and chemical systems.

The partners stated that the objectives of the collaboration are to demonstrate that fully quantum mechanical modelling of protein-ligand interacts is possible. Further, the two companies will determine the scientific and economic viability of large-scale density functional theory calculations for practical applications.

Thomas Kurian, CEO of Google Cloud, outlined that accelerating drug discovery may be one of the most important applications for AI and high-performance computing in the healthcare industry, in terms of how new discoveries can be made with greater accuracy and speed.

“Bayer’s aspiration to be among the leading innovators drives us to continue to invest in novel and disruptive technologies to solve complex problems. Partnering with Google Cloud on TPU powered quantum chemistry complements our ambition to work with industry leaders and experts to quickly deliver on digital transformation,” said Bijoy Sagar, chief information and digital transformation officer at Bayer.

For Bayer, the partnership with Google to apply AI is one in a series of such steps for the company, as it looks to turn to digital solutions to build out its pipeline.

In 2019, the company employed Accenture’s AI clinical data collection and management tool in an effort to accelerate drug development and improve patient outcomes. The tool collected internal and external clinical data into a single platform, which can then be used to deliver actionable insights.

Bayer is not the only company engaged in the use of AI and machine learning for drug discovery, as the industry seeks to find ways to make the drug development process more effective. Biogen and Accenture Labs also signed a collaboration agreement to develop a quantum-enabled molecular comparison application.

While the industry also explores the potential for AI to improve manufacturing processes by predicting when upkeep work would be necessary, and thereby avoid unplanned maintenance.