Google Cloud Launches AI-powered Tools To Improve Drug Discovery And Precision Medicine

Google Cloud has announced two new AI-powered tools to help pharmaceutical and biotech companies accelerate new drug discovery and advance precision medicine.

The first of these tools is the Target and Lead Identification Suite. It has been developed to make it easier for companies to predict and understand the structure of proteins, which is a fundamental part of drug development. The second is the Multinomics Suite, which will help researchers capture, store, analyze and share large amounts of genetics data.

Both the tools will help companies in the biopharmaceutical sector invest less money in the drug discovery and launch processes, as they will help speed up their development times. So creating a new drug will not only cost companies less with these tools. They will also reduce time to market. Of course, this is not a simple process, as most drugs developed by biomedical and pharmaceutical companies fail to receive authorization to go on the market.

Both are already available to Google Cloud customers, and their cost will vary depending on each company and their needs. There are several pharmaceutical companies, such as Pfizer Pharmaceutical, as well as some biotech companies, that are already using both devices during a private trial phase.

Target and Lead Identification y Multinomics

The mission of the Target and Lead Identification Suite is to accelerate the first critical step in drug development: identifying a biological target that researchers can focus on, in order to design a treatment around it.

A biological target is in most cases a protein, and target detection involves identifying its structure, which determines its function, or its role in a disease. If you can understand this role and the structure of the protein, you can start developing drugs around it. But this process takes a long time and is often unsuccessful.

It can take researchers 12 months to identify just one biological target, and the two investigative techniques commonly used by researchers to determine protein structures also have high failure rates. But Google Cloud Suite relies on three principles to solve the problem.

First, it allows scientists to capture, share, and manage molecular data on a single protein with Google Cloud’s Analytics Hub. It is a platform that allows users to exchange data between organizations in a secure manner. Researchers can then use the data to predict the protein’s structure with AlphaFold2, a machine learning model developed by a Google collaborator.

AlphaFold2 runs on Google’s Vertex AI channel, a platform that enables researchers to rapidly develop and deploy machine learning models. That’s why, in just minutes, AlphaFold2 can predict a protein’s 3D structure with greater accuracy than traditional techniques, and do it at the scale that researchers need. Predicting such a structure is important, as it can help researchers understand the protein’s role in disease.

The third and final component of this suite helps researchers identify how protein structure interacts with different molecules. A molecule may become the basis for a new drug if it alters the function of a protein, thereby demonstrating its ability to treat disease.

With it, researchers can use Google Cloud’s high-performance computing resources to identify the most promising molecules for new drug development. These services provide the infrastructure businesses need to accelerate, automate, and scale their work.

For Google Cloud Multinomics Suite, it aims to assist researchers with the analysis of genetic data. Among other things, the suite seeks to give companies in the biomedical industry the structure they need to find useful information in large volumes of data, and to let them find it faster, so they can spend more time on new discoveries, and Less analysis in the data. According to Google Cloud, in addition to accelerating innovation in medicine, its functions and capabilities could be useful in the development of more personalized medicines and treatments.

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