New AI tools are aimed at speeding up drug discovery and precision medicine.
Google Cloud announced a suite of new AI tools for drug discovery and precision medicine at the Bio-IT World Conference & Expo in Boston.
The first announcement was the Target and Lead Identification Suite, which is for researchers working on identifying the functionality of amino acids and predict the structure of proteins. Google is utilizing its subsidiary DeepMind for the protein structure database, AlphaFold 2, alongside the deployment of Vertex AI data pipelines, to streamline data ingestion.
With this suite of tools, pharmaceutical companies and researchers can more quickly discover potential candidates and whittle down the most promising, while also setting up virtual screening. All of this is aimed at reducing the overall costs of drug discovery, which is reportedly in the range of $1 billion to $2 billion per successful drug.
There has been a lot of announcements recently in the world of drug discovery and utilizing AI to improve the time to discovery and time to market. A team of researchers from MIT built a generative AI model to speed up drug discovery by removing the need for drug docking, while researchers from the University of Toronto and Insilico Medicine built a drug discovery platform which designed a drug in under a month which could potentially treat primary liver cancer.
Google has obviously seen this interest and has made tools available which are easily operable with the Google Cloud platform. Data can easily be managed under Google Cloud’s Analytics Hub, and connected to the many tools on Google Cloud marketplace.
Some of the early adopters of this suite include pharmaceutical giant Pfizer and biotech company Cerevel. “We are partnering with Google on exploring how AlphaFold2 can potentially accelerate our drug discovery process and speed up our researchers’ ability to conduct their experiments,” said Nicholas Labello, principal computational scientist at Pfizer.
The second suite of tools is the Mutiomics Suite, which is aimed at providing organizations with the capability to store, distribute, and analyze high volumes of genomic data, which is becoming very difficult for researchers to analyze at a high level due to the volume doubling every 10 to 12 months. Google has a set of tools available which improve the data processing and storage, reducing the overall costs for organizations, while also providing analytical tools from first and third-party sources able to analyze genomic data and unlock new discoveries.
“We’ve long been involved with creating new tools for understanding and working with the code of life, like high performance computing for genomic analytics, and artificial intelligence that can predict three-dimensional models of proteins,” said Shweta Maniar, global director, Life Sciences Strategy and Solutions, Google Cloud. “These new solutions launching today can transform life sciences organizations by accelerating drug discovery and bringing therapeutics to market faster. When patients are waiting for that life-saving treatment in cancer care or that quality-of-life medicine for migraine headaches, this faster time-to-market can have an incredibly positive impact on lives.”
Artificial intelligence is expected to hit all industries in one way or the other. For pharmaceutical and medicine, it looks to be a mostly positive area of development, as researchers will be provided with an assistant able to go over hundreds of thousands of data points in a matter of hours, whereas it would take a human months to glean over every individual protein structure or genomic data. But researchers will still be necessary in the process, as quality control to ensure the AI is not having a hallucination or error due to faulty data. This could reduce the overall costs of developing drugs while also speeding up the discovery and production time considerably.