Google Cloud Expands Its Partnership With Ginkgo Bioworks For Two New AI-Tools Faster Drug Development

Zinger Key Points
  • Ginkgo Bioworks launches a protein large language model and a model API to accelerate drug discovery, developed with Google Cloud.
  • Ginkgo’s API offers competitive pricing and a free tier, making advanced AI tools accessible to researchers and scientists worldwide.

Tuesday, Ginkgo Bioworks Holdings, Inc. DNA announced two tools to streamline the drug development process for pharmaceutical and biotech companies.

Building on its partnership with Alphabet Inc’s GOOG GOOGL Google Cloud, Ginkgo introduced a protein large language model (LLM) and a model API, both designed to accelerate medicine development by leveraging AI and proprietary biological data.

These offerings aim to simplify and enhance how researchers and companies discover new therapeutics.

Researchers at Google DeepMind have developed AlphaFold 3, an new artificial intelligence (AI) model.

AlphaFold 3 can predict the structure and interactions of biological molecules. This includes proteins, DNA RNA, and small molecules that could function as drugs

The new protein LLM, developed in collaboration with Google Cloud Consulting and built on Vertex AI, offers powerful insights derived from Ginkgo’s private data to individual researchers and enterprise companies.

The model can help identify new therapeutic targets by analyzing protein structures and interactions, speeding up the discovery and development of life-saving medicines.

This tool is expected to revolutionize drug development pipelines, optimizing the process from lead identification to final approval.

In addition to the LLM, Ginkgo has launched its model API, an accessible and affordable tool aimed at providing machine learning scientists with AI models trained on Ginkgo’s proprietary protein and DNA datasets.

This API is available on Ginkgo’s website, with plans for enterprise access through Google Cloud’s Vertex AI Model Garden.

The API enables users to generate insights through advanced methods like masked language modeling and embedding calculations.

Ankit Gupta highlighted that predictions on protein sequences could be obtained for as little as $0.18 per million tokens, allowing researchers to scale their experiments without incurring high costs.

Ginkgo plans to release more models over the next year, broadening the API’s capabilities and expanding its suite of tools to tackle complex drug discovery, synthetic biology, and genomics challenges.

Price Action: DNA stock is up 11.60% at $6.95 at the last check on Tuesday.

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