--- title: Google’s Drug Discovery LLM Signals Industry-Specific Shift | PYMNTS description: Google’s Drug Discovery LLM Signals Industry-Specific Shift. PYMNTS article, featuring Connie Yang, Managing Principal, AI and Data Science, DesignMind. image: https://www.designmind.com/hubfs/An%20illustration%20of%20virtual%20data.jpeg --- [![DesignMind Data and Analytics Experts](https://www.designmind.com/hubfs/logo-desingdind__whitetext.svg)](https://www.designmind.com) - [About Us](https://www.designmind.com/about-us) [About Us](https://www.designmind.com/about-us) [Leadership](https://www.designmind.com/leadership) [Press](https://www.designmind.com/press) [Clients](https://www.designmind.com/clients) [Technology Partners](https://www.designmind.com/technology-partners) - [Services](https://www.designmind.com/services) [Services](https://www.designmind.com/services) [AI and Data Science](https://www.designmind.com/ai-and-data-science-solutions) [Data and Analytics](https://www.designmind.com/data-and-analytics-services) [Data Lakehouse](https://www.designmind.com/data-and-analytics-services/data-lakehouse) [Data Warehouse](https://www.designmind.com/data-and-analytics-services/data-warehouse) [Master Data Management](https://www.designmind.com/data-and-analytics-services/master-data-management) [Modern App Dev](https://www.designmind.com/modern-application-development-services) [Power BI](https://www.designmind.com/power-bi-services) [Power BI Migrations](https://www.designmind.com/power-bi-services/power-bi-migrations) [Ad Hoc Consulting](https://www.designmind.com/ad-hoc-consulting) - 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[Jobs](https://www.designmind.com/jobs) - # DesignMind in the Media ## Company News # Google’s Drug Discovery LLM Signals Shift Toward Industry-Specific Approach [**DesignMind Featured in PYMNTS | October 16, 2024**](https://www.pymnts.com/artificial-intelligence-2/2024/googles-drug-discovery-llm-signals-shift-toward-industry-specific-approach/) Google DeepMind [has developed](https://research.google/blog/tx-llm-supporting-therapeutic-development-with-large-language-models/) an AI model to predict key properties of potential drugs, aiming to accelerate pharmaceutical research. The new Tx-LLM (Therapeutic Large Language Model) model exemplifies a shift toward specialized artificial intelligence tools for specific industries. This targeted approach could prove more valuable than general-purpose AI in addressing complex commercial challenges. “Industry-specific AI models are fundamentally reshaping business operations by leveraging the nuances of individual industries,” Adnan Masood, chief AI architect at [UST](https://www.ust.com/), told PYMNTS. Tx-LLM is an example of AI model fine-tuning, which involves taking a pre-trained model and refining it on a specific task or dataset to improve its performance in that area. This process allows the model to adapt to specialized needs without being built from scratch. ## **Tailoring AI to Industry Needs** Google’s new AI model aims to speed up drug discovery by predicting how potential medicines might behave in the body. Trained on a vast array of drug-related data, it outperformed specialized models in many tasks, from identifying promising molecules to forecasting clinical trial outcomes. This all-in-one approach could slash the time and money needed to bring new drugs to patients. “In drug discovery, AI models can be trained on specific biological data, speeding up processes like molecule identification or protein folding predictions,” said [Connie Yang](https://www.linkedin.com/in/connie-qin-yang), managing principal of data science and ML at [DesignMind](https://www.designmind.com/). “This leads to much faster R&D cycles and cost reductions.” But pharma is not the only industry feeling the impact. Fine-tuning could help factories get smarter, too. “Manufacturing leverages custom AI to predict equipment failures and optimize production lines through real-time analysis of supply chain dynamics, energy costs, and market demand,” Masood said. This means less downtime, more efficient production and lower consumer costs. Even car companies are revving up their AI engines. Yang pointed out that “AI can accelerate the design and testing phases for new vehicle models in the automotive industry.” This could mean seeing new, innovative cars hit the roads faster. ## **Transforming High-Stakes Sectors** Some industries have more to gain — and more to lose — when it comes to artificial intelligence. “Pharmaceuticals, finance and transportation are the front-runners for custom AI development,” Yang said. In the world of medicine, AI is a potential game-changer. “In pharma, AI can drastically cut the time it takes to go from discovery to market, even navigating some of the regulatory hurdles that typically slow down the process,” Yang said. For the money mavens, AI offers a sharp edge. “In finance, algorithms tuned to specific markets or risk profiles can provide a competitive edge,” said Yang. This might translate to better returns for investors or more stable financial systems. [Visit PYMNTS to read the full article >](https://www.pymnts.com/artificial-intelligence-2/2024/googles-drug-discovery-llm-signals-shift-toward-industry-specific-approach/)   “In drug discovery, AI models can be trained on specific biological data, speeding up processes like molecule identification or protein folding predictions, this leads to much faster R&D cycles and cost reductions." ##### Connie Yang ###### Managing Principal, AI and Data Science, DesignMind Featured in PYMNTS article, 10/16/24 [About DesignMind](https://www.designmind.com/about-us) DesignMind is a premier nationwide Analytics and AI consulting firm. Its experts implement industry-leading Digital Transformation, Data Modernization, and Artificial Intelligence initiatives for their clients. 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