Deepak Jha’s Post

The potential of generative AI in drug discovery has captivated the pharmaceutical industry, but what is the reality behind the hype? Generative AI has shown promise in accelerating the traditionally slow and expensive drug discovery process, with startups and established companies partnering up to capitalize on its potential. However, challenges such as technical limitations, data quality, and ethical concerns still need to be addressed. Applying generative AI in drug discovery has the potential to revolutionize the industry, from predicting molecular structures to discovering biomarkers for diseases. But there are also limitations, as AI struggles to fully comprehend the complexities of human biology. How do you think generative AI can be effectively integrated into drug discovery? — Hi, 👋🏼 my name is Doug, I love AI, and I post content to keep you up to date with the latest AI news. Follow and ♻️ repost to share the information! #generativeAI #drugdiscovery #pharmaceuticalindustry

1. Deep Genomics discovered a treatment for Wilson disease in 2019, marking the first AI-discovered therapeutic candidate. 2. The company tested over 200 million molecules but has since halted its Wilson disease program and has no drugs in clinical trials as of today. 3. Founder Brendan Frey criticized AI's effectiveness in drug discovery, stating it has not delivered on its promises over the past decade. 4. Drug discovery remains challenging, with 90% of candidates failing clinical trials, and AI has not significantly accelerated the process. 5. Deep Genomics is shifting focus to a new AI approach, developing a foundation model called BigRNA to simplify operations and improve drug development. 6. Other companies like Variational AI are also creating AI models tailored for drug discovery, offering cost-effective solutions for generating molecular structures. 7. The industry faces challenges, including data quality and the need for expertise in both AI and pharmaceuticals to validate predictions. 8. Frey remains hopeful about the future of AI in drug discovery, emphasizing the potential of foundation models to drive significant advancements.

Check out this fascinating breakthrough: AI models are transforming drug discovery, speeding up the process, and enhancing precision. 🚀💊 It's exciting to see how our industry is driving change in healthcare! 💡 What other areas do you think AI is set to disrupt next? Let’s discuss! 👇 👉 Read the article here #AI 💻 #HealthcareInnovation 🏥 #DrugDiscovery 🔬"

Do you want to know People in AI and how they are taking AI to another level? Read this interesting article. I have met personally Anne Lee, Chief Technology Office Partner, Nokia Bell Labs. It’s great to hear the vision of AI & data from her. #nokia #Belllabs #AI #futuretechnologies https://lnkd.in/gK9d7mwB

Hot off the press from Forbes: #AI Will Not Destroy The World—AI Illiteracy And Misuse Could Drug Discovery: Insilico Medicine, a drug discovery company, used #generativeAI to design a new drug candidate to treat idiopathic pulmonary fibrosis. They used generative AI throughout the preclinical drug discovery process to identify targets, generate drug candidates, and predict #clinicaltrial outcomes. This approach reduced the time and cost significantly, achieving results for one-tenth of the traditional cost and in one-third of the time, reaching the first clinical trial phase in just 2.5 years, compared to six years using conventional methods. Continue reading here: https://lnkd.in/eVxWbdgu

AI continues to be a hot topic in biotech, but let’s not forget the challenges that come with advanced technology. AI is not a magic cure, but a powerful tool that, combined with human expertise, can lead to significant advancements in treating diseases. The real magic happens when we blend AI's analytical capabilities with the insights of scientists to tackle untreatable diseases more effectively. More insights from STAT’s Casey Ross here: https://lnkd.in/dT6upRpt #AI #DrugDiscovery #UntreatableDiseases

Google DeepMind's unveiling of its next-generation drug discovery AI model. https://lnkd.in/ec_ksV3g This model is designed to accelerate the process of finding new treatments and medicines, leveraging the power of artificial intelligence to analyze vast amounts of data and identify potential breakthroughs. ..... #AINews #ArtificialIntelligence #Google #DeepMind #AIModel #DataModel #DrugResearch #NextGeneration

The next drug you take may be designed by AI. The current drug discovery process has a failure rate of about 90%. That is quite an impressive number. How can we apply AI to bring that number down? New AI models like AlphaFold 3 which can predict the structure and interactions of all of life’s molecules may be a fast step forward, still they need to prove their efficacy in the real world, which is often much more complex than simplified environments anticipated for predictions. #ai #drugdiscovery

Following extensive research within our community, the Lab of the Future Congress Europe 2024 includes case studies and use cases from exciting biopharma experts, insightful sessions on collaborative research partnerships, and discussions on how to address the challenges of onboarding novel technologies in research, development, and manufacturing. The multi-track program is focused on the following themes: -       AI to Innovate -       AI to Optimize -       Supporting the Biotechs of the Future -       Connected Lab -       Automated Lab -       Digital Transformation -       Data Strategy -       Lab Operational Excellence Learn more here:  https://lnkd.in/exU8kGHB #labofthefuture #ai #digitaltransformation #lotfeu2024

Check out this article... It talks about how AI is changing the game in drug design. Imagine, algorithms doing the heavy lifting, sifting through data at lightning speed. "AI has the potential to revolutionize drug discovery." What's next for AI?