Barrie Wilkinson’s Post

Webinar Alert!!! 📢 In my last post, I had asked you which topic in Batch Process optimization would you like us to cover in our upcoming webinar. Many of you said Yield optimization. Well, let's talk about that and other challenges as well such as cycle time reduction. Join us in our upcoming webinar on "Decoding AI for Batch Process Optimization" For which industry is it helpful? 1. Biomanufacturing (we are going to talk about Bioreactors for sure) 2. Pharma Manufacturing 3. F&B 4. Specialty Chemicals So, if you are someone into operations or digitalization of Batch Processes, this webinar is for you ✌ And don't worry while delayering this Onion of AI for Batch optimization, you will not have teary eyes but some know-how of doing it yourself 😀 #batchprocess #biopharma #pharma #specialtychemicals #Foodandbeverages

Imagine being able to talk to your data like you would with a colleague—no complicated tools or delays. That’s what WhizAI does: the "easy button" for pharma analytics, giving you instant insights when you need them." #Pharma #Commercial #Analytics #WhizAI #GenAI

In the ever-evolving world of #pharma, data can often feel like an insurmountable challenge leading to missed opportunities and delayed market responses. But with WhizAI, the "easy button" is now a reality. We’ve simplified the process, delivering actionable insights at the speed of thought. Real-World Transformative Impact: - Global Pharma Success: Transitioned from weeks to minutes for insights, transforming decision-making and seizing market opportunities. - Small Biotech Breakthrough: Reduced report generation by 90%, enabling swift responses to market shifts and sustained competitiveness. We're not just simplifying analytics—we're shaping its future. Learn more: https://lnkd.in/dJnGDk3U #GenAI #ConversationalAnalytics #LifeSciences

👩🔬 Why many PharmaCos' datasets are more attic than treasure trove 🤖 AI requires three ingredients: Data, algorithms and compute - and many pharma companies are convinced that they at least have plenty of the first. However, biology is different from physics or engineering in that biological data is mostly relative and lacks (absolute) standards. This makes many pharma companies’ (huge) datasets more like grandma’s attic than the expected treasure trove of insights. Many have wasted a lot of time trying to sort through 50 years of dusty files, old diaries and random boxes of photos without finding the jewels they though must have been hidden in there somewhere. (#Data42 anyone?) Given that companies continue to generate more data with every study, every day, a better approach is to clean out the attic and start fresh with some new, clearly labelled shelves and a clear filing strategy. Or to put it less metaphorical: Pharma companies can build a competitive advantage by standardizing and structuring their ongoing data collection, within one to two years they would have a real (data) asset. Do you agree? Or I am I too negative here?

At Novome Biotechnologies we did some of the most interesting and certainly most complex experiments I’ve been involved in, and I loved our discussions trying to identify the potential mechanisms to explain some surprising result. One frustration, though, that stuck with me was the many times I knew we did an experiment that would help address the specific point we were on, but couldn’t dig back into the old data fast enough to inform our discussion. Above is a picture I took of us attempting to have a discussion with all of the data in front of us. Actually trying to sort through the more than 300 experiments we ran on our biocontainment project during a real-time discussion was really fun but overwhelming. I am hoping we are on to a solution to this with Tabulous, a project Will DeLoache, Michael Lee, Zachary Russ and I have been working on for the last 6 months. We made some lightweight software designed to connect our favorite experiment organization system from Novome with AI assisted analysis. Basically, everything is organized in Google Drive and you work in Google Sheets but can also do the analysis either with code or by chatting with an assistant. I’ve been using it to remake some Novome plots for eventual publishing, and it’s worked better for me than Excel+Prism or a Jupyter notebook. Besides being easy to use, it connects everything in a way that I think will enable asking the assistant “Did we ever run strain X in an experiment where we did Y?” If you’re interested in checking it out, you can start using it for free at Tabulous (tabulous.ai). We’d love to get feedback on this. https://lnkd.in/eqaEFRqT

🔬 👨🔬 🤖 TetraScience just returned from the Databricks Data+AI Summit, where the future of scientific AI was on full display! Exciting times as we leverage AI to transform raw data into powerful insights, speeding up drug discovery and improving manufacturing processes. Our strategic partnership with Databricks is set to revolutionize life sciences, making data management seamless and AI-ready. From digital twins enhancing vaccine production to AI-driven predictive models, the possibilities are endless.   Moreover, unlocking scalable access to engineered scientific data with Databricks further transforms the life sciences industry. TetraScience’s lakehouse architecture captures all scientific data and makes it AI-ready, allowing for seamless handling of raw, semi-structured, and unstructured data. This unified approach enhances data management, governance, and advanced analytics capabilities, boosting scientific productivity and accelerating drug discovery and development.   #DataAISummit #ScientificAI #LifeSciences #AI #DataTransformation https://lnkd.in/gMPkXUBK https://lnkd.in/gp5fgXJQ

Our daily challenges!!! #cloud is already a commodity, we have to go #next! #GenAI but not only! Have a look here! SDG Group Italy Francesco Gerbino Marco Capirossi Federica Valle Giuseppe Pastore Luca Bergamini Paolo Menna #Transformation #adoption #advisory #AI #pharma #innovation #Innovation #DataDrivenDecisions #SuccessStory #TransformativeAnalytics #cloud #Management #data #technology #Analytics #GenAI #pharma #healthcare

🌟 New Launch Alert We're thrilled to announce the launch of Dimensions Knowledge Graph, a game-changer for the pharmaceutical and life science sectors! 🎉 Unlock the power of internal and global research data with the Dimensions Knowledge Graph, powered by metaphacts GmbH. Dive into approximately 350 million records and 50+ public datasets, seamlessly integrating external knowledge with your internal data repositories. Curious to learn more about how Dimensions Knowledge Graph can revolutionize your research and development process? 🤔 Find out more in our news article https://lnkd.in/eUk4rHEk Discover how Dimensions Knowledge Graph can fast-track target discovery, streamline processes, and accelerate drug discovery. Don't miss out on this opportunity to supercharge your insights! #DimensionsKnowledgeGraph #AI #Research #DataIntegration #DrugDiscovery #LifeSciences

Initial Data Offering (IDO): PharmaKB PharmaKB is a comprehensive data on drugs, companies, and diseases, curated by scientists for investors.   It contains most widely curated public data, standardized and cross-referenceable, and ready for your machine learning or for analysts to dive deep and uncover what scientists all over the world are working on. From clinical trials, specific targets, therapeutic areas, or scientific articles, government reimbursement, or just everything about a company and its competitors across the world. Semantic technology standardizes data for easy cross-referencing and integrations with AI Applications. Automated data streams from hundreds of sources, updated daily. See more details, request an introduction, and join the community in the link below