BioBridges’ Post

Turning AI buzz words into a pharma / lifesciences business case To avoid getting swept up in news cycles and startup pitches, pharma leaders need to hone in on the concrete ways that AI can change jobs across their teams and organizations. In the latest piece from Rock Health Advisory, Sari Kaganoff, Irene Golden and Mihir Somaiya share a simple, straightforward approach to help #pharma leaders build AI use cases and ask the right questions to get to business decisions. Here is their read: https://lnkd.in/eyq-SUFw I present plenty of usecases of #AI in #healthcare in my #keynotes on this topic: https://lnkd.in/eQRVjtKV #artificialintelligence #aiinhealthcare #jobstobedone #biotech #lifesciences

'What does Data Science UA offer you in the #pharmaceutical industry?'🧪 My inbox is flooded by this and a lot of similar questions after numerous events in the #healthcare industry 🧬 Vasyl Chumachenko, PhD with his exceptional expertise in chemistry and pharma heads the AI consulting department at Data Science UA and is ready to upgrade your business with: 🔹Quality Control augmentation 🔹Safety and Security improvement 🔹Computer Vision assisted Defect Detection 🔹Warehouse and Supply Chain Management 🔹Drug Discovery Assistance Data Science UA team has over 8 years of developing AI solutions. We bring together talent with unique niche experiences in different areas🦾 Do you want to know how to get high-quality results with low management in the short term? Let's get in touch 💻 #DataScience #FutureOfTech #Innovation #Technology #AI #aisolutions

🌟 Transforming Biotech with Large Context LLMs 🌟 The biotech industry is significantly transforming, thanks to the advancements in large context language models (LLMs). These powerful #AI tools are set to revolutionize various aspects of #biotech, offering unprecedented opportunities for innovation and efficiency. Here's how LLMs are changing the biotech landscape: Accelerating #DrugDiscovery and #DrugDevelopment: LLMs can analyze vast amounts of biomedical literature, clinical trial data, and research articles, identifying patterns and insights that expedite the drug discovery process. This capability can lead to faster development of new therapies and a deeper understanding of drug interactions and side effects, ultimately reducing costs and timelines. Enhancing Clinical Research: By leveraging LLMs, researchers can streamline the process of literature review and data extraction, enabling them to focus on high-value tasks such as hypothesis generation and experimental design. This efficiency boost can significantly accelerate the pace of clinical research and innovation. Improving Patient Care: LLMs can assist #healthcare professionals by summarizing complex clinical notes, extracting essential information, and generating clear, concise summaries. This not only saves time but also enhances the accuracy of patient records, leading to better-informed medical decisions and improved patient outcomes. Advancing Personalized Medicine: With the ability to analyze large datasets, LLMs can identify personalized treatment plans based on a patient’s molecular genetic profile, medical history, and current health status. This approach promises more effective and tailored treatments and implementation of #personalizedmedicine approaches, improving the overall quality of healthcare. Supporting #Regulatory Compliance: In the highly regulated biotech industry, ensuring data integrity and compliance with standards like HIPAA and GDPR is crucial. LLMs can help by automating the documentation and reporting processes, ensuring accuracy and reducing the risk of non-compliance. As we continue to explore and harness the potential of large context LLMs, the biotech industry stands to benefit immensely from these innovations. Embracing these technologies will lead to more efficient research, better patient care, and groundbreaking discoveries.

🔍 Using data engineering to drive innovation in pharma 💊 Data engineering is the unsung hero in the quest for groundbreaking treatments. By harnessing vast amounts of data, pharma companies can accelerate the development of life-changing therapies. From genetic insights to patient outcomes, every data point is a step closer to a medical breakthrough. 💡 Incorporating cutting-edge technology and analytics, data engineers help streamline processes, identify patterns, and unlock valuable insights. This pivotal role not only expedites research but also enhances precision in treatment development. 🚀 As we delve deeper into the realms of data-driven healthcare, the synergy between data engineering and pharma unveils endless possibilities for transformative advancements. Let's continue to innovate and collaborate towards a healthier future together. 💪 #DataEngineering #PharmaInnovation #HealthTech --- Crafted with engagement and value in mind, this post aims to spark discussions and illuminate the vital role of data engineering in pharmaceutical innovation. Let me know if you need any further assistance.

In our latest article, Marissa Moore, CFA dives into the evolving dynamics of biopharma R&D, addressing key challenges like declining productivity and increasing fragmentation. Where might new technologies, particularly AI and advanced data analytics, create significant opportunities to enhance efficiency and success rates in both early-stage and clinical-stage R&D? 💡 From improving target validation to optimizing clinical trial operations, tech innovations could have a profound impact. Key insights: • The role of AI in early-stage R&D • Opportunities in clinical trial management and automation • Challenges with software adoption in preclinical research • The importance of differentiated capabilities for success If you’re working in this space or have insights to share, Marissa Moore, CFA would love to hear from you! 📖 Read the full article here: https://lnkd.in/gdu_zHbq

🔬 AI adoption is accelerating across life sciences, with growing enthusiasm in departments leveraging open-source data - competitive intelligence, medical affairs, R&D, BD, new product planning, etc. In my recent talks at the Pharma CI Conference and Pharma and MedTech Information (PhMTI) conferences, I discussed how various AI levels can be effectively used across these functions. Few key takeaways from my talk and recent industry observations: 👥 The AI spectrum (simple to general) requires task-appropriate application, balancing AI capabilities with domain expertise for the right use cases 🎯 Successful AI implementation requires clear business objectives, strategic implementation, and ongoing ROI measurement 🚀 AI workflow development and pilot project selection are crucial steps in the execution phase #AIinLifeSciences #DigitalTransformation #OpenSourceAI #CompetitiveIntelligence #AIStrategy #kognitic #pharma

What happens when we combine the precision of AI with the life-saving potential of drug discovery? 🔬 The answer: An accelerated path to treatment for countless patients. But are our current development processes prepared for this new era? Let's explore. In today’s world, AI is tapping into the wealth of Real-World Data (RWD). This data comes from various sources like electronic health records, claims data, and emerging ones such as biobanks, omics panels, genomics studies, patient registries, and digital pathology. Importantly, patients are now empowered to share data, advancing research in privacy-respecting ways, with AI models trained to uphold privacy standards. AI is transforming these vast datasets into actionable insights, revolutionizing how we understand and approach healthcare. 🤖💡 From strategic asset selection to refining clinical trial designs, the potential of AI and RWD is enormous. However, the current AI and RWD adoption in clinical development often remains confined to isolated use cases within pharma companies. Initiatives to build and scale capabilities across portfolios and asset life cycles are crucial for realizing the full potential of this groundbreaking era in drug development. Those who strategically embrace and adopt AI and RWD are set to stay ahead in the dynamic landscape of clinical development. 🚀💊 Scroll through our carousel to learn about the digital innovations shaping the future of healthcare! 🔬 #AI #Pharma #ClinicalDevelopment #Innovation #LifeSciences #DigitalTransformation

𝐀𝐩𝐩𝐥𝐲𝐢𝐧𝐠 𝐀𝐈 𝐚𝐧𝐝 𝐌𝐋 𝐭𝐨 𝐎𝐩𝐭𝐢𝐦𝐢𝐬𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬 𝐚𝐧𝐝 𝐄𝐧𝐡𝐚𝐧𝐜𝐞 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐒𝐚𝐟𝐞𝐭𝐲 𝐢𝐧 𝐏𝐡𝐚𝐫𝐦𝐚𝐜𝐨𝐯𝐢𝐠𝐢𝐥𝐚𝐧𝐜𝐞 This insightful article is featured in "𝐏𝐡𝐚𝐫𝐦𝐚 𝐅𝐨𝐜𝐮𝐬 𝐄𝐮𝐫𝐨𝐩𝐞 𝐌𝐚𝐠𝐚𝐳𝐢𝐧𝐞 𝐈𝐬𝐬𝐮𝐞 𝟎𝟒." In the realm of #drugsafety, traditional clinical studies, they have their limitations. With only a fraction of potential adverse reactions identified pre-launch, continuous monitoring post-marketing becomes paramount. Bianca Piachaud-Moustakis, PhD explores how 𝐚𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐚𝐧𝐝 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 revolutionize this landscape. Leveraging advanced algorithms, AI sifts through vast datasets in real-time, detecting subtle patterns and anomalies that human oversight might miss. This proactive approach not only accelerates the identification of adverse #drug reactions but also enhances the precision and scope of safety monitoring. 𝐉𝐨𝐢𝐧 𝐮𝐬 𝐢𝐧 𝐫𝐞𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐭𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐩𝐡𝐚𝐫𝐦𝐚𝐜𝐨𝐯𝐢𝐠𝐢𝐥𝐚𝐧𝐜𝐞! 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫 𝐡𝐨𝐰 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐚𝐫𝐞 𝐩𝐚𝐯𝐢𝐧𝐠 𝐭𝐡𝐞 𝐰𝐚𝐲 𝐭𝐨𝐰𝐚𝐫𝐝𝐬 𝐬𝐚𝐟𝐞𝐫 𝐩𝐡𝐚𝐫𝐦𝐚𝐜𝐞𝐮𝐭𝐢𝐜𝐚𝐥𝐬. 🔗𝐋𝐞𝐚𝐫𝐧 𝐌𝐨𝐫𝐞:https://lnkd.in/gTWh6982 🔗 𝐃𝐨𝐰𝐧𝐥𝐨𝐚𝐝 𝐭𝐡𝐞 𝐞-𝐛𝐨𝐨𝐤 𝐧𝐨𝐰: https://lnkd.in/gv7R4SPi #AIinPharmacovigilance #PatientSafety #DrugSafety #ArtificialIntelligence #MachineLearning #HealthTech #Innovation #HealthcareAI #ClinicalResearch #DigitalHealth #PharmaTech #Bioinformatics #DataScience #MedTech #HealthcareInnovation

🌟 Join us for the Lead Generation & Optimization track, at the AI in Drug Discovery Xchange, Boston. 🌟 COMPLIMENTARY registration here! https://bit.ly/43qUJXC Our industry experts will share invaluable insights and strategies to boost your lead generation efforts and how AI can advance you further! 📈 👀 Here's a glimpse of what to expect: 👩🏫 Taking advantage of new methods in lead generation and optimization. 🗣️ Yating (Claire) Chai, Associate Director, Computational Biology & ML/AI, Astellas Pharma 🧑🏫 Informed lead generation from the screening of ultra large databases. 🗣️ Alexis Molina, Director of AI, Nostrum Biodiscovery Don't miss out on this opportunity to network with industry peers and gain actionable insights to drive your business forward. Register now to secure your spot! 🚀 🏆 Our Partners 🏆 🔺 Optibrium 🔺 Biorelate Ltd. 🔺 DrugBank 🔺 Nostrum Biodiscovery 🔺 Strand Life Sciences 🔺 Seqera 🔺 Collaborative Drug Discovery - CDD Vault * Agenda subject to change 💊 Only available for Senior Scientists and above, from Bio and Pharma companies with a drug pipeline. 💊 #LeadGeneration #Optimization #Networking #Innovation #AIinDrugDiscovery #NetworkingEvent #IndustryInsights #AIinLeadGeneration #LifeSciencesNetworking #hubXchange #Roundtable #FreePass #RegisterNow #ComplimenatryPass

Learning about the life sciences sector has been eye-opening The data streams these companies generate is colossal We're talking: - Regulatory filings - Clinical trial results - Market Research Data - Risk Assessment Results - Resource Utilization Metrics - Investment and Financial Data The challenge staring life sciences leaders in the face? ↪ Sifting through this data maze. Extracting insights to inform strategic decision-making. It's not just about making sense of this data. But actually using it to shape the R&D goals. Managing the portfolio, mitigating potential risks, and ensuring compliance. And this isn't really an option - it's a necessity. Think about the decisions that rest on this data... ↪ The development of life-altering drugs. ↪ The next milestone in personalized medicine. ↪ The next innovative therapeutic technique. These aren't decisions to be taken lightly. To handle this, companies need to use many different solutions together. A way to understand and organize data. A way to link big goals with research work. A way to enable a workplace that adapts to changes quickly. On top of this... Leaders need to be open to using new tech, like AI and Machine Learning, to predict what will happen next. It's an exciting time to be at Planview. We're helping Life Sciences Leaders make better decisions. Create new things faster. And, in the end, lead to a healthier future. The key shift that is defining the market leaders this year is this: Moving from just having lots of data, to really using it. Using it to achieve the ultimate mission of this industry. Serving patients better. Because, ultimately, the goal of all the data, all the technology, all the innovations... is to improve the lives of millions. Call me cheesy... but I think this partnership between technology and humanity is beautiful. This is the future! #lifesciences #biotech #biopharma