Meg Heim’s Post

🌟 2024 Predictions: AI and Automation in Life Sciences 🌟 Experts across the life sciences sector are highlighting the transformative role of AI, ML, and automation for the coming year and beyond. From pharmacovigilance to drug discovery and patient engagement, these technologies are set to revolutionize how we approach some of the industry's most pressing challenges. 🔍 Key Insights: Pharmacovigilance: Updesh Dosanjh from IQVIA notes that automation is essential to handle increasing case volumes. However, implementing AI in broken processes could hinder long-term success. Organizations must adopt holistic strategies for effective transformation. Drug Discovery: Cameron Ross of Elsevier highlights AI's impact on small molecule discovery, reducing costs and accelerating the development pipeline. With AI-driven processes growing annually, we're on the brink of a new wave of innovative drugs. Clinical Trials: Leslie Orne from Trinity Life Sciences emphasizes AI's role in patient enrollment for cell and gene therapies, which is crucial for advancing life-saving treatments. Manufacturing: Matt Todd of Ori Biotech foresees AI enhancing CGT manufacturing through dynamic supply chain management and scenario-based forecasting, leading to better patient outcomes. AI is not just a tool but a catalyst for innovation, efficiency, and better patient care. As regulations evolve, the challenge will be integrating these technologies responsibly while maintaining data privacy and patient safety. Read the full article: https://lnkd.in/dNgqNJ7e Join us as we navigate this exciting future, leveraging AI to unlock new possibilities in life sciences! #AI #MachineLearning #Automation #LifeSciences #Pharmacovigilance #DrugDiscovery #ClinicalTrials #Biotech #HealthcareInnovation #KostenDigital

🚀 Sci-Fi Saturday: Unveiling the Next Frontier in Pharmaceutical Innovation 🌌💡 Greetings, fellow explorers of the unknown! Today, on Sci-Fi Saturday, we're embarking on a journey through the uncharted territories of pharmaceutical innovation, where science fiction meets scientific reality in the most intriguing ways. 🔬 Nanorobotics Revolution: Prepare to be amazed by the marvels of nanorobotics, where miniature machines navigate the intricate landscapes of the human body to deliver targeted therapies with unprecedented precision. Imagine a future where tiny nanobots patrol our bloodstream, detecting and neutralizing cancer cells before they can wreak havoc. With the potential to revolutionize drug delivery and disease treatment, nanorobotics is paving the way for a new era of personalized medicine. 🧬 Gene Editing Epiphanies: Step into the realm of gene editing, where CRISPR technology reigns supreme as the tool of choice for rewriting the code of life itself. Explore the possibilities of curing genetic diseases, enhancing human potential, and even resurrecting extinct species through the power of genetic manipulation. As scientists unlock the secrets of the genome, the boundaries of what's possible are pushed ever further into the realms of science fiction. 🌿 Plant-Based Pharmaceuticals: Venture into the world of plant-based pharmaceuticals, where ancient remedies meet modern science in a botanical symphony of healing. Discover the untapped potential of medicinal plants, from the Amazon rainforest to the depths of the ocean floor, as researchers harness nature's pharmacy to develop new drugs and treatments for a myriad of ailments. With sustainability and natural efficacy at the forefront, plant-based medicine offers a tantalizing glimpse into the future of healthcare. 🔮 AI-Powered Drug Discovery: Peer into the crystal ball of artificial intelligence, where machine learning algorithms sift through vast datasets to uncover hidden patterns and potential drug candidates. Witness the dawn of a new era in drug discovery, where computers become the ultimate lab assistants, accelerating the pace of innovation and unlocking new avenues for therapeutic intervention. As AI continues to evolve, the possibilities for drug development are limited only by our imagination. Join us as we embark on a voyage of discovery, where imagination knows no bounds and the future of pharmaceuticals is limited only by our collective creativity. Together, let's explore the frontiers of science fiction and forge a path towards a brighter, healthier tomorrow. #PharmaInnovation #SciFiSaturday #FutureOfMedicine #Nanorobotics #CRISPR #PlantMedicine #AIinPharma #DrugDiscovery #PharmaceuticalRevolution #HealthcareTechnology

Profluent Harnesses AI to Streamline Medicine Discovery Founded by former Salesforce researcher Ali Madani, Profluent is a recently-launched startup that uses generative AI to create custom-fit proteins and gene editors for pharmaceutical companies. By leveraging AI to accelerate the standard drug research process, Profluent allows pharma companies to shift from accidental discovery to intentional design of biotech solutions - helping substantially reduce the cost and development time of new genetic medicines. Profluent is supported by Google, and is backed by several top VCs including Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures. For GlenFlow and our MedTech venture OxyDial - we're thrilled to see the rapid expansion of AI in the medical research and drug discovery process, with startups like Profluent and Basecamp Research harnessing the power of these new tools to push the envelope of what is possible. Read more: https://lnkd.in/gGfYMe2D #profluent #ai #generativeai #proteinengineering #geneediting #pharmaceuticals #drugdiscovery #geneticmedicinel #medicalresearch

Thank you Mike Montello, GSK, SVP R&D Digital and Technology, for fantastic interview on leveraging technology to accelerate growth! GSK is one of the top 10 pharmaceutical companies in the world.  It’s therapeutic areas of strength include infectious disease, HIV, respiratory, immunology and oncology. Key takeaways:   -  GSK pipeline is genetically inspired; links medicine developed to underlying genetics. This needs many dimensions of data such as imaging, DNA type, structured, unstructured, etc.    -  GSK proprietary research data platform scales use of AI in drug discovery -  For example, use of imaging AI tools helps find patterns and starting points. AI is applied to various data sources, such as real world evidence, to find patients who will respond the most to medicines and vaccines. Picking better targets results in high probability of success.   -  Completed significant investment to build standard platform across all GSK clinical studies (i.e., research for vaccine or medicine). Examples of outcomes: achieved upper quartile cycle times of phase 3 studies and saved 20 mn pounds (currency) per year.  -  GSK has enterprise AI governance council that reviews use cases to evaluate and monitor benefit vs. responsible use of AI before implemented at scale to many users -  Open to business with start ups who understand GSK priorities which include: increase probability of success before run clinical studies or accelerate clinical studies; enrollment - find patients that meet inclusion or exclusion criteria and enroll them faster into trials   Your thoughts on technology and AI being accelerators in the pharmaceutical industry? Link to full episode in comment box below. Thank you for watching The HLTH Daily Show!  #health #healthcare #wellness #ceo #leadership #innovation #technology #digital #transformation #business #patientcare #pharma #gsk #data #ai #artificialintelligence #venturecapital #privateequity #investing #entrepreneurship #founders #startups #hlth HLTH

Recent Trends in the Pharma Industry: Shaping the Future of Healthcare 🌟 The pharmaceutical industry is undergoing transformative changes, driven by technological advancements, innovative therapies, and a heightened focus on patient-centric care. Here are some key trends shaping the future of pharma: Digital Transformation & AI Integration. AI and Machine Learning: Revolutionizing drug discovery and development by predicting outcomes, optimizing clinical trials, and personalizing medicine. Telemedicine & Digital Health: Enhancing patient access to care and enabling remote monitoring and virtual consultations. Personalized Medicine & Genomics 🧬 Genetic Profiling: Tailoring treatments based on individual genetic profiles to increase efficacy and reduce side effects. Biomarkers and Companion Diagnostics: Facilitating the development of targeted therapies and more precise treatment plans. Advanced Therapeutics 💉 Cell and Gene Therapy: Offering potential cures for previously untreatable diseases through groundbreaking treatments like CAR-T therapy and CRISPR gene editing. mRNA Technology: Expanding beyond vaccines to potentially treat a variety of diseases, harnessing the power of messenger RNA. Sustainability and Green Chemistry 🌱 Eco-friendly Practices: Implementing sustainable manufacturing processes and reducing environmental impact through green chemistry and waste reduction initiatives. Circular Economy Models: Promoting recycling and reuse of materials within the pharmaceutical supply chain. Patient-Centric Approaches - Enhanced Patient Engagement: Utilizing digital tools and platforms to improve patient education, adherence, and outcomes. Value-Based Care Models: Shifting focus from volume to value, ensuring that patient outcomes and quality of life are prioritized. Regulatory Innovations - Fast-Track Approvals: Accelerating the approval process for breakthrough therapies, ensuring patients get access to life-saving treatments faster. Real-World Evidence (RWE): Leveraging data from everyday clinical practice to support regulatory decisions and post-market surveillance. Transformative Data Solutions 📊 Data Analytics & Insights: Harnessing big data to provide actionable insights, optimizing drug development processes, and improving patient outcomes. Collaborative Platforms: Enabling seamless collaboration between researchers, clinicians, and stakeholders to drive innovation and enhance efficiency. The pharma industry is at the cusp of a new era, where innovation and patient care go hand in hand. Embracing these trends, including cutting-edge data solutions, will not only drive growth but also lead to better health outcomes worldwide. #PharmaTrends #HealthcareInnovation #DigitalHealth #PersonalizedMedicine #Sustainability #PatientCentric #AIinPharma #FutureOfHealthcare #Resonacle

"By working on mini-proteins, Ordaōs may be able to cut a slice of the AI generative pie that no one else will touch. However, if Insilico Medicine and Recursion Pharmaceuticals are real generative AI companies, they may have gotten hits for mini proteins." #computationalchemistry #machinelearning #artificialintelligence #drugdesign #biotherapeutics #mRNA

Interested in learning what is coming for biotech in 2024? Check out a recent article from Bio-IT World wich includes perspective from our own Jo Varshney : Half of new drug applications will feature AI, but translation will remain a challenge: In 2023, the FDA issued a request for industry comment on the integration of AI in drug and biologics development. They acknowledged the growing use of AI by sponsors, noting that more than 100 IND submissions received in 2021 included AI/ML components. We believe that 2024 will see an increase to ~400 applications referencing AI/ML data and analyses. But despite the increased prevalence, AI-enhanced drug candidates may not fare well in the clinic, as was evidenced in 2023. This is because much of the early application of AI has been on molecule discovery. And while using AI to explore chemical space and unlock new targets is valuable, its potential to guide translational research has been far less adopted. Sadly, this bottleneck still prevents the accelerated access to novel therapies for patients in need, as clinical trials fail from endpoint misses and toxicity. In 2024, pharma companies and emerging biotechs will improve candidate safety profiles and reduce off-target effects by exploiting predictive intelligence unlocked by AI.

🚀 Exciting News in AI-Driven Drug Discovery! Deep Pharma Intelligence's groundbreaking research takes center stage in Bloomberg's latest article on Insilico Medicine's pivotal strides. #AIinPharma #DrugDiscovery #InnovationInHealthcare #DrugDiscovery #DeepPharmaIntelligence #InsilicoMedicine

Deep Pharma Intelligence is pleased to have its Pharma AI industry analytics research featured in a recent article in Bloomberg by Kanoko Matsuyama, ‘Race for First Drug Discovered by AI Nears Key Milestone’, on Insilico Medicine’s recent progress in bringing an AI-discovered drug for idiopathic pulmonary fibrosis to mid-stage trials in China and the US. “The results of Insilico’s trials are being closely watched in the drug industry because the company used AI to identify a new approach to fight against the deadly disease and produce a novel molecule to treat it. UK-based researcher Deep Pharma Intelligence says that the Insilico therapy is the global industry’s first fully AI-based preclinical candidate.” “Insilico says the steps from finding a novel target to designing a medicine to make it ready for human testing took just about 18 months at a budget of around $2.7 million. That’s roughly a third of the time and a 10th of the cost it might have taken without algorithms.” If you'd like to stay informed about these and other latest developments in the AI in Pharma space, be sure to subscribe to our newsfeed at https://lnkd.in/diHDVUEv, where you can also access many of our most recent Pharma AI industry analytics, market reports and case studies, as well as learn more about our proprietary analytics and commissioned consultancy services. Read the full article in Bloomberg here: https://lnkd.in/d-Dakuz9

As the third quarter of 2023 ends, here is a recap on how AI is changing the pharma landscape rapidly- 💊 Game-Changing AI-Designed Drugs: Companies like Schrödinger, Insilico, and Verge Genomics are making significant strides with AI-designed drugs. These include treatments for lymphoma, idiopathic pulmonary fibrosis, and amyotrophic lateral sclerosis (ALS). 💊Human-Centric Approach: Verge Genomics is challenging traditional drug development by utilizing human data and models in the discovery phase, potentially offering more insightful findings than animal models. 💊Not a One-Size-Fits-All Solution: Success with one AI-designed drug doesn't guarantee success for all. Different disease areas have unique targets and chemistry, requiring a deeper understanding of which data is predictive in specific contexts. 💊Data is the Foundation: Access to extensive and high-quality data is crucial for AI systems to design drugs accurately. Smaller companies like Dompé face challenges in generating sufficient data, highlighting the need for central repositories like the European Health Data Space (EHDS). 💊EHDS: Leveling the Playing Field: The EHDS proposal aims to simplify data access for research through a permitting system, potentially benefiting both public authorities and pharmaceutical companies. The goal is to create standards, improve interoperability, and provide access to vast datasets without excessive bureaucracy. 💊Human Expertise is Essential: AI in drug development isn't about replacing humans but enhancing their capabilities. It's often referred to as "human in the loop AI." The collaboration between AI systems and experts is seen as the key to success. 💊Pharma Industry's Adoption: Big Pharma is increasingly embracing AI-driven drug discovery. Numerous collaborations and partnerships are emerging to harness AI's potential, with companies like Pfizer, AstraZeneca, and Sanofi at the forefront. 💊AstraZeneca's AI Integration: AstraZeneca, for instance, applies AI tools to approximately 70% of its drug discovery projects. They're even venturing into complex projects like antibody design, hinting that AI may soon create drugs from start to finish. 💊The Future is AI: Many industry experts believe that AI is the future of drug development, and the transition is already well underway. AI is reshaping the way drugs are discovered and developed, leading to more efficient and innovative processes. What are your speculations for the next quarter? What more changes would you love to see in 2024? #aitechnology #aiandml #bigdata #aiinpharma #aihealthtech #healthtech