Eularis provides strategic use of Artificial Intelligence to address challenges within the BioPharma industry, emphasizing maximum impact and efficiency.

Eularis

AI in Pharma: Discovery is focused on exploring the applications of AI-based technology in drug discovery and development, specifically how AI, ML, NLP, data science, and generative deep learning models can optimize the pharmaceutical and biotechnology industries.

AI in Pharma: Discovery

Iktos leverages AI and robotics to transform drug discovery, integrating generative AI with automated synthesis and testing to accelerate the development of new treatments.

Iktos

Smile AI focuses on increasing online sales through its platform tailored for pharmaceutical e-commerce, self-described as a leader in the industry.

Smile AI

Eularis | 1,018 followers on LinkedIn. Accelerating pharma business results using Artificial Intelligence. | Join our training for Pharma Execs on AI:
https://eularis.com/ai-training-for-pharma/

We innovate to solve pharma/biotech/med device business challenges using AI to maximize our clients’ measurable results. We have been in business since 2003 and were the first company to use AI in pharma, and continue to lead in innovation with the projects we participate in. 

Our teams consist of pharma business strategists, data scientists, big data engineers, full stack developers, computational linguists and user interface designers.

Chairman/Founder/CEO @ Eularis | AI Pharma Expert, Keynote Speaker | Neuroscientist | Our pharma clients achieve measurable exponential growth in…

Dr. Andrée Bates

Strategist | Fractional Chief of Staff & Advisor | Competitive & Market Intel | Writer

Jen DuBois, MBA

🎙 I am thrilled to announce the release of our latest podcast episode featuring @Andrew Rut , CEO of @Metadvice , where we delved into the fascinating world of AI-driven healthcare solutions. 🎙 In this episode, we explored how AI is revolutionizing clinical decision-making to drive improved outcomes for patients, clinicians, and healthcare systems. Here are three key takeaways from the insightful conversation with Dr. Rut: ⭐️ Personalized Medicine Through AI: Dr. Rut highlighted the importance of personalized medicine in healthcare. With the help of neural networks trained in medicine and specific therapeutic areas, Metadvice is leveraging AI to provide tailored recommendations for individual patients. By analyzing historical data and creating digital twins of patient cohorts, the system can optimize treatment strategies based on individual responses, moving us closer to achieving true precision medicine. ⭐️ Diverse Data for Better Representation: One of the standout features of Metadvice's approach is the use of synthetic data to ensure a more representative sample. By incorporating data from various ethnic populations and regions, the AI system can offer nuanced recommendations that cater to the specific needs of diverse patient groups. This emphasis on inclusivity and diversity in data sets is crucial for addressing healthcare disparities and improving outcomes globally. ⭐️ Collaboration with Pharma for Post-Approval Programs: Dr. Rutt discussed the collaboration between Metavise and pharmaceutical companies in the post-approval phase of drug development. By leveraging AI to analyze real-world data and optimize treatment plans, pharma companies can enhance their evidence base for reimbursement and formulary positioning. This strategic approach during late-phase clinical trials can lead to more compelling benefit-risk profiles and better outcomes for patients. If you're interested in learning more about the intersection of AI and healthcare, I highly recommend tuning in to this episode with Dr. Andrew Rut. See below on spotify or find on Apple podcasts. https://lnkd.in/e4-hZ6eZ To listen to the full conversation and gain valuable insights into the future of clinical decision-making, visit Metavise or reach out to Dr. Rut directly at info@metadvice.com . #AIinHealthcare #clinicaldecisionmaking #diversity

🎙️ Our latest podcast episode featuring an in-depth conversation with @Philipp Lorenz, the CTO of @Basecamp Research. In this episode, we delved into the world of foundational data sets for biological AI and the groundbreaking work being done by Basecamp Research. Here are three key takeaways from our enlightening discussion: 🌏 Diversity and Context Matter: The importance of diversity and context in biological data sets cannot be overstated. Basecamp Research has recognized the limitations of current public data sets and has taken a proactive approach to address this issue. By collecting diverse biological sequence data from nature parks across five continents, including unique metadata, Basecamp Research has built a knowledge graph with over six billion relationships. This approach not only enhances the accuracy of AI models but also provides a comprehensive understanding of the biological world. In fact, their data provides accuracy of SIX times Alphafold2! 🖥 Ethical Data Collection and Sharing: Basecamp Research's commitment to ethical data collection and sharing sets a new standard in the industry. By engaging with biodiversity stakeholders, obtaining consent, and entering into benefit-sharing agreements, Basecamp Research ensures that the value generated from the data is shared with those who have contributed to its collection. This ethical approach not only fosters trust but also highlights the importance of responsible data practices in the field of biology. ⚕ Future Innovations and Collaborations: The potential for future developments and collaborations in the field of biology is vast. Basecamp Research's expansive data set opens up opportunities for innovative research and applications, particularly in areas such as gene editing, therapeutics, and biocatalysis. If you are interested in learning more about the cutting-edge work being done by Basecamp Research and the impact of foundational data sets on biological AI, I highly recommend listening to the full podcast episode. You can find the episode, episode 114, of the AI for Pharma Growth Podcast, on both Apple or Spotify podcasts. https://lnkd.in/d6hf624f 🌿 Let's continue to explore 🔦 the frontiers of biological AI and innovation together! 🌿💻 #BiologicalAI #Innovation #Drugdiscovery

🌟 Eularis is hosting a free Webinar event on the 17th April 2024 at 5pm UK/ 6pm EU/ Midday EST/ 9am PT. On this webinar, experienced AI in Pharma expert Dr. Andrée Bates 👩 from Eularis will help you understand what AI is all about in pharma and how to get real impact from it for your business unit - including: ● 30% – 60% reduction in drug discovery, R&D and clinical trial time. ● 1,000% efficiency increase in regulatory and medical affairs. ● Faster and broader market access for higher profit ● Maximize launch success in year 1 ● Generate higher revenue and profit from in-market brands ● Rapid finding of rare disease patients ● Soften the impact of the patent cliff Registration link: https://lnkd.in/daNMa4GD

Eularis is hosting a free Webinar event on the 24th July 2024 at 5pm UK/ 6pm EU/ Midday EST/ 9am PT. On this webinar, experienced AI in Pharma expert Dr. Andrée Bates from Eularis will help you understand what AI is all about in pharma and how to get real impact from it for your business unit - including: ● 30% – 60% reduction in drug discovery, R&D and clinical trial time. ● 1,000% efficiency increase in regulatory and medical affairs. ● Faster and broader market access for higher profit ● Maximize launch success in year 1 ● Generate higher revenue and profit from in-market brands ● Rapid finding of rare disease patients ● Soften the impact of the patent cliff

🌟 Three Key Takeaways from the episode the Future of Leadership and Innovation in Pharma 🌟 We discussed the future of leadership and innovation in the pharmaceutical industry. In this episode, I had the pleasure of speaking with @Adam Kingl, a globally renowned expert in innovation management practice and strategy. 🌟Here are three key takeaways from our insightful conversation: 1️⃣ Adam emphasized the importance of changing the mindset within organizations to foster genuine innovation. By encouraging curiosity, exploration, and celebrating failures, companies can create an environment where innovative ideas can thrive. 2️⃣ We discussed the detrimental impact of bureaucracy on innovation and how organizations can overcome it. By reducing the number of approvals needed, streamlining resource allocation, and incentivizing managers for innovation, companies can bust through bureaucratic barriers. 3️⃣ Adam highlighted the power of challenging long-held assumptions when it comes to business models. By questioning who the customer is, what is being offered, and how it is being offered, companies can spark dramatic innovations that revolutionize the industry. 🚀 If you want to learn more about these key takeaways and gain valuable insights into the future of leadership and innovation in pharma, make sure to listen to the full episode here: https://lnkd.in/eqwQHDQC #PharmaInnovation #Leadership #FutureofWork

Compose Health Inc. is an #AI platform that gives its users a precise method of drafting and generating #pharma content that is suitable for mandatory compliance laws. It facilitates the production of professional, personalised content that is generated to stand out in a sea of digital media. This is achieved through a genAI system that tracks content guidelines as it generates marketing material that efficiently suits the prompts of its user. Co-founders Patrick Glinski and Ryan Brotman, Ph.D. discuss how the platform uses AI to make relevant content reviews and how it helps #pharmamarketing teams create unity between content creation and compliance review processes here: https://lnkd.in/dC-yWtzg

Synthetic data is a form of artificially generated information that closely emulates the characteristics of real data. Essentially, it is fabricated data designed to match the statistical properties found in authentic datasets. The process of creating synthetic data involves training machine learning models on extensive sets of real data to identify patterns and relationships. Various models, including generative adversarial networks (GANs) and recurrent neural networks, can be employed for this purpose. Generative adversarial networks operate with two opposing models – a generator and a discriminator. The generator produces synthetic samples, and the discriminator assesses them for authenticity. Through an iterative process, the generator refines its output, generating increasingly realistic synthetic examples capable of deceiving the discriminator. More details about #syntheticdata and #digitaltwins here: https://lnkd.in/dPaPaa_a

Pharmaceutical companies like Pfizer, Merck, and AstraZeneca are leveraging AI to sift through petabytes of unstructured data, identifying new drug targets in significantly less time than traditional methods. Studies suggest that AI could halve the time required for drug discovery. In clinical trials, AI enhances research by precisely matching patients to studies, potentially reducing trial time by over 50% and costs by 30%. With AI capabilities advancing exponentially, experts predict that within this decade, AI may contribute to discovering every new medicine. Successful application of AI holds the promise of reducing billions in industry R&D costs, expediting life-saving cures and ensuring the long-term sustainability of the pharmaceutical business model. More about these amazing advancements here: https://lnkd.in/d-Ww882c

In the rapidly evolving landscape of the #pharmaceuticalindustry , the entry of tech giants brings a seismic shift that promises to redefine conventional practices. Their massive funds, technological advancements, and data-driven capabilities have ignited a wave of disruption, forcing the industry to adapt or risk being left behind. For instance, in 2022 alone, these tech giants invested over $100 billion into work in the #pharmaceutical domain, marking a remarkable tenfold increase from the mere $10 billion invested in 2015. This exponential growth underscores their profound commitment to reshaping the industry’s course (and enhancing their own growth). Delve deep into how this profoundly impact the #pharma landscape here: https://lnkd.in/dbQbtbdx

Greg Woolf of AI Think Tank draws from his experience launching #AI companies to discuss the growing $10 trillion #cybercrime industry. He addressed threats facing #healthcare like ransomware and identity theft exploiting medical data breaches. Greg also covers challenges of reliability, bias and other risks with AI systems. However, he believes AI can be applied ethically to enhance threat detection and help organisations assess vulnerabilities. Learn about the growing threat of cybercrime and how criminals are using AI Specific risks faced by healthcare companies regarding data privacy here: https://lnkd.in/dFYgUhcq

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Company Name	Eularis	AI in Pharma: Discovery	Iktos	Smile AI
Symbol
MSH ID	COM:EULARIS	COM:AIINPHARMA-DISCOVERY	COM:IKTOS	DE:SMILEAI
Market	PRIVATE	PRIVATE	PRIVATE	PRIVATE
Sector	Healthcare & Health Services	Healthcare & Health Services	Healthcare & Health Services	Technology
Industry	Pharmaceuticals	Pharmaceuticals	Pharmaceuticals	Pharmaceutical E-Commerce
Country	US	US	FR	DE
Stage			Series A	Seed
Employee Count
Website	eularis.com	aiinpharma-discovery.com	iktos.com	smileai.de
LinkedIn	eularis		iktos	smileai
Founders

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Monthly Web Traffic	1.21K
Web Traffic Growth	-0.40
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Raised Capital	16.41M	113.32K

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EULA

COM:EULARIS

Eularis

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