Core Insights - NetraMark Holdings Inc. is focused on leveraging AI solutions to enhance clinical trial design in the pharmaceutical industry, as highlighted by a new publication led by founder Dr. Joseph Geraci [1][2][6] - The publication discusses the integration of AI/ML in clinical trials, emphasizing the need for alignment with Good Clinical Practice (GCP) [2][4] - The collaborative effort includes contributions from various regulatory and pharmaceutical organizations, showcasing a broad consensus on the potential of AI/ML in improving clinical trial outcomes [3][4] Group 1: Publication Overview - The manuscript titled "Current Opportunities for the Integration and Use of AI/ML in Clinical Trials: Good Clinical Practice Perspectives" is now available in the Journal of the Society for Clinical Data Management [2] - It outlines ideal conditions for AI applications in clinical trials and stresses the importance of compliance, transparency, and patient safety [2][4] - The publication identifies seven real-world use cases where AI can enhance clinical trial effectiveness [4] Group 2: Challenges and Ethical Considerations - The manuscript addresses challenges and ethical considerations in adopting AI/ML in clinical trials, including data quality monitoring and patient stratification [4][5] - Key challenges include data attributability in wearable device data and the need for robust privacy controls [5] - Ethical considerations focus on ensuring AI is lawful, ethical, and socially robust, with an emphasis on explainability and auditability [5] Group 3: Company Commitment and Future Directions - NetraMark is committed to collaborating with sponsors to maximize the benefits of AI/ML in clinical trials, aiming to set industry standards for ethical compliance [6] - The company utilizes a novel topology-based algorithm to analyze patient data, enabling effective segmentation and classification for clinical trials [7] - NetraMark's approach allows for the use of smaller datasets while maintaining accuracy in disease classification and treatment efficacy [7]

Core Insights - BullFrog AI Holdings, Inc. has announced a strategic collaboration with Sygnature Discovery to enhance drug development using AI and machine learning [1][2] - This partnership is expected to generate between $15 million and $30 million in revenue for BullFrog AI through 2028 [2] Company Overview - BullFrog AI is a technology-enabled drug development company that utilizes AI and machine learning to improve the development of pharmaceuticals and biologics [1] - The company’s proprietary platform, BullFrog Data Networks™, is powered by the bfLEAP™ engine and aims to provide AI-driven data insights [1][3] Collaboration Details - The collaboration with Sygnature Discovery will introduce BullFrog Data Networks™ to Sygnature's global client base, enhancing brand recognition and user uptake [2][3] - Sygnature Discovery is a UK-based contract research organization specializing in drug discovery, and this partnership will complement their existing capabilities [4] Platform Capabilities - BullFrog Data Networks™ accelerates the exploration of complex datasets, aiding in early target identification, mechanism-of-action elucidation, patient stratification, drug repurposing, and clinical trial optimization [3] - The platform is designed to meet the needs of small to mid-sized biopharma companies, which are often underserved by current bioinformatics solutions [4]

Core Insights - The article discusses the author's academic and professional background in Machine Learning, Economics, and Finance, highlighting affiliations with prestigious institutions and experience in financial advisory, particularly in banking and mergers & acquisitions [1]. Group 1 - The author holds a PhD in Machine Learning with a focus on Economics and Finance [1]. - The author has academic affiliations with IESE Business School, ESADE Business School, and the Barcelona Supercomputing Center [1]. - The professional experience includes working at Deloitte Financial Advisory, specializing in banking and mergers & acquisitions [1]. Group 2 - The author's interests include machine learning and generative AI applications in finance and economics [1]. - The author is proficient in programming languages such as Python, R, and SQL [1].

Core Insights - Compugen Ltd. is a clinical-stage cancer immunotherapy company that utilizes AI/ML driven predictive computational research to enhance understanding of complex cancer biology [1][2]. Group 1: Conference Presentations - Compugen will present at the 2025 Annual Congress of the European Association for Cancer Research in Lisbon, Portugal, from June 16-19, with a poster titled "Prediction of immune evasion and immunotherapy resistance mechanisms associated with distinct TNBC subtypes" [2]. - Another presentation will occur at the International Society for Computational Biology and European Conference on Computational Biology in Liverpool, UK, from July 20-24, featuring a poster titled "Computational prediction of TNBC tumor subtypes from an integrative single cell atlas elucidates immune evasion and immunotherapy resistance mechanisms" [2]. Group 2: Company Overview - Compugen employs a predictive computational discovery platform (UnigenTM) to identify new drug targets and biological pathways for cancer immunotherapy development [3]. - The company has two proprietary product candidates in Phase 1 development: COM701, an anti-PVRIG antibody, and COM902, an antibody targeting TIGIT for solid tumors [3]. - Rilvegostomig, a PD-1/TIGIT bispecific antibody, is in Phase 3 development by AstraZeneca under a licensing agreement [3]. - GS-0321, a high affinity anti-IL-18 binding protein antibody, is also in Phase 1 development and licensed to Gilead [3]. - Compugen's therapeutic pipeline includes early-stage immuno-oncology programs aimed at enhancing anti-cancer immunity [3].

Core Insights - The article discusses the expertise of a DevOps Engineer specializing in AI tools and applications, highlighting their deep knowledge in generative AI systems and machine learning algorithms [1] - The engineer is pursuing advanced AWS machine learning certifications to enhance their expertise in AI and machine learning [1] - The engineer contributes insights on AI and machine learning through an investment-focused lens on Seeking Alpha [1] Group 1 - The engineer is a subject-matter expert in the buildout, deployment, and maintenance of AI tools and applications [1] - The engineer ranks 856 out of 30,634 financial bloggers and 1,404 out of 40,003 experts according to TipRanks [1] - The engineer has no stock or derivative positions in any mentioned companies and expresses personal opinions in the article [1]

Group 1 - Edge Total Intelligence Inc. has been recognized by Gartner in its Hype Cycle for the Future of Enterprise Applications, 2024, as a Sample Vendor in the Digital Twins category [1][2] - The report highlights a transformation in enterprise applications from simple tools to systems of intelligence that enhance algorithmic process optimization and AI-based decision-making [2][4] - The company's edgeCore™ software provides a data mesh capability that integrates authoritative information with control systems across various domains, leveraging generative AI and machine learning to enhance decision-making [4][7] Group 2 - Digital twins are being utilized by enterprises to accelerate business processes and contribute to machine learning and GenAI foundation models, leading to improvements such as cost optimization and enhanced visibility [4][5] - The CEO of edgeTI emphasized that digital twins allow for a unified view across siloed data, facilitating more intelligent operations and better matching the needs of executives and employees [5][6] - EdgeTI offers demonstrations and free evaluations of its digital twin technology to prospective enterprises, showcasing its commitment to innovation in real-time operations [5][7]

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):ML researchers just built a new ensemble technique.It even outperforms XGBoost, CatBoost, and LightGBM.Here's a complete breakdown (explained visually): ...

Here's the visual again for your reference:To recap, instead of training 32 (or K) separate MLPs, TabM uses one shared model and a lightweight adapter layer.Check this visual 👇 https://t.co/lF0yc2UjBb ...

Who is afraid that AI is going to destroy human civilization. Now, don't be shy. It can't see you right now.Who knows someone who is afraid that AI is going to destroy human civilization. Who is afraid of dying. In a black box, AI and death share a room.What's inside this black box. We don't know. In a 2023 New York Times column, Ezra Klene wrote about AI.We do not understand these systems, and it's not clear we even can. I am an artist dealing in embodiment and livveness. As such, I have taken AI and death ...

Core Insights - NextNRG, Inc. has been included in the Russell 2000® and Russell 3000® Indexes, marking a significant milestone in its growth and recognition in the market [1][3] - The reconstitution of the Russell indexes will take effect after market close on June 27, 2025, with trading in the new indexes starting on June 30, 2025 [2] - The inclusion in these indexes is expected to enhance institutional engagement and long-term value creation for NextNRG as it scales its projects across the country [3] Company Overview - NextNRG is focused on AI-powered energy innovation, utilizing advanced technologies such as the Next Utility Operating System®, smart microgrid infrastructure, and wireless EV charging [1][5] - The company aims to create an integrated ecosystem for renewable energy, energy infrastructure, battery storage, and on-demand mobile fuel delivery [5] Strategic Developments - NextNRG has experienced strong quarterly growth and strategic advancements, including new state expansions and enterprise partnerships [4] - The company is expanding its fleet of fuel delivery trucks and has acquired Yoshi Mobility's fuel division and Shell Oil's trucks, reinforcing its leadership in the on-demand fueling industry [7] - NextNRG is integrating sustainable energy solutions into its mobile fueling operations and plans to assist fleet customers in transitioning to electric vehicles (EVs) [7] Technological Innovations - The Next Utility Operating System® employs AI and machine learning to enhance energy management efficiency [6] - NextNRG's smart microgrids utilize AI-driven energy management alongside solar power and battery storage to improve energy efficiency and grid resiliency [6]