Weekly TechBio News 🥑
🟢 MIT & Recursion Pharmaceuticals Launch 🚀 Boltz-2: A Next-Gen AI Model for Binding Affinity Prediction
MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) and Jameel Clinic, and Recursion Pharmaceuticals have jointly released Boltz-2, an advanced AI model designed to predict molecular binding affinity—a critical factor in drug discovery that determines how strongly a drug molecule binds to its target protein (MIT and Recursion Release Boltz-2: Next Generation AI Model to Predict Binding Affinity at Unprecedented Speed, Scale, and Accuracy). Powered by Recursion's NVIDIA supercomputer 🦸♀️ BioHive-2 for its training and validation, this next-generation AI model achieves best-in-class accuracy in jointly modeling complex structures and binding affinities. Boltz-2 represents the next step beyond existing biomolecular structure prediction models like AlphaFold3 and its predecessor, Boltz-1.
Key Features
Speed 🚄, Scale 🪜, and Accuracy 🎯: Boltz-2 outperforms previous models by offering faster predictions across larger molecular datasets with higher precision.
Boltz-2 is the first biomolecular co-folding model to combine structure and binding affinity prediction, approaching the accuracy of physics-based free energy perturbation (FEP) calculations but at speeds up to 1️⃣0️⃣0️⃣0️⃣✖️ faster in standard benchmarks.
Impact:
Recursion Pharmaceuticals' stock surged following the announcement, reflecting investor confidence in the potential of this technology to transform their pipeline and offer competitive advantages in drug discovery (Recursion Pharmaceuticals Stock Surges On Breakthrough AI Model Launch With MIT).
Recursion Pharmaceuticals Inc (RXRX), which went public in April 2021, is a leader 🎩 in digital biology, and has built the world’s most advanced ultra-high throughput wet-lab and ML platform. Its ability to generate proprietary, high-dimensional, multi-modal and relatable datasets of human cellular biology at massive scale, and apply advanced ML approaches to reveal novel biological relationships, has resulted in a proven, target-agnostic drug-discovery engine. Back on April 09, 2025, Recursion announced the generation of screening libraries leveraging tools within its AI/ML platform, the Recursion OS, together with Enamine's REAL Space, the world’s largest source of make-on-demand small molecules (Recursion and Enamine Release New AI-Enabled Targeted Compound Libraries). More specifically, the two companies have curated 1️⃣0️⃣ enriched screening libraries from over 1️⃣5️⃣,0️⃣0️⃣0️⃣ newly synthesized compounds designed to accelerate drug discovery against 1️⃣0️⃣0️⃣ key and clinically relevant drug targets in difficult to address biological areas. By combining the expansive REAL Space with the Recursion OS to predict small molecule compatibility with protein targets, the collaboration allows for the creation of smaller, highly focused libraries that outperform traditional high-throughput screening (HTS) collections.
Moreover, LOWE, LLM-orchestrated workflow software, is an LLM agent, that represents the next evolution ⛹️♀️ of the Recursion OS (Recursion Operating System, OS), that supports drug discovery programs by orchestrating complex workflows that chain together a variety of steps and tools, from finding significant relationships within Recursion’s Maps of Biology and Chemistry to generating novel compounds and scheduling them for synthesis and experimentation.
For more about Recursion’s collaborations and extensive pipeline:
🟩 DiffSMol: AI Model for Generating Accurate 3D Molecular Structures
A new AI model called DiffSMol has been developed to generate precise 3D structures of small molecules, crucial for rational drug design (Generating 3D small binding molecules using shape-conditioned diffusion models with guidance).
Key Features
🔸 DiffSMol generates 3D small binding molecules based on known ligand shapes.
🔸 DiffSMol encapsulates ligand shape details within pretrained, expressive shape embeddings and generates binding molecules through a diffusion model.
🔸 DiffSMol further modifies the generated 3D structures iteratively using shape guidance to better resemble ligand shapes, and protein pocket guidance to optimize binding affinities.
🔸 DiffSMol outperforms state-of-the-art methods on benchmark datasets. When generating binding molecules resembling ligand shapes, DiffSMol with shape guidance achieves a success rate 61.4%, substantially outperforming the best baseline (11.2%), meanwhile producing molecules with de novo graph structures.
🔸 DiffSMol with pocket guidance also outperforms the best baseline in binding affinities by 13.2%, and even by 17.7% when combined with shape guidance.
Case studies for two critical drug targets demonstrated very favourable physicochemical and pharmacokinetic properties of generated molecules, highlighting the potential of DiffSMol in developing promising drug candidates.
🍏 Lantern Pharma’s AI Platform Delivers Breakthrough Predictive Capabilities Using ctDNA
Lantern Pharma Inc is leveraging AI to analyze circulating 🎣 tumor DNA (ctDNA)—fragments of cancer DNA found in blood samples—in order to predict treatment response and identify novel biomarkers (Empowering Liquid Biopsies with AI: Unlocking Hidden Signals and Turning Genomic Data Into Decisions).
At Lantern Pharma, they developed a biologically-informed feature engineering methodology (for which they have filed for a provisional patent) that applies unbiased ML to extract predictive signals from the broader genomic context, moving beyond isolated mutation tracking or aggregate ctDNA quantification.
Working with publicly available data from the TRACERx NSCLC cohort, their approach demonstrated robust predictive performance:
✅ Patient stratification with log-rank p-value <0.0001,
✅ 86% accuracy in treatment response prediction on held-out test sets, and
✅ Identification of engineered genomic features that independently correlate with clinical outcomes
Through explainable AI analysis, they uncovered specific genomic patterns that may represent novel biomarkers suitable for companion diagnostic development—signals that remain hidden in conventional ctDNA analysis workflows.
⛳ Nurix Therapeutics Secures 💲1️⃣5️⃣M Additional Milestone Payment from Sanofi
Nurix Therapeutics (NASDAQ:NRIX), a clinical-stage biopharmaceutical company with a current market capitalization of 💲8️⃣1️⃣0️⃣M, received an additional 💲1️⃣5️⃣M under a licensing agreement with Sanofi, triggered by achieving a research milestone (Nurix secures additional $15 million from Sanofi license deal) related to the development of Nurix’s STAT6 program, including the drug candidate NX-3911. This payment increased Nurix’s total receipts from Sanofi to 💲1️⃣2️⃣7️⃣M under their 2019 collaboration agreement.
NX-3911 is an orally administered drug designed to degrade STAT6, a protein implicated in type 2 inflammation, which is a factor in diseases such as atopic dermatitis and asthma. The drug has shown promise in preclinical models, offering a potential new treatment option in the field of allergic conditions.
Back on April 02, 2025, Nurix Therapeutics (Nurix Inc Also Known As Kura Therapeutics; NASDAQ:NRIX) announced that Sanofi has exclusively licensed an undisclosed Nurix program targeting a previously undruggable transcription factor for autoimmune diseases. The undisclosed target is a central regulator of the inflammatory response and is distinct from the previously disclosed STAT6 degrader program (Nurix Licenses a Drug Discovery Program to Sanofi Targeting a Novel Transcription Factor for Autoimmune Diseases).
Nurix is a clinical stage biopharmaceutical company focused on the discovery, development and commercialization of targeted protein degradation medicines, the next frontier in innovative drug design aimed at improving treatment options for patients with cancer and inflammatory diseases. Their DEL-AI discovery engine leverages the combined power of their data-rich DEL capabilities, automated chemistry, and ML to accelerate drug discovery. More specifically, DEL-AI harnesses Nurix’s varied high-throughput data streams to learn the rulebook of targeted protein degradation.
The development of the DEL Foundation Model was led by Nurix in collaboration with Loka, a Silicon Valley-based software development firm, and supported by Amazon Web Services (AWS), leveraging AWS SageMaker and AWS managed MLflow to provide enterprise-grade reliability and scalable infrastructure.
Moreover, on April 17, 2025 Nurix announced that FDA has cleared 🚦 the IND for the IRAK4 degrader GS-6791/NX-0479, enabling the initiation of a Phase 1 trial, which is anticipated to begin in Q2 2025 (Nurix Announces FDA Clearance of IND Application for GS-6791/NX-0479 - a Novel IRAK4 Degrader for Inflammatory Conditions). Nurix’s collaboration partner, Gilead Sciences, licensed the program in 2023 and is responsible for advancing this program through clinical development, and Nurix will receive a 💲5️⃣M milestone payment from Gilead for FDA clearance of the IND, bringing the total amount received under the 2019 collaboration agreement to 💲1️⃣3️⃣5️⃣M.
GS-6791/NX-0479 is a potent, selective, oral IRAK4 degrader. IRAK4 plays a critical role in toll-like receptor (TLR) and interleukin-1 family receptor (IL-1R) signaling, and has both scaffold and kinase functions, making it an ideal target for disruption by targeted protein degradation. Degradation of IRAK4 by GS-6791/NX-0479 has potential applications in the treatment of rheumatoid arthritis and other inflammatory diseases.
🔬 Tempus Unveils Foundational AI Model for Precision Medicine
Tempus has launched 🚀 a new program to develop a foundational AI model trained on its vast multimodal dataset—including clinical, genomic, imaging, and real-world data—named the Fuses program (Tempus Introduces Fuses, A Program Designed to Transform Therapeutic Research and Build the Largest Diagnostic Platform Using its Novel Foundation Model). This initiative will harness Tempus’ proprietary dataset to generate valuable insights for both patient care and research, combining the power of its data and ML capabilities to develop an AI enabled-diagnostic platform offering physicians the largest suite of algorithmic tests designed to make precision medicine a reality.
🔸 Fuses will accelerate Tempus’ comprehensive testing portfolio, expanding its suite of AI-enabled diagnostics. Insights from Fuses will be developed into clinically validated algorithmic diagnostics that may enable highly personalized care, such as identifying patients unlikely to respond to approved therapies or those at risk of severe treatment-related events.
🔸 Tempus has already begun this work with last year’s launch of its Immune Profile Score (IPS) a multimodal biomarker that can be used as a prognostic indicator for adult patients with metastatic pan-solid tumors eligible for immune checkpoint inhibitor (ICI)-based therapy.
The foundational model behind Fuses is learning generalizable rules determining prognosis and drug benefit in real-world practice. With the goal of furthering researchers’ understanding of why certain clinical trials fail, identify new indications for investigational drugs, optimize trial design, and uncover combination therapies to broaden patient benefit. By revealing biomarker rules, the model may also surface mechanisms of drug response and resistance to inspire a new generation of companion diagnostics and therapeutic research.
“Future of healthcare?
Tempus AI (TEM) quietly embeds 1️⃣,0️⃣0️⃣0️⃣➕ AI agents directly into the electronic health record (EHR) systems used by hospitals and doctors:
Future of healthcare? Tempus AI (TEM) quietly embeds 1,000+ AI agents in hospitals.
Moreover, on April 01, 2025 Tempus AI announced the expansion of Tempus One—its generative AI clinical assistant—with direct integration into electronic health record (EHR) systems. By integrating AI at every point of the clinical care process, the expanded capabilities of Tempus One offer physicians in oncology and beyond more support in treatment decisions (Introducing Tempus One in the EHR with Integrated Guidelines).
Apart from the Fuses program and the Tempus One, back on April 24, 2025, AstraZeneca, Tempus and Pathos AI signed a multi-year agreement to develop a large-scale multimodal DL model (AstraZeneca enters $200m AI cancer pact with Tempus and Pathos) that will be used to extract biological and clinical insights, identify novel drug targets, and support the development of new cancer therapies. Under the terms of the deal, Tempus will receive 💲2️⃣0️⃣0️⃣M in data licensing and model development fees, and will contribute its large library of de-identified oncology data to help build the model, which will be shared by all three parties once completed.
On top of that, on April 28, 2025 Tempus Introduced Loop, an AI-Powered Target Discovery and Validation Platform. Loop is Tempus’ proprietary approach to novel target identification that integrates real-world patient data (RWD) with human-derived biological models and CRISPR-screens, all leveraging AI to rapidly uncover insights for pre-clinical therapeutic development.
Further, almost two months ago (April 11, 2025) Tempus announced it has acquired Deep 6 AI, a leading AI-powered precision research platform for healthcare organizations and life sciences companies (Tempus Announces Acquisition of Deep 6 AI). Deep 6 AI, utilizes AI to mine medical records to accelerate finding and recruit patients for clinical trials within minutes. Its AI-powered software matches patients to clinical trials by mining real-time structured and unstructured electronic medical record (EMR) data across a broad ecosystem, which includes academic medical centers, National Cancer Institute (NCI)-Designated Cancer Centers, and NCI Community Oncology Research Programs. Deep 6 is integrated with over 750 provider site locations spanning more than 30 million patients, which will materially add to Tempus’ existing network.
Finally on more thing ➡️ Boehringer and Tempus AI announced on May 15, 2025, a multi-year strategic collaboration to boost cancer R&D. In particular, Boehringer Ingelheim will use Tempus’ multimodal patient data and AI tools for biomarker discovery, patient stratification, and oncology drug development across its pipeline (Boehringer and Tempus AI forge multi-year partnership).
🗣️ SoundHound AI & Allina Health Launch Voice AI Agent for Patient Calls
SoundHound AI, Inc (Nasdaq: SOUN), a global leader in voice artificial intelligence, and Allina Health have deployed a voice 🎤 AI agent that now handles most patient calls, significantly reducing wait times (SoundHound AI and Allina Health Launch AI Agent to Redefine Patient Engagement). Alli, is an AI agent for patient engagement, powered by the Amelia conversational AI platform.
🔸 Alli answers calls within Allina Health’s Customer Experience Center and integrates directly with Allina Health’s electronic medical record system, allowing it to instantly identify and authenticate callers.
🔸 The AI agent allows patients to manage their appointments, and in the future patients will be able to refill medications, find doctors or locations, and receive answers to non-clinical questions–all without having to wait on hold. This eliminates the need for customer experience representatives to spend time on manual verification, accelerating access to care.
Since launch, Alli has significantly improved operational performance for Allina Health. Average call time has improved by 5️⃣–1️⃣0️⃣ seconds, and 8️⃣0️⃣💯 of calls are now answered in 4️⃣5️⃣ seconds or less ⬇️, without increasing staffing levels.
SoundHound AI, Technology for a voice-enabled world, develops voice and conversational AI solutions that let businesses offer incredible experiences to their customers. Built on proprietary technology, SoundHound’s voice AI delivers best-in-class speed and accuracy in numerous languages to product creators and service providers across retail, financial services, healthcare, automotive, smart devices, and restaurants via groundbreaking AI-driven products like Smart Answering, Smart Ordering, Dynamic Drive-Thru, and Amelia AI Agents. Along with SoundHound Chat AI, a powerful voice assistant with integrated Generative AI, SoundHound powers millions of products and services, and processes billions of interactions each year for world class businesses.
🔥 SoundHound AI, Serve Robotics, and Nano-X Imaging Are Getting Crushed Today (Hint: It Has to Do With Nvidia) (February 14, 2025).
🔥 Nvidia Sells Stakes in SoundHound AI, Serve Robotics, and Nano-X; Cuts Arm Investment (February 14, 2025).
Allina Health is a not-for-profit organization dedicated to the prevention and treatment of illness and enhancing the greater health of individuals, families and communities throughout Minnesota and western Wisconsin, US.
📒 Enveda Biosciences: AI-Discovered Anti-Inflammatory Advances to Atopic Dermatitis Trials
Enveda Biosciences has just successfully completed 🏌️♂️ a Phase 1 safety testing of its AI-discovered oral anti-inflammatory drug candidate, marking a major milestone for AI-first drug development (Enveda Reports Favorable Phase 1 Safety for Novel Oral Anti-Inflammatory, Launches Phase 1b Trial in Atopic Dermatitis).
✅ ENV-294, is a novel oral therapeutic for atopic dermatitis, asthma, and beyond, that is a first-in-class anti-inflammatory small molecule derived from chemistry unearthed by Enveda’s platform. Based on the favorable safety and tolerability results in healthy volunteers, the Safety Review Committee endorsed advancement to a Phase 1b clinical trial evaluating ENV-294 in patients with atopic dermatitis.
🔔 On November 13, 2024, Enveda announced it has entered its candidate named ENV-294, into a Phase I clinical trial, with the first patient dosed at the end of October.
✅ The Phase 1a trial for ENV-294 was a randomized, double-blind, placebo-controlled, single and multiple ascending dose study in healthy adult subjects. ENV-294 was found to be well-tolerated with a favorable safety profile across all dose levels, with no dose-limiting toxicities or serious adverse events reported. Pharmacokinetic data demonstrated dose-proportional exposure and support the potential for once-daily oral dosing.
✅ Phase 1b initiation is currently expected to begin in the second half of 2025.
Enveda Biosciences (Enveda Biosciences Inc) is unlocking the planet's chemistry to discover next-generation therapies, by using breakthroughs in ML, metabolomics and robotics, to index nature’s untapped chemical space for new drug discovery. The company has secured significant funding 👛 from Sanofi on February 26, 2025, bringing its total Series C financing to 💲1️⃣5️⃣0️⃣M. The investment will support the advancement of Enveda’s AI-driven drug discovery programs into clinical trials, focusing on precision medicine and novel therapeutics (Enveda Gains Backing from Sanofi to Advance AI-Driven Drug Discovery to Clinical Trials Bringing Total Series C Financing to $150M).
⚜️ La Trobe University Advances AI Innovation with NVIDIA Supercomputer
La Trobe University in Australia 🦘 has deployed an NVIDIA-powered supercomputer 🦸♀️, boosting its capacity for AI-driven life sciences research (La Trobe University: Advancing AI innovation with NVIDIA supercomputer). La Trobe University’s deployment of NVIDIA DGX H200 systems are the first to be commissioned at a university in Australia, giving scientists the ability to push the boundaries of AI-driven medical and biotech research.
The supercomputer’s arrival follows the launch last year of La Trobe’s Australian Centre for Artificial Intelligence in Medical Innovation (ACAMI), the world’s first university centre specialized in using AI to develop immunotherapies, cancer vaccines, med-tech, and healthcare.
The DGX H200 infrastructure and ACAMI are backed by a 💲1️⃣0️⃣M Victorian Government investment through mRNA Victoria, positioning La Trobe University as a national hub for AI-in-medical innovation.
🫁 Insilico Eyes 👀 Q4 Start for Late-Stage Trials in IPF
Insilico is preparing 🏹 to begin late-stage trials (Phase IIb/III) of its IPF (Idiopathic Pulmonary Fibrosis) candidate in Q4 2025, pending ⚖️ regulatory discussions (Insilico Announces Nature Medicine Publication of Phase IIa Results of Rentosertib, the Novel TNIK Inhibitor for Idiopathic Pulmonary Fibrosis Discovered and Designed with a Pioneering AI Approach). Rentosertib (known as ISM001-055), is a TNIK inhibitor developed using Insilico’s generative AI platform, Pharma.AI.
Highlights:
✅ Phase IIa study results of Rentosertib were published simultaneously in Nature Medicine (IF = 58.7) and presented at the American Thoracic Society (ATS) 2025.
✅ Encouraging clinical data showed that patients receiving 60 mg QD Rentosertib experienced the greatest mean improvement in lung 🫁 function, as measured by forced vital capacity (FVC), with a mean change of +98.4 mL, compared to a mean decline of -20.3 mL in the placebo group.
✅ Exploratory biomarker analysis further validated the biological mechanism of TNIK, the novel target identified through a generative AI approach, supporting Rentosertib’s potential anti-fibrotic and anti-inflammatory effects.
✅ “These results not only suggest that Rentosertib has a manageable safety and tolerability profile, but also warrants further investigation in larger-scale clinical trials of longer duration, demonstrating the transformative potential of AI in drug discovery and development and paving the way for faster and more innovative therapeutic advancements,” said Alex Zhavoronkov, PhD, Founder and CEO of Insilico Medicine.
✅ However, the sample size in each patient group was relatively limited, and these findings will need to be validated in larger cohort studies," said Dr. Zuojun Xu, Professor at the Peking Union Medical College and the lead investigator of the Phase IIa clinical trial of Rentosertib in IPF patients.
✅ The Phase IIa GENESIS-IPF trial (Generative AI Enabled Novel Experimental Study of ISM001-055 in Subjects with IPF) reported in this paper is a double-blind, placebo-controlled trial that enrolled 71 patients with IPF across 22 sites in China 🇨🇳. Participants were randomly assigned to receive either placebo, 30 mg Rentosertib once daily (QD), 30 mg twice daily (BID), or 60 mg QD for 12 weeks.
Regarding Insilico Medicine, Aging and AI:
Super Agers - Eric Topol's New Longevity Book by 🧵
📢 “Thirteen years later, many predictions from The Ageless Generation have materialized.
We have advanced AI, cellular reprogramming is a reality, and artificial organs are far more sophisticated.
Yet, despite being marginally better at treating certain diseases, no single technology has truly transformed longevity.
Many have failed. All startups in the area have failed or are failing and we are back to DYMT.”
A New Blueprint⁉️
📢 “Dr. Eric Topol is not another longevity influencer. He is a world-renowned physician-scientist, cardiologist, and geneticist at Scripps Research. His work is steeped in data, and his goal with Super Agers is to cut through the pseudoscience and "overblown or premature claims" that plague the field.”
📢 “His central argument is both pragmatic and powerful: the most effective strategy for a long, healthy life isn't about finding a "cure" for aging.
It's about aggressively using science and technology to prevent or delay the major chronic diseases that wreck our later years: heart disease, cancer, diabetes, and neurodegenerative decline. It’s a relentless focus on extending healthspan, not just lifespan.”
📢 “So, what’s his plan? Topol organizes it around 5️⃣ foundational pillars, moving far beyond the basics:
….1️⃣. Lifestyle+ (The DYMT Upgrade), 2️⃣. Cells, 3️⃣. Omics, 4️⃣. Artificial Intelligence, and 5️⃣. Drugs & Vaccines.”
For more ➡️
🔍 Diagnostics.ai – First 🥇 CE-IVDR Certified Transparent AI Platform for Molecular Diagnostics
Diagnostics.ai has launched 🚀 the first 🥇 CE-IVDR certified AI platform for molecular diagnostics in Europe (Diagnostics.ai Launches Industry's First CE-IVDR Certified Transparent AI Platform for Molecular Diagnostics as Regulatory Deadlines take Effect), a fully-transparent ML platform for clinical real-time PCR diagnostics, demonstrating exactly how each result was achieved, a first 🥇 for molecular-testing machine learning. The technology is backed by over 15 years of experience and millions of successfully processed samples with >99.9% proven accuracy.
📢 “While most diagnostic algorithms remain an impenetrable ‘black box,’ ◼️ the PCR.AI API was engineered with transparency included from the ground up. Our platform delivers transparency and traceability that meet and support the highest standards set by CE-IVDR, making the AI decision-making process visible, understandable, and traceable.”
said Aron Cohen, Chief Executive Officer of Diagnostics.ai.
Diagnostics.ai is an established leader in AI-powered PCR analysis with over 15 years of experience serving clinical laboratories worldwide. The company has processed millions of samples with documented >99.9% accuracy and maintains full CE-IVDR and MHRA compliance. PCR.AI’s transparent machine learning platform transforms laboratory efficiency while enabling regulatory compliance.
Highlighted Benefits
✅ Transparent Result Attribution: Directly shows how and why a result was achieved, eliminating reliance on post-hoc interpretations.
✅ Real-Time Model Monitoring: Allows laboratories to track model performance and detect drift in real time–meeting IVDR Article 72 requirements.
✅ Per-Test Algorithm Accountability: Easy to understand per test reports, ensuring comprehensive auditability.
✅ Clinician-Ready Explanation Generation: Provides laboratory professionals and clinicians with clear, auditable explanations of diagnostic outcomes, supporting informed clinical communication.
💻 IBM & Roche Co-Develop AI-Powered Diabetes App 📲 for Hypoglycemia Prediction
IBM Research and Roche Diabetes Care have partnered 🤝 to develop an AI-powered app that uses real-time glucose data to predict hypoglycemic events (IBM and Roche Co-Created an Innovative Solution to Support People with Diabetes in their Daily Lives with AI-Enabled Glucose Predictions).
Roche’s Accu-Chek® SmartGuide Predict app was launched in Switzerland 🇨🇭 a few months ago, and results from the combination of the extensive healthcare and digital expertise of the companies. Is designed to enable people with diabetes to better manage their glycemic control with the help of an AI-enabled solution. Being paired with Roche’s Accu-Chek SmartGuide continuous glucose monitoring (CGM) sensor, the Accu-Chek SmartGuide Predict app uses predictive algorithms informed by real-time glucose values and allows for insights to improve glycemic control and reduce the risk of hypoglycemia or hyperglycemia.
⏱️ Natus Neuro Launches 🚀 BrainWatch–AI-Driven Point-of-Care EEG
Natus Medical announced that it launched BrainWatch, a point-of-care EEG solution driven by AI. Natus Medical Incorporated (Natus) offers medical equipment, software, supplies and services for the diagnosis, monitoring, and treatment of impairments and disorders effecting the brain, neural pathways, and eight sensory nervous systems. BrainWatch, AI-enhanced, portable EEG system 🧠, delivers the most ACNS-compliant rapid EEG solution for critical care, enabling full referential analysis. It also offers exclusive on-device software with integrated Persyst algorithms for seizure detection 🤯and seizure burden (Natus Neuro launches BrainWatch AI-driven, point-of-care EEG).