Latest TechBio News 🗣️
🧠 CleverPoint – The Future of Immersive Biofeedback 🔁
CleverPoint in Poland 🇵🇱 creates hardware to understand brain processes using VR (virtual reality) integrated wearable technology. The company records the electrical activity of brain in the prefrontal cortex (EEG), the eye movement as well as the facial muscle movement (EMG), and the electrical activity of the heart (EKG) in order to analyze the user’s physiological response to VR content. Once the biosignals are collected then during offline data analysis, the software is able to calculate (with CleverLAB and Stressonika):
the levels of alpha, beta, gamma, and theta brain 🧠 waves,
indicators of heart 🫀 rate variability,
level of concentration/relaxation ☺️, and
stress ♨️ leveles.
CleverPoint’s VR-integrated wearable platform by combining neurofeedback (to assess attention, stress, relaxation, and emotional response), cardiofeedback (tracks heart rate variability, pulse, and cardiac coherence for autonomic nervous system insights), and biometric sensors (galvanic skin response, eye 👁️ tracking readiness, movement tracking, and more), unlocks deep insights into cognitive and physiological engagement—enabling smarter content design, personalized therapy, and advanced research in VR environments.
Just this week (May 3️⃣1️⃣st 2️⃣0️⃣2️⃣5️⃣) Kirill Krasnogir, the CEO of Clever Point, announced that CleverPoint Neuro, CleverPoint Marine, and their visionary partner Novikontas Training Center have won the Best XR Experience at the XR Awards 2️⃣0️⃣2️⃣5️⃣! In particular, this recognition highlights the center’s pioneering efforts in transforming corporate training and employee well-being through cutting-edge XR solutions. At the core of this success is Stressonika, the advanced XR-based system developed by CleverPoint Neuro, and member of XR Polska that supports all spatial technologies and entities that are working in the extended reality field. Basically XR Polska serves as a hub for XR professionals in Poland, where developers, artists, researchers, and enthusiasts come together to support each other, aiding in the expansion of their network.
The implementation of Stressonika at Novikontas Training Center is supported by their marine industry partner, CleverPoint Marine (Digital Health technologies and Data-driven Wellbeing solutions for the Marine Industry), ensuring seamless adaptation for maritime professionals. By fusing cutting-edge XR technology with precise biometric monitoring, CleverPoint is revolutionizing how specific businesses optimize performance, reduce stress and human factors, and enhance employee well-being. Their latest achievement at XR Awards 2️⃣0️⃣2️⃣5️⃣ confirms that Novikontas Training Center is setting a new benchmark in digital transformation and corporate training, by utilizing VR-integrated wearable technology. In fact by using the immersive and controlled nature of virtual reality with instantaneous ECG, EEG/EMG recording, Stressonica provides a comprehensive and accurate assessment of a person's psychophysiological state, combining objective physiological data with realistic simulation of cognitive and stress tasks.
The Key 🔑 Achievements ✅ of this implementation include so far:
Over 6️⃣0️⃣0️⃣ ship 🚢 crew members that have successfully completed immersive stress assessments,
8️⃣0️⃣% cost reduction compared to traditional evaluation methods,
8️⃣7️⃣.1️⃣% user engagement, demonstrating strong adoption & impact,
Scalable, data-driven optimization for personalized well-being solutions.
The device costs €2800 for a kit composition of a CleverPoint device, a Facial Interface, a ECG cable and an Annual license on CleverLab, €8500 for Stressonika, and €9700 for CleverPro.
Currently CleverPoint Neuro is looking for investors 🧚.
🧪 Pioneering Precision: How South Korea’s 🇰🇷 Galux is Redefining Antibody Discovery with AI
Galux (Galux Inc, 갤럭스) was established in 2️⃣0️⃣2️⃣0️⃣ with the incorporation of molecular design technology that has been developed over a period of 1️⃣5️⃣ years at Seoul National University, and leverages AI, physics and chemistry. Galux (💲1️⃣8️⃣M in funding to date, lead investor is InterVest) is currently developing 👨💻🚧 a drug design platform (the protein structure modeling platform "GALAXY") for
protein structure prediction: GaluxFold, GaluxTBM, GaluxDBM, GaluxRefine, GalaxyLoop, GalaxyDomDock,
protein-protein/peptide interaction prediction: GalaxyHomomer, GalaxyHetermoer, GalaxyTongDock, GalaxyRefineComplex, GalaxyPepDock, GaluxPepMimic
protein-ligand interaction prediction: GalaxyDock, GaluxVS, GalaxySagittarius, Galaxy7TM, GalaxyWater and GalaxySite.
🔰 In March 2️⃣0️⃣2️⃣5️⃣, Galux confirmed that has designed with its 'de novo' protein design platform six types of antibody proteins that can be used for disease treatment (Korean AI firm Galux develops six novel therapeutic antibodies using innovative design methods). The antibodies bind to the PD-L1, HER2, EGFR, ACVR2A/B, FZD7, and ALK7 proteins (Precise, Specific, and Sensitive De Novo Antibody Design Across Multiple Cases).
Galux's De Novo Antibody Design:
Galux's study showcases AI's versatility in designing antibodies for multiple therapeutic targets, paving the way for personalized medicine (Pioneering Precision: How South Korea’s Galux is Redefining Antibody Discovery with AI).
The company is also focused on identifying and developing novel therapeutics for incurable and rare diseases through its AI-based drug design platform and in vitro/in vivo validation (Discovery of Highly Active Kynureninases for Cancer Immunotherapy through Protein Language Model).
🌐 Wipro Launches Global Innovation Network to Accelerate AI-Powered Innovation in India 👳
🔍 Initiative Overview
Wipro Limited (India 🇮🇳 based global IT services firm) just launched a Global Innovation Network (GIN) to foster cross-industry collaboration using AI, cloud, and data science, including healthcare and life sciences companies (Wipro Launches Global Innovation Network to Accelerate AI-Powered Co-Innovation). Wipro also unveiled a first-of-its-kind 6️⃣0️⃣, 0️⃣0️⃣0️⃣ sqft Innovation Lab at its Kodathi campus in Bengaluru, envisioned as a hub for exploring next-generation solutions.
💡 Key Features
Collaborative labs with academic and corporate R&D teams, and
Focus on enterprise AI, digital health, and data interoperability,
📈 Strategic Implications
Expands Wipro’s footprint in health tech and AI-driven drug development, and
Reinforces India’s role in supporting AI innovation at scale.
✳️Mastering the Tech-Pharma Landscape in India: Essential Skills to Succeed in a Transforming Industry✳️
India’s pharmaceutical industry is currently valued at over 💲5️⃣0️⃣ billion (₹4.2 lakh crore) as of 2️⃣0️⃣2️⃣3️⃣ and is poised to reach 💲1️⃣3️⃣0️⃣ billion by 2️⃣0️⃣3️⃣0️⃣, according to IBEF (India Brand Equity Foundation). A large portion of this growth is being driven not only by expanded production and exports, but by digitization across R&D, manufacturing, supply chain, and customer engagement.
Emerging technologies such as AI, ML, blockchain, Internet of Things (IoT), and robotic process automation (RPA) are no longer peripheral—they are central to how pharmaceutical firms innovate, operate, and comply.
Some notable trends include:
● AI in drug discovery reducing R&D time by 1️⃣5️⃣–2️⃣0️⃣%
● Blockchain ensuring drug traceability under regulatory mandates
● IoT-enabled smart packaging for real-time temperature tracking
● Cloud-based pharmacovigilance platforms for adverse event reporting
🛒 John Snow Labs Acquires WiseCube to Bolster AI-Powered Biomedical Knowledge and Drug Discovery 🛠️
🔍 Acquisition Details
John Snow Labs (an award-winning healthcare AI company for rapid adoption of AI in healthcare and life sciences organizations, providing high-compliance AI platform, state-of-the-art NLP libraries, and data market) just acquired WiseCube (with a biomedical knowledge graph platform and AI-powered literature analysis) to enhance AI-driven drug discovery through integrated biomedical knowledge (John Snow Labs Acquires WiseCube to Bolster AI-Powered Biomedical Knowledge and Drug Discovery). Financial details of the acquisition were not disclosed. 🤐
💡 Why It Matters
By combining NLP-based clinical text understanding (Spark NLP) with knowledge graphs (WiseCube) to extract insights from unstructured scientific literature, it facilitates an holistic analysis of unstructured data and medical ontologies and supports target discovery, biomarker identification, and mechanism-of-action analysis, creating in the end one of the most comprehensive AI-driven biomedical knowledge platforms.
WiseCube AI (Washington US, 2016) specializes in unifying and analyzing disjointed biomedical datasets to provide rapid, literature-backed answers to complex medical questions with their 3 products:
✳️ Orpheus API: is a transformative service poised to redefine biomedical research and drug discovery. Amidst the rapidly expanding universe of biomedical data, Orpheus stands out as a beacon of innovation, offering healthcare providers, biomedical researchers, and drug developers direct access to the most relevant, literature 📚 supported medical insights and advanced Semantic AI based discovery tools.
✳️ Orpheus GPT: is a gateway to a revolutionary approach in biomedical research. Integrating seamlessly with Wisecube’s comprehensive biomedical database, it enhances ChatGPT with insights, curated lists of research articles and clinical trials. Each entry is meticulously detailed, providing direct links to pivotal papers, thus facilitating citation-rich insights and aiding in the synthesis of authoritative research findings.
✳️ AI Fact-Check: is a solution for ensuring the factual integrity of AI-generated content (a crucial hallucination 🤡 detection tool). This innovative approach empowers you to validate the accuracy of information produced by AI systems, building confidence in your AI-powered applications and fostering trust.
🧬 Deep Genomics Expands AI Foundation Model Platform for Decoding RNA Biology
On May 19, 2️⃣0️⃣2️⃣5️⃣, Deep Genomics announced the latest addition to its foundation model platform (Deep Genomics Expands AI Foundation Model Platform for Decoding RNA Biology). The new deep learning model, REPRESS, accurately predicts microRNA (miRNA) binding and mRNA degradation directly from RNA sequences (Sequence based prediction of cell type specific microRNA binding and mRNA degradation for therapeutic discovery).
REPRESS (Regulatory Element PRediction of post-transcriptional Events using Sequence Signals) enables the fast and accurate analysis of patient mutations and therapeutic approaches that act through mRNA stability. mRNA stability is crucial for maintaining normal protein levels and boosting protein levels, both of which offer therapeutic benefits.
Trained on millions of miRNA-mRNA interaction and degradation sites from human and mouse tissues, REPRESS reveals regulatory mechanisms previously hidden, even from state-of-the-art technologies. By learning to predict miRNA binding and mRNA degradation directly from sequence, it sheds light 🔦 on a critical and underexplored layer of gene regulation.
REPRESS outperforms other advanced methods and neural architectures on a comprehensive suite of seven orthogonal tasks, including identifying genetic variants that affect microRNA binding, predicting out-of-distribution data from massively parallel reporter assays, and predicting canonical and non-canonical miRNA mediated repression.
Deep Genomics (2️⃣0️⃣1️⃣5️⃣, Canada) has a proprietary AI platform, BigRNA, that is the world’s first RNA foundation model for RNA therapeutics that can predict tissue-specific RNA expression, splicing, microRNA sites and RNA binding protein specificity. BigRNA can uniquely discover a wide range of new biological mechanisms and RNA therapeutic candidates that would not be found using traditional approaches that measure only overall gene expression levels. In contrast, BigRNA is trained to predict RNA expression at sub-gene resolution, such as polyadenylation, exon skipping, and intron retention (An RNA foundation model enables discovery of disease mechanisms and candidate therapeutics).
The company made headlines back in 2️⃣0️⃣1️⃣9️⃣ with discovering a novel target and a novel RNA therapeutics candidate, DG12P1, for rare Wilson disease using BigRNA, all within 1️⃣8️⃣ months of initiating target discovery efforts (Deep Genomics Nominates Industry’s First AI-Discovered Therapeutic Candidate). In particular,
Deep Genomics’ AI system scanned over 2,400 diseases and over 100,000 pathogenic mutations while searching for good drug development opportunities and was able to predict and confirm the precise disease-causing mechanism of the mutation Met645Arg.
That is one of several genetic mutations that leads to loss of function of the ATP7B copper-binding protein, a genetic mutation that impairs the body’s ability to remove copper, and thereby identify a clear therapeutic target.
The AI system was then used to identify 12 lead candidates out of thousands of potential compounds, taking into account in vitro efficacy and toxicity.
In particular, TDG12P1 was designed to correct the exon skipping mechanism of Met645Arg and after tolerability experiments Deep Genomics declared it the ideal candidate to advance toward IND.
🎳 On June 12, 2024, Deep Genomics announced the opening of its new office and lab facility in Cambridge, Massachusetts (the expansion of its Toronto office) and several key leadership hires. Deep Genomics raised so far a total of $1️⃣8️⃣0️⃣M to automate drug discovery.
RXRX vs. SDGR: Which AI-Powered Drug Discovery Stock Has More Upside?
👉 Despite the challenges, both these stocks have the potential to revolutionize the drug discovery process by delivering breakthrough therapies at a lower cost compared to traditional drug/biotech companies. Their in-house clinical pipeline, as well as ongoing collaboration agreements, have the potential to drive significant growth 📈 in the future, which will boost shareholder wealth.
👉 However, investors should exercise caution before investing in Schrodinger at its current stock price. The stock appears to be nearing its peak, trading above its five-year average, which may indicate an impending decline 📉. Additionally, analysts anticipate wider losses for SDGR in 2025, potentially triggering a sell-off.
👉 Based on the above discussion, Recursion Pharmaceuticals, with its innovative pipeline of candidates, encouraging collaboration agreement, narrowing loss estimates, and cheaper valuation, is a far better bargain for investors looking to invest in AI-powered drug discovery stocks with higher growth potential.
RXRX is thus a clear-cut winner.
💉 Medtech AI Startups ProteinQure and AssistIQ Each Close Series A Rounds
Two promising Canadian medtech-AI startups, ProteinQure and AssistIQ, have recently closed Series A funding rounds, signaling growing investor confidence in AI-driven healthcare innovation across both drug discovery and clinical care delivery (Medtech AI startups ProteinQure and AssistIQ each close Series A rounds).
Montréal-based AssistIQ has secured 💲1️⃣1️⃣.5️⃣M in financing for its AI-powered hospital supply management platform (from Boston-based Battery Ventures, with participation from return investor Tamarind Hill), while Toronto-based ProteinQure nabbed 💲1️⃣1️⃣M for its AI-powered drug discovery platform (from Tom Williams of Heron Rock Fund, with participation from Golden Ventures and Kensington Capital).
AssistIQ has developed a software platform for hospital supply management, allowing facilities to track equipment such as personal protective equipment and surgical tools, while ProteinQure has developed an AI-powered drug discovery platform that uses statistical and ML approaches to identify new proteins that could be used in treatments for cancers and rare diseases.
In particular, ProteinQure (Toronto, Canada 2017) uses AI and physics based methods for the computational design of de-novo protein therapeutics like antibodies, peptides, and other protein-based drugs that are capable of targeting a broad range of biological targets outside the scope of traditional small molecule therapeutics. They have developed ProteinStudio™ an integrated platform of proprietary technologies to solve complex drug design challenges involving peptides and proteins. ProteinStudio™ harnesses molecular simulations and custom AI models on petascale supercomputers, enabling the creation of unique molecular scaffolds.
ProteinQure is set to run its first clinical trial for a drug candidate for triple-negative breast cancer (pipeline).
Potent inhibition of Triple Negative Breast Cancer (TNBC) tumor growth by ProteinQure clinical candidate PQ203 (peptide drug conjugate) in a mouse model of human disease.
PQ203, a groundbreaking peptide drug conjugate, was designed to target SORT1 with unparalleled precision.
🔠 Meta Open-Sources Atomic-Scale AI Model for Scientific Discovery: Introducing UMA
Meta has open-sourced a new atomic-scale AI model called UMA (Unified Molecular Atlas), capable of simulating 1️⃣0️⃣0️⃣ M atomic interactions and replicating results from density functional theory (DFT) up to 1️⃣0️⃣0️⃣0️⃣0️⃣ times faster. This breakthrough represents a major leap in AI for computational chemistry, with far-reaching implications across drug discovery, materials science, and energy storage.
UMA models (UMA: A Family of Universal Models for Atoms) are trained on half a billion unique 3D atomic structures (the largest training runs to date) by compiling data across multiple chemical domains, e.g. molecules, materials, and catalysts.
They are releasing the UMA code, weights, and associated data to accelerate computational workflows and enable the community to continue to build increasingly capable AI models.
⭐ BostonGene to Showcase its Multimodal AI Platform Advancing Drug Development at the 2025 ASCO® Annual Meeting
BostonGene just announced (May 27, 2025) that six abstracts 📃 have been accepted at the 2025 ASCO Annual Meeting (ASCO), scheduled to take place May 31 – June 3, 2025, at McCormick Place Convention Center in Chicago, IL (BostonGene to Showcase its Multimodal AI Platform Advancing Drug Development at the 2025 ASCO® Annual Meeting). The presentations will highlight advancements in transcriptomic analysis, immune microenvironment profiling, histomolecular subtyping and blood-based predictors—key tools for improving clinical trial design and driving precision treatment strategies.
In March 2025, BostonGene Corporation was recognized for its AI innovation, underscoring the growing importance of ML in advancing precision medicine (BostonGene Named a Fierce Life Sciences Innovation Awards Winner in the AI Innovation Category). ➡️ BostonGene founded in 2015 is a biotechnology company specializing in advanced computational biology and precision medicine. Their AI-powered multiomics platform decodes cancer patients' molecular profiles, including their immune system and tumor microenvironment, to uncover key disease drivers, identify novel drug targets and recommend the most effective treatments. With advanced bioanalytics, an indication-specific cancer library and a next-generation CLIA-certified, CAP-accredited high-complexity laboratory, they deliver precise, clinically validated insights that drive precision medicine and advance oncology research. On February 4, 2025, BostonGene Contributed to Friends of Cancer Research White Paper Introducing a Novel Process for Companion Diagnostics for Rare Biomarkers and Indications.
🧪 Latest Nature Communications Study: AI-Enabled Development of Next-Generation ENPP1 Inhibitors for Innate Immune Modulation by Insilico Medicine
In a groundbreaking study published in Nature Communications, Insilico Medicine has reported the successful development of 🆕 potent ENPP1 inhibitors using its AI-driven drug discovery platform. These compounds show promise as innate immune modulators, opening new therapeutic avenues in oncology and autoimmune diseases (Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors).
The study identifies and validates ENPP1 as a critical immune checkpoint among multiple solid tumors and assists in developing a highly specific oral ENPP1 inhibitor, ISM5939, for immunotherapy.
ISM5939, is an orally bioavailable ENPP1-selective inhibitor capable of stabilizing extracellular cGAMP and activating bystander antigen-presenting cells without inducing either toxic inflammatory cytokine release or tumor-infiltrating T-cell death. In murine syngeneic models across cancer types, ISM5939 synergizes with targeting the PD-1/PD-L1 axis and chemotherapy in suppressing tumor growth with good tolerance.
These findings provide evidence supporting ENPP1 as an innate immune checkpoint across solid tumors and reports an AI design-aided ENPP1 inhibitor, ISM5939, as a cutting-edge STING modulator for cancer therapy, paving a path for immunotherapy advancements.
🔐 23andMe, Regeneron and the Future of Human Genomic Data Privacy and Security
As one of the largest direct-to-consumer (DTC) genetic testing companies, 23andMe has played a pivotal role in making personal genomics accessible to millions. However, recent data breaches, including regulatory scrutiny, as well as growing public awareness have placed genomic data privacy 🫥 and security 🗝️ at the center of ethical and legal ⚖️ debates.
This raises critical questions about how consumer genetic data is collected, stored, shared, and used, not just by 23andMe but across the broader landscape of personalized medicine, biotech research, and AI-driven drug discovery.
Privacy risks associated with sensitive biological data represent a critical area of concern. TechBio applications rely heavily on vast datasets, including genomic information and medical records, to train AI algorithms and develop predictive models. While this reliance enables groundbreaking advancements, it also exposes patients to significant privacy vulnerabilities.
Unauthorized access, data misuse, and cloud security breaches pose substantial threats to the confidentiality of biological data. To address these challenges, advanced cybersecurity measures, robust data anonymization techniques, and stronger encryption protocols must be implemented. Additionally, blockchain technology is emerging as a promising solution for secure and transparent consent management through immutable metadata recording and smart contract enforcement (The Ethical Implications of AI in Clinical Practice in 2025).
Then on May 19, 2️⃣0️⃣2️⃣5️⃣, Regeneron announced the acquisition of 23andMe for 💲2️⃣5️⃣6️⃣M (Regeneron Pharmaceuticals (NasdaqGS:REGN) Adopts Innovative Technology for Faster Drug Discovery).
🗨️ “When the deal closed, the final price tag was 💲2️⃣5️⃣6️⃣M for substantially all of 23andMe’s assets. For context, 23andMe isn’t just any biotech startup – it’s the company that persuaded over 1️⃣5️⃣ million people to spit in a tube and share their DNA in exchange for ancestry tidbits and health trait reports.
Regeneron’s purchase includes that entire database of genotypes and the associated phenotypic and survey data those customers provided.
Do the math and it comes out to around 💲1️⃣7️⃣ per customer profile, or about 💲2️⃣1️⃣ per genome for those who consented to research use.
In the world of biotech, that’s an astonishingly low ⬇️ cost per genome.
It’s as if a luxury sports car 🏎️ was suddenly selling for the price of a used bicycle 🚲.”
For more ➡️
23andMe and the Future of Human Genomic Data Privacy and Security
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🐭 Lantern Pharma’s LP-184 Shows Promising In Vivo Activity in Atypical Teratoid Rhabdoid Tumors (ATRT)
At the SNO (Society for Neuro-Oncology) Pediatric Conference, Lantern Pharma presented compelling new data demonstrating in vivo efficacy of LP-184 in Atypical Teratoid Rhabdoid Tumor (ATRT) models—a rare and aggressive pediatric brain cancer (Lantern Pharma's LP-184 Shows Promising In Vivo Activity in Atypical Teratoid Rhabdoid Tumors (ATRT) at SNO Pediatric Conference, Further Validating Rare Pediatric Disease).
ATRT is a rare, fast-growing tumor of the brain and spinal cord that typically occurs in children aged three years and younger, though it can occur in older children and adults. These tumors are characterized by the loss of function of the SMARCB1 gene. ATRTs account for approximately 1️⃣-2️⃣% of all pediatric brain tumors but represent a disproportionately high percentage of brain tumors in infants. Current treatment involves a combination of surgery, intensive chemotherapy, and, in some cases, radiation therapy. Despite aggressive treatment, the prognosis remains poor, with a median survival of approximately 1️⃣7️⃣ months, highlighting the urgent need for more effective therapies. Hopefully, the single-agent activity of LP-184 in models suggests it could potentially transform the treatment landscape for children with these brain tumors.
🛍️ Datavant Acquires Aetion to Expand Real-World Evidence (RWE) Capabilities
In a strategic move to strengthen its position in the life sciences and healthcare analytics space, Datavant has acquired Aetion, a leading provider of real-world evidence (RWE) analytics software (Datavant to acquire real-world evidence company Aetion to boost its life sciences business). Aetion Inc provides RWE solutions to biopharmaceutical companies, medical device manufacturers, payers and regulators. The company has 220 employees and works with more than 40 leading biopharma organizations and 80-plus data partners. The deal combines Datavant’s network of 300+ data partners with Aetion’s analytics to offer end-to-end real-world evidence tools for biopharma and regulators.
Datavant specializes in breaking down silos 🧱 and analyzing health data securely and privately and its primary goal, like most healthcare analytics companies, is to help organizations achieve their data strategies. This real-world data ecosystem powers accurate insights by linking proprietary data (clinical trials data, social determinant data, etc) with third-party data (lab data, claims data, etc). Back on January 7️⃣, 2️⃣0️⃣2️⃣5️⃣ Datavant was on the M&A hunt as the $7B health data company bulks up before a potential IPO. However, Datavant has not yet gone public through an IPO.
✳️ OpenAI and Babylon Biosciences Use Reinforcement Learning to Predict Clinical Trial Outcomes
OpenAI and Babylon Biosciences have partnered to develop fine-tuned AI models that predict the likelihood of success in clinical trials using reinforcement learning (RL). The system was trained across a dataset of 4️⃣3️⃣0️⃣ clinical trials, achieving improved AUC (Area Under the Curve) accuracy, marking a major step forward in applying AI to de-risk drug development (With fine-tuned AI models, OpenAI, Babylon aim to predict clinical trial successes). In particular, with biomedical data collected by Sleuth Insights, researchers helped sculpt a version of OpenAI’s o3-mini model using scientific literature and findings from 430 clinical trials spanning cancers, neurology, metabolic diseases and rare disorders.
Babylon Biosciences is on a mission to deliver effective medicines for patients with diseases of the brain. To do this, they develop therapeutics that rescue essential functions in the brain rather than clearing emergent pathology, leveraging Babylon's proprietary high-throughput assay.
🌀 Absci Advances Lead AI-Designed Candidate for IBD into the Clinic
Biotech company Absci has taken a significant step forward in the development of its AI-designed antibody for inflammatory bowel disease (IBD) by initiating a Phase 1 clinical trial. The trial is currently evaluating the safety, tolerability, and pharmacokinetics (PK) of the drug candidate—targeting 🎯 TL1A (TNF-like ligand 1A)—in approximately 4️⃣0️⃣ healthy volunteers (Absci Advances Lead AI-Designed Candidate for IBD into the Clinic).
The move highlights how AI is accelerating the traditionally long and costly drug development process. By leveraging ML to predict and optimize antibody structures before lab testing even begins, companies like Absci can significantly reduce timelines from discovery to clinic.
TL1A, also known as Tumor necrosis factor-like cytokine 1A or TNFSF15, is a cytokine, a protein that acts as a chemical messenger in the immune system. It is a member of the TNF (Tumor Necrosis Factor) superfamily and plays a role in both mucosal immunity and intestinal homeostasis. TL1A is upregulated in inflammatory bowel disease (IBD) and other conditions, including skin, joint, and autoimmune disorders.
Latest News from Absci:
➡️ Absci Corporation (ABSI) Reports Q1 Loss, Misses Revenue Estimates,
➡️ AbSci Corp (ABSI) Sees Borrow Rate Increase | ABSI Stock News.
Absci (Nasdaq: ABSI) is a generative AI drug creation company that combines AI with scalable wet lab technologies to create better biologics for patients, and faster. The company is known for becoming in January 2023 the first company “to create and validate de novo antibodies in silico” using generative AI. Absci and Owkin announced on January 0️⃣1️⃣, 2️⃣0️⃣2️⃣5️⃣ a partnership bringing together two leading AI platforms to rapidly discovering and designing novel therapeutics for patients (Absci and Owkin Synergize Leading TechBio Platforms to Advance Generative AI Drug Discovery).
Absci's latest financial updates reflect the growing commercial viability of AI-powered drug discovery platforms (Absci Reports Business Updates and Fourth Quarter and Full Year 2024 Financial and Operating Results). Its last report highlighted:
➡️ updates across proprietary pipeline and demonstrated new breakthroughs by their AI platform;
➡️ the collaboration 🤝 with AMD, including a 💲2️⃣0️⃣M strategic investment in Absci;
➡️ collaborations 🤝 with Owkin, Twist Bioscience, Invetx, and Memorial Sloan Kettering Cancer Center;
➡️ and cash, cash equivalents, and short-term investments.
🔬 CryoCloud Raises €2️⃣M to Scale Automated Cryo-EM Analysis
CryoCloud (a Dutch biotech) raised €💶2️⃣M to scale automated cryo-electron microscopy (cryo-EM) data analysis via cloud-based platform (Dutch biotech CryoCloud raises €2M to enhance machine learning for drug discovery). CryoCloud's web-app provides instant access to cloud resources, image analysis workflows & storage solutions for cryo-EM data analysis. It eliminates queues, downtimes, the need for setup costs & hardware maintenance, while providing optimized & accelerated computation via an intuitive UI.
Features:
AWS cloud infrastructure,
Petabyte-scale storage,
Fast analysis that starts upon demand on fast cloud resources, allowing e.g. for motion correction of >1,600 K3 movies/ hour (5.6x4k, 75 frames),
End-to-end image analysis: CryoCloud provides access to all Relion jobs & more popular packages to come (Topaz, DeepEMhancer, OpenFold),
Data Uploads: upload data via their standalone CryoCloud uploader running on Windows, Linux & Mac,
Data Archiving: affordable archiving starting from 2€/ TB/ month.
🧬 NeoGenomics & Ultima Genomics Partner on High-Throughput Cancer Diagnostics
NeoGenomics is partnering with Ultima Genomics to develop cancer diagnostics using a platform that delivers over 10 - 12 billion reads per wafer, enabling cost-effective, high-throughput sequencing 🔤 at high quality, by using the UG 100 sequencing platform and its ppmSeq™ technology (NeoGenomics and Ultima Genomics collaborate to expand clinical test offerings in Oncology using the UG 100 sequencing platform).
Few words now about Ultima Genomics and NeoGenomics.
Ultima Genomics (US) is providing high-throughput, cost-effective sequencing for the generation of AI-scale single cell datasets like the 100M Tahoe dataset. Moreover, Ultima’s UG100 sequencer was selected back in January 0️⃣9️⃣, 2️⃣0️⃣2️⃣5️⃣ by the UK Biobank Pharma Proteomics Project (UKBB-PPP) to be the sequencing technology for the largest 🦣 human proteome project in the world (Ultima Genomics Announces UG 100™ Sequencing Platform Selected for UK Biobank's Groundbreaking Human Proteome Study).
In particular, together with 14 pharma and AI companies, over 600,000 samples will be sequenced at Regeneron using the Olink Proteomics’s HT platform. The UG 100 was built for large-scale studies and factors such as quality, data accuracy, complementarity with Olink, cost-effectiveness and reliability were paramount. Ultima’s seamless integration with Olink, its ease of user adoption and compatibility with laboratory information management systems (LIMS) that will ensure streamlined workflows to support this project.
Ultima Genomics (and 10x Genomics) also partnered 🤝 with Arc Institute to accelerate the development of the Arc Virtual Cell Atlas (10x Genomics and Ultima Genomics partner with Arc Institute to accelerate development of the Arc Virtual Cell Atlas). More specifically, the Arc Institute launched in February 2025 the Arc Virtual Cell Atlas, a growing resource for computation-ready single-cell measurements, starting with data from over 300 million cells. The initial release of the Atlas was Arc’s first step toward assembling, curating, and generating large-scale cellular data to fuel new insights from AI-driven biological discovery.
✳️ The Atlas has two foundational datasets: the first is a new, open source, perturbation dataset called Tahoe-100M, created by Vevo Therapeutics, comprising 100 million cells and mapping 60,000 drug-cell interactions across 50 cancer cell lines. The second dataset, scBaseCamp, is the first single-cell RNA sequencing dataset from public data to be curated and reprocessed at scale using AI agents. Arc mined observational data from more than 200 million cells representing 21 different species sourced from public repositories, and processed them to a standardized form (Arc Virtual Cell Atlas launches, combining data from over 300 million cells).
NeoGenomics, Inc (Nasdaq:NEO), is a leading 🔝 provider of oncology diagnostic solutions, specializing in cancer genetics testing and information services. Apart from the its recent collaboration with Ultima Genomics, NeoGenomics also partnered with ConcertAI in 2024. And in 2025, the two announced a joint software-as-a-service solution in hematological malignancies for research analytics, clinical trial design, and clinical trial operational optimization. CTO-H provides a research data solution that is unprecedented in its scale, longitudinality and biomarker depth (ConcertAI and NeoGenomics Announce New AI Software-as-a-Service Solution for Hematology Clinical Research).
🤝 Boehringer Ingelheim Partners with Tempus AI for Oncology R&D 👩🔬
Boehringer and Tempus AI announced on May 1️⃣5️⃣, 2️⃣0️⃣2️⃣5️⃣ 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).
The Chicago-based Tempus—that specializes in AI and precision medicine and has one of the world’s largest libraries of clinical and molecular data—provides integrated solutions such as sequencing, companion diagnostics, clinical trial solutions, data collaborations, biological modeling and etc by applying AI. 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.
Apart form the two collaborations with AstraZeneca PLC (AZN) and Boehringer Ingelheim, Tempus has recently announced also the following partnerships ➡️
Tempus and🔺 Northwestern Medicine Announce Collaboration to Bring Practical Application of AI to Healthcare,
Tempus Announces Collaboration with🔺 IFLI Aimed at Supporting Development of Targeted Therapies for Follicular Lymphoma,
🔺 Artera Announces Collaboration with Tempus to Expand Access to Personalized Prostate Cancer Treatment,
🔺 Imagene Announces a Collaboration With Tempus to Advance AI-Driven Diagnostics for Non-Small Cell Lung Cancer,
🔺 Avacta partners Tempus AI to boost cancer therapy development,
🔺 SoftBank partners with Tempus AI to launch AI healthcare venture,
Tempus Announces Collaboration With🔺 JW Pharmaceutical to Apply Real-World Data and Biological Modeling to Enhance Early Research and Development.
Moreover, almost a month ago (April 11, 2025), Tempus AI (NASDAQ: TEM) 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), in 2024 Tempus AI acquired 🛒 Ambry Genetics (Tempus AI to Buy Ambry Genetics for $600M), and in 2022 Tempus acquired the medical imaging AI developer 🛒 Arterys.
🎤 Noetik Presents Multimodal Discovery Engines at AACR 2️⃣0️⃣2️⃣5️⃣
At the American Association for Cancer Research (AACR) Annual Meeting 2025, Noetik unveiled two groundbreaking AI-driven discovery tools: ✳️ OCTO-virtual cell and ✳️ Perturb-map. These multimodal discovery engines are designed to accelerate drug discovery by modeling complex biological systems and predicting cellular responses to genetic or chemical perturbations (Noetik Presents Multimodal Discovery Engines at AACR 2025: OCTO-virtual cell and Perturb-map). OCTO-virtual cell is a foundation model of cell and tissue biology, and Perturb-map, a high-throughput in vivo system for therapeutic target identification and immunophenotype modeling.
“OCTO-virtual cell is a step function improvement in how we interpret the cellular and spatial architecture of human tumors. By training on vast amounts of multimodal data, it learns rich, generalizable representations of biology - helping us identify distinct patient subpopulations and uncover new, spatially informed drug targets that were previously inaccessible."
said Yubin Xie, Ph.D., Senior Machine Learning Scientist at Noetik.
Perturb-map, that models human immunotypes in vivo at scale by mapping the impact of >600 perturbations on tumor immunotypes and response to immune checkpoint blockade, demonstrates that is possible to generate mouse models at scale that better capture the heterogeneity of human disease. In fact, they can now test pharmacologic and therapeutic hypotheses in these models simultaneously, which helps to identify which patient population would benefit the most from any given drug.
Noetic is an AI drug discovery company leveraging spatial data (being the biggest user of two new platforms from two different spatial companies, one for proteomics and the other for transcriptomics) to develop cancer immunotherapies, and was launched with💲1️⃣4️⃣M seed 🌱 financing from two former leaders of Recursion Pharmaceuticals hoping to bring a data-obsessed mentality to cancer research. Noetik combines self-supervised learning with the industrial-scale generation of human multimodal data.
In 2023, Noetik announced the pairing of their multimodal human data atlas with an innovative in vivo functional genomics platform to power the development of precision cancer immunotherapies (Noetik Launches "Perturb-map" In Vivo Functional Genomics Platform and Adds Precision Immunology Leader Brian Brown, Ph.D. to Scientific Advisory Board). The result was Perturb-map, the groundbreaking spatial functional genomics technology that allows pooled parallel analysis of hundreds of genetically modified tumor clones in a single experiment.
On September 14, 2014, Noetic announced that it has been selected for the second cohort of the AWS Generative AI Accelerator, launched by Amazon Web Services Inc (AWS), that gives to the participants AWS credits, mentorship and, learning resources around AI and ML technologies and grow their businesses. On August 30, 2024, AI-based Noetik closed on an oversubscribed $40M series A. The company plans to use the money to expand its atlas of human cancer biology with its in vivo CRISPR platform to advance a pipeline of cancer therapeutics to the clinic.