Alchemab Selected to Access NVIDIA Cambridge-1 Supercomputer to Advance Machine Learning Enabled Antibody Discovery – Business Wire
BOSTON & CAMBRIDGE, England--(BUSINESS WIRE)--Alchemab Therapeutics, a biotechnology company focused on the discovery and development of naturally-occurring protective antibodies and immune repertoire-based patient stratification tools, has been selected by NVIDIA to harness the power of the UKs most powerful supercomputer, Cambridge-1. Alchemab will use the NVIDIA DGX SuperPOD supercomputing cluster, powered by NVIDIA DGX A100 systems, to gain greater understanding and insights from its extensive neurology and oncology datasets.
We are honored to collaborate with NVIDIA to advance our work applying machine learning to the prediction of antibody structure and function, said Douglas A. Treco, PhD, Chief Executive Officer of Alchemab Therapeutics. Using Cambridge-1, Alchemab will vastly accelerate our capabilities and we are excited about the potential to collaborate with NVIDIAs world-leading team to better understand the language of antibodies.
Craig Rhodes, EMEA Industry Lead for Healthcare and Life Sciences at NVIDIA, commented: Cambridge-1 enables the application of machine learning to help solve the most pressing clinical challenges, advance health research through digital biology, and unlock a deeper understanding of diseases. The system drives workloads that are scaled and optimised for supercomputing and will help extraordinary organisations like Alchemab, a member of the NVIDIA Inception program, to further their research on antibodies and other protective therapeutics for hard to treat diseases.
Our collaboration with NVIDIA will unlock countless opportunities to advance Alchemabs state-of-the-art platform, facilitating the discovery of novel therapeutics and patient stratification techniques, said Jake Galson, PhD, Head of Technology at Alchemab Therapeutics. Machine learning is accelerating research across multiple therapeutic areas and will be pivotal in helping Alchemab predict the function of novel antibodies based on their sequence alone.
An individuals antibody repertoire encodes information about past immune responses and potential for future disease protection. Alchemab believes that deciphering information stored in these antibody sequence datasets will transform the fundamental understanding of disease and enable discovery of novel diagnostics and antibody therapeutics. Using self-supervised machine learning, Alchemab has developed antibody-specific language model AntiBERTa (Antibody-specific Bi-directional Encoder Representation from Transformers), a 12-layer transformer model which provides a contextualized numeric representation of antibody sequences. AntiBERTa learns biologically relevant information and is primed for multiple downstream tasks which are improving our understanding of the language of antibodies.
Attend Alchemabs session on deciphering the language of antibodies on March 24 at GTC, a free to register global AI conference. Find more details on the Nvidia Inception program here. Find project updates and more information on Cambridge-1 projects here.
About AlchemabAlchemab has developed a highly differentiated platform which enables the identification of novel drug targets, therapeutics and patient stratification tools by analysis of patient antibody repertoires. The platform uses well-defined patient samples, deep B cell sequencing and computational analysis to identify convergent protective antibody responses among individuals that are susceptible but resilient to specific diseases.
Alchemab is building a broad pipeline of protective therapeutics for hard-to-treat diseases, with an initial focus on neurodegenerative conditions and oncology. The highly specialized patient samples that power Alchemabs platform are made available through valued partnerships and collaborations with patient representative groups, biobanks, industry partners and academic institutions.
For more information, visit http://www.alchemab.com.
Originally posted here:
Alchemab Selected to Access NVIDIA Cambridge-1 Supercomputer to Advance Machine Learning Enabled Antibody Discovery - Business Wire
- Exploring LLMs with MLX and the Neural Accelerators in the M5 GPU - Apple Machine Learning Research - November 23rd, 2025 [November 23rd, 2025]
- Machine learning model for HBsAg seroclearance after 48-week pegylated interferon therapy in inactive HBsAg carriers: a retrospective study - Virology... - November 23rd, 2025 [November 23rd, 2025]
- IIT Madras Free Machine Learning Course 2026: What to know - Times of India - November 23rd, 2025 [November 23rd, 2025]
- Towards a Better Evaluation of 3D CVML Algorithms: Immersive Debugging of a Localization Model - Apple Machine Learning Research - November 23rd, 2025 [November 23rd, 2025]
- A machine-learning powered liquid biopsy predicts response to paclitaxel plus ramucirumab in advanced gastric cancer: results from the prospective IVY... - November 23rd, 2025 [November 23rd, 2025]
- Monitoring for early prediction of gram-negative bacteremia using machine learning and hematological data in the emergency department - Nature - November 23rd, 2025 [November 23rd, 2025]
- Development and validation of an interpretable machine learning model for osteoporosis prediction using routine blood tests: a retrospective cohort... - November 23rd, 2025 [November 23rd, 2025]
- Snowflake Supercharges Machine Learning for Enterprises with Native Integration of NVIDIA CUDA-X Libraries - Snowflake - November 23rd, 2025 [November 23rd, 2025]
- Rethinking Revenue: How AI and Machine Learning Are Unlocking Hidden Value in the Post-Booking Space - Aviation Week Network - November 23rd, 2025 [November 23rd, 2025]
- Machine Learning Prediction of Material Properties Improves with Phonon-Informed Datasets - Quantum Zeitgeist - November 23rd, 2025 [November 23rd, 2025]
- A predictive model for the treatment outcomes of patients with secondary mitral regurgitation based on machine learning and model interpretation - BMC... - November 23rd, 2025 [November 23rd, 2025]
- Mobvista (1860.HK) Delivers Solid Revenue Growth in Q3 2025 as Mintegral Strengthens Its AI and Machine Learning Technology - Business Wire - November 23rd, 2025 [November 23rd, 2025]
- Machine learning beats classical method in predicting cosmic ray radiation near Earth - Phys.org - November 23rd, 2025 [November 23rd, 2025]
- Top Ways AI and Machine Learning Are Revolutionizing Industries in 2025 - nerdbot - November 23rd, 2025 [November 23rd, 2025]
- Snowflake Supercharges Machine Learning for Enterprises with Native Integration of NVIDIA CUDA-X Libraries - Yahoo Finance - November 18th, 2025 [November 18th, 2025]
- An interpretable machine learning model for predicting 5year survival in breast cancer based on integration of proteomics and clinical data -... - November 18th, 2025 [November 18th, 2025]
- scMFF: a machine learning framework with multiple feature fusion strategies for cell type identification - BMC Bioinformatics - November 18th, 2025 [November 18th, 2025]
- URI professor examines how machine learning can help with depression diagnosis Rhody Today - The University of Rhode Island - November 18th, 2025 [November 18th, 2025]
- Predicting drug solubility in supercritical carbon dioxide green solvent using machine learning models based on thermodynamic properties - Nature - November 18th, 2025 [November 18th, 2025]
- Relationship between C-reactive protein triglyceride glucose index and cardiovascular disease risk: a cross-sectional analysis with machine learning -... - November 18th, 2025 [November 18th, 2025]
- Using machine learning to predict student outcomes for early intervention and formative assessment - Nature - November 18th, 2025 [November 18th, 2025]
- Prevalence, associated factors, and machine learning-based prediction of probable depression among individuals with chronic diseases in Bangladesh -... - November 18th, 2025 [November 18th, 2025]
- Snowflake supercharges machine learning for enterprises with native integration of Nvidia CUDA-X libraries - MarketScreener - November 18th, 2025 [November 18th, 2025]
- Unlocking Cardiovascular Disease Insights Through Machine Learning - BIOENGINEER.ORG - November 18th, 2025 [November 18th, 2025]
- Machine learning boosts solar forecasts in diverse climates of India - researchmatters.in - November 18th, 2025 [November 18th, 2025]
- Big Data Machine Learning In Telecom Market by Type and Application Set for 14.8% CAGR Growth Through 2033 - openPR.com - November 18th, 2025 [November 18th, 2025]
- How Humans Could Soon Understand and Talk to Animals, Thanks to Machine Learning - SYFY - November 10th, 2025 [November 10th, 2025]
- Machine learning based analysis of diesel engine performance using FeO nanoadditive in sterculia foetida biodiesel blend - Nature - November 10th, 2025 [November 10th, 2025]
- Machine Learning in Maternal Care - Johns Hopkins Bloomberg School of Public Health - November 10th, 2025 [November 10th, 2025]
- Machine learning-based differentiation of benign and malignant adrenal lesions using 18F-FDG PET/CT: a two-stage classification and SHAP... - November 10th, 2025 [November 10th, 2025]
- How to Better Use AI and Machine Learning in Dermatology, With Renata Block, MMS, PA-C - HCPLive - November 10th, 2025 [November 10th, 2025]
- Avoiding Catastrophe: The Importance of Privacy when Leveraging AI and Machine Learning for Disaster Management - CSIS | Center for Strategic and... - November 10th, 2025 [November 10th, 2025]
- Efferocytosis-related signatures identified via Single-cell analysis and machine learning predict TNBC outcomes and immunotherapy response - Nature - November 10th, 2025 [November 10th, 2025]
- Arc Raiders' use of AI highlights the tension and confusion over where machine learning ends and generative AI begins - PC Gamer - November 3rd, 2025 [November 3rd, 2025]
- From performance to prediction: extracting aging data from the effects of base load aging on washing machines for a machine learning model - Nature - November 3rd, 2025 [November 3rd, 2025]
- Meet 'kvcached': A Machine Learning Library to Enable Virtualized, Elastic KV Cache for LLM Serving on Shared GPUs - MarkTechPost - October 28th, 2025 [October 28th, 2025]
- Bayesian-optimized machine learning boosts actual evapotranspiration prediction in water-stressed agricultural regions of China - Nature - October 28th, 2025 [October 28th, 2025]
- Using machine learning to shed light on how well the triage systems work - News-Medical - October 28th, 2025 [October 28th, 2025]
- Our Last Hope Before The AI Bubble Detonates: Taming LLMs - Machine Learning Week US - October 28th, 2025 [October 28th, 2025]
- Using multiple machine learning algorithms to predict spinal cord injury in patients with cervical spondylosis: a multicenter study - Nature - October 28th, 2025 [October 28th, 2025]
- The diagnostic potential of proteomics and machine learning in Lyme neuroborreliosis - Nature - October 28th, 2025 [October 28th, 2025]
- Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central... - October 28th, 2025 [October 28th, 2025]
- The prognostic value of POD24 for multiple myeloma: a comprehensive analysis based on traditional statistics and machine learning - BMC Cancer - October 28th, 2025 [October 28th, 2025]
- Reducing inequalities using an unbiased machine learning approach to identify births with the highest risk of preventable neonatal deaths - Population... - October 28th, 2025 [October 28th, 2025]
- Association between SHR and mortality in critically ill patients with CVD: a retrospective analysis and machine learning approach - Diabetology &... - October 28th, 2025 [October 28th, 2025]
- AI-Powered Visual Storytelling: How Machine Learning Transforms Creative Content Production - About Chromebooks - October 28th, 2025 [October 28th, 2025]
- How beauty brand Shiseido nearly tripled revenue per user with machine learning - Performance Marketing World - October 28th, 2025 [October 28th, 2025]
- Magnite introduces machine learning-powered ad podding for streaming platforms - PPC Land - October 26th, 2025 [October 26th, 2025]
- Krafton is an AI first company and will invest 70M USD on machine learning - Female First - October 26th, 2025 [October 26th, 2025]
- Machine learning prediction of bacterial optimal growth temperature from protein domain signatures reveals thermoadaptation mechanisms - BMC Genomics - October 24th, 2025 [October 24th, 2025]
- Data Proportionality and Its Impact on Machine Learning Predictions of Ground Granulated Blast Furnace Slag Concrete Strength | Newswise - Newswise - October 24th, 2025 [October 24th, 2025]
- The Evolution of Machine Learning and Its Applications in Orthopaedics: A Bibliometric Analysis - Cureus - October 24th, 2025 [October 24th, 2025]
- Sentiment Analysis with Machine Learning Achieves 83.48% Accuracy in Predicting Consumer Behavior Trends - Quantum Zeitgeist - October 24th, 2025 [October 24th, 2025]
- Use of machine learning for risk stratification of chest pain patients in the emergency department - BMC Medical Informatics and Decision Making - October 24th, 2025 [October 24th, 2025]
- Mass spectrometry combined with machine learning identifies novel protein signatures as demonstrated with multisystem inflammatory syndrome in... - October 24th, 2025 [October 24th, 2025]
- How Machine Learning Is Shrinking to Fit the Sensor Node - All About Circuits - October 24th, 2025 [October 24th, 2025]
- Machine learning models for mechanical properties prediction of basalt fiber-reinforced concrete incorporating graphical user interface - Nature - October 24th, 2025 [October 24th, 2025]
- Ohio wins national cybersecurity award for fraud solutions using machine learning - Spectrum News NY1 - October 24th, 2025 [October 24th, 2025]
- Itron Partners with Gordian Technologies to Enhance Grid Edge Intelligence with AI and Machine Learning Solutions - Quiver Quantitative - October 24th, 2025 [October 24th, 2025]
- Wearable sensors and machine learning give leg up on better running data - Medical Xpress - October 23rd, 2025 [October 23rd, 2025]
- Geophysical-machine learning tool developed for continuous subsurface geomaterials characterization - Phys.org - October 23rd, 2025 [October 23rd, 2025]
- Ohio wins national cybersecurity award for fraud solutions using machine learning - Spectrum News 1 - October 23rd, 2025 [October 23rd, 2025]
- Machine learning predictions of climate change effects on nearly threatened bird species ( Crithagra xantholaema) habitat in Ethiopia for conservation... - October 23rd, 2025 [October 23rd, 2025]
- A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region - Nature - October 23rd, 2025 [October 23rd, 2025]
- ECBs New Perspective on Machine Learning in Banking - KPMG - October 23rd, 2025 [October 23rd, 2025]
- Ensemble Machine Learning for Digital Mapping of Soil pH and Electrical Conductivity in the Andean Agroecosystem of Peru - Frontiers - October 21st, 2025 [October 21st, 2025]
- New UA research develops machine learning to address needs of children with autism - AZPM News - October 21st, 2025 [October 21st, 2025]
- NMDSI Speaker Series on Weather Forecasting: What Machine Learning Can and Can't Do, Oct. 23 - Marquette Today - October 21st, 2025 [October 21st, 2025]
- Polyskill Achieves 1.7x Improved Skill Reuse and 9.4% Higher Success Rates through Polymorphic Abstraction in Machine Learning - Quantum Zeitgeist - October 21st, 2025 [October 21st, 2025]
- University of Strathclyde opens admission for MSc in Machine & Deep Learning for Jan 2026 intake - The Indian Express - October 21st, 2025 [October 21st, 2025]
- Reducing Model Biases with Machine Learning Corrections Derived from Ocean Data Assimilation Increments - ESS Open Archive - October 19th, 2025 [October 19th, 2025]
- Unlocking Obesity: Multi-Omics and Machine Learning Insights - Bioengineer.org - October 19th, 2025 [October 19th, 2025]
- Lockheed Martin advances PAC-3 MSE interceptor using artificial intelligence and machine learning - Defence Industry Europe - October 19th, 2025 [October 19th, 2025]
- Semi-automated surveillance of surgical site infections using machine learning and rule-based classification models - Nature - October 19th, 2025 [October 19th, 2025]
- AI and Machine Learning - City of San Jos to release RFP for generative AI platform - Smart Cities World - October 19th, 2025 [October 19th, 2025]
- Machine learning helps identify 'thermal switch' for next-generation nanomaterials - Phys.org - October 17th, 2025 [October 17th, 2025]
- Machine Learning Makes Wildlife Data Analysis Less of a Trek - Maryland.gov - October 17th, 2025 [October 17th, 2025]
- An interpretable multimodal machine learning model for predicting malignancy of thyroid nodules in low-resource scenarios - BMC Endocrine Disorders - October 17th, 2025 [October 17th, 2025]
- In First-Episode Psychosis Patients, Machine Learning Predicted Illness Trajectories to Potentially Improve Outcomes - Brain and Behavior Research - October 17th, 2025 [October 17th, 2025]
- Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes - The American Journal of Managed Care (AJMC) - October 17th, 2025 [October 17th, 2025]