Ortent Life Sciences Radar research beta

Revolutionizing drug R&D with Lab-in-a-Loop Aviv Regev, Head of Genentech Research and Early Development (gRED)

Our ‘R&D Excellence’ initiative, launched two years ago to accelerate our research and development, is showing strong progress.

Evolve our R&D engine and invest in its excellence Ongoing R&D investments Boston Innovation Center focusing on CVRM and AI in drug development opened

Pathobiology maps have scaled and accelerated our pipeline Example: IBD pathobiology maps

BRAID (biology AI) PrescientDesign1 (antibodies AI) gRED Computational Sciences (gCS) consolidated ... Recursion collaboration1 ... NVIDIA partnership OpenAI pilot partnership1 AI factory (NVIDIA)

AI-enhanced pathobiology maps across our TAs ... +155% First map deployed (IBD) 4 neurology maps deployed increase in LI entries in 2 years

We pursued breakthrough discoveries on three fronts. ... Partnerships were forged to deploy AI to help decode biology, with the potential to accelerate the discovery of new treatments

today announced it is building the most powerful supercomputer owned and operated by a pharmaceutical company, in collaboration with NVIDIA

The supercomputer is the world's first NVIDIA DGX SuperPOD with DGX B300 systems. It is powered by more than 1,000 B300 GPUs on a unified networking fabric

Launched a platform, giving biotechnology companies access to artificial intelligence (AI)-enabled drug discovery models.

Lilly TuneLab, which together support biotech innovation by providing access to strategic capital, lab space and technology, and research and development capabilities including advanced AI models.

Lilly TuneLab, an AI and machine learning platform, provides biotech companies with access to select Lilly models for drug discovery built on decades of Lilly's proprietary data.

Key research & development enablers ... End-to-end AI ... and data science

Significant changes in our R&D set-up ... and AI capabilities to deliver at quality ... and pace

External innovation is a key enabler to expand the pipeline and strengthen competencies in AI ... Partnering with leading AI providers

AI is leveraged to improve speed, success and productivity across the research & development value chain Select achievements in 2026

Pre-clinical asset identified with key outputs ... Combine human-designed sequences with ML-assisted design in an ... active-learning loop

Novo Nordisk and AWS have created a co-innovation hub in London ... to compress the path from drug target to first human dose ... a dedicated co-innovation hub within our existing facility in London

we are investing significantly in transformative technologies that will shape the future of medicine ... This includes harnessing the power of AI where, for example, 90% of our small molecule discovery pipeline is already AI-assisted

Our $2.5 billion investment expands early discovery and development and incorporates an AI and data science laboratory.

In R&D, we are developing an ecosystem of foundation models and AI agentic frameworks to accelerate our drug discovery

Over 90% of our small molecule discovery pipeline is AI-enabled, with similar approaches actively applied to other areas, including biologics.

>90% of our small molecule discovery pipeline is enabled by AI

Delivered industry-leading genomic insights while remaining sustainable, redesigning algorithms that cut CO2 emissions and compute time by 99.8% compared to global standards.

Our focus on innovation includes leveraging data and integrating AI across the business to become a more efficient organization and accelerate the delivery of medicines to patients.

all of our small molecule experiments and half of our large molecule experiments are now using an AI model to predict probability of success

today announced it will expand its compute infrastructure to deploy an NVIDIA DGX SuperPOD with DGX Vera Rubin NVL72 systems

builds on nearly three years of collaboration that began when BMS first deployed NVIDIA DGX SuperPOD infrastructure to support its Research and Development activities

all of our small molecule experiments and half of our large molecule experiments are now using an AI model to predict probability of success

AI informs the design of every small molecule program and the majority of the company’s large molecule programs

Identify next BGTs by 2030 ... 当社は、2030年までに次世代のBGTsを特定することを重要な戦略目標として位置づけております。 ... 国内外の研究拠点の拡充やAI・データ駆動型創薬の推進

Expanding Drug Discovery Research Capabilities: ... Expanding and strategizing AI-driven drug discovery into multi-modality research ... AI-driven molecular design

Smart Lab: Enabling Competitive AI-driven Drug Discovery ... Seamless data feedback to molecular design AI ... Smart Lab is the cornerstone of AI-driven drug design success.

OpenFold-3をはじめとする最先端のAIモデルを社内環境に導入し、研究者が利用できるアプリケーションとしてクラウド環境上で提供しています。

大規模言語モデルによるヒト遺伝子データの分析 複雑で膨大な遺伝子情報を高性能Graphics Processing Unit（GPU）で処理し

AIエージェントをバイオインフォマティクス業務に導入し、生命科学データの探索・解析を効率化・高度化しています。実際のデータ解析業務を通じてその有用性を検証し

We aim to complete sequencing of 10 million samples and integrate AI and big data tools to improve drug discovery and digital health solutions by 2030.

through the Regeneron Genetics Center ... we’re committing to sequencing 10 million samples and integrating artificial intelligence (AI) and big data tools to advance drug discovery

SCIENCE-LED 2030 GOALS WILL HOLD US ACCOUNTABLE ... Completing sequencing of 10M samples and integrating AI and big data tools to improve drug discovery

We use innovative technologies, such as machine learning, to sequence exomes, align with health information and perform large-scale analyses to make meaningful associations between genes and diseases.

Our lab technicians, data scientists and bioinformaticians collect and analyze large amounts of data using cloud technology to simultaneously look at genes, proteins, health records and more.

RGC leverages organoid models, siRNA, and CRISPR knockout models to validate genetic associations that lead to new therapeutic targets. ... These efforts at RGC have led to the identification of more than 40 novel genetic targets.

A key partnership is our participation in Tokyo-1 ... This initiative utilizes the Tokyo-1 GPU supercomputer to accelerate our research in molecular simulation and AI-based molecular design

in drug discovery research, we aim to accelerate the development of biopharmaceuticals and improve productivity, not only through NVIDIA's AI-powered supercomputing for small molecule drug design that has already been implemented

Strategic investments in AI will help us improve speed, quality and ... decision-making across R&D ... Research ... Human-in-the-Loop platform, an AI ... and robotics integrated system to optimize drug candidates ... NVIDIA-powered supercomputing to ... dramatically accelerate early-stage ... drug discovery

It also includes automated synthesis and assay systems using robots, and tools ... for automatically creating structure-activity relationship (SAR) tables ... The platform also ... incorporates the ability to remotely monitor the operation of the robots

Astellas has been ahead of the curve, integrating AI into its drug development processes since 2019. The company's innovative "Human-in-the-Loop" platform is central to this effort

in drug discovery research, we aim to accelerate the development of biopharmaceuticals and improve productivity, not only through NVIDIA's AI-powered supercomputing for small molecule drug design that has already been implemented

3) Accelerate efficiency ... AI and data science are already supporting our teams in areas such as accelerating drug discovery

organized around four key priorities: 1) focus on growth; 2) lead with innovation; 3) accelerate efficiency; and 4) reinvent how we work

We are an R&D driven, AI-powered biopharma company committed to improving people’s lives and creating compelling growth.

Digital ... In R&D: ... 90% targets in the pipeline now being credentialed using our data and AI systems

100% small and large molecule drug design efforts now supported by AI/ML methods, doubling molecular throughput of research teams

our Target Discovery engines have delivered seven novel drug targets in just one year

Putting AI at the Heart of Drug Discovery ... Amgen is working toward using artificial intelligence and machine learning to shorten that timeline and raise the odds of success.

making the following changes effective June 1, 2026 ... will serve as executive vice president, Research and Development, Artificial Intelligence and Data.

highlights the company's continued investment in scientific research, artificial intelligence in drug discovery, and advanced manufacturing.

Amgen has developed an integrated ... generative loop, where AI and automation continuously refine each other.

Amgen's AI platforms help identify genetically validated targets, generate novel proteins and predict how drug candidates will perform before they reach the lab.

Head's team applies protein and chemistry language models and other AI-enabled design approaches to drug discovery

"Our ambition is to leverage AI to increase R&D productivity by 40 percent by 2030," said Sai Jasti, Senior Vice President, Head of Data Science & Artificial Intelligence, Bayer Pharmaceuticals R&D.

By integrating AI platform architecture with anonymized ... data, our data scientists are empowered to maximize our in-house biologics portfolio, validate AI models, and scale solutions, thereby ultimately speeding up drug discovery.

Through this acquisition, Bayer subsidiary Vividion Therapeutics Inc. is expanding its capabilities in terms of proprietary methods for computer-based genomic screening. ... Bayer paid an upfront consideration of around €19 million to acquire Tavros.

Combining the Tavros platform with Vividion’s chemoproteomics expertise and capabilities continues to greatly enhance Vividion’s efforts to generate potential best- and first-in-class drug targets across oncology and immunology.

Following a successful proof of concept, Bayer selected Cradle as its best suited partner from among several vendors.

entered a three-year strategic collaboration to deploy Cradle's scientific AI software platform for protein engineering ... Bayer will integrate the generative AI platform into existing R&D workflows to enhance lead generation and optimization across its therapeutic antibody pipeline.

At every step of the R&D process, we are using data tech, including AI, and platform technologies to be faster, more effective and more predictive in discovering and developing innovative medicines and vaccines.

Our AI-powered, end-to-end oligonucleotide platform, 'Oligopolis', which incorporates the Elsie platform we acquired in 2024, is redefining research in chemistry and biology. The platform automates cycles of design, synthesis and testing

GSK announced that it had acquired Elsie Biotechnologies, a San Diego-based private biotechnology company dedicated to unlocking the full potential of oligonucleotide therapeutics, for a total consideration of up to US$51 million

Our digital chemistry platform uses AI/machine learning (ML) and automation to accelerate design-build-test cycles in small-molecule discovery.

Our AI-powered, end-to-end oligonucleotide platform, 'Oligopolis', which incorporates the Elsie platform we acquired in 2024, is redefining research in chemistry and biology. The platform automates cycles of design, synthesis and testing

GSK uses these AI methods to compare expression data from healthy lung tissue with samples from COPD patients

we also use it internally in our Healthcare business sector in early stages of drug discovery. Our AI in drug discovery program will accelerate the discovery of new and better drug candidates

successfully launch a state-of-the-art high-performance computer in Munich, Germany, designed to accelerate innovation across the three business sectors ... streamline drug discovery processes in its Healthcare business sector

RDKit helps our research and development scientists within our Healthcare business sector ... said Arvind Rajpal, Head of Discovery & Development Technologies at Research and Development within the Healthcare business sector of Merck KGaA, Darmstadt, Germany

AIDDISON™, our generative AI-powered active ingredient discovery platform. In addition to external commercialization, we also use it internally in our Healthcare business sector in early stages of drug discovery.

Predictive Modeling Platform , a tool for AI-driven design of drug-like molecules for the Healthcare business sector, recently recognized with an in-house award

RDKit helps our research and development scientists within our Healthcare business sector turn chemical data into AI-ready representations and actionable insights for faster, better-informed molecular design.

says Justin Scheer, Vice President, In Silico Discovery, Innovative Medicine R&D, Johnson & Johnson ... Using our highly sophisticated AI, built on in-house data, we aim to accelerate the delivery of medicines

Once promising disease targets are identified, Johnson & Johnson is then leveraging AI to help discover molecules that could interact with the target.

By combining data, AI and machine learning (ML), and advanced computing with our scientific expertise, Johnson & Johnson is setting a new pace for discovering life-changing treatments for patients in need.

Johnson & Johnson is then leveraging AI to help discover molecules that could interact with the target. ... The company is doing this through its own state-of-the-art technologies, as well as in partnership with external collaborators.

So in molecular design in discovery, it's shortening the time from hit to lead. So we can do things faster.

So we have a number of examples of oral medicines that we are getting into humans much faster than we were able to do pre utilizing AI. ... we are clearly using it, and it's already ongoing.

The collaboration builds on Merck's broader investments in AI/ML-enabled discovery, spanning computational or spatial biology, AI foundation models and real-world data

Merck's ambition to harness AI-enabled virtual cell technologies to enhance disease understanding, improve target identification and drive early development decisions

We also use data science, AI, and machine learning ... (ML) to help overcome bottlenecks in discovery, research, and development.

KERMT isn't just helping our researchers; as an open-source model, its code is available to the whole scientific community.

We recently developed two foundation models which uncover patterns in disease to find better drug targets, allow faster molecular design and rapidly test small molecules

Developed in collaboration with Nvidia, KERMT, pronounced "Kermit" and short for Kinetic GROVER Multi-Task, is a deep-learning computer model trained on more than 11 million molecules.

Power innovation through our Scientific Intelligence Engine Harness data, AI/ML, automation, and robotics to accelerate discovery and continuously improve how we work

Our AI strategy turns platform data and biological insight into faster innovation

Across Moderna, we are building what we call our Scientific Intelligence Engine—a system that combines data, AI and machine learning, automation, and robotics to accelerate discovery and improve how we work.

At the research stage, our digital and AI infrastructure allows our scientists to design novel mRNA constructs, use AI algorithms to optimize them and order them from our high throughput preclinical scale production line.

Lucy is at the heart of Moderna's scientific intelligence engine. Lucy connects everything that we've built in AI, automation, experimentation, and data into a continuously improving learning system.

We do have an ongoing program to try and improve this algorithm. In fact, we're using artificial intelligence to try to develop the next algorithm.

UCB has acquired the Patient Insight Business of IMIDomics ... which applies advanced biostatistics, machine learning, and AI to uncover new therapeutic targets, responder biomarkers

Patient Insight Business enhances UCB’s ability to identify novel drug targets, discover responder biomarkers, and design molecularly informed patient stratification approaches

On 1 May 2026, the Group acquired the Patient Insight Business of IMIDomics. The acquisition provides UCB with direct access to one of the most advanced, deeply curated human datasets in immunology

Our collaborations with Schrödinger are also integrating advanced modeling and computational design, to accelerate discovery and enhance data quality across key R&D pillars such as multi-specific medicines and digital antibody engineering.

On 1 May 2026, the Group acquired the Patient Insight Business of IMIDomics. The acquisition provides UCB with direct access to one of the most advanced, deeply curated human datasets in immunology

In January 2025, UCB entered into a license agreement on XtalFold™, a biologics AI platform developed by Ailux Biologics, a division of XtalPi. UCB will leverage XtalFold™ for the discovery and engineering of biologics.

Anticipated £150M investment over 10 years as part of Boehringer's commitments in AI across R&D, with the first 50 AI experts in place by end of 2027

Computational science is central to our innovation strategy.

Computational Innovation identifies and builds confidence in new therapeutic concepts and increases the likelihood of success across our portfolio.

Boehringer Ingelheim today announced the expansion of its global Computational Innovation footprint with the launch of a new center for AI and machine learning in King's Cross, London, UK

Computational Innovation now has locations in Austria, Germany, UK and USA specializing in AI, machine learning, human genetics, and computational biology.

Molecule design: Leveraging AI to help create high-quality molecules faster.

Through our areas of innovation, which include data convergence, artificial intelligence (AI), genetic medicine and genomics, patient-focused disease medicine and therapeutic modalities, we are leveraging powerful tools in order to accelerate discovery

AI: We are integrating AI into our R&D processes to support improved drug discovery and development. We use AI to extract knowledge from data across our entire pipeline, from enabling more efficient molecule property prediction

Under the terms of the collaboration, Iambic will receive an upfront payment and is eligible to receive success-based milestone payments and tiered royalties on net sales from products generated from the collaboration.

today announced a multi-year collaboration to accelerate the discovery and development of small molecule therapies with first-in-class and best-in-class potential across immunology, neuroscience and oncology

Under the terms of the collaboration, Iambic will receive an upfront payment and is eligible to receive success-based milestone payments and tiered royalties on net sales from products generated from the collaboration.

AI: We are integrating AI into our R&D processes to support improved drug discovery and development. We use AI to extract knowledge from data across our entire pipeline, from enabling more efficient molecule property prediction

Our Novartis R&D leaders, Fiona Marshall ... have defined a clear strategy for how these technological advances should be integrated from end-to-end, across the R&D continuum.

Scaling AI across the value chain to unlock productivity and performance ... Target Discovery Engine ... Small molecule GenChem and optimization

This is playing out in focused initiatives across Novartis R&D: Target identification and validation: AI models can integrate evidence from human genetic and multi-omic datasets

Reviewed AI use case on “New Target Identification”, “Driving Translation through Data Science and AI”, “Present and Future of AI Augmented Chemistry”, and “AI/ML in Biologics”

These efforts are shifting how teams work so they’re spending less time sifting through data and more time on creative iteration and decision-making.

Our 2026 key priorities are: ... Scale AI across our business.

In addition, we are scaling AI across R&D, manufacturing, commercial and patient engagement to improve productivity and accelerate innovation.

Build an end-to-end AI-native R&D organization

To meet the growing AI demand, over the next two years, we are expanding to more than 1,200 GPUs, largely driven by R&D application of AI.

We are embedding AI into each functional line in R&D.

It's going to be by deploying AI, which already happened in 2025 with excellent results that creates significant productivity gains. This is where we are reducing the cost of R&D.

We seek to achieve a foundational shift that embeds AI into every stage of drug discovery, redesigning workflows to include automated, data-driven, predictive processes that accelerate innovation.

By using advanced models to predict how molecules will behave, we can identify high-quality candidates earlier and rapidly optimize their design.

Through bold investments in digital, data and AI-driven capabilities, our teams are delivering for patients at speed and scale.

Iambic Therapeutics U.S. Cross-therapeutic area discovery research alliance to leverage Iambic’s computational-driven discovery engine

By using advanced models to predict how molecules will behave, we can identify high-quality candidates earlier and rapidly optimize their design.

Gilead will build and maintain leadership capabilities to govern AI responsibly while applying these powerful new tools to support drug discovery, improve the employee experience and expedite responsible business reporting efforts.

Brings Together Oncology, Inflammation and Research Data Science Teams to Foster Scientific Collaboration

Adopt and Scale AI to Transform How We Work

today celebrated the opening of its 182,000-square-foot Research Center at its Foster City headquarters, expanding capabilities in oncology, inflammation and research data science

By co-locating key research disciplines and expanding our data science capabilities, we are strengthening the infrastructure needed to accelerate discovery and advance meaningful innovations.

Expanding Drug Discovery Research Capabilities: Creation of BGTs through the integration of expanded research functions, digital transformation (DX) of drug discovery research, and open innovation

Opening of Smart Research Lab San Diego ... Building AWS infrastructure and data utilization systems ... Completion of new research building (Smart Lab)

Launched Smart Research Lab in San Diego to Accelerate Innovation ... Integrated robotic automation for end-to-end workflows ... DS’s first dedicated drug discovery base in the U.S.

実験装置にAIを組み込み、これまで人が目視で行っていた液体の量の測定や ... リアルタイムで自動的に行えるようになりました。これにより、実験操作の一部が自動化され、作業の正確性と効率が向上しています。

研究者が設計した多様な実験工程をロボットで実行します。 ... 「メタデータ」を取得し、実験結果とともにデータプロダクトとして標準化して保存します。実験結果を電子ノートへまとめる仕組みも整備しています。

At the SRL, advanced robotics and in-house developed, sophisticated software is being utilized to significantly enhance the efficiency of drug discovery research

Integrating Genetics, Proteomics, and Big Data ... World’s largest DNA and proteomics-linked healthcare database, enabling advanced drug discovery, development, and healthcare analytics

Integrating Genetics, Proteomics, and Big Data ... World's largest DNA and proteomics-linked healthcare database, enabling advanced drug discovery, development, and healthcare analytics

over the last decade, we have made enormous investments to build the world's largest collection of "big data" in which de-identified electronic health records ("EHRs") are linked to molecular data (DNA sequence and proteomics data).

RGC utilizes laboratory automation and innovative approaches to cloud computing to achieve high-quality throughput, attaining over 3 million samples sequenced to date.

we partnered with DNAnexus to provide infrastructure ... today, it underpins everything from large-scale sequencing projects to trusted research environments used by global collaborations

We are also introducing more automation to improve coverage uniformity, and re-engineer bioinformatics workflows so sequencing data can be analyzed even faster.

Marti Head, Associate Vice President, Automation, Research Data Systems, Informatics, and AI

$125M investment expands Amgen's South San Francisco research hub ... Integrated labs bring medicinal chemistry, biology, protein sciences, automation, and data science together to accelerate discovery

the labs are purpose-built to support more than 100 scientists and equipped with advanced technologies ... from high-throughput automation and robotics to state-of-the-art analytical tools

the labs are purpose-built to support more than 100 scientists and equipped with advanced technologies ... from high-throughput automation and robotics to state-of-the-art analytical tools

AI designs proteins with desired properties. Robots make and test them at scale. Results feed back into the AI model, improving its predictions.

High-throughput automation further minimizes bottlenecks, scales operations efficiently and helps Amgen bring more potential therapeutics forward faster.

A key initiative at Astellas is to enhance our global data infrastructure and governance to enable further AI adoption

by actively promoting the use of data, including the proactive utilization of real-world data, integration of R&D database, and AI-driven simulation and modeling, we are working to speed up

but also by introducing AI-enabled protein station for research automation

It also includes automated synthesis and assay systems using robots, and tools ... for automatically creating structure-activity relationship (SAR) tables ... The platform also ... incorporates the ability to remotely monitor the operation of the robots

we are building and enhancing ... dedicated in-house databases for each modality. Furthermore, the deployment ... of robotic technology to our overseas and joint research facilities is progressing, ... creating a global network to collect more uniform, high-quality data

but also by introducing AI-enabled protein station for research automation

The R&D centre includes ten floors of interconnecting laboratories to allow a flow of seamless science enabled by cutting-edge technologies that integrate robotics, continuous automation, and agentic AI.

AstraZeneca today announced the opening of its newest global strategic research and development (R&D) centre, in Kendall Square

ten floors of interconnecting laboratories to allow a flow of seamless science enabled by cutting-edge technologies that integrate robotics, continuous automation, and agentic AI

AstraZeneca today announced the opening of its newest global strategic research and development (R&D) centre, in Kendall Square

The R&D centre includes ten floors of interconnecting laboratories to allow a flow of seamless science enabled by cutting-edge technologies that integrate robotics, continuous automation, and agentic AI.

$171m expense within Research and development expense in relation to severance as well as the transformation of clinical, regulatory and other R&D data and systems.

In 2025, we accelerated and expanded the deployment of advanced data and platform technologies end-to-end in R&D.

by integrating advanced computational protein modelling with an end-to-end automated lab-in-the-loop platform. This closes the design-build-test cycle so we can reliably deliver therapeutic large molecules, faster.

our AI/ML-powered lab-in-the-loop automated systems, which scale experimentation and reduce resource duplication, are redefining how we optimise therapies in HIV and immunology.

by integrating advanced computational protein modelling with an end-to-end automated lab-in-the-loop platform. This closes the design-build-test cycle so we can reliably deliver therapeutic large molecules, faster.

our AI/ML-powered lab-in-the-loop automated systems, which scale experimentation and reduce resource duplication, are redefining how we optimise therapies in HIV and immunology.

In 2025, we accelerated and expanded the deployment of advanced data and platform technologies end-to-end in R&D.

Power innovation through our Scientific Intelligence Engine Harness data, AI/ML, automation, and robotics to accelerate discovery and continuously improve how we work

Learning at scale requires a fundamentally different experimentation and data infrastructure

This really requires fundamentally changing the way that we do experimentation and also the data infrastructure that is required to take the data in and make it usable for all of our modern AI tools.

High-throughput automation and custom engineered equipment allow us to produce and deliver high quality mRNA and formulated constructs ... our proprietary platform is capable of producing up to 1,000 lots of mRNA sequences and formulations per month

a series of in vitro based assays and that is what we do within a closed-loop platform ... We've built platforms that allow us to do in vivo multiplex screening in mice and in nonhuman primates.

This has been possible, in part, due to the ability of researchers in the Moderna ecosystem to order constructs through an integrated digital portal that tracks materials end-to-end in less than 45 days.

As Chief Data and Digital Officer, I’m driven by the idea that data science and AI can help us understand disease

That question led me to develop what became Data42 within Biomedical Research

Today, I’m proud to say that Data42 underpins our growing ecosystem of AI-driven research. By connecting clinical, molecular, preclinical and biology data, it enables us to tackle scientific questions across domains

R&D Excellence: Our solutions Moving from implementation to “business as usual” ... Build a simplified system landscape and data foundation

Our ‘R&D Excellence’ initiative, launched two years ago to accelerate our research and development, is showing strong progress.

Towards autonomous labs for drug R&D Our Autonomous Lab Accelerator to enhance the loop

Medra's platform integrates with Genentech’s internal ML infrastructure and its laboratory information management system

Medra physical AI, MHS (Anthropic1) Autonomous Lab Accelerator

Build a simplified system landscape and data foundation Implemented and moving into business as usual Implementation in progress

We have been setting the foundation with AI-ready data, agentic workflows and compute capacity.

Pfizer has a vast repository of small and large molecule, translational and clinical data and AI is creating the opportunity to unlock insights

Progress with making petabytes of data AI ready

The collaboration will initially focus on creating a continuous learning system that tightly connects Lilly's agentic wet labs with computational dry labs, enabling 24/7 AI-assisted experimentation to support biologists and chemists.

NVIDIA and Lilly will pioneer robotics and physical AI to accelerate and scale medicine discovery and production.

allowing them to work side by side to generate large-scale data and build powerful AI models that can accelerate medicine development

The collaboration will initially focus on creating a continuous learning system that tightly connects Lilly's agentic wet labs with computational dry labs, enabling 24/7 AI-assisted experimentation to support biologists and chemists.

The two companies will invest up to $1 billion in talent, infrastructure and compute over five years to support the new AI co-innovation lab.

The two companies will invest up to $1 billion in talent, infrastructure and compute over five years to support the new AI co-innovation lab.

Through our areas of innovation, which include data convergence, artificial intelligence (AI), genetic medicine and genomics, patient-focused disease medicine and therapeutic modalities, we are leveraging powerful tools in order to accelerate discovery

Data convergence: We have integrated data across our areas of expertise through technology into a unified knowledge platform, improving how we collect, analyze and apply data to generate insights faster

Data convergence: We have integrated data across our areas of expertise through technology into a unified knowledge platform, improving how we collect, analyze and apply data to generate insights faster

We are centralizing and connecting data from more than 170 internal and external sources, enabling us to more quickly generate comprehensive insights to inform R&D.

We are continuing to build our automated design-make-test-analyze platform powered by lab automation and AIDDISON

We are continuing to build our automated design-make-test-analyze platform powered by lab automation and AIDDISON

For Mr. Meyers, in the role of Chief Digital & Technology Officer, the Committee considered his: (i) leadership in driving transformation and innovation at scale across the business, and in simplifying and strengthening scientific and digital foundations

Connecting Claude to the institutional knowledge that lives across BMS. Through secure integrations with the systems and repositories where BMS' scientific, clinical, regulatory, and commercial expertise resides

today announced a strategic agreement with Anthropic to deploy Claude across the company's research, clinical development, manufacturing, commercial, and corporate functions

today announced a strategic agreement with Anthropic to deploy Claude across the company's research, clinical development, manufacturing, commercial, and corporate functions

Connecting Claude to the institutional knowledge that lives across BMS. Through secure integrations with the systems and repositories where BMS' scientific, clinical, regulatory, and commercial expertise resides

This includes using services such as Amazon Bio Discovery and Amazon Bedrock to identify drug targets, design new therapies faster, and connect genomic, imaging and clinical data

Research activities further utilise digital scientific methodologies and other technology platforms

Faster, standardised ... execution ... Simplifying and automating core ... processes

Agreement establishes AWS as Novo Nordisk's preferred cloud provider and strategic AI partner to accelerate drug discovery and modernise its technology infrastructure

This includes using services such as Amazon Bio Discovery and Amazon Bedrock to identify drug targets, design new therapies faster, and connect genomic, imaging and clinical data

Research activities further utilise digital scientific methodologies and other technology platforms

embedding computational biology, artificial intelligence (AI), and data excellence into every step of our innovation pipeline

On-demand automation of multimodal, analysis-ready datasets across genomics, imaging, and clinical data.

embedding computational biology, artificial intelligence (AI), and data excellence into every step of our innovation pipeline

This includes deploying Gemini Enterprise across end-to-end R&D workflows

This multi-year investment, valued at up to $1 billion, will deploy an agentic platform across Merck's research & development (R&D), manufacturing, commercial, and corporate functions

This includes deploying Gemini Enterprise across end-to-end R&D workflows

focus on the systematic implementation of digital technologies and the deployment of data sciences to increase the speed, reliability and effectiveness of our R&D processes.

focus on the systematic implementation of digital technologies and the deployment of data sciences to increase the speed, reliability and effectiveness of our R&D processes.

Dr. Reed: ... Executive Vice President, Innovative Medicine R&D ... Deepened investment in data science and digital health to accelerate discovery and development across the portfolio.