Use cases — stage 02
Build
Named examples from the foundation-model labs and platforms pharma teams use to actually construct, train and generate the model or application.
259 stories across 49 vendors
AWS47
- 01Sanofi Accelerates Drug Discovery with AI on AWS
- 02Key Takeaways from Gilead's Innovation Talk at re:Invent 2023
- 03AWS Life Sciences Symposium 2025 | Development Assistants at AstraZeneca
- 04Cloud-based genomics-sequencing data processing at scale
- 05Roche Accelerates Personalized Healthcare R&D While Reducing Costs Using AWS HealthOmics
- 06AWS re:Invent 2023 - Customer Keynote Pfizer
- 07AWS Founder Spotlight: Noetik
- 08Mapping Earth's DNA | AWS Pioneers Project
- 09Delivering innovative health with generative AI solutions at Merck
- 10AWS Life Sciences Symposium 2025 Keynote - Merck | clinical data layer on AWS | AWS Events
- 11Merck Improves Speed and Reduces Manual Effort to Assess Change Proposals Up to 70% on AWS
- 12Novo Nordisk's AI Revolution: Anthropic, MongoDB & AWS in Pharma
- 13ICF helps FDA accelerate the drug labeling review process with AWS machine learning
- 14Baxter Improves Operational Efficiency with Predictive Maintenance Using Amazon Monitron
- 15Amazon Pharmacy Increases Forecast Accuracy and Reduces Manual Efforts Using AWS Supply Chain
- 16Reduces GxP compliance validation time from weeks to minutes
- 17Amazon Pharmacy now provides home delivery of select diabetes, obesity, and migraine medications to LillyDirect patients
- 18Alnylam Transforms Product Complaint Management with Generative AI Using Amazon Bedrock
- 19Alcon modernizes its application with easily scalable and secure AWS Lambda
- 20Drives commercial innovation using Amazon Connect and AI
- 21Used AWS compute to initiate clinical trials for 7 drugs (9 more in pipeline
- 22Uses SageMaker to match patients to relevant content across 1.5B+ member-written words
- 23Built Thermo Fisher Cloud to help scientists store/analyze/share data globally
- 24Uses AWS tools to accelerate scientist productivity and lab operations
- 25Runs 90% of computing on AWS (WorkSpaces, Lambda
- 26Scales DNA sequencing globally, cuts costs 100x
- 27Intensive clinical-trial simulations with 98% time savings
- 28Accelerates cancer-research processes to develop therapeutics
- 29Analyzes billions of compounds in one day; compute costs down 50%
- 30Reduced drug-discovery calculation time more than 10x
- 31Built a HIPAA-compliant genomic analysis platform
- 32Enables secure collaboration between researchers and academic labs
- 33Processes whole genomes in minutes to accelerate diagnosis
- 34Saves $800,000/year in drug-discovery compute costs
- 35Manages a pandemic-influenza catalog with 18M simulations
- 36Analyzes 1,150% more reproductive-genetics samples on demand
- 37Processed 800 Alzheimer's genomes in 60 minutes vs. two weeks
- 38Complex genetics analysis at 40% cost savings
- 39Renders cardiac models in 10 minutes vs. a 90-minute industry standard
- 40Scales genome annotation in parallel while managing cost
- 41Potentially cuts genomics research time 50% with AWS Batch
- 42Ran an 80,000+ vCPU job, finishing a workload 33% ahead of schedule
- 43Analyzed 30-40TB of genetic-diversity data in days
- 44Accelerates drug development, saves researchers hundreds of thousands of hours
- 45Screened billions of molecules in under 24 hours for oncology therapeutics
- 46Grew its bioinformatics platform 160% in 18 months, cut costs 87%
- 47Insilico Achieves 99% Cost Savings in Drug Candidate Discovery Using AWS
Anthropic30
- 01League cuts product development cycle times in half with Claude
- 02DXC brings Claude to the insurance backbone running billions of policies
- 03Integrates Claude into its internal "Concierge" app for enterprise-wide efficiency across the value chain.
- 04Connector linking Claude responses back to experimental data, notebooks and records.
- 05Collaborates with Manifold on Terra to build AI agents for scientists.
- 06Connector enabling single-cell/spatial analysis via natural-language conversation with Claude.
- 07Uses Claude to streamline drug-to-market processes and produce GxP-compliant outputs from clinical data.
- 08Builds transparent, auditable healthcare-analytics solutions for regulated environments with Claude.
- 09Uses Claude for document/content automation in pharma development (see also dedicated case study below).
- 10Building "Paper2Agent," turning research papers into interactive AI agents ("virtual corresponding authors").
- 11Pairs life-sciences sector expertise with Claude to reimagine clinical, regulatory and commercial operations.
- 12Uses Claude Code to accelerate software development "up to 10x faster in some cases."
- 13Built a bioinformatics AI agent on Claude for research workflows.
- 14Uses Claude to model biological data and advance life-science discovery.
- 15Builds AI agents translating scientific questions into technical execution across specialized datasets.
- 16Uses Claude for bioinformatics and literature-analysis workflows.
- 17Uses Claude Code and Claude agents with MCP servers to predict drug toxicity.
- 18Novo Nordisk accelerates clinical documentation and drug development with Claude
- 19Banner Health battles physician burnout with Claude-powered AI platform
- 20Qualified Health and the University of Texas System use Claude to identify patients who need life-saving care
- 21Elation Health delivers faster clinical insights with Claude
- 22Carta Healthcare cuts clinical data processing time by 66% with Claude
- 23Computational-biology firm using Claude Opus 4.5 for coding and scientific figure analysis.
- 24Medical AI company citing Claude's reasoning and safety design.
- 25Oncology real-world-evidence company; researchers now converse directly with datasets via Claude.
- 26Life-sciences software platform combining Veeva's applications/data with Claude for industry-specific agentic AI.
- 27Converts clinical processes into compliant AI agents with Claude.
- 28Healthcare performance-improvement network (4,400+ organizations) using Claude for workflow automation.
- 29Ambient clinical-documentation automation built on Claude.
- 30Healthcare AI startup using Claude for clinical data extraction/QA.
IQVIA27
- 01Integrated PV Tech and Services Solution - Case Study
- 02Overcoming the Challenges of Managing Regulatory Information
- 03Vigilance Detect Case Study Brochure
- 04Complex Workflow and Data Collection through IQVIA Research Management Platform
- 05Integrated Search Content Strategy
- 06Advanced Patient Finding & Disease Modeling
- 07Closing Data Gaps
- 08Client Case Study: Revealing the Treatment Landscape and Patient Pathways in a new Market
- 09Building a Compliance Program from the Ground Up
- 10Healthcare Insights Through AI and Machine Learning
- 11AI Case Study – How IQVIA Increased Target Patient Identification 15X
- 12Improving Patient Profiling and Physician Targeting
- 13Case Study Download: Respiratory Treatment Research
- 14Meeting Global Transparency Reporting Requirements
- 15Case Study Education and Support for Caregivers
- 16Critical Milestones Achieved Ahead of Schedule in Lung Cancer Study
- 17IQVIA Investigator Site Portal: An Enterprise Implementation
- 18Transforming Oncology Research: IQVIA's End-to-End Patient Experience Data Approach
- 19Fast-Tracking Clinical Trials
- 20Improving Predictive Precision of Oncology Patient Modeling with Enriched Data and Integrated Field Alerts
- 21Removing Barriers, Restoring Hope: Transforming Access to Immunotherapy with IQVIA Patient Engagement and Support
- 22IQVIA's Health Data Transformation Solutions Integrate With Client's Big Data Platform
- 23Adapting to COVID-19: Adjudication and Oversight Group Management
- 24IQVIA Alerts reduced Sales Reps' lead to engagement time from 5 weeks to 48 hours with daily triggers
- 25How Emerging Biopharma Companies Can Successfully Launch Their Asset
- 26Accelerating Market Expansion with End-to-End HCP/O Engagement Services
- 27Biovac's Drive for Innovation: Partnering with IQVIA to Advance Healthcare
Google21
- 01Built an AI-native operating system for drug discovery on Google Cloud, using deep learning to speed development and success rate of new treatments.
- 02XtalPi: Accelerating drug discovery and development to offer more timely and affordable medical treatments
- 03AI-based computational disease models on Google Cloud to help pharma shorten clinical trials and cut drug-development costs.
- 04Oncology biotech uses Google Cloud to scale molecular dynamics simulations, cutting simulation time from weeks to overnight and false positives by 50%.
- 05Cradle: Revolutionizing Protein Engineering with a secure AI platform built on Google Cloud
- 06AI-driven drug discovery company; moved to GKE for flexible, scalable protein-structure processing (millions of structures).
- 07Allcyte: Breaking new ground in cancer precision medicine with AI and Google Cloud
- 08Accelerated discovery of new materials/therapeutics using Google Cloud, with significant power/cost/time savings.
- 09Merck Life Science: Ensuring scientists get the products they need with powerful ML models
- 10doc.ai: A mobile AI app blazes trails in medical research
- 11AI research assistant achieving 95% accuracy extracting/summarizing medical-research literature data on Google Cloud.
- 12AI patient-scheduling agent ("Asa") tackling the $150B missed-appointment problem, built on Google Cloud (tagged Healthcare + Life Sciences).
- 13Knolens platform delivers always-on AI for life-sciences (clinical trials, regulatory filings, literature) on Google Cloud.
- 14UZ Leuven: Enhancing patient care with powerful genomics in a secure cloud
- 15Colorado Center for Personalized Medicine: Integrating genetic data and patient records in the cloud to personalize care
- 16How Bayer is transforming healthcare through responsible AI adoption
- 17Homegrown Gemini-based agent accelerates workflows 70% and saves $2.3M. — referenced on cloud.google.com/blog (healthcare-life-sciences topic hub); exact case-study URL not independently confirmed.
- 18Advancing discovery of better drugs and medicine
- 19Partnerships | Isomorphic Labs
- 20Partnerships | Isomorphic Labs
- 21Partnerships | Isomorphic Labs
Certara15
- 01Prelude Therapeutics reduces their quality control (QC) process for regulatory submissions from hours to minutes with Certara's GlobalSubmit eCTD Software
- 02Arvinas Selects Certara's D360 to Advance Speed and Efficiency of Discovery Research
- 03Enhancing Pharmacokinetics Workflows at Charles River
- 04Standardizing Real World Data in Rare Disease: ATHN's Journey
- 05Certara & Dizal Partner to Fast-Track FDA Approval of Sunvozertinib for Lung Cancer
- 06Using customer engagement technology to create value communication tools for ABILIFY MAINTENA® (aripiprazole)
- 07Asciminib – PBPK Modeling Streamlines Development and Avoids Over 10 Clinical Trials
- 08Medicines that matter: Biohaven's Nurtec™ drug development journey
- 09Biogen Transforms Study Metadata Management with Certara's Metadata Repository
- 10De-Risking Phase 3 Rheumatoid Arthritis Trials with Model-Based Meta-Analysis (MBMA)
- 1163 Runs and No Convergence: When RsNLME Succeeded Where Others Couldn't
- 12Model-Informed Development Accelerates Transformative Treatment for Sleeping Sickness
- 13How Certara Enabled Fruquintinib FDA Approval for Metastatic Colorectal Cancer
- 14Integrated PK/PD Modeling and Machine Learning to Support CNS Compound Selection
- 15Accelerated ADC Approval Through Expert Modeling and Data Rescue
OpenAI10
- 01OpenAI's dedicated healthcare vertical page/launch post.
- 02Frontier reasoning model built for biology, drug discovery and translational medicine; named qualified customers include Amgen, Moderna, Allen Institute, and Thermo Fisher Scientific.
- 03follow-up update to the life-sciences model.
- 04"How Amgen uses GPT-5": Amgen applies GPT-5/frontier models to help accelerate delivery of potential new therapies; found GPT-5 met scientific-accuracy standards.
- 05Moderna and OpenAI partner to accelerate development of treatments; ChatGPT Enterprise deployed to thousands of employees company-wide.
- 06Longevity biotech collaborated with OpenAI to build and research GPT-4b micro, a version of GPT-4o specialized for protein engineering.
- 07OpenAI-published benchmark (750 expert-authored tasks across 7 life-science workflows/domains) — not a customer story but a life-sciences-specific artifact on OpenAI's own site.
- 08Partnership referenced within the GPT-Rosalind announcement as a named qualified customer for the life-sciences model (no separate dedicated story page found).
- 09Referenced within the GPT-Rosalind materials as leveraging frontier AI to help researchers analyze complex datasets and test hypotheses faster (no separate dedicated story page confirmed).
- 10Three-way collaboration (Sanofi, Formation Bio, OpenAI) to fine-tune models on Sanofi data and build drug-development agents (Muse tool for trial recruitment); could not confirm a dedicated openai.com story page exists (search only surfaced third-party press coverage) — flagged as unconfirmed on-site presence.
Schrödinger10
- 01Hit to development candidate in 10 months: Rapid discovery of SGR-1505, a novel, potent MALT1 inhibitor
- 02Design of a highly selective, allosteric, picomolar TYK2 inhibitor using novel FEP+ strategies
- 03Design of a novel, potent CDC7 inhibitor development candidate with high ligand efficiency and optimized properties
- 04Discovery of a novel, potent ACC inhibitor driven by computationally-guided design and assessment of water energetics in the binding site
- 05High precision, computationally-guided discovery of highly selective Wee1 inhibitors for the treatment of solid tumors
- 06Indiana Biosciences Research Institute enables drug discovery using CDD Vault and Schrodinger LiveDesign
- 07Morphic Therapeutic leverages digital chemistry strategy to design a novel small molecule inhibitor of α4β7 integrin
- 08Advancing lipid nanoparticle development with structure-based modeling platform and services
- 09Characterizing lipid nanoparticle self-assembly and structure using coarse-grained simulations
- 10Advancing the design and optimization of drug formulations with combined computational and experimental approaches
Iktos9
- 01Integrated drug-discovery collaboration (Jan 2026
- 02Iktos announces Strategic Collaboration with Servier
- 03Iktos announces strategic collaboration with Cube biotech
- 04Iktos and Elsevier announce their partnership
- 05Collaboration: Iktos and Italfarmaco
- 06Iktos AI de novo design applied to select Pfizer small-molecule discovery programs (2021
- 07Additional AI-for-new-drug-design collaboration (Nov 2020
- 08Collaboration in AI for drug design (Jun 2022
- 09Partnership with MMV in Anti-Malarial Drug Discovery
Microsoft Azure7
- 01Novo Nordisk Accelerates Clinical Insight with Custom Agents on Azure
- 02Transforming drug discovery: Novo Nordisk uses the power of AI and Azure with Microsoft Research
- 03Novo Nordisk Accelerates Life-Changing Research Using Azure DevOps and GitHub
- 04Adaptive Biotechnologies Transforms Data Stream Into New Immune Medicine Platform with Azure
- 05Mercy lays the foundation for a future of innovation in patient care using Microsoft Azure to unlock insights from data in the cloud
- 06St. Luke's delivers exceptional, scalable service for providers and patients with Epic on Azure
- 07Jefferson Health Modernizes as it Migrates On-Premises Epic Environment to Azure
Insilico Medicine7
- 01Insilico Medicine Featured in Harvard Business School Case Study on Rentosertib
- 02Insilico Medicine Featured in Harvard Business School Case Study on Rentosertib
- 03Insilico Medicine Featured in Harvard Business School Case Study on Rentosertib
- 04Insilico Medicine Featured in Harvard Business School Case Study on Rentosertib
- 05Insilico Medicine Featured in Harvard Business School Case Study on Rentosertib
- 06Insilico Medicine Featured in Harvard Business School Case Study on Rentosertib
- 07Insilico Medicine Featured in Harvard Business School Case Study on Rentosertib
Owkin7
- 01Boehringer Ingelheim used Owkin's K Pro multi-omic reports to prioritize targets and find spatially informed patient-selection biomarkers.
- 02An oncology pharma used Owkin's K Pro and MOSAIC data to triage bispecific ADC candidates in silico.
- 03Owkin's K Pro Autopilot agent proposed a KRAS G12D drug combination that widened eligible patients from about 10% to 60%.
- 04Owkin's MesoNet model predicts mesothelioma survival from pathology images and could shrink Phase 3 trial sizes.
- 05Owkin and AstraZeneca developed an AI pre-screen that flags likely gBRCA mutation carriers from digitised pathology slides.
- 06Owkin is building purpose-made AI agents on K Pro for Sanofi under a multi-year collaboration and five-year licence.
- 07Owkin and Gustave Roussy formed a strategic alliance to speed oncology clinical research with AI.
Axtria5
- 01Axtria used NLP and GenAI to turn audio interviews with field reimbursement managers into structured insights.
- 02Axtria built AI/ML sub-national demand forecasts for a women's health portfolio.
- 03Axtria used an ML algorithm on patient-level data to predict non-adherence and project $15M in extra prescription revenue.
- 04Axtria applied GenAI and NLP to 2,500-3,000 monthly medical inquiries and visualised trends in Power BI.
- 05Axtria built a generative AI query engine over market research, ATU studies and regulatory filings.
Benchling5
- 01Absci replaced spreadsheet sample handoffs with a Benchling registry and API integration to improve data for AI model training.
- 02MacroGenics digitalized Research and Biopharmaceutical Development on one Benchling platform.
- 03Ori Biotech used Benchling R&D Cloud to standardize and centralize cell and gene therapy process development data.
- 04Synlogic unified its informatics in Benchling and used the API to automate fermentation data processing.
- 05Cue Biopharma used Benchling to carry discovery data through to biologics process development.
Dotmatics5
- 01A chemicals and materials company replaced macro-based workflows with Dotmatics Luma to cut analysis turnaround.
- 02A large CRDMO moved chemistry and biology workflows onto the Dotmatics ELN and Data Discovery Platform.
- 03Krystal Biotech rolled the Dotmatics ELN and Platform across five R&D groups.
- 04Sygnature Discovery deployed the Dotmatics ELN and Data Discovery Platform with a client portal.
- 05Charles River rolled out the Dotmatics ELN to about 500 early discovery researchers.
MathWorks4
- 01MedImmune automated flow cytometry analysis in MATLAB, cutting turnaround from weeks to minutes.
- 02Lund University trained neural networks in MATLAB to match heart donors and recipients.
- 03Battelle decoded brain signals with MATLAB machine learning to restore hand movement in a paralysed patient.
- 04Preceyes developed the control system of an eye-surgery robot with MATLAB and Simulink model-based design.
Palantir3
- 01Healthcare-system partnership with Palantir (ontology-driven platform; specific workflow not confirmable via static fetch
- 02Clinical teams use Palantir's ontology platform to navigate systems and enroll patients from one place, submitting bed-placement requests in a single click
- 03Major US healthcare distributor uses Foundry to build an end-to-end distribution network for delivering lifesaving products
NVIDIA3
- 01Amgen trained antibody language models on NVIDIA BioNeMo and DGX Cloud, reaching three-month goals in four weeks.
- 02Astellas trained its own antibody language models on NVIDIA BioNeMo to predict antibody properties before measurement.
- 03Deloitte built its Quartz Atlas AI drug discovery platform on NVIDIA BioNeMo, DGX Cloud and NIM microservices.
Accenture3
Recursion3
- 01Recursion and Roche/Genentech run a multi-year collaboration using Recursion OS and Maps of Biology in neuroscience and oncology.
- 02Recursion and Sanofi collaborate to discover and advance up to 15 novel targets in oncology and immunology.
- 03Recursion and Bayer collaborate on up to seven precision oncology programs.
Genesis Therapeutics (Genesis Molecular AI)3
- 01Gilead and Genesis deployed the GEMS platform to find small molecules against targets that lack training data.
- 02Incyte and Genesis expanded their collaboration to at least five new targets, with Incyte data used to train GEMS.
- 03Genesis introduced Pearl, a generative 3D foundation model for protein-ligand structure prediction.