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.
187 stories across 12 vendors
AWS47
- 01AI-powered assistant for company-policy Q&A, used by over 80% of employees
- 02Generative AI for target identification on resilient cloud infrastructure
- 03AI-powered agent for natural-language access to clinical trial data
- 04Cloud-based genomics-sequencing data processing at scale
- 05Reduces analysis time 80% and storage costs 90% with Amazon HealthOmics
- 06AI to achieve global scale for treatment delivery
- 07Transforms personalized cancer treatment with AI on AWS
- 08Building the world's first DNA search engine on AWS
- 09Reduces false rejects 50% across production lines using generative AI
- 10Created a unified clinical data layer, accelerating processes
- 11Built the Change Assessment Knowledge Engine (CAKE) on Amazon Neptune, cutting change-assessment duration up to 90%
- 12Slashed clinical documentation time 90% using Claude 3.5 on AWS
- 13Accelerated drug-labeling review with AWS machine learning
- 14Improves operational efficiency with predictive maintenance
- 15Increases forecast accuracy, reduces manual effort
- 16Reduces GxP compliance validation time from weeks to minutes
- 17Leverages Amazon Pharmacy for home delivery of select medications
- 18Transforms product-complaint management, reducing triage time
- 19Modernizes Custom Pak Designer application on AWS
- 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%
- 4799% cost savings; PandaOmics/Chemistry42 on AWS took a fibrosis candidate from target discovery to compound validation in <18 months for $2.6M
Anthropic30
- 01Canadian digital-health/benefits platform; "went all in on Claude in a regulated industry," cut product-development cycle times in half
- 02Brings Claude to the insurance backbone (adjacent to healthcare/insurance, not pharma-specific)
- 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
- 18Dedicated case study: cut clinical study report writing from ~12 weeks to ~10 minutes via "NovoScribe," an AI documentation platform built with Claude Code, aiming to automate full Common Technical Document (CTD) production
- 19Health system applying Claude with a Constitutional-AI safety approach
- 20Healthcare startup building safety-focused clinical applications on Claude
- 21Healthcare software company leveraging Claude for clinical products
- 22Medical-records AI platform deployed via Claude on Amazon Bedrock
- 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 pharmacovigilance tech + services solution; Vigilance Detect reviewed 250,000+ records in under two months, auto-filtering 15,000+
- 02Overcoming the challenges of managing regulatory information with a cloud-based Regulatory Intelligence platform
- 03Vigilance Detect case study brochure
- 04Complex workflow and data collection via the IQVIA Research Management Platform for an investigational digital slide-scanner study
- 05Integrated search content strategy
- 06Advanced patient finding and disease modeling using AI/ML with real-world data assets
- 07Closing data gaps
- 08Revealing the treatment landscape and patient pathways in a new market
- 09Building a compliance program from the ground up for a first US launch
- 10Healthcare insights through AI and machine learning (real-world data + AI/ML for clinical and commercial success
- 11AI case study: increased precision of target patient identification 15x and HCP linkage 10x
- 12Improving patient profiling and physician targeting by combining fragmented data sources
- 13Respiratory treatment research using real-world data and AI/ML
- 14Meeting global transparency-reporting requirements across regions
- 15Digital-first education and support program for caregivers of children with a rare brain disease
- 16Critical milestones achieved ahead of schedule for a Phase III lung-cancer (ALK inhibitor, NSCLC) trial
- 17IQVIA Investigator Site Portal enterprise implementation
- 18Transforming oncology research with an end-to-end patient-experience data approach (COA/eCOA
- 19Fast-tracking clinical trials using NLP to extract oncology/diabetes trial data, cutting cost/time/errors
- 20Improving predictive precision of oncology (CAR-T) patient modeling with enriched data via Integrated Field Alerts
- 21Removing barriers, restoring hope: transforming access to immunotherapy via patient-access/financial-assistance programs
- 22Health data transformation solutions integrated with client's big-data platform (NLP
- 23Adapting to COVID-19: adjudication and oversight group management
- 24IQVIA Alerts cut sales reps' lead-to-engagement time from 5 weeks to 48 hours
- 25How emerging biopharma companies can successfully launch their asset (Launch Excellence
- 26Accelerating market expansion with end-to-end HCP/O engagement services
- 27Partnering with IQVIA to advance healthcare innovation
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
- 02AI/automation drug-development company; uses Google Cloud GPU/VM instances to accelerate drug discovery and lower computing costs
- 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%
- 05Built its protein-design platform (used across pharma/chemicals/food/ag R&D) on Google Cloud
- 06AI-driven drug discovery company; moved to GKE for flexible, scalable protein-structure processing (millions of structures)
- 07Combines microscopy + AI on Google Cloud to help pharma develop new drugs and enable precision oncology
- 08Accelerated discovery of new materials/therapeutics using Google Cloud, with significant power/cost/time savings
- 09Moved its data stack to Google Cloud (BigQuery, Vertex AI, Looker) for supply-chain optimization and product recommendations
- 10AI mobile-health platform; 35,000+ consumers use it to monitor health / join research trials, built on Google Cloud
- 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
- 14Google Cloud + Localyse solve genomics-pipeline and app-development challenges
- 15Google Cloud powers a patient-record/genetic-data warehouse to personalize diagnosis, treatment and therapy development
- 16Interview-format case study on Google Cloud's transform hub: Bayer's head of applied imaging/innovation discusses generative AI across research and regulatory documentation
- 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
- 18AlphaFold 3 & drug discovery blog — DeepMind's own blog names Schrödinger as a partner applying AlphaFold alongside its physics-based software to design selective therapeutic molecules
- 19Novartis — Strategic research collaboration (announced Jan 2024, expanded Feb 2025) to discover small-molecule therapeutics against challenging targets (up to 6 programs)
- 20Eli Lilly and Company — Strategic partnership to discover small-molecule therapeutics against undisclosed targets using Isomorphic's AI drug-design engine
- 21Johnson & Johnson — Multi-target, cross-modality collaboration combining AI drug design with J&J's discovery expertise (small molecules + biologics) for hard-to-treat diseases
Certara15
- 01Cut QC time for regulatory submissions from hours to minutes using GlobalSubmit
- 02Shortened design-make-test-analyze discovery cycle using D360
- 03Enhanced pharmacokinetics workflows with a cloud-based PK solution
- 04Standardized real-world rare-disease data for FDA compliance
- 05Fast-tracked FDA approval of sunvozertinib for NSCLC via pharmacometrics
- 06Communicated clinical/economic value using BaseCase interactive apps (Abilify Maintena
- 07PBPK modeling of Asciminib streamlined development, avoiding 10+ clinical studies
- 08Fast-tracked Nurtec ODT approval using PBPK modeling, skipping a Phase I study
- 09Transformed study metadata management with Pinnacle 21 Enterprise
- 10De-risking Phase 3 rheumatoid arthritis trials with model-based meta-analysis (MBMA
- 11RsNLME solved a PK/PD convergence challenge other software couldn't
- 12Model-informed development accelerated a transformative sleeping-sickness treatment
- 13Expert guidance streamlined timely FDA approval for metastatic colorectal cancer
- 14Integrated PK/PD modeling and machine learning to support CNS compound selection
- 15Accelerated antibody-drug-conjugate 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 a novel, potent MALT1 inhibitor (SGR-1505) using large-scale virtual screening of 8.2B compounds
- 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
- 05High-precision, computationally guided discovery of highly selective Wee1 inhibitors
- 06Enables drug discovery using CDD Vault (with Schrödinger platform integration
- 07Leverages a digital chemistry strategy (LiveDesign) to design α4β7 integrin inhibitors
- 08Advancing lipid nanoparticle (LNP) 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
- 02Multi-target strategic collaboration, potential deal value >€1B (Jan 2026
- 03Novel small-molecule amylin-receptor agonists for obesity, diabetes, cardiometabolic disease (Jan 2025
- 04Partnership combining Reaxys chemistry database with Iktos AI for a predictive retrosynthesis platform (Mar 2024
- 05Collaboration to develop next-generation HDAC inhibitors for non-oncological diseases (Jun 2024
- 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 in anti-malarial drug discovery (Nov 2022
Microsoft Azure7
- 01Deployed a governed AI reasoning agent on Azure so researchers analyze clinical data and test hypotheses in minutes instead of weeks
- 02Built an AI platform on Azure with Microsoft Research; predictive AI models for cardiovascular-disease risk outperform existing clinical standards
- 03Built a research collaboration platform (multi-cloud) on Azure DevOps + GitHub, linking clinical and academic partners
- 04Generates patient test results much faster using Azure
- 05Modernized data infrastructure, unified siloed archives, reduced patient length-of-stay via dashboards, automated insurance-card scanning with Azure AI Document Intelligence
- 06Migrated Epic® environment to Azure, integrated Teams with Epic
- 07Migrated Epic® to Azure and secured patient records with Microsoft Defender
Insilico Medicine7
- 01Rentosertib (ISM001-055), a TNIK inhibitor for idiopathic pulmonary fibrosis: first drug with both an AI-discovered target and AI-designed molecule to reach Phase II; preclinical candidate nomination in 18 months (vs. ~4.5-year industry average) after synthesizing only 78 molecules; Phase IIa showed dose-dependent lung-function improvement
- 02DDR1 kinase inhibitor: proof-of-concept identifying potent inhibitors in 21 days using generative chemistry (Chemistry42
- 03QPCTL immuno-oncology program: candidate nomination in 9 months, co-developed with Fosun
- 04~$1.2B collaboration referenced as a partnership milestone
- 05$80M upfront licensing deal for ISM3091
- 06Partnership potentially worth >$500M
- 07Partnership worth >$100M
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