Life sciences innovation
Applies AI to research, development, and analysis in life sciences workflows. It helps organizations accelerate discovery, improve experimental planning, and support evidence-based decisions.
Data updated
Where it is used
Pharma accounts for 75% of these deployments.
- PharmaSurging · 2 in the last 6 months9
- HealthcareQuiet · 0 in the last 6 months2
- FinanceQuiet · 0 in the last 6 months1
What it delivers
2 deployments publish a number. The rest describe results in words, grouped below.
Quality & accuracy
1 metric
Reduction · median and middle half−80%fewMedian reduction −80%, middle half −80% to −80%, from 1 metricProductivity & throughput
1 metric
No reductions reportedIncrease · median+150%1 metric · few
Grey figures rest on fewer than 5 published metrics. Read them as examples, not as a typical result.
Results described in words
- New product / capability100% of these deployments12
- Speed & agility92% of these deployments11
- Better decisions & insight42% of these deployments5
- Customer experience & trust33% of these deployments4
- Risk & compliance33% of these deployments4
- Cost efficiency17% of these deployments2
How it is built
Microsoft is named in 67% of these deployments.
- Custom-built80% · 8
- Bought10% · 1
- Mixed10% · 1
The build approach is known for 10 of 12 deployments (83%). The rest are left out.
Cloud providers named
- Microsoft8 deployments67%
- AWS3 deployments25%
- GCP1 deployment8%
Technologies that recur
- Azure AI 4
- Azure OpenAI 3
- Azure HPC 2
- Copilot 2
- Azure 2
- AI 2
- Amazon Bedrock 2
- Azure ML 1
Deployments over time
2 deployments in the last six full months, against 2 in the six before. Counted by publication month since Oct 2023.
- 27 May 2026PharmaUnited Kingdom
Sonrai Accelerates Single-Cell RNA-seq Data Analysis Using Amazon Bedrock
Sonrai · AWS
Researchers in the biotech and pharmaceutical industries grapple daily with the complexity and volume of single-cell RNA sequencing (scRNA-seq) datasets, which are crucial for understanding diseases and developing targeted therapies. Sonrai sought to use generative AI to simplify and streamline interpretation of scRNA-seq data and reduce the manual burden on immunologists. Sonrai Discovery uses large language models through Amazon Bedrock to automate cluster annotation, generate consistent text reports, and support faster analysis on AWS.
- 27 May 2026PharmaUnited States
PozeSCAF Discovery Solutions — Amazon Bedrock + high-performance simulation on AWS to accelerate drug discovery
PozeSCAF Discovery Solutions · AWS
PozeSCAF Discovery Solutions (formerly Immunocure Discovery Solutions) turned to AWS for scalable, high-performance infrastructure to optimize molecular dynamics workloads. The company cut simulation runtimes by more than half, reduced compute costs, and accelerated its drug discovery pipeline. It also began exploring generative AI/agentic workflows with Amazon Bedrock to build knowledge graphs from project data and flag potential side effects earlier.
- 29 Apr 2026HealthcareUnited States
Genentech leverages generative AI with Amazon Bedrock Agents to accelerate drug discovery
Genentech · AWS
Genentech uses Amazon Bedrock Agents with Anthropic Claude Sonnet 3.5 to automate complex biomedical research workflows for biomarker validation. The gRED Research Agent processes and synthesizes information from millions of scientific data sources using multi-agent collaboration and Retrieval Augmented Generation (RAG). This automation reduces manual research time from weeks to minutes, freeing scientists to focus on high-impact tasks and accelerating drug discovery.
- 3 Mar 2026PharmaCanada
BenchSci decodes disease biology with Neo4j and Google Cloud to accelerate drug discovery
BenchSci · GCP
BenchSci transforms fragmented biomedical evidence into a graph-native model of disease biology, empowering 9 of the top 10 pharmaceutical companies to de-risk and accelerate discovery. BenchSci’s ASCEND platform combines large language models with the Biological Evidence Knowledge Graph (BEKG), an experimentally grounded knowledge system that integrates open-access literature, closed-access publications, and proprietary pharmaceutical datasets. Its LENS extraction engine uses Google Cloud Vertex AI and Gemini models to interpret scientific papers with contextual awareness and validate claims against associated imagery before materializing structured assertions into Neo4j.
- 10 Jun 2025PharmaUnited States
EY accelerates drug discovery and development in pharma
EY · Microsoft
EY guides pharmaceutical companies through adopting generative AI (GenAI) to accelerate and automate early-stage drug discovery processes. GenAI enables significant breakthroughs in molecule creation, compound screening, and toxicity prediction, previously requiring extensive time and costs. EY collaborates with life sciences industry leaders, providing strategy and change management for successful GenAI implementation. The solution leverages deep learning algorithms for virtual screening, target identification, and optimal resource allocation. Predictions point toward cost savings from 44% to 67% and time reductions up to 50% for critical research phases, as GenAI adoption accelerates. The methodology streamlines clinical trial design and data analysis, improves regulatory submission, and automates documentation and compliance. EY works with both large and small biopharma companies to extend the benefits industry-wide, including for organizations lacking in-house AI capabilities. The approach helps CDMOs and CROs differentiate using advanced AI for outsourced drug research steps. Results reported by EY clients and survey respondents describe speed-to-market and cost reduction as primary impacts. The article describes a transformation in research and development operating models for faster patient benefit and broader treatment diversity.
- 19 May 2025PharmaUnited States
Global Innovators Accelerate Scientific Discovery with AI-Driven Agents
GSK · Microsoft
Microsoft Discovery is a new enterprise AI agent platform designed to transform research and development (R&D) across sectors. By orchestrating specialized AI agents with a sophisticated graph-based knowledge engine, researchers and scientists can reason contextually through complex data, simulate experiments, and iterate research plans faster than ever before. Built on Azure High Performance Computing (HPC) and Azure AI Foundry, it emphasizes trust, compliance, and extensibility. Real-world impact is demonstrated by Microsoft researchers rapidly developing a sustainable immersion datacenter coolant, a process that normally takes years, in just 200 hours. GSK aims to accelerate medicinal chemistry, while The Estée Lauder Companies focuses on faster product innovation. The platform integrates partner technology from NVIDIA, Synopsys, and PhysicsX to enable advances in pharma, materials, semiconductor design, and industrial engineering. Strategic alliances with Accenture and Capgemini are helping scale deployments. Microsoft Discovery is positioned as a future-proof system for solving the most challenging R&D problems using AI agents and Microsoft’s secure cloud foundation.