Drug discovery

Ryvu Therapeutics is an oncology biotech company that relies on computational methods such as molecular docking, molecular dynamics, protein structure prediction, and physics-based free energy perturbation calculations to prioritize chemical compounds for drug discovery.The company needed to overcome an on-premises compute bottleneck that pushed simulation turnarounds from hours into weeks and slowed down medicinal chemistry synthesis cycles. It built an automated in silico evaluation pipeline on Google Cloud using Google Batch, Compute Engine GPUs, Cloud Storage, and Nextflow orchestration, with Gemini also mentioned among products in the source.

Ryvu TherapeuticsPharma

Phagos applies generative AI to match bacteriophages with target bacteria for personalized phage therapy.The company built AI models on AWS to simulate millions of phage-bacteria interactions and accelerate treatment discovery.

PhagosPharma

Tangram Therapeutics is a UK biotech company focused on solving human disease through computational RNA interference (RNAi) medicines.To accelerate drug target discovery and evaluation, Tangram built LLibra OS, an agentic AI platform that unifies proprietary, licensed, and curated public datasets for research and target-indication assessment.The platform supports retrieval augmented generation, web search, and text-to-SQL to help researchers identify novel targets, evaluate therapeutic potential, and design medicines.

Tangram TherapeuticsPharma

AstraZeneca is a global, science-led biopharmaceutical company focused on discovery, development and commercialization of prescription medicines.The company uses AWS to support research through commercialization, and specifically applies Amazon Bedrock to accelerate clinical trials by combining structured and unstructured data.An agentic AI-powered Development Assistant gives clinical, regulatory, safety, and quality teams conversational access to trusted insights in seconds.

AstraZenecaPharma

Schrödinger uses Google Cloud as the foundation for its physics-based molecular simulation platform to accelerate drug discovery and reduce the cost and time of lab work.The company runs compute-intensive simulation workloads that previously took up to three weeks on on-premises clusters; with Google Cloud, it can scale horizontally across more GPUs and CPUs to finish computations within hours.Schrödinger added BigQuery as a data hub for hundreds of billions of molecules, reagents, and iterations, and uses machine learning to narrow simulation results toward the most promising candidate molecules.

SchrödingerPharma

AWS supports healthcare and life sciences organizations in deploying generative AI to accelerate drug discovery, improve clinical trial development, enhance medical imaging and pathology analysis, automate clinical documentation, and streamline regulatory compliance.Customers such as Pfizer, Natera, Clario, Aetion, Sanofi, Philips, Hippocratic AI, Solventum, Amazon Pharmacy, and Radboud University Medical Center use AWS technologies to enhance research, care delivery, and compliance workflows.AWS technologies employed include Amazon Bedrock, Amazon SageMaker, AWS HealthScribe, Amazon Textract, and Amazon Comprehend.Applications include rapid drug candidate screening, protocol generation, synthetic defect image generation, compliant content creation, real-world evidence analysis, sales team compliance improvement, clinician task automation, call center productivity, prior authorization automation, and compliance reporting.

PfizerHealthcare

Merck & Co., Inc. modernized its clinical data ecosystem to overcome siloed systems and accelerate drug development and manufacturing efficiency using AWS generative AI and analytics technologies.The company implemented a data platform spanning 300+ clinical trials and deployed AI models for medical coding, database workflows, and drug design using AWS HealthOmics and Anthropic Claude models on Amazon Bedrock.Merck also used generative AI text-to-SQL for natural language querying of healthcare data, improving analyst efficiency and accelerating R&D decisions.The manufacturing data analytics platform was rebuilt on AWS, leading to a 3x performance boost and 50% cost reduction.These innovations enabled a 70% reduction in clinical trial costs, 3x faster data processing, and overall operational cost savings.

MerckPharma

Sanofi launched its Digital Accelerator to speed up digital innovation across research and development, clinical, commercial, and manufacturing workflows.The initiative aims to shorten the time from discovery to therapy and improve patient, provider, and employee experiences through AI-powered solutions.

SanofiPharma

This article discusses how generative AI, powered by platforms like Microsoft Azure AI, is transforming pharmaceutical R&D by drastically reducing the time and cost involved in drug discovery and clinical trials. It highlights specific examples such as the case of Insilico Medicine, which used generative AI to achieve preclinical drug identification in just 18 months at a significantly reduced cost. Applications of generative AI include literature review, drug target prediction, compound generation, and even patient recruitment for clinical trials. It also discusses partnerships, such as Cognizant's collaboration with Microsoft Azure AI, to further embed generative AI technologies into life sciences R&D workflows, enhancing drug stability and patient compliance.

Insilico MedicinePharma

UCB, a global healthcare biopharmaceutical company, collaborates with Microsoft to integrate computational services, AI, and cloud technologies for more efficient drug discovery and development. By leveraging Microsoft’s platforms, UCB scientists now analyze multi-modal, high-dimensional data to identify more effective treatment modalities. Their partnership, originating from contributions to the COVID Moonshot project, focuses on improving patient experiences, understanding disease biology, discovering therapeutic molecules faster, and accelerating clinical trial timelines.

UCBHealthcare