Custom foundation models are AI systems specially trained with a large amount of healthcare and life sciences data. Unlike general AI, these models focus on healthcare language, rules, and challenges. They serve as the base for agentic AI workflows, which are smart AI programs that can do specific jobs on their own in clinical research or healthcare.
Agentic AI workflows can handle many-step tasks by themselves. These include finding patients for clinical trials, creating documents, submitting paperwork, reviewing clinical data, and checking research papers. By doing these jobs automatically, AI reduces human work, cuts mistakes, and lets healthcare workers focus more on patients and planning.
Companies like IQVIA and NVIDIA lead in making these AI tools. IQVIA works in over 100 countries and uses huge healthcare data and knowledge to build special AI agents focused on healthcare. NVIDIA offers the technology needed to build and run these AI models, using platforms like NVIDIA AI Foundry and AI Enterprise.
Clinical trials are very important for medical research but take a long time and cost a lot. They include many steps like choosing trial sites, recruiting patients, monitoring trials, collecting data, following rules, communication, and reporting. Each step needs a lot of care and organization. In the U.S., clinical trials usually take about 11 years from start to finish.
AI with special foundation models and agentic workflows helps make these steps faster and easier. For example, IQVIA and NVIDIA showed that AI can do difficult tasks like picking trial sites and finding patients, which cuts down delays and helps recruit more patients. The AI uses large data sets to quickly find the best sites and patients, making trials more efficient while following strict rules.
AI also speeds up making documents and sending paperwork by pulling useful information from big amounts of healthcare data, like text in PDF files. NVIDIA’s AI tool for extracting data from PDFs helps find important data that was hard to get before by hand. These AI methods also help follow U.S. rules like FDA guidelines and HIPAA privacy laws, making sure AI use is safe and legal.
NVIDIA’s DGX Cloud and RAPIDS libraries give lots of computing power to build detailed knowledge graphs. These graphs show connections in healthcare data. They help researchers look at clinical data faster, find patient groups more quickly, and plan trials better.
By improving workflows, AI can cut down the time needed for clinical trials. This means new medicines can reach patients faster in the U.S.
Personalized medicine, like cancer care, has many data details that are hard to manage. Cancer diagnosis and treatment use many types of data such as images, genes, tissue samples, and patient histories. Doctors often spend 1.5 to 2.5 hours per patient looking at all these data to make personalized treatment plans. This takes a lot of time and limits how many patients can get personal care.
Agentic AI workflows help speed this work by using AI agents that look at many types of data together. For example, Microsoft’s healthcare AI system uses different AI tools to study X-rays, pathology slides, genetic information, and clinical notes. It gives doctors useful information like cancer stage, treatment ideas based on guidelines, and clinical trial options, all in minutes instead of hours.
Top U.S. cancer centers like Stanford Medicine and University of Wisconsin are testing these AI tools to make tumor board work faster. Early results show less work for doctors and better access to detailed advice based on evidence. AI assistants also help doctors make more accurate treatment plans by using trusted cancer staging and treatment guidelines.
These AI systems can help patients get faster and better cancer care by lowering delays caused by data complexity and paperwork.
In the U.S., healthcare is highly regulated, so AI tools must follow strict rules to keep patient information private and safe. Companies like IQVIA focus on AI that protects privacy, meets rules, and keeps patients safe.
Medical managers and IT staff need AI systems that follow laws like HIPAA and FDA rules. They also must work with standards like HL7 and FHIR to share health data properly. NVIDIA’s AI platforms offer safe processing environments, audit tools, and connection to secure identity systems to meet these needs.
Human oversight is still very important. Many AI systems include a step where clinicians check AI suggestions before making decisions. This way, AI helps doctors rather than replaces their judgment.
For medical office managers, owners, and IT staff in the U.S., AI workflow automation is useful right now. Clinical trials and healthcare often have many repetitive tasks like scheduling, patient recruitment, paperwork, and communication with regulators.
Agentic AI workflows can automate many front and back-office jobs, lowering admin work and letting staff handle more important duties. AI phone systems by companies like Simbo AI improve patient contact by scheduling appointments, answering calls, and handling common questions without human help. This makes it easier for patients and offices to work.
In clinical research, AI agents quickly find eligible patients by checking big data sets, replacing slow manual reviews. Automated document creation and paperwork reduce delays caused by compliance tasks.
AI also helps match patient needs, doctor availability, and study rules in scheduling. This lowers missed appointments and uses resources better.
IT staff benefit from cloud AI platforms like NVIDIA AI Foundry or AWS cloud services. These let healthcare groups create AI workflows that fit their needs without building from scratch. They also connect easily with electronic health record (EHR) systems to move patient data safely and support real-time decisions.
Using AI workflow automation helps U.S. clinics and research centers lower staff burnout, speed clinical trials, and improve patient engagement while keeping privacy and rules in place.
Custom foundation models and agentic AI workflows help fix problems in clinical research and healthcare management. Companies like IQVIA and NVIDIA use large data and strong computing power to build AI systems that can make research faster, care better, and admin work easier in the U.S.
These AI tools are useful not just for research and cancer care but also for drug discovery, genetics, X-rays, lab work, and managing long-term illnesses. AI helps handle different data types like images, notes, genes, and lab results that are important in today’s healthcare.
Medical managers and IT teams have a chance to get ready for these AI tools. By focusing on safe AI use, following rules, and working with current systems, healthcare groups can improve their work and patient care.
AI development in healthcare will keep changing quickly. Those who use these tools wisely will be able to give better care and help medical research move forward in the United States.
The collaboration aims to build custom foundation models and agentic AI workflows that accelerate research, clinical development, and access to new treatments, ultimately improving patient outcomes through enhanced efficiency and innovation in healthcare.
IQVIA uses its vast healthcare-specific data and deep domain expertise, termed Connected Intelligence, to train AI applications that optimize clinical trials and planning for therapy and device launches, utilizing comprehensive analytics and technologies.
NVIDIA AI Foundry provides tools and platforms like custom model building, AI Blueprints, and GPU cloud resources to streamline the development of specialized AI agents tailored for healthcare workflows and clinical trial support.
Clinical trials involve complex, multi-step workflows such as site selection, participant recruitment, regulatory compliance, and communication; customized AI agents can automate these tasks, reducing time and improving accuracy.
Technologies include the NVIDIA AI Enterprise platform, NIM microservices with Llama and Cosmos Nemotron model families, NeMo for generative AI, AI Blueprints for workflows, and DGX Cloud capacity for scalable computing.
It unlocks valuable healthcare data locked within PDFs by extracting text, graphs, charts, and tables, enabling training of domain-specific AI models and agents with previously inaccessible information.
NVIDIA RAPIDS accelerates data processing and the creation of knowledge graphs, enabling efficient handling and organization of vast healthcare data necessary for building intelligent AI workflows.
IQVIA commits to privacy, regulatory compliance, and patient safety by grounding its AI-powered capabilities within responsible frameworks, branding them as Healthcare-grade AI.
Automation can reduce time spent on complex tasks such as document generation and patient recruitment, allowing healthcare professionals to prioritize strategic decisions and human-centered care.
The partnership offers these customers access to customized AI agents and workflows powered by NVIDIA and IQVIA technologies, accelerating drug development and device launch processes with increased efficiency and innovation.
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