How Multimodal Real-World Data is Revolutionizing Oncology and Personalized Treatment Approaches

Multimodal real-world data means gathering many different kinds of information to get a full picture of a patient’s health. In cancer care, this data includes things like genetic information, medical records, imaging, liquid biopsies, lab test results, and behavior details. This data is different from what is collected in controlled clinical trials because it comes from real patient experiences like hospital visits and treatments.
By combining these data sources, doctors can understand cancer better. They can see the genetic changes causing the disease, how it shows up in the body, and how patients react to treatments over time. This helps doctors create treatments made for each patient.

The Role of AI in Using Multimodal Real-World Data

Artificial intelligence, or AI, helps process and study large amounts of multimodal data. Doctors cannot easily look at millions of pieces of information to find links between genes, treatments, and results. AI can quickly find patterns, guess which treatments might work best, and suggest new options.
For example, AI systems study genetic codes, patient histories, and results to predict which cancer treatments have a better chance of working. This is better than giving all patients the same treatment. AI also helps find patients who can join clinical trials, which can be very important when normal treatments don’t work well.

Tempus: A Leader in Multimodal RWD and AI for Oncology

In the United States, a company called Tempus is a major user of multimodal data and AI in cancer care. Tempus works with about 65% of big medical centers and more than half of U.S. cancer doctors.
Tempus has the world’s largest collection of anonymous clinical and genetic data. They have over 8 million patient records and a huge amount of data for research. Their system combines different data types like tumor and normal DNA sequencing and detailed patient information to provide useful knowledge. Studies show this helps find more treatment options by uncovering genetic targets that other tests might miss.
Tempus also works with more than 200 drug companies, including 95% of the top 20 U.S. cancer drug makers. This helps create new medicines based on genetic cancer profiles, allowing doctors to give new treatments sooner.

Benefits of Multimodal Real-World Data in Oncology

• Improved Treatment Personalization: By using details like DNA changes, RNA levels, and clinical symptoms together, doctors can choose treatments that match a patient’s specific cancer type instead of using a one-size-fits-all plan. This often leads to better results and fewer side effects.

• Earlier and More Accurate Diagnoses: Using tissue genotyping along with liquid biopsies and other data gives a clearer picture of how tumors behave. Liquid biopsies can find tumor DNA in the blood that regular tissue tests might miss. This is a less invasive way to watch the cancer and how it responds to treatment.

• Clinical Trial Matching: AI tools match patients to clinical trials based on their genetics and health records. This helps more patients get access to experimental treatments, speeds up enrolling in trials, and improves chances of success.

• Closing Care Gaps: These tools can spot missed screenings or late treatment steps. This helps providers manage patient care better and make sure treatments are followed as needed.

Incorporating AI and Workflow Automation in Oncology Practices

Medical administrators and IT staff need to think about how AI affects daily work when adding AI-powered multimodal data systems. AI helps with medical decisions but also automates many routine office tasks.
This part explains how AI-driven automation can make cancer clinics run more smoothly in the U.S.

Automated Front-Office Communication

Many oncology clinics get a lot of phone calls for scheduling, test results, and treatment questions. AI phone systems can answer calls fast and handle common questions. This lowers wait times and helps patients get through quicker. Companies like Simbo AI offer these phone automation services.
Automating calls also means fewer missed appointments and higher patient satisfaction. This is important because cancer care needs to be precise and timely.

Streamlined Appointment Scheduling and Patient Follow-Up

AI tools can book and confirm appointments automatically. They can send reminders and follow up with patients who miss visits. This keeps patient visits on schedule and helps treatments happen at the right times. Automated scheduling cuts down the work for office staff, so they can spend more time helping patients.

Enhanced Data Integration and Analytics

AI platforms, such as those by Tempus, help IT teams connect many types of data into one system. This makes it easier to watch patient health in real time and use advanced data analysis. Automated reports can highlight patients who need urgent care or who can join clinical trials.

Supporting Clinician Decision-Making

AI does not replace doctors. It supports them by providing clear data summaries, risk information, and treatment suggestions based on multimodal data. This helps doctors make better decisions and handle tough cases without getting overwhelmed.

Impact on Medical Practices Across the United States

• About 65% of academic medical centers use Tempus technology. This shows big cancer centers rely on AI and multimodal data to improve care.

• More than 50% of U.S. cancer doctors use Tempus tools for sequencing and finding clinical trials. This helps make personalized treatments more common across the country.

• Tempus works with 95% of the top 20 U.S. cancer drug companies. This close connection speeds up the process of getting new drugs to patients everywhere.

For administrators and IT managers, these facts show why preparing for AI system integration is important. Using these tools not only improves patient care but also helps clinics stay competitive.

AI-Enabled Patient Engagement Tools

AI platforms also offer tools that help patients manage their health. Tempus created “olivia,” an AI personal health assistant app for cancer patients and caregivers. Olivia helps users organize their health data, keep track of treatments, and learn about clinical trials and therapy options.
This kind of app helps patients take charge of their care, follow treatment plans better, and communicate more easily with their doctors.

Looking Ahead at AI and Multimodal Data in Oncology

• These technologies give cancer doctors deeper understanding about molecules that guide what treatments to choose.

• They help improve how early and accurately doctors can find cancer or its return.

• They connect patients to clinical trials more quickly.

• They support regular and efficient patient communication through automation.

• All of this helps produce better treatment results.

Medical administrators and IT staff should think about how to update their systems and workflows to use these technologies. Working with AI providers, investing in data systems, and training staff will be important steps.
As multimodal real-world data becomes a key part of cancer care, oncology practices that use AI tools will be better at helping patients and running efficiently.