BETA What are computational models, and how are they used in personalizing treatments?

In this Health Tree University lesson, we break down what computational models really are, how they work, and why they're becoming a game changer in personalizing treatment for multiple myeloma. Learn how artificial intelligence and big data are helping doctors tailor therapies with greater accuracy than ever before. Whether you're a patient, caregiver, or just curious about precision medicine, this is your crash course into the future of myeloma care. Don't forget to like, subscribe, and turn on notifications to stay updated on the future of healthcare. What are computational models? Computational models are trying to be more sophisticated at estimating patients' prognosis. We use lots of data points to put into a statistical model to try and estimate an individual's risk of progression. Conventionally, we would look at a few markers, maybe genomic alterations such as translocations or deletions in tumor cells. We would just use a handful of these markers to try and estimate someone's prognosis. That was really based off of a populational data. I can estimate the prognosis of a population of myeloma patients, but it doesn't translate as well to an individual. We know many individuals who have a specific translocation that's high risk, yet they do very, very well. That's where the computational models fit in, is to try and take into account more factors, both clinical factors, genetic factors, and crunch the numbers and basically provide a more realistic estimate for that individual. What is the University of Miami's Individual Risk Myeloma Assessment, or IRMA, computational model? The IRMA model, or I-R-M-A, is the Individual Risk Myeloma Assessment model. This is a model that was developed at the University of Miami. It allows physicians to use DNA sequencing in combination with clinical risk factors and to input this data into an online calculator. It will provide a report estimating a patient's prognosis. It will do so with greater accuracy than using standard staging type of information or just relying on one or two high risk markers. We believe it is a more sophisticated and accurate individual risk assessment. How can computational models improve precision medicine? Once we can more accurately assess an individual's risk of progression, we can be more confident in deciding the next treatment option for them. Perhaps it might be more aggressive treatment, like a autologous stem cell transplant, versus less aggressive treatment, maybe just continuing on with maintenance. These models, I think, will allow us to not treat a patient like they are a population, but more as an individual. If you found this lesson helpful, consider giving us a like and be sure to watch the other lessons in Health Tree University's Precision Medicine in Multiple Myeloma course. Our mission is to educate patients and their care partners and spread awareness about multiple myeloma. We'd like to thank our doctors, our sponsors, and of course our audience for making this video possible.