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Welcome to the Empowered Patient Podcast with Karen Jagoda.  This show is a window into the latest innovations in applying generative AI, novel therapeutics and vaccines, and the changing dynamics in the medical and healthcare environment. One focus is on how providers, pharmaceutical companies, and payers are empowering patients.  In addition, conversations are often about how providers, care facilities, pharmaceutical companies, and payers are being empowered by technology to improve patient outcomes and reduce friction across the healthcare landscape.

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  • Virtual and digital health
  • Use of AI, ML, and LLM in healthcare and drug discovery, development, trials
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  • Next-generation immuno, cell, and gene therapies
  • Vaccines
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The audience includes life science leaders, researchers, medical professionals, patient advocates, digital health entrepreneurs, patients, caregivers, healthcare solution providers, students, journalists, and investors. 

 

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Empowered Patient Solutions

Aug 9, 2023

Tuvik Beker, CEO, and Ranit Aharonov, CTO of Pangea Biomed, have designed ENLIGHT, a computational platform driving precision oncology that matches cancer tumors with available therapies. Drawing on an understanding of synthetic mortality and synthetic rescue, this approach focuses on how the interaction between genes increases or decreases the tumor cell's fitness and the likely response to a drug. Determining which populations might benefit most from a drug opens the door to new treatments for common and rare diseases.

Tuvik explains, "When we match therapies to patients, just according to the pure genetic characteristics of the tumor, sometimes we miss potential therapies, and sometimes we give patients therapies that do not work very effectively. To solve that, we developed ENLIGHT, which looks at the broader characteristics of the tumor, not just at the target gene, but multiple interactions, and that way, we can find potential therapies that are missed by the current guidelines and common biomarkers."

Ranit elaborates, "So when we search for these interactions between genes, we look at a lot of available cancer data. We have a large database of a lot of cell lines that were treated and human tumors, and we know the survival of the patients and so on, but we don't need to know anything about what drugs they got. Our algorithms allow us, by looking at a lot of correlations between different activations of genes and survival and what happens to cells, we are able to find what are the pairs in the entire genome of genes that their co-activation affects the fitness or the tumor survival. And by knowing this, you can think of it as a sort of vulnerability map of tumors."

"One of the things I haven't yet described and I think wouldn't have happened without this revolution is that we can now move a step further. When we look at a patient's tumor, we don't necessarily need to measure the RNA expression or the activation of genes directly. We can look at the tumor through a microscope using standard histopathology slides, the ones with the bluish and pinkish coloring that have been used for decades and are really available everywhere."

#PrecisionsMedicine #Oncology #PrecisionOncology #RareDisease #Biotech #Startup #AI #MachineLearning

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