Infleqtion, the world’s quantum information company, announced that it had been awarded funding from Wellcome Leap’s Quantum for Bio (Q4Bio) program with a team of renowned researchers and medical doctors at the University of Chicago (UChicago) and Massachusetts Institute of Technology (MIT). This collaborative effort aims to transform cancer care by harnessing the power of artificial intelligence (AI) and quantum algorithms to drive personalized diagnostics and treatments. Founded by the Wellcome Trust in 2020, Wellcome Leap is a U.S. non-profit that builds and executes bold, unconventional programs designed to increase the number and speed of breakthroughs in human health.
The Q4Bio program brings together highly skilled and multidisciplinary teams with cross-institution collaborations. The team led by Infleqtion, a company with extensive experience in commercializing quantum technologies, includes leaders in quantum computing (QC), algorithm development, multimodal genomics, and clinical cancer care.
Dr. Frederic Chong, Chief Scientist for Quantum Software at Infleqtion and the Seymour Goodman Professor of Computer Science at the University of Chicago, and Teague Tomesh, a Quantum Software Engineer at Infleqtion, both bring expertise in QC systems and cross-layer optimizations. Dr. Alexander T. Pearson, a clinical oncologist and Associate Professor of Medicine at the University of Chicago, contributes his knowledge in computational oncology and digital pathology. Dr. Samantha Riesenfeld, an Assistant Professor of Molecular Engineering and Medicine at the University of Chicago, adds her expertise in genomic data science and systems immunology. Dr. Aram Harrow, a Professor of Physics at MIT, is a renowned quantum algorithms developer.
Together, the team is uniquely positioned to leverage their powerful computational resources to develop quantum cancer biomarker algorithms. This ambitious project will integrate diverse data modalities, including genomics, transcriptomics, and pathology, utilizing advanced AI and ML algorithms empowered by quantum computing capabilities.
“I am thrilled to work with the incredible team tackling this key biomedical challenge. We are thinking about cancer biomarker identification in new ways to take advantage of both multimodal biological data and the unique strengths and constraints of quantum computing systems,” said Dr. Samantha Riesenfeld.
Cancer, the second-leading cause of death in the United States, continues to be a significant health challenge. Last year, approximately 2 million new cases were diagnosed, and according to the Centers for Disease Control & Prevention, there is a projected 50% increase in new cancer cases between 2015 and 2050 as the population ages and more people are exposed to cancer-causing agents.
Despite the availability of extensive data, a big challenge lies in integrating and analyzing these data streams simultaneously to unravel the intricate biology of cancer and identify relevant subtypes. By incorporating diverse datasets, researchers can uncover previously undiscovered patterns and correlations, enabling more accurate prognostic assessments and treatment decisions.
“This proposal represents an exciting opportunity to test quantum machine learning algorithms on real-world data sets. The field will need empirical evaluation in order to move forward, and these hard problems with multiple forms of data make ideal challenges,” said Dr. Aram Harrow.
This approach can potentially increase the likelihood of early detection, precise prognostication, and tailored treatment plans, improving survival rates for cancer patients worldwide by ensuring patients receive treatments specifically designed to target the unique molecular characteristics of their cancer.
“This is a tremendous honor and validation of our commitment to driving transformative advancements in global health,” said Dr. Frederic Chong, the Chief Scientist for Quantum Software at Infleqtion. “Through our collaborations with the University of Chicago and MIT, we will unlock the potential of AI and quantum algorithms to derive knowledge across multiple forms of medical data, reshaping cancer diagnostics and treatment strategies. This represents a significant step forward in personalized medicine and offers hope to patients worldwide.”
Efficient healthcare systems are critical for delivering quality care. The program also aims to optimize healthcare systems by applying AI, ML, and quantum technologies. Leveraging quantum-enabled findings to streamline future data analysis, researchers and doctors can improve patient flow, resource allocation, and treatment planning, ultimately enhancing the efficiency and effectiveness of healthcare delivery.
“We are excited to partner with Infleqtion to tackle the pressing challenges in cancer diagnostics and treatments. By combining our expertise in research, medicine, and quantum technologies, we have the opportunity to make significant strides in personalized oncology. Our collaborative efforts have the potential to transform patient outcomes and advance the field of cancer care,” said Dr. Alexander T. Pearson.
SOURCE: PRNewswire
