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KAUST participates in MIT Hacking Medicine event

KAUST ·

KAUST alumni and students participated in the first MIT Hacking Medicine event in the Middle East, held in Riyadh at Princess Nourah Bint Abdulrahman University. The event, organized by the MIT-Ibn Khaldun Fellowship Alumni Society and sponsored by King Abdulaziz City for Science and Technology, involved 100 participants working on healthcare, science, engineering, and business development problems. KAUST alumna Haleema Al Amri organized the University's participation, while KAUST alumna Ameerah Bokhari served as a mentor to participating teams. Why it matters: The event fosters collaboration and innovation in healthcare and technology, aligning with Saudi Arabia's focus on advancing these sectors through international partnerships and knowledge exchange.

A new model for drug development

MBZUAI ·

MBZUAI's Professor Le Song is developing an AI-driven simulation to model the human body at societal, organ, tissue, cellular, and molecular levels. The goal is to reduce the time and cost associated with bringing new medicines to market by removing the need for wet lab biological research. Song aims to create a comprehensive model using machine learning. Why it matters: This research could revolutionize drug discovery in the region by accelerating the development process and reducing reliance on traditional research methods.

Hacking the SARS-CoV-2 genome

KAUST ·

KAUST researchers are analyzing the SARS-CoV-2 genome to identify potential targets for treatment and vaccine development. They are using the KAUST Metagenome Analysis Platform (KMAP) and the university's supercomputer to compare and analyze genomic data. The research focuses on identifying key genes for detection and treatment of COVID-19. Why it matters: This research contributes to the global effort to combat the pandemic and highlights KAUST's capabilities in genomic data analysis and computational bioscience.

Actionable and responsible AI in Medicine: a geometric deep learning approach

MBZUAI ·

Pietro Liò from the University of Cambridge will discuss geometric deep learning techniques for building a digital patient twin using graph and hypergraph representation learning. The talk will focus on integrating Computational Biology and Deep Learning, considering physiological, clinical, and molecular variables. He will also cover explainable methodologies for clinicians and protein design using diffusion models. Why it matters: This highlights the growing interest in applying advanced AI techniques like geometric deep learning and diffusion models to healthcare challenges in the region, particularly for personalized medicine.

Big-model AI in drug design

MBZUAI ·

MBZUAI hosted a two-day workshop on "Big Model AI in Drug Design" starting February 20, 2023. The workshop featured presentations from researchers in public and private institutions working on AI and health. MBZUAI Adjunct Professor Eran Segal opened the workshop with a talk on the Human Phenotype Project. Why it matters: The event highlights the growing interest and activity in applying AI, particularly large models, to advance drug discovery and personalized medicine within the UAE's research ecosystem.

WEP 2020: A futuristic approach to medicine

KAUST ·

KAUST's 2020 Winter Enrichment Program (WEP) focused on 'Personalized Medicine' with lectures and workshops from international and local speakers. Topics ranged from health management technology to digital health, encompassing various disciplines at KAUST. HRH Dr. Maha Bint Mishari AlSaud and Rene Frydman were among the keynote speakers. Why it matters: The program highlights KAUST's commitment to advancing precision medicine and fostering interdisciplinary collaboration in healthcare innovation within the Kingdom.

Personalized medicine based on deep human phenotyping

MBZUAI ·

Eran Segal from Weizmann Institute of Science presented The Human Phenotype Project, a large-scale prospective cohort with over 10,000 participants. The project aims to identify novel molecular markers and develop prediction models for disease onset using deep profiling. The profiling includes medical history, lifestyle, blood tests, and molecular profiling of the transcriptome, genetics, microbiome, metabolome and immune system. Why it matters: Such projects demonstrate the growing focus on personalized medicine in the region, utilizing advanced AI and machine learning techniques for disease prevention and treatment.

Inaugural hackathon explores AI healthcare solutions

MBZUAI ·

MBZUAI and the Weizmann Institute of Science (WIS) jointly hosted the inaugural Human Phenotype Project Hackathon in Abu Dhabi, focusing on AI-driven healthcare solutions. 24 postgraduate students and researchers analyzed "real data" from a deep-phenotype multi-omic biobank to develop personalized and predictive analytics. The hackathon utilized data from WIS and Pheno.AI’s Human Phenotype Project (HPP) in Israel, marking the first time an international university has been granted access to this data. Why it matters: This collaboration demonstrates the growing emphasis on leveraging AI for healthcare innovation in the UAE and fostering international partnerships to address global health challenges.