** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** DESPITE MORE THAN 150 YEARS OF RESEARCH, LIPID OXIDATION REMAINS A MAJOR CHALLENGE FOR THE FOOD INDUSTRY DUE TO THE COMPLEXITY OF THE PRODUCTS AND THE MULTIPLE ELEMENTS THAT INFLUENCE OXIDATION. BESIDES THE ECONOMIC LOSSES, RANCID FOOD CAN ALSO AFFECT THE HEALTH OF CONSUMERS. TO CONTROL THIS PROCESS, ANTIOXIDANTS ARE COMMONLY ADDED TO FOODS, OFTEN IN COMBINATIONS OF TWO OR MORE COMPOUNDS. THIS APPROACH CAN EFFECTIVELY INCREASE THE TOTAL ANTIOXIDANT CAPACITY OF THE MIXTURE AND ALLOWS ONE TO DECREASE THE TOTAL AMOUNT OF ANTIOXIDANT USED AND/OR EXTEND THE SHELF-LIFE OF FOODS. ONE ISSUE WITH THIS STRATEGY IS THAT PREDICTING THE INTRICATE INTERPLAY OF VARIABLES INVOLVED IN THESE INTERACTIONS REMAINS A SIGNIFICANT SCIENTIFIC CHALLENGE. THUS, OUR GROUP SEEKS TO LEVERAGE THE POWER OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE TO STREAMLINE THE DEVELOPMENT OF NOVEL ANTIOXIDANT FORMULATIONS. WE AIM TO DEVELOP A ROBUST AI MODEL THAT CAN SIGNIFICANTLY ACCELERATE THE DISCOVERY AND VETTING OF NEW ANTIOXIDANT COMBINATIONS THAT WILL ENHANCE FOOD SAFETY AND ENSURE THE STABILITY OF FATS AND OILS THAT ARE CRITICAL TO THE FOOD SUPPLY CHAIN.