Aging Solutions Inc

NOVEL ISOTOPIC SPECTROSCOPY IMAGING TOOLS FOR ADVANCING TARGETED ALPHA CANCER THERAPIES - PROJECT SUMMARY / ABSTRACT TARGETED ALPHA THERAPY IS AN EMERGING TECHNIQUE FOR TREATING CANCER SHOWING GREAT PROMISE TO DELIVER A PRECISE AND POTENT CELL-KILLING TREATMENT TO MULTIPLE CANCER VARIETIES. THE DESIGN OF THESE TARGETED RADIOPHARMACEUTICALS COMBINES A TUMOR- SELECTIVE CARRIER MOLECULE BOUND TO AN ALPHA-PARTICLE-EMITTING RADIONUCLIDE. THE CARRIER MOLECULE SELECTIVELY BINDS TO THE INTENDED CANCER CELLS, AND THE LIMITED LETHAL SPATIAL RANGE OF ALPHA PARTICLES EMITTED BY THE ATTACHED RADIONUCLIDE YIELDS A TARGETED THERAPEUTIC EFFECT BY DESTRUCTION OF THE CANCER CELLS. RESEARCHERS ARE DESIGNING A VARIETY OF CARRIER MOLECULES AND EXPERIMENTING WITH RADIONUCLIDE ISOTOPES TO GET THE BEST THERAPEUTIC EFFECT. THE NOVELTY OF THE FIELD MEANS THAT TOOLS ARE STILL LACKING TO HELP RESEARCHERS AND OTHER MEDICAL INNOVATORS TO (1) CHARACTERIZE THE SPATIAL DISTRIBUTION OF THE THERAPEUTIC RESULTING FROM CARRIER MOLECULE DESIGN AND (2) FULLY UNDERSTAND THE FATE OF THEIR CHOSEN ISOTOPES WHICH CHAIN-WISE DECAY INTO PROGENY ISOTOPES WHICH MAY HAVE DIFFERENT AFFINITIES, TOXICITIES, AND EFFECTS. OUR GOAL IN THIS GRANT IS TO DEVELOP AN INNOVATIVE, QUANTITATIVE RADIATION IMAGING TOOL THAT ALLOWS RESEARCHERS AND RADIOPHARMACEUTICAL DEVELOPERS TO NOT ONLY SEE THE SPATIAL DISTRIBUTION OF TARGETED ALPHA THERAPY MOLECULES AT A NEAR-CELLULAR LEVEL, BUT TO ALSO SEE THE EMITTING MOLECULES LABELED BY THEIR EMITTING ISOTOPE, EFFECTING A FORM OF ISOTOPIC SPECTROSCOPY. THIS WORK BUILDS UPON OUR PREVIOUS RESEARCH IN WHICH WE DEMONSTRATED A NON-OPTIMIZED BUT INNOVATIVE ALGORITHM FOR LABELING PARENT AND PROGENY ISOTOPES. WE NOW AIM TO REFINE THIS ALGORITHM TO ACHIEVE REAL-TIME ISOTOPIC SPECTROSCOPY, COMBINE IT WITH A HIGHLY OPTIMIZED HARDWARE DESIGN FOR ISOTOPIC IMAGING, AND BRING THE COMBINED RESULT TO MARKET. THIS DEVICE WILL BE AN EXTREMELY USEFUL TOOL FOR RADIOPHARMACEUTICAL EXPERTS, PRODUCING QUANTITATIVE, QUALITY-ASSURED RESULTS TO SUPPORT THEIR DEVELOPMENT OF THE NEXT GREAT CANCER TREATMENTS. WE BELIEVE THIS PROJECT BRINGS TOGETHER OUR EXPERTISE IN IMAGE SCIENCE, REAL-TIME ALGORITHM DESIGN, AND PRODUCT DEVELOPMENT TO PRODUCE AN INVALUABLE TOOL FOR RESEARCHERS WORKING IN THIS MOST-PROMISING AREA OF CANCER THERAPY RESEARCH.

PURPOSE: THIS PHASE II PROJECT PROPOSES THE DEVELOPMENT OF AN INTERPRETABLE AI/DEEP LEARNING SYSTEM, THAT TOGETHER WITH THE HYPERSPECTRAL IMAGING SYSTEM DETECTS CELL VIABILITY, GLUCOSE AND LACTATE CONCENTRATION AND ANTIBODY GLYCOSYLATION AND AGGREGATION USING LABEL-FREE CONTACTLESS HYPERSPECTRAL IMAGES IN THE SWIR SPECTRAL RANGE OF CELL CULTURE SAMPLES CONTAINING CHINESE HAMSTER OVARY (NISTCHO) CELLS GROWN IN FED-BATCH MODE IN A 3L BIOREACTOR. COLLECTIVELY, THIS WORK WILL ADVANCE THE SAFE AND EFFICIENT ADOPTION OF CONTACTLESS AI/DEEP LEARNING SENSING SYSTEMS FOR FINE CONTROL OF A VARIETY OF BIOREACTOR ENVIRONMENTS.ACTIVITIES TO BE PERFORMED: PHASE II ACTIVITIES TO BE PERFORMED WILL CONSIST OF RESEARCH AND DEVELOPMENT FOR PREDICTING MAB QUALITY ATTRIBUTES SUCH AS GLYCOSYLATION, AGGREGATION AND DEAMIDATION FOR FINE ONLINE QUALITY CONTROL IN REAL-TIME.EXPECTED OUTCOMES: OUTCOMES RESULTING FROM THIS PHASE II PROJECT IS EXPECTED TO ADVANCE THE SAFE AND EFFICIENT ADOPTION OF CONTACTLESS AI/DEEP LEARNING SENSING SYSTEMS FOR FINE CONTROL OF A VARIETY OF BIOREACTOR ENVIRONMENTS.INTENDED BENEFICIARIES: ADVANCED BIOLOGICS MANUFACTURERS, HEALTHCARE IT COMPANIES, AND THE LIFE SCIENCES INDUSTRY.SUBRECIPIENT ACTIVITIES: THE APPLICANT HAS PROPOSED TO MAKE A SUBAWARD TO UNIVERSITY OF MARYLAND, COLLEGE PARK.

PURPOSE: THERE CURRENTLY EXISTS A NEED IN THE BIOPHARMACEUTICAL INDUSTRY FOR A SENSOR TO ACCURATELY DETECT CELL AND METABOLITE PROPERTIES IN REAL TIME. RESEARCHERS IN THIS PHASE I PROPOSE TO DEVELOP AN ARTIFICIAL INTELLIGENCE (AI) DEEP LEARNING SYSTEM THAT SEEKS TO FILL THIS NEED.ACTIVITIES TO BE PERFORMED: ACTIVITIES TO BE PERFORMED WILL INCLUDE CONDUCTING EXPERIMENTS, CALIBRATIONS, MEASUREMENTS, AND TESTS TO PROVE THE FEASIBILITY OF THE RESEARCH.EXPECTED OUTCOMES: THIS RESEARCH WILL ADVANCE THE SAFE AND EFFICIENT ADOPTION OF CONTACTLESS (AI) DEEP LEARNING SENSING SYSTEMS FOR CONTROL OF A VARIETY OF BIOREACTOR ENVIRONMENTS.INTENDED BENEFICIARIES: THIS RESEARCH WILL BENEFIT THE BIOPHARMACEUTICAL INDUSTRY AND THE NEAR INFRARED (NIR) AND RAMAN SPECTROSCOPY MARKET.SUBRECIPIENT ACTIVITIES: THE RECIPIENT PLANS TO SUBAWARD FUNDS FOR DEVELOPMENT OF ALGORITHMS, DATA ANALYSIS AND RELATED EXPERIMENTS.