Partelligence

Abstract Halo Labs proposes to developPartelligencea particle ID technique that enables accurate and rapid identification of contaminating particles in biopharmaceutical formulationsProtein therapeutics currently represent betweenandof the overall pharmaceutical marketThe primary concern for this class of therapeutics is that they can elicit an immune response from patients who develop antidrug antibodiesThe drug s effect is therefore eliminated betweenandpercent of patients who return to their original disease stateThe presence of particulate matter in these therapeuticse gshed glass from a syringe or a protein aggregatecan enhance this immune response anddue to the patient safety risk the FDA regulates the amount of particles that can be presentThere are always some number of particles in each injected sampleand although their presence can be detectedthey don t know what the particles actually areA QC tool that can identify the particles would help manufactures trace them back to their sourcee ga bad lot of syringesand eliminate themPartelligence aims to make particle identification routine in biopharma QCThe technology builds off our current instrumentHorizonwhich was launched in midand already sold to some of the world s largest pharmaceutical companiesThe technique works by analyzing several combinatorial features including sizemorphologyoptical contrastand intrinsic fluorescenceand in this proposal we will test which features are key to enable the most accurate and rapid particle recognitionTo datewe have performed feasibility experiments validating our ability to identify a few commonly found particles in biopharma solutionsGiven thisour goals in Phase I are to expand on these studies by building a comprehensive training set and by testing a number of different algorithmsWe will first start with reference samplesand then move to real biopharmaceutical samples provided by our pharma collaboratorsAt the end of the studywe will do a feasibility analysis to determine if the throughputspecificity and reliability meets the needs of the industry Narrative We propose to evaluate a particle recognition technique to enable accurate and rapid identification of unwanted contaminating particles in biopharmaceutical formulationsSuccessful development of this analytical technique would improve bioprocess control by identifying dangers early on in development and throughout the manufacturing processresulting in safer protein drugsreduced recalls and shortened time to market