title: Physicochemical signatures of nanoparticle-dependent complement activation.
abstract: Nanoparticles are potentially powerful therapeutic tools that have the capacity to target drug payloads and imaging agents. However, some nanoparticles can activate complement, a branch of the innate immune system, and cause adverse side-effects. Recently, we employed anin vitro hemolysis assay to measure the serum complement activity of perfluorocarbon nanoparticles that differed by size, surface charge, and surface chemistry, quantifying the nanoparticle-dependent complement activity using a metric called Residual Hemolytic Activity (RHA). In the present work, we have used a decision tree learning algorithm to derive the rules for estimating nanoparticle-dependent complement response based on the data generated from the hemolytic assay studies. Our results indicate that physicochemical properties of nanoparticles, namely, size, polydispersity index, zeta potential, and mole percentage of the active surface ligand of a nanoparticle, can serve as good descriptors for prediction of nanoparticle-dependent complement activation in the decision tree modeling framework.
authors.affiliation: Knowledge Discovery and Informatics, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
authors.forename: Dennis G
authors.initials: DG
authors.lastname: Thomas
authors.affiliation: Knowledge Discovery and Informatics, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
authors.forename: Satish
authors.initials: S
authors.lastname: Chikkagoudar
authors.affiliation: Applied Statistics and Computational Modeling, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Heredia-Langer
authors.affiliation: Applied Statistics and Computational Modeling, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
authors.forename: Mark F
authors.initials: MF
authors.lastname: Tardiff
authors.affiliation: Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA.
authors.forename: Zhixiang
authors.initials: Z
authors.lastname: Xu
authors.affiliation: Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
authors.forename: Dennis E
authors.initials: DE
authors.lastname: Hourcade
authors.affiliation: Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
authors.forename: Christine T N
authors.initials: CT
authors.lastname: Pham
authors.affiliation: Division of Cardiology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
authors.forename: Gregory M
authors.initials: GM
authors.lastname: Lanza
authors.affiliation: Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA.
authors.forename: Kilian Q
authors.initials: KQ
authors.lastname: Weinberger
authors.affiliation: Knowledge Discovery and Informatics, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
authors.forename: Nathan A
authors.initials: NA
authors.lastname: Baker