1 / 16

Research Summary 06/2010

Dr. Andrej Mošat` Prof. A. Linninger, Laboratory for Product and Process Design, M/C 063 University of Illinois at Chicago 23 Jun 2010. Research Summary 06/2010. Kinetic Inversion for Drug Delivery. Advances in algorithms:

Download Presentation

Research Summary 06/2010

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Dr. Andrej Mošat` Prof. A. Linninger, Laboratory for Product and Process Design, M/C 063University of Illinois at Chicago 23 Jun 2010 Research Summary 06/2010

  2. Kinetic Inversion for Drug Delivery Advances in algorithms: • Working on Solvers.V6 – 50% donenew: function minimizers,much improved: linear algebra, integrators • Constrained optimization available LANCELOT: a Fortran Package for Large-Scale Nonlinear Optimization (Release A), by A. R. Conn, N. I. M. Gould and Ph. L. Toint, Springer Series in Computational Mathematics, Volume 17, Springer Verlag (Heidelberg, New York), ISBN 3-540-55470-X, 1992.- equality constraints- inequality constraints- bounds on variables

  3. Constrained optimization example: A trifurcation

  4. First principle model

  5. Kinetic Inversion on Cyclosporine A case

  6. Kinetic Inversion on Cyclosporine A case Tanaka’s (Cierra’s) Silicone Rat Heart: 4 ChambersSmooth muscle

  7. Autoregulation on a model of vasculature

  8. Semester Plan

  9. First principle model

  10. Empirical model vs. First principle model

  11. Approach to PBPK Modeling using Vasculature Network 1. 2. Intrinsic Hepatic Clearance Tanaka: CLi = F(Hct, t, organ type)Our proposal: CLi = F(Hct) => const. 4. Vasculature network combined with “tissue equations” Result:CCyA,i=F(t) 3. Kinetic organ models:F(CCyA(t, injection, CLliver, CLorgans ), params(Cplasma) ) 5. KIP for 1 parameter: CLi

  12. Literature Review Cierra found: Gueorguieva, I.; Aarons, L.; Ogungbenro, K.; Jorga, K.; Rodgers, T. & Rowland, M. Optimal Design for Multivariate Response Pharmacokinetic Models Journal of Pharmacokinetics and Pharmacodynamics, 2006, 33, 97-124 “We assume that measurements made at distinct times are independent, but measurements made of each concentration are correlated with a response variance--covariance matrix. “

  13. Outlook • Test rSQP for KIP of a “Rat50” model • Research Global optimization methods • Outline of a paper • REU preparation

  14. Experiment: Rats’ Blood and Tissue concentrations of CyA Blood Tissue concentration-to-time profiles of CyA in various organs of rats after 1.2- (circles), 6- (squares), and 30- (triangles) mg/kg doses. Each measurement in the unit of mg/ml or g represents an average value from three rats with S.D. (vertical bar). The solid line is log-linear interpolation between the measurements.

  15. ODE Solvers overview at our disposal

More Related