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Iterative optimization, tissue

Figure 1. Schematic of the iterative optimization approach to designing a tissue engineering scaffold with the addition of a biologically active peptide. Figure 1. Schematic of the iterative optimization approach to designing a tissue engineering scaffold with the addition of a biologically active peptide.
Metabolic control analysis (MCA) assigns a flux control coefficient (FCC) to each step in the pathway and considers the sum of the coefficients. Competing pathway components may have negative FCCs. To measure FCCs, a variety of experimental techniques including radio isotopomers and pulse chase experiments are necessary in a tissue culture system. Perturbation of the system, for example, with over-expression of various genes can be applied iteratively to understand and optimize product accumulation. [Pg.356]

The development of in vitro assays using animal tissues became an essential support tool for tracking structure-activity relationships (SAR) and allowing chemists to optimize structures before whole animal testing. This allowed a wide range of compounds to be made around a SAR hypothesis. If the lead compound subsequently failed in animal testing, new compounds could be made based on the in vitro SAR and retested in the animal model. In this iterative process, potency and other druglike properties could be "built in" to the lead structure in a coordinated, planned fashion and tested. [Pg.40]


See other pages where Iterative optimization, tissue is mentioned: [Pg.345]    [Pg.433]    [Pg.98]    [Pg.276]    [Pg.39]    [Pg.192]    [Pg.253]   


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