Goals of Formulation

In household cleaning the consumer has several options of avoiding skin contact such as 

This is not to say that surfactants or surfactant-like compounds are absolutely risk-free. However, the risk, in some cases, is from the contaminants that may accompany the surfactants, rather than from the surfactants themselves. An example of this was seen a few years ago in the concern over nitrosamine contamination of amine oxide surfactants, either from their manufacture or from the circumstances of their formulation. For example  

This was a serious concern that was approached by processing technology. 

The choice of surfactant(s) for the formula often has a very direct effect on cleaning, skin irritation, shine, and effort. Surfactant choice has a more indirect effect on surface safety, time, task pleasanmess, and surface conditioning. These aspects are more often controlled by other formula ingredients or even packaging. However, surfactants can also contribute to these as well, as shall 

Another consideration of formulators is that consumers, as stated above, do not view products as being as neatly compartmentalized as manufactmers do. When a consumer wishes to clean a dirty bathtub, for example, they may have tried a cleanser, a dilutable APC, and a specialty spray soap scum ranover to do the job. All of these products are competing for the same job—cleaning soap scum from the bathtub surface. The consumer may use any or all of them to get the job done, according to their own personal standard of cleanliness, desire to apply elbow grease, and evaluation of the surface condition (new or worn, sensitive or impervious, etc.). 

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The goal of formulation development is to design a quality product and its manufacturing process to deliver consistently the intended performance of the product. A good formulation must be manufacturable, chemically and physically stable throughout the manufacturing process and product shelf-life, and bioavailable upon administration. It also must meet many other quality standards and special requirements to ensure the efficacy and safety of the product. 

Now that all the experimental work has been presented in the preceding chapters, the opportunity arises to survey what has been accomplished. In the next section we will evaluate whether or not the goals as formulated at the end of Chapter 1 have been reached. 

In 1982 a study of the usefulness of DBBF in the production of a blood substitute was reported (99). A single modification achieved the dual goals of reduced oxygen affinity and restricted tetramer—dimer dissociation. This work was confirmed in 1987 (98). The product, called aa-hemoglobin, was formulated in Ringer s lactate. P q under physiologic conditions is 3.7 kPa (28.0 torr). Hill s parameter is 2.2, and the Bohr effect was reduced (100). Plasma retention was increased, and the product appeared to be less heterogeneous than some of the other derivatives under study. Its production was scaled up by Baxter Healthcare Corp., under contract to the U.S. Army. 

The goal of approximate and numerical methods is to provide convenient techniques for obtaining useful information from mathematical formulations of physical problems. Often this mathematical statement is not solvable by analytical means. Or perhaps analytic solutions are available but in a form that is inconvenient for direct interpretation... 

Scientists commonly interpret a theory in terms of a model, a simplified version of the object of study. Like hypotheses, theories and models must be subjected to experiment and revised if experimental results do not support them. For example, our current model of the atom has gone through many formulations and progressive revisions, starting from Dalton s vision of an atom as an uncut-table solid sphere to our current much more detailed model, which is described in Chapter 1. One of the main goals of this text is to show you how to build models, turn them into a testable form, and then refine them in the light of additional evidence. 

The goal of all fabricators is to minimize the cycle time and maintain part quality. The process parameters involved are winding speed, mold and press temperatures and polymer formulation. 

Lidocaine (112), xyloceiine, and dibucaine (113) have been formulated in homo- and copolymers of lactide and glycolide. The goal of these studies has been relatively short-term (24-hr) controlled release of the anesthetic. Injectable microcapsules of lidocaine hydrochloride were produced by an air suspension coating technique and administered i.m. to rabbits (112). Serum levels of Udocaine indicated an initial rise over the first 2 hr and then a gradual decline with clearance after about 8-10 hr. 

A unique method of formulating delivery systems based on starch/ PLA systems was studied (138). In that approach, the goal was to provide a better matrix for delivery of high molecular weight hydrophilic molecules. A hydrophilic material, starch, was combined through graft polymerization to PLA. The carbolactic polymers were then used to entrap bovine serum albumin in microspheres. 

The formulation of objective functions is one of the crucial steps in the application of optimization to a practical problem. As discussed in Chapter 1, you must be able to translate a verbal statement or concept of the desired objective into mathematical terms. In the chemical industries, the objective function often is expressed in units of currency (e.g., U.S. dollars) because the goal of the enterprise is to minimize costs or maximize profits subject to a variety of constraints. In other cases the problem to be solved is the maximization of the yield of a component in a reactor, or minimization of the use of utilities in a heat exchanger network, or minimization of the volume of a packed column, or minimizing the differences between a model and some data, and so on. Keep in mind that when formulating the mathematical statement of the objective, functions that are more complex or more nonlinear are more difficult to solve in optimization. Fortunately, modem optimization software has improved to the point that problems involving many highly nonlinear functions can be solved. 

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