Functionality-related characteristics

European Pharmacopoeia. 2008. <5.15> Functionality-related characteristics of excipients, 6th ed. 

The Ph. Eur. monograph Pharmaceutical Preparations states When physico-chemical characteristics of active substances and functionality-related characteristics (FRCs) of excipients (e.g. particle-size distribution, viscosity, polymorphism) are critical in relation to their role in the manufacturing process and quality attributes of the pharmaceutical preparation, they must be identified and controlled. ... 

The section titled labelling describes any specific information that should be included on the label, including any quality relevant parameters, for example a certain viscosity gradient for cellulose derivatives. Those parameters are called functionally related characteristics (FRCs). 

Subsequently, the BPI provides a Ust of all active substances and excipients, in a way that defines their identity and quality unambiguously. For example, it should be clear if the free active substance has to be used or the salt form, or, when multiple hydrates exist, which hydrated form is required (see Sect. 23.1).To define the quality of the raw materials it is advisable to use their pharmacopoeial names wherever possible. Preferably, additional specifications (Functional related characteristics, FRCs) which are not mentioned in the monograph that distinguish between different qualities, are added to the name of the raw material. Examples are the particle size of a solid material, the viscosity of a liquid or a cellulose derivative, or the concentration of a solution. Sometimes a brand name reflects the quality better (e.g. Witepsol H15 instead of Adeps solidus). If confusion may stiU be possible (crystal water, salt forms), addition of the chemical formula might be useful. 

The section includes the specifications for the raw materials and containers to be used. Preferably raw materials of a suitable pharmaceutical grade should be used (see Sect. 23.1.2), but this may not always be possible. All the considerations that played a role in the choice of the raw materials are recorded in this section, including the excipients, preservatives, colourants and flavours. Amounts and calculated doses are mentioned, and the need for specific properties (Functionally Related Characteristics) such as purity, fineness or viscosity where this is essential for the firtal quality. 

There exists a form of energy, known as internal energy, which for. systems at internal equilibrium is an intrinsic propei ty of the. system, functionally related to its characteristic coordinates. 

You should be able to fill in the gaps and finish the rest of the work in deriving the transfer functions. In this case, we may want to use the steam mass flow rate as the manipulated variable. The transfer function relating its effect on T will be second order, and the characteristic polynomial does not have the clean form in simpler textbook examples. 

A general principle is governing the relation between physical parameters and underlying distribution functions. Its paramount importance in the field of soft condensed matter originates from the importance of polydispersity in this field. Let us recall the principle by resorting to a very basic example molecular mass distributions of polymers and the related characteristic parameters. 

The structural hypothesis, which was formulated in response to observations that axonal transport rate components move as discrete waves, each with a characteristic rate and a distinctive composition, can explain the coherent transport of functionally related proteins and is consistent with the relatively small numbers of motor molecules in neurons. The only assumption is that the number of elements that can interact with transport motor complexes is limited, and this requires appropriate packaging of the transported material. Different rate components result from packaging of transported material into different, cytologically identifiable, structures. In fact, the faster rates reflect the transport of proteins preassembled as membranous organelles, including vesicles and... 

Another aspect of matching output to user needs involves presentation of results in a statistical framework—namely, as frequency distributions of concentrations. The output of deterministic models is not directly suited to this task, because it provides a single sample point for each run. Analytic linkages can be made between observed frequency distributions and computed model results. The model output for a particular set of meteorologic conditions can be on the frequency distribution of each station for which observations are available in sufficient sample size. If the model is validated for several different points on the frequency distribution based on today s estimated emission, it can be used to fit a distribution for cases of forecast emission. The fit can be made by relating characteristics of the distribution with a specific set of model predictions. For example, the distribution could be assumed to be log-normal, with a mean and standard deviation each determined by its own function of output concentrations computed for a standardized set of meteorologic conditions. This, in turn, can be linked to some effect on people or property that is defined in terms of the predicted concentration statistics. The diagram below illustrates this process ... 

The velocity of ideal deton is completely determined by the thermohydrodynamics of the explosive, with.the independent variables being the original density p of the expl and its chem compn, all quantities being calculable, at least in principle, thru the thermohydrodynamic theory and an apppropriate equation of state. For each given ideal explosive, velocity. is a function only of the original density, i.e., D=D(p ), but three fundamentally different types of D(p ) relations have been found in ideal deton. The most common is the linear D(p ) relation characteristic of solid C-H-N-0 expls at densities... 

A mathematical model is expressed as an equation or a system of equations. The variables involved correspond to measurable or calculable characteristics of a real process or operation. They are functionally related to each other so that they behave much as the variables in the real system that they simulate. Some of the variables may assume, at least over a limited range, any values at the discretion of the operations planner. Others may be determined by external factors. Still others are the dependent variables, or responses, of the system. The convenient prediction of these responses for chosen values of the controllable variables is the principal reason for the formulation of a mathematical model. 

Worldwide food trade as well as customers expectations regarding foodstuffs enforce implementation of measures which improve sensory, physicochemical, functional, and health-related characteristics of food products. Food producers themselves, aware of the importance of product quality, do not neglect the question of sensory, visual, and marketing features of food products. This, along with the required economic efficiency, encourages food manufacturers to use various additives in food processing technologies, which improve the characteristics of food products demanded by shoppers. In short, food additives play an important role in today s complex food supply. 

Even without software support, the process engineer can still obtain certain predictions by a precise analysis of the processes involved. In this case, process-specific diagrams are very helpful. These illustrate, for example, the specific energy input (Fig. 11.9) or other quality-related characteristics as a function of viscosity, throughput, speed, or discharge pressure. With the aid of enthalpy (Fig. 11.10) as a physical, process-independent value, initial forecasts can be obtained as to the energy that will be required to melt a resin and to extrude at a specified end temperature. 

Interestingly, plant AGPs have been also impbcated in cellular processes that are identical to those described above for phytocyanins (Noth-nagel, 1997). As we have already mentioned, most phytocyanins in their mature form are predicted to be composed of a BCB domain and a domain with sequence characteristics reminiscent of those of described for AGPs. Thus, phytocyanins are interesting examples of the recently developed Rosetta stone sequence concept, which postulates that when two different proteins also occur in parallel as a fused, larger composite protein, it is an indication that they are functionally related and may even physically interact (Eisenberg et al., 2000 Marcotte, 2000). 

It is generally known that only a very limited number of packaging materials such as glass or metal provide absolute protection properties concerning the penetration of chemical compounds from layers behind or from the environment. In the case of multi-layers with plastics materials as functional barriers there occurs, in most cases to a certain extent, an unavoidable mass transfer from the plastics layers into the product. This must be understood as a functional quantity which, however, must comply with food regulations. Therefore it is necessary firstly to understand functional barrier characteristics and mechanisms and, secondly, to define the functional barrier efficiency in relation to food safety and to establish appropriate test methods. This is especially important with those food packaging applications where recycled plastics are covered by plastics functional barriers. 

Comparison of this result with Eq. (5.5) yields the simplest possible functional relation for V, namely, f T) = T. We conclude that the kelvin temperature scale, based on the properties of ideal gases, is in fact atliennodynamic scale, independent of the characteristics of any particular substance. Substitution of Eq. (5. TjintoEq. (5.2) gives ... 

The transfer function relates two variables in a process one of these is the forcing function or input variable, and the other is the response or output variable. The transfer function completely describes the dynamic characteristics of a system. The input and output variables are usually expressed in the Laplace domain and are written as deviations from the set-point values. 

The first term, Gexp is a constant characteristic of the experimental set-up used, while the remaining terms are predicted theoretically. B o), T) is a temperature function related to the Boltzman population factor n co)... 

Protein Components Principal Functions Structural Characteristics Related Figure(s) or Tables... 

The results of the waveform analysis show that for a pulse power of 210 Hz "theta Bl" and "theta M" obey the same functional relation during the pulse duration, the characteristic of a well-behaved adiabatic pulse. The excitation profile reveals for the x-and y-components intense flanks at +/- 1000 Hz either side of zero while the z profile has a value of -1 over a range of +/- 750 Hz either side of zero. With a pulse power of 160 Hz the excitation profile changes very little, the intensity of the flanks for the x- and y-components is reduced while the z-component is virtually unchanged. However the wave form analysis shows a deviation between "theta Bl" and "theta M" for the latter period of the pulse duration. "Theta M" corresponds to an oscillating function which describes an envelope of "theta B1" indicating that at this pulse power the 50 ms CHIRP pulse does not fulfil the requirements of a good adiabatic pulse. 

Newell and coworkers found that, during particular stages of fruit construction in Dictyostelium discoideum, four functionally related enzymes accumulated, reached characteristic levels of specific activity, and then disappeared partly or completely. These enzymes were UDP-d-glucose pyrophosphorylase, trehalose 6-phosphate synthetase, UDP-d-galactose 4-epimerase, and UDP-D-galactose polysaccharide n-galactosyl transferase. 

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