Pharmaceutical reality

SMB is now accepted as a real production tool. For instance, the Belgium pharmaceutical company U.C.B. Pharma announced recently the use of SMB for performing multi-ton scale purification of an enantiopure drug substance. The concept of large-scale purification of enantiomers using chromatographic techniques has moved from a dream to a reality within the last few years. 

Ultimately, software is bought to accomplish a business result. Therefore, software offerings in pharmaceutical R D ought to somehow accelerate R D productivity, or at least give cost savings along the pipeline. Yet the reality is that most scientific software is not sold on the basis of delivering... 

Figure 17.3 Pharmaceutical industry future reality tree.

Simulation is best described as the process of translating a real system into a working model in order to run experiments. A simulation does not duplicate a system rather it is an abstraction of reality using mathematics to express cause-and-effect relationships that determine the behavior of the system. Hence the representation displayed on a computer may not always be pictori-ally similar to the real system, and, if it is, then it must be regarded as an added bonus. Software for computer simulation is often customized and based on that developed in academia. There are not many commercial packages available for pharmaceutical formulation. 

I would like to thank Dr. Cynthia Randall of Sanofi Pharmaceuticals not only for an excellent contribution in the field of ion exchange chromatography presented as an update to Chapter 5, but also for substantial assistance in tracking down literature. Without her help and encouragement, the second edition would not have become reality. Thanks are also due to Denise Lawler, without whose help family obligations would have made this work impossible. 

Within the realm of physical reality, and most important in pharmaceutical systems, the unconstrained optimization problem is almost nonexistent. There are always restrictions that the formulator wishes to place or must place on a system, and in pharmaceuticals, many of these restrictions are in competition. For example, it is unreasonable to assume, as just described, that the hardest tablet possible would also have the lowest compression and ejection forces and the fastest disintegration time and dissolution profile. It is sometimes necessary to trade off properties, that is, to sacrifice one characteristic for another. Thus, the primary objective may not be to optimize absolutely (i.e., a maxima or minima), but to realize an overall pre selected or desired result for each characteristic or parameter. Drug products are often developed by teaching an effective compromise between competing characteristics to achieve the best formulation and process within a given set of restrictions. 

These developments are so impressive that we may wonder if the development of a virtual pharmaceutical company, which owns NDAs but contracts out all the activities requisite for the approval, manufacture, evaluation, and marketing of its products, may become reality. 

Diffusion in a sphere may be more common than that in a cylinder in the pharmaceutical sciences. The example we may think of is the dissolution of a spherical particle. Since convection is normally involved in solute particle dissolution in reality, the dissolution rate estimated by considering only diffusion often underestimates experimental values. Nevertheless, we use it as an example to illustrate the solution of the differential equations describing diffusion in the spherical coordinate system [1],... 

On the supply side, patents allow the innovating company considerable discretion in pricing their new products. However, new products may be complements or substitutes of those of rival companies. In reality, pharmaceutical firms operate in oligopolistic markets characterized by a limited number of competitors (especially in submarkets such as that of cardiovascular products, for example), differentiated products and competitive innovation strategies. 

For HCS to be fully accepted by academia, several conditions will need to be fulfilled. Current HCS instruments are closed black boxes and their expensive maintenance contracts do not allow any hardware or software modifications for adaptation to the diverse needs of academic research. Academic research is typically more diversified than pharmaceutical industry research and the instruments need to be more customizable than they are now. In addition, the image and data formats need to be accessible and open. In academia data is shared between collaborators and will be analyzed with various, partly custom-made software. Therefore the data needs to be accessible and open. Lastly, the yearly costs of maintenance contracts and licenses are particularly difficult to finance in academic research that relies heavily on grants. Grants typically do not cover licensing costs or if they do, when the grant runs out, new sources of funding must be found. In reality, those costs must generally be covered by institutional funds. 

All the studies reviewed rely on health care or pharmaceutical spending rather than on health or pharmaceutical output as a proxy for health care received by consumers. One unintended interpretation of a positive relationship between dollars spent and outcomes would be that health care price increases alone could extend life. In reality, of course, increased spending reflects a combination of increased quantity, increased quality, and increased price of pharmaceuticals. Since these three factors cannot be separated and since pharmaceutical prices are increasing even after controlling for quality, the relationship between spending and health outcome will understate the true underlying relationship between spending and the combination of quality and quantity increases. 

Since we follow an analytical, quantitative, and open-source computational approach, our pharmaceutical product/process and project management method and software toolset are implemented as (Internet browser readable) MS-Excel spreadsheets, integrated with several hyperlinks to the rule base and to optional 2D video and 3D virtual-reality objects for visualization. 

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