Pharmaceutical industry companies

As markets for enantiopure drugs continue to develop, the pharmaceutical industry, fine chemical companies, and academic chemists are prospecting for new enan-tioselective technologies to produce them. 

Another critical factor could be image. High-technology companies like to reinforce their image by having addresses that are synonymous with education and science. Others may want to associate themselves with an area traditional for high-quality manufacturing or research and development such as in the pharmaceutical industry, which is concentrated in Switzerland. 

As the twentieth century came to a close, the job market for computational chemists had recovered from the 1992-1994 debacle. In fact, demand for computational chemists leaped to new highs each year in the second half of the 1990s [135]. Most of the new jobs were in industry, and most of these industrial jobs were at pharmaceutical or biopharmaceutical companies. As we noted at the beginning of this chapter, in 1960 there were essentially no computational chemists in industry. But 40 years later, perhaps well over half of all computational chemists were working in pharmaceutical laboratories. The outlook for computational chemistry is therefore very much linked to the health of the pharmaceutical industry itself. Forces that adversely affect pharmaceutical companies will have a negative effect on the scientists who work there as well as at auxiliary companies such as software vendors that develop programs and databases for use in drug discovery and development. 

Over the last four decades, we have witnessed waves of new technologies sweep over the pharmaceutical industry. Sometimes these technologies tended to be oversold at the beginning and turned out to not be a panacea to meet the quota of the number of new chemical entities that each company would like to launch each year. Experience has shown that computer technology so pervasive at one point in time can almost disappear 10 years later. 

Direct instrument control (or the lack of it) was an important issue for the earlier version of CDS. The scheme of connecting the detector channels through A/Ds to CDS worked well in analytical laboratories across the pharmaceutical industry. The scheme provided enough flexibility so that the CDS could collect data from a variety of instruments, including GC, HPLC, IC, SFC, and CE. It was equally important that the CDS could be connected to instruments that were manufactured by different vendors. It was not uncommon to find a variety of instruments from different vendors in a global pharmaceutical research company. The disadvantage of this scheme was that the instrument metadata could not be linked to the result file of each sample analyzed. It could not be guaranteed that the proper instrument parameters were used in sample analysis. Another need came from the increased use of... 

Data integration and more powerful search technologies are the IT backbone for deriving business value from the plethora of data fogging the pharmaceutical industry today. Fortunately, this is not a problem for this industry alone, and the best and brightest of IT minds and companies are focused squarely on this problem. In addition, further advances in how humans process data and information will also come to bear. 

In the last few years, optimization techniques have become more widely used in the pharmaceutical industry. Some of these have appeared in the literature, but a far greater number remain as in-house information, using the same techniques indicated in this chapter, but with modifications and computer programs specific to the particular company. An excellent review of the application of optimization techniques in the pharmaceutical sciences was published in 1981 [20]. This covers not only formulation and processing, but also analysis, clinical chemistry, and medicinal chemistry. 

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