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Pharmaceutical industry research data

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. [Pg.107]

Any document used to collect research data on clinical study subjects may be genetically classed as a data collection form. These completed forms provide evidence of the research conducted. The most common type of data collection form is the CRF. Other types of data collection forms include diary cards, dispensing records, quality of life forms, etc. The CRF must allow for proper analysis of the data and proper reporting of the data in the final clinical study report and it must reflect the protocol exactly no more and no less data must be collected. Thus, a CRF must be created for each clinical study and must be prepared in parallel with the protocol. CRFs are usually also prepared by spon-sors/CROs in pharmaceutical industry research because of the demanding requirements for their design and contents. [Pg.71]

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... [Pg.56]

In addition to the increased precision in the communication between the researcher and the programmer, there will be an increase in the accuracy of the data involved in the research. As Mason [23] pointed out early on in the history of computer use, authenticity and correctness are necessary for accuracy. One current controversy in the pharmaceutical industry, in fact, depends on accuracy, which in turn affects liability. People in and out of the industry are discussing how best to make research visible to potential users of drugs. [Pg.721]

Within the pharmaceutical industry we have progressed from the point where computers in the laboratory were rarely present or used beyond spreadsheet calculations. Now computers are ubiquitous in pharmaceutical research and development laboratories, and nearly everyone has at least one used in some way to aid in his or her role. It should come as no surprise that the development of hardware and software over the last 30 years has expanded the scope of computer use to virtually all stages of pharmaceutical research and development (data analysis, data capture, monitoring and decision making). Although there are many excellent books published that are focused on in-depth discussions of computer-aided drug design, bioinformatics, or other related individual topics, none has addressed this broader utilization of... [Pg.831]

The Association for Clinical Data Management (ACDM) and Statisticians in the Pharmaceutical Industry (PSI) publish an excellent document called Computer Systems Validation in Clinical Research A Practical Guide, which can be found at http //www.cr-csv.org/. [Pg.295]

Hammond, T.G., Carlsson, L., Davis, A. S., Lynch, W.G., MacKenzie, I., Redfern, W.S., Sullivan, A.T. and Camm, A.J. (2001) Methods of collecting and evaluating non-clinical cardiac electrophysiology data in the pharmaceutical industry results of an international survey. Cardiovascular Research, 49, 741-750. [Pg.87]

In 2008, the top 10 pharmaceutical companies spent 50 billion on research and development (see Figure 2.1 for a NP reference point). Sadly, much of the research data they accumulated will never be made publicly available, so it is not easy to analyse the results of cross-industry research. It is possible that the major pharmaceutical companies possess data which would allow a much better analysis of the possible differences between... [Pg.89]

Pracon, Incorporated, "Study to Assess Impacts of Releasing Safety and Effectiveness Data on the Pharmaceutical Industry s Incentives to Invest In and Conduct Research and Development Programs", Food and Drug Administration Contract No. 228-77-8052, Vienna, Virginia, 1978. 10... [Pg.165]


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