Pharma IT Articles

There was a time when information technology (IT) professionals needed only technical skills to obtain positions in the pharma and biotech industries. Today, this has all changed. Recently, the demand for skilled professionals in pharma has been hot, and that's expected to continue as 2007 unfolds.

In today's highly competitive pharma and biotech environments, hiring managers are seeking candidates with strong technical and domain skill sets, as well as extensive industry knowledge, resulting in a much more critical eye when trying to fill crucial IT positions. But with a tight job market, hiring managers will have a hard time finding candidates with a combination of tech skills and industry expertise, and will need to wade deeper than before into the talent pool.

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When revenue gains soften, costs start to attract greater executive attention. And so it is with Pharma. It’s widely acknowledged that the pressure to control and reduce costs is the next major challenge facing companies contributing to the Pharma industry’s global value chain. Growing generic competition, imminent patent expirations, and shorter pipelines are all contributing to eroding margins.

But as part of their efforts to improve financial performance, many pharmaceutical companies are finding it hard not to turn the cost-cutting spotlights on IT. And for good reason; not only does the Pharma industry, according to recent research, spend six times more on IT than the average U.S. industry (15% of revenues vs. 2.5%) but many companies are still waiting to chalk up measurable IT-driven business value from this huge and growing investment. It’s little wonder that pharmaceutical executives are asking why IT costs so much and yet seems to deliver so little.

Bryan L. Singer, CISSP
The adoption of open networks in manufacturing environments, and the expanding connectivity and decentralization of computer systems and databases, are making the need to secure a company's automation and production systems more important than ever. The direct linking of manufacturing systems to information systems through the presence of Ethernet on the factory-floor creates an environment where traditional information technology (IT) and manufacturing worlds collide. This trend increases the vulnerability of these systems to the same security threats facing today's IT environments. Attacks — whether direct or indirect — from hackers, worms, viruses, and employees can affect the safety and security of people, products, processes, and productivity.

The master plan should be developed early in the life cycle, with input from the targeted user community, the quality unit (regulatory/compliance), and the information technology group responsible for the system (development and support personnel). If the personnel that will maintain the system in production are different than the personnel responsible for implementing it, the former should also be represented. Although not always closely involved in plan development, it is critical that the system owner or sponsor (management of the business area the system will support) understand what is documented in the plan and be an approval authority.

Laboratory information management systems evolved from the needs of both researchers and regulators.



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A significant bias in parameters, estimated with the proportional odds model using the software NONMEM, has been reported. Typically, this bias occurs with ordered categorical data, when most of the observations are found at o­ne extreme of the possible outcomes. The aim of this study was to assess, through simulations, the performance of the Back-Step Method (BSM), a novel approach for obtaining unbiased estimates when the standard approach provides biased estimates. BSM is an iterative method involving sequential simulation-estimation steps. BSM was compared with the standard approach in the analysis of a 4-category ordered variable using the Laplacian method in NONMEM. The bias in parameter estimates and the accuracy of model predictions were determined for the 2 methods o­n 3 conditions: (1) a nonskewed distribution of the response with low interindividual variability (IIV), (2) a skewed distribution with low IIV, and (3) a skewed distribution with high IIV.

Biotechnology firms, as well as smaller pharmaceutical companies, face many of the same regulatory and technology challenges of large pharma, often without the budgets to match. It is critical that these companies carefully identify and implement technology solutions that both satisfy regulatory requirements and enable them to bring products to market sooner. The following article discusses the business benefits of an electronic content management solution and provides an approach for implementation in mid-tier, cost-conscious life science organizations.

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Computer validation in the pharmaceutical, medical devices and biotech industries is frequently viewed as a necessary evil. It often is under estimated and under resourced. The United States Food and Drug Administration (FDA) and other agencies have mandates that must be adhered to, but these requirements do not constitute the glitzy part of any project. It is important to explore the psychology and personal dynamics in a project lifecycle, and avoid some of the pitfalls of leaving the ‘paperwork’ until the end. This article assumes that computer validation is good business and engineering practice regardless of the industry being regulated.

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Active Pharmaceutical Ingredients Committee of CEFIC.

Data mining for life sciences and drug discovery research. The forty-niners had it easy, relatively speaking, panning for gold and blasting their way through the Rockies to search for fragments of a shining noble element. These days, gold comes in many shades and forms, not all of them as tangible as a bag of 24-carat dust. Information is the new vein to be tapped, and there is no richer mother lode than the information nuggets to be found in drug discovery.

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