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Phoenix, AZ, United States

Matteson S.,Quintiles | Paulauskis J.,International Genomics Consortium | Foisy S.,GenoLogics | Hall S.,Pfizer | Duval M.,Pfizer
Pharmacogenomics | Year: 2010

The use of human genetic polymorphism data in drug development is not a recent event. Typically, the detection of patients fgenetic variations in drug-metabolizing enzymes has become common practice in clinical laboratories. What is new is the scale and diversity of genomics data that has entered into the drug research and development decision-making process. At least three concurrent events contribute to this paradigm shift: first the growing body of evidence that establishes that interindividual variation in both therapeutic response and adverse events are attributable to a genetic component; second the technological progress that enables the consistent and reproducible detection of human genomic quantities; third the expectation that the productivity of new drug development will be increased by identifying which patients would benefit from candidate therapies early in the clinical process. This influx of human genomics data into clinical laboratories requires some logistical adjustment in terms of data management. The major specifications of an information solution system intended for a clinical genomic laboratory are its compliance with regulatory procedures, regarding the handling of human genetic data and its subsequent integration into an existing clinical data management system from the hosting institution. The purpose of this article is to inform the community of the challenges in setting up a center for genomics data that ensures accurate, traceable and integrated data for laboratory management. This is by no means the only way to accomplish the same goal, and is simply presented as one way that Pfizer chose to solve these issues. © 2010 Future Medicine Ltd.


Patent
International Genomics Consortium | Date: 2011-02-08

Systems, devices, and methods for removing areas of tissue are described. A programmable laser may remove precise areas of tissue while the tissue remains substantially frozen. The laser is programmed in part by analyzing a reference image of a representative tissue section. A software program may receive digital images of test slices. Areas of interest in the image may be selected by a user. The software program can then create and send cut instructions to the programmable laser. The laser may be configured to make perforated cuts to remove the area of interest without melting the removed section.


Patent
International Genomics Consortium | Date: 2012-09-24

The present disclosure describes a method to estimate a geometric parameter to describe the degradation pattern (i.e. the proportion of bases that are damaged) in a sample. Using the values provided by the described systems and methods, researchers can estimate the proportion of undamaged fragments that are a certain base pairs in length or can estimate the number of errors within a fragment of certain base pairs in length.


Patent
International Genomics Consortium | Date: 2014-05-30

Systems, devices, and methods for removing areas of tissue are described. A programmable laser may remove precise areas of tissue while the tissue remains substantially frozen. The laser is programmed in part by analyzing a reference image of a representative tissue section. A software program may receive digital images of test slices. Areas of interest in the image may be selected by a user. The software program can then create and send cut instructions to the programmable laser. The laser may be configured to make perforated cuts to remove the area of interest without melting the removed section.


Morris S.,International Genomics Consortium | Morris S.,Arizona State University | Gel E.S.,Arizona State University | Smith J.V.,International Genomics Consortium | And 4 more authors.
Pharmacogenomics | Year: 2013

Aims: Biobanks are frequently required to verify specimen relationships. We present two algorithms to compare SNP genotype patterns that provide an objective, high-throughput tool for verification. Methods: The first algorithm allows for comparison of all holdings within a biobank, and is well suited to construct sample relationships de novo for comparison with assumed relationships. The second algorithm is tailored to oncology, and allows one to confirm that paired DNAs from malignant and normal tissues are from the same individual in the presence of copy number variations. To evaluate both algorithms, we used an internal training data set (n = 1504) and an external validation data set (n = 1457). Results: In comparison with the results from manual review and a priori knowledge of patient relationships, we identified no errors in interpreting sample relationships within our validation data set. Conclusion: We provide an efficient and objective method of automated data analysis that is currently lacking for establishing and verifying specimen relationships in biobanks. Original submitted 11 October 2012; Revision submitted 25 January 201. © 2013 Future Medicine Ltd.

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