New Approach Provides a Unique Way to Collect Human BioMaterials on Demand

4th September 2012

Tissue Solutions has now been granted approval for a virtual sample collection, allowing researchers to request a range of samples on demand from ethically consented patients. These samples are available to both commercial and non-commercial organisations on approval of a project application. Donors consent in advance to provide specimens, such as blood, urine, saliva and skin biopsies and the samples are collected on a need-to-use basis.

The participating clinical sites have access to a wide range of donors and so can provide both diseased and normal control samples often in very specialised areas. Tissue Solutions oversee every step of the process to ensure that samples are collected and processed according to each researchers specific request.

Prospectively sourced samples from consented patients such as these are much in demand for scientific research. While banked collections are an invaluable resource, it can sometime be difficult for researchers to source the exact material required for a project, and the lack of harmonisation across organisations can lead to variations in sample and data quality.

In the past, researchers considering undertaking their own prospective collection face the difficult task of locating clinical collaborators with access to suitable donors, obtaining ethical approval for the project, and overall management of the study. The practical implications and challenges to such studies are often prohibitive to the individual researcher.

Working in this way is advantageous to both patient and scientist. High quality samples are made available to the scientific community and donors are assured that their samples will be used in the laboratory for a relevant project and not stored in a long-term freezer. The rapid turn around of the samples means they are of the very highest quality, and furthermore, the control over sample collection, handling and storage reduces variations and inconsistencies across the samples.

 

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