OBJECTIVE: : Preclinical biological research is mandatory for developing new drugs to investigate the toxicity and efficacy of the drug. In this paper, the focus is on radiobiological research as an example of advanced preclinical biological research. In radiobiology, recent technological advances have produced novel research platforms which can precisely irradiate targets in animals and use advanced onboard image-guidance, mimicking the clinical radiotherapy environment. These platforms greatly facilitate complex research combining several agents simultaneously (in our example, radiation and non-radiation agents). Since these modern platform can produce a large amount of wide-ranging data, one of the main impediments in preclinical research platforms is a proper data management system for preclinical studies. METHODS: : A preclinical data management system, inspired by current radiotherapy clinical data management systems was designed. The system was designed with InterSystems technology, i.e. a programmable Enterprise Service Bus solution. New DICOM animal imaging standards are used such as DICOM suppl. 187 for storing small animal acquisition context and the DICOM second generation course model. RESULTS: : A small animal big data warehouse environment for research is designed to work with modern image-guided precision research platforms. Its modular design includes (1) a study workflow manager, (2) a data manager, and (3) a storage manager. The system provides interfaces to, e.g. preclinical treatment planning systems and data analysis plug-ins, and guides the user efficiently through the many steps involved in preclinical research. The system manages various data source locations, and arranges access to the data centrally. CONCLUSION: : A novel preclinical data management system can be designed to improve preclinical workflow, facilitate data exchange between researchers, and support translation to clinical trials. ADVANCES IN KNOWLEDGE:: A preclinical data management system such as the one proposed here would greatly benefit preparation, execution and analysis of biological experiments, and will eventually facilitate translation to clinical trials.
OBJECTIVE: : Preclinical biological research is mandatory for developing new drugs to investigate the toxicity and efficacy of the drug. In this paper, the focus is on radiobiological research as an example of advanced preclinical biological research. In radiobiology, recent technological advances have produced novel research platforms which can precisely irradiate targets in animals and use advanced onboard image-guidance, mimicking the clinical radiotherapy environment. These platforms greatly facilitate complex research combining several agents simultaneously (in our example, radiation and non-radiation agents). Since these modern platform can produce a large amount of wide-ranging data, one of the main impediments in preclinical research platforms is a proper data management system for preclinical studies. METHODS: : A preclinical data management system, inspired by current radiotherapy clinical data management systems was designed. The system was designed with InterSystems technology, i.e. a programmable Enterprise Service Bus solution. New DICOM animal imaging standards are used such as DICOM suppl. 187 for storing small animal acquisition context and the DICOM second generation course model. RESULTS: : A small animal big data warehouse environment for research is designed to work with modern image-guided precision research platforms. Its modular design includes (1) a study workflow manager, (2) a data manager, and (3) a storage manager. The system provides interfaces to, e.g. preclinical treatment planning systems and data analysis plug-ins, and guides the user efficiently through the many steps involved in preclinical research. The system manages various data source locations, and arranges access to the data centrally. CONCLUSION: : A novel preclinical data management system can be designed to improve preclinical workflow, facilitate data exchange between researchers, and support translation to clinical trials. ADVANCES IN KNOWLEDGE:: A preclinical data management system such as the one proposed here would greatly benefit preparation, execution and analysis of biological experiments, and will eventually facilitate translation to clinical trials.
Authors: Fei-Fei Liu; Paul Okunieff; Eric J Bernhard; Helen B Stone; Stephen Yoo; C Norman Coleman; Bhadrasain Vikram; Martin Brown; John Buatti; Chandan Guha Journal: Clin Cancer Res Date: 2013-09-16 Impact factor: 12.531
Authors: Patrick V Granton; Ludwig Dubois; Wouter van Elmpt; Stefan J van Hoof; Natasja G Lieuwes; Dirk De Ruysscher; Frank Verhaegen Journal: Int J Radiat Oncol Biol Phys Date: 2014-09-04 Impact factor: 7.038
Authors: Sanaz Yahyanejad; Patrick V Granton; Natasja G Lieuwes; Lesley Gilmour; Ludwig Dubois; Jan Theys; Anthony J Chalmers; Frank Verhaegen; Marc Vooijs Journal: Mol Imaging Date: 2014 Impact factor: 4.488
Authors: Zineb Belcaid; Jillian A Phallen; Jing Zeng; Alfred P See; Dimitrios Mathios; Chelsea Gottschalk; Sarah Nicholas; Meghan Kellett; Jacob Ruzevick; Christopher Jackson; Emilia Albesiano; Nicholas M Durham; Xiaobu Ye; Phuoc T Tran; Betty Tyler; John W Wong; Henry Brem; Drew M Pardoll; Charles G Drake; Michael Lim Journal: PLoS One Date: 2014-07-11 Impact factor: 3.240