Biobanking is entering the new era-era of big data. New technologies, techniques, and knowledge opened the potential of the whole domain of biobanking. Biobanks collect, analyse, store, and share the samples and associated data. Both samples and especially associated data are growing enormously, and new innovative approaches are required to handle samples and to utilize the potential of biobanking data. The data reached the quantity and quality of big data, and the scientists are facing the questions how to use them more efficiently, both retrospectively and prospectively with the aim to discover new preventive methods, optimize treatment, and follow up and to optimize healthcare processes. Biobanking in the era of big data contribute to the development of predictive, preventive, and personalised medicine, for every patient providing the right treatment at the right time. Biobanking in the era of big data contributes to the paradigm shift towards personalising of healthcare.

Faculty of Medicine in Pilsen Charles University Husova 3 30100 Pilsen Czech Republic

Laboratory of Immunoanalysis University Hospital in Pilsen Edvarda Beneše 1128 13 30599 Pilsen Czech Republic

Zobrazit více v PubMed

Rony J, Rooney R, Nagisetty N, Davis R, Hains D. Biorepository and integrative genomic initiative: designing and implementing a preliminary platform for predictive, preventive and personalized medicine at a pediatric hospital in a historically disadvantaged community in the USA. EPMA J. 2018;9:225–234. doi: 10.1007/s13167-018-0141-y. PubMed DOI PMC

Golubnitschaja O, Baban B, Boniolo G, Wang W, Bubnov R, Kapalla M, et al. Medicine in the early twenty-first century: paradigm and anticipation – EPMA position paper 2016. EPMA J. 2016;7:23. doi: 10.1186/s13167-016-0072-4. PubMed DOI PMC

Kinkorova J. Biobanks in the era of personalized medicine: objectives, challenges, and innovation: overview. EPMA J. 2016;7:4. doi: 10.1186/s13167-016-0053-7. PubMed DOI PMC

Coppola L, Cianflone A, Grimaldi AM, Incoronato M, Bevilacqua P, Messina F, et al. Biobanking in health care: evolution and future directions. J Transl Med. 2019;17:172–190. doi: 10.1186/s12967-019-1922-3. PubMed DOI PMC

Liu AG, Pollard K. Advances in experimental medicine and biology, vol 864. Berlin: Springer; 2015. Biobanking for personalized medicine. In: Karimi-Busheri F. ed. Biobanking in the 21st century; pp. 55–68. PubMed

Kozlakidis Z, Lewandowski D, Betsou F. Precision medicine and biobanking: future directions. 2018.

Kinkorova J, Topolcan O. Biobanks in Horizon 2020: sustainability and attractive perspectives. EPMA J. 2018;9:345–353. doi: 10.1007/s13167-018-0153-7. PubMed DOI PMC

Kauffmann F, Cambon-Thomsen A. Tracing biological collections: between books and clinical trials. JAMA. 2008;299:2316–2318. doi: 10.1001/jama.299.19.2316. PubMed DOI

Hewitt R, Watson P. Defining biobank. Biopreserv Biobank. 2013;11(5):309–315. doi: 10.1089/bio.2013.0042. PubMed DOI

Vaught J, Rogers J, Myers K, Lim MD, Lockhart N, Moore H, Sawyer S, Furman JL, Compton C. An NCI perspective on creating sustainable biospecimen resources. J Natl Cancer Inst Monogr. 2011;42:1–7. doi: 10.1093/jncimonographs/lgr006. PubMed DOI

Drosou M, Jagadish HV, Pitoura E, Stoyanovich J. Diversity in big data: a review. Big Data. 2017;5(2):73–84. doi: 10.1089/big.2016.0054. PubMed DOI

Scott CT, Caulfield T, Borgelt E, Illes J. Personal medicine – the new biobank crisis. Natur Biotechnol. 2012;30(2):141–147. doi: 10.1038/nbt.2116. PubMed DOI

Rashidi P, Mihailidis A. A survey on ambient-assisted living tools for older adults. IEEE J Biomed Health Informat. 2013;17(3):579–590. doi: 10.1109/JBHI.2012.2234129. PubMed DOI

Leff DR, Yang G-Z. Big data for precision medicine. Engineering. 2015;1(3):277–279. doi: 10.15302/J-ENG-2015075. DOI

Hulsen T, Jamuar SS, Moody AR, Karnes JH, Varga O, Hedensted S, et al. From big data to precision medicine. Front Med (Lausanne) 2019;6:34. doi: 10.3389/fmed.2019.00034. PubMed DOI PMC

Ayers R. Can big data help provide affordable healthcare? DATACONOMY. 2019. http://www.dataconomy.com/2019/02/can-big-data-help-provide-affordable-healthcare/. Accessed 17 March 2020.

Minelli M, Chambers M, Dhiraj A. Big data, big analytics: emerging business intelligence and analytic trends for today´s business: Wiley & Sons; 2013.

Ma Y, Chen H, Lei R, Ren J. Biobanking for human microbiome research: promise, risks, and ethics. Asian Bioethic Rev. 2017;9:311–324. doi: 10.1007/s41649-017-0033-9. DOI

Bolan S, Seshadri B, Talley NJ, Naidu R. Bio-banking gut microbiome samples. EMBO Rep. 2016;17(7):929–930. doi: 10.15252/embr.201642572. PubMed DOI PMC

Andreu-Perez J, Poon CC, Merrifield RD, Wong ST. Y GZ. Big data for health. IEEE J Biomed Health Inform. 2015;19(4):1193–1208. doi: 10.1109/JBHI.2015.2450362. PubMed DOI

Kumar B. An encyclopedic overview of ´big data´ analytics. Int J Appl Engin Res. 2015;10(3):5681–5705. doi: 10.13140/RG.2.2.31449.62566. DOI

Sun Z. 10 bigs: big data and its ten big characteristics, BAIS No. 17010, 2018; PNG University of Technology.

Dhar V. A message from the editor-in-chief of big data. Big Data. 2017;3(4):175–176. doi: 10.1089/big.2017.29021.vda. PubMed DOI

Cirillo D, Valencia A. Big data analytics for personalized medicine. Curr Opin Biotechnol. 2019;58:161-167. www.sciencedirect.com. Accessed 17 March 2020. PubMed

Ayers R. 5 ways the healthcare industry could use big data – and why it´s not. DATACONOMY. 2017. dataconomy.com/2017/08/5-ways-healthcare-big-data/. Accessed 17 March 2020.

Hewitt RE. Biobanking: the foundation of personalized medicine. Curr Opin Oncol. 2011;23:112–119. doi: 10.1097/CCO.0b013e32834161b8. PubMed DOI

Chen J, Kozlakidis Z, Cheong IH, Zhou X. Precision medicine research and biobanking in China. 2019. https://www.openaccessgovernment.org/precision-medicine-biobanking-in-china/77789/. Accessed 17 March 2020.

Kitchin R. Big data, new epistemologies and paradigm shifts. Big Data Soc. 2014;1:1–12. doi: 10.1177/2053951714528481. DOI

Luo J, Wu M, Gopukumar D, Zhao Y. Big data application in biomedical research and health care: a literature review. Biomed Inform Insights. 2016:8 1–10 doi: 10.4137/Bii .s31559 PubMed PMC

Gerner C, Costigliola V, Golubnitschaja O. Multiomic patterns in body fluids: technological challenge with a great potential to implement the advanced paradigm of 3P medicine. Mass Spectrometry Rev. 2019. 10.1002/mas. PubMed

Gartner, “Big data” 2016. http://www.gartner.com/it-glossary/big-data/. Accessed 17 March 2020.

Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C et al. "Big data: the next frontier for innovation, competition, and productivity," McKinsey, May 2011. http://www.mckinsey.com/business-functions/business-technology/our-insights/big-data-the-next-frontier-for-innovation . Accessed 17 March 2020.

Cukier K. Data, Data everywhere: a special report on managing information. Economist. 2010;394:3–5.

Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, Efron MJ, Iyer R, Schatz MC, Sinha S, Robinson GE. Big Data astronomical or genomical? Plos Biol. 2015;13(7):e1002195. doi: 10.1371/journal.pbio.1002195. PubMed DOI PMC

Craven M, Page CD. Big data in healthcare: opportunities and challenges. Big Data. 2015;3(4):209–210. doi: 10.1089/big.2015.29001.mcr. PubMed DOI

Philip Chen CL, Zhang CY. Data-intensive applications, challenges, techniques and technologies: a survey on Big Data. Information Sciences. 2014;275:314–347. doi: 10.1016/j.ins.2014.01.015. DOI

Veracity: https://www.gutcheckit.com/blog/veracity-big-data-v/. Accessed 17 March 2020.

Ibnouhsein I, Jankowski S, Neuberger K, Mathelin C. The big data revolution for breast cancer patients. Eur J Breast Health. 2018;14:61–62. doi: 10.5152/ejbh.2018.0101. PubMed DOI PMC

The 7 V´s of Big Data. impact. blog post. 2016; https://impact.com/marketing-intelligence/7-vs-big-data/). Accessed 17 March 2020.

Saggi MK, Jain S. A survey towards an integration of big data analytics to big insights for value-creation. Inf Process Manag. 2018;54(5):758–790. doi: 10.1016/j.ipm.2018.01.010. DOI

Puin T. How big is a petabyte, exabyte or yottabyte? What’s the biggest byte for that matter? ZME Science. 2017; https://www.zmescience.com/science/how-big-data-can-get/. Accessed 17 March 2020.

Borne K. Top 10 big data challenges – a serious look at 10 big data V´s. MapR. 2014; https://mapr.com/blog/top-10-big-data-challenges-serious-look-10-big-data-vs/. Accessed 17 March 2020.

Faroukhi AZ, El Alaoui I, Gahi Y, Amine A. Big data monetization throughout big data value chain: a comprehensive review. J Big Data. 2020;7:3. doi: 10.1186/s40537-019-0281-S. DOI

Turpin J. Healthcare as it Happens. Managing real-time data in healthcare. Real Time Data White Paper. 2017; www.orionhealth.com. Accessed 17 March 2020.

The 4 Characteristics of Big Data. Enterprise Big Data Framework. 2019; https://www.bigdataframework.org/four-vs-of-big-data/. Accessed 17 March 2020.

Williams E, Moore J, Li SW, Rustici G, Tarkowska A, Chessel A, Leo S, Antal B, Ferguson RK, Sarkans U, Brazma A, Carazo Salas RE, Swedlow JR. The image data resource: a bioimage data integration and publication platform. Nat Methods. 2017;14:775–781. doi: 10.1038/nmeth.4326. PubMed DOI PMC

Rosenbloom ST, Denny JC, Xu H, Lorenzi N, Stead WW, Johnson KB. Data from clinical notes: a perspective on the tension between structure and flexible documentation. J Am Med Inform Assoc. 2011;18(2):181–186. doi: 10.1136/jamia.2010.007237. PubMed DOI PMC

Lependu P, Iyer SV, Fairon C, Shah NH. Annotation analysis for testing drug safety signals using unstructured clinical notes. J Biomed Semantics. 2012;3(suppl 1):S5. doi: 10.1186/2041-1480-3-S1-S5. PubMed DOI PMC

Hollander G. What is Structured Data vs. Unstructured Data? 2019; https://www.m-files.com/blog/what-is-structured-data-vs-unstructured-data/. Accessed 17 March 2020.

Margolis R, Derr L, Dunn M, Huerta M, Larkin J, Sheehan J, Guyer M, Green ED. The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data. J Am Med Inform Assoc. 2014;21(6):957–958. doi: 10.1136/amiajnl-2014-002974. PubMed DOI PMC

Siddiqa A, Hashem IAT, Yaqoob I, Marjani M, Shamshitband S, Gani A, et al. A survey of big data management: taxonomy and state-of-the-art. J Netw Comput Appl. 2016;71:151–166. doi: 10.1016/j.jnca.2016.04.008. DOI

Zhang Y. Quora 2015; https://www.quora.com/What-is-the-difference-between-raw-and-processed-data. Accessed 17 March 2020.

Agarwal D, El Abbadi A, Shyam A, Sudipto D. Data management challenges in cloud computing infrastructures. In: Kikuchi S, Sachdeva S, Bhalla S (eds). Databases in Networked Information Systems. DNIS 2010. Lecture Notes in Computer Science, vol 5999. Springer, Berlin Heidelberg.

What is artificial intelligence? Centric Digital. 2020; https://centricdigital.com/resources/what-is-artificial-intelligence/. Accessed 17 March 2020.

Horgan D, Romao M, Moreé SA, Kalra D. Artificial intelligence: power for civilisation – and for better healthcare. Public Health Genomics. 2019;22(5-6):145–161. doi: 10.1159/000504785. PubMed DOI

Bresnick J. Top 12 ways artificial intelligence will impact healthcare. Health IT Analytics. 2018; https://healthitanalytics.com/news/top-12-ways-artificial-intelligence-will-impact-healthcare. Accessed 17 March 2020.

Study Panel for the Future of Science and Technology, EPRS – European Parliamentary Research Service, Scientific Foresight Unit (STOA). Understanding algorithmic decision-making: opportunities and challenges. PE 624.261 – March 2019. https://www.europarl.europa.eu/Reg-Data/etudes/STUD/2019/624261/EPRS_STU(2019)624261_EN.pdf. Accessed 17 March 2020.

Dilsizian SE, Siegel EL. Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment. Curr Cardiol Rep. 2014;16(1):441. doi: 10.1007/s11886-013-0441-8. PubMed DOI

Chung B. How to use the right data at the right time for better customer relationship. The Future of Commerce. 2017; https://www.the-future-of-commerce.com/2017/05/17/how-to-use-the-right-data-at-the-right-time-for-better-customer-relationships/. Accessed 17 March 2020.

Barrett M, Boyne J, Brandts J. Brunner La Rocca H-P, De Maesschalck L, De Wit K, et al. Artificial intelligence driven patient self-care: a paradigm shift in chronic heart failure treatment. EPMA J. 2019;10:445–464. doi: 10.1007/s13167-019-00188-9. PubMed DOI PMC

Kunin A, Polivka J, Jr, Moiseeva N, Golubnitschaja O. “Dry Mouth” and “Flammer” syndromes - neglected risks in adolescents and new concepts by predictive, preventive and personalised approach. EPMA J. 2018;9:307–317. doi: 10.1007/s13167-018-0145-7. PubMed DOI PMC

Lu M, Zhan X. The crucial role of multiomic approach in cancer research and clinically relevant outcomes. EPMA J. 2018;9:77–102. doi: 10.1007/s13167-018-0128-8. PubMed DOI PMC

Fröhlich H, Patjoshi S, Yeghiazaryan K, Kehrer C, Kuhn W, Golubnitschaja O. Premenopausal breast cancer: potential clinical utility of the multi-omic based machine learning approach for patient stratification. EPMA J. 2018;9:175–186. doi: 10.1007/s13167-018-0131-0. PubMed DOI PMC

Golubnitschaja O, Polivka J, Jr, Yeghiazaryan K, Berliner L. Liquid biopsy and multiparametric analysis in management of liver malignancies: New concepts of the patient stratification and prognostic approach. EPMA J. 2018;9:271–285. doi: 10.1007/s13167-018-0146-6. PubMed DOI PMC

Qian S, Golubnitschaja O, Zhan X. Chronic inflammation: key player and biomarker-set to predict and prevent cancer development and progression based on individualized patient profiles. EPMA J. 2019;10:365–381. doi: 10.1007/s13167-019-00194-x. PubMed DOI PMC

Zlotta AR. Words of wisdom: Re: Genome sequencing identifies a basis for everolimus sensitivity. Eur Urol. 2013;64:516. doi: 10.1016/j.eururo.2013.06.031. PubMed DOI

Polivka J, Jr, Polivka J, Pesta M, Rohan V, Celedova L, Mahajani S, Topolcan O, Golubnitschaja O. Risks associated with the stroke predisposition at young age: facts and hypotheses in light of individualized predictive and preventive approach. EPMA J. 2019;10:81–99. doi: 10.1007/s13167-019-00162-5. PubMed DOI PMC

Hand DJ. Aspects of data ethics in a changing world: where are we now? Big Data. 2018;6(3):176–190. doi: 10.1089/big.2018.0083. PubMed DOI PMC

Bates DW, Saria S, Ohno-Machado L, Shah A, Escobar E. Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff. (Millwood) 2014;33(7):1123–1131. doi: 10.1377/hlthaff.2014.0041. PubMed DOI

Xu H, Aldrich MC, Chen Q, Liu H, Peterson NB, Dai Q, Levy M, Shah A, Han X, Ruan X, Jiang M, Li Y, Julien JS, Warner J, Friedman C, Roden DM, Denny JC. Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality. J Amer Med Informat Assoc. 2015;22(1):179–191. doi: 10.1136/amiajnl-2014-002649. PubMed DOI PMC

Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation. http://data.europa.eu/eli/reg/2016/679/oj Accessed 17 March 2020.

Greene T, Shmueli G, Ray S, Fell J. Adjusting to the GDPR: the impact on data scientists and behavioral researchers. Big Data. 2019;7(3):140–162. doi: 10.1089/big.2018.0176. PubMed DOI

Education for future biobankers - The state-of-the-art and outlook