jueves, abril 16, 2015

Quality by Design (QbD) & Paperless Lab Consultancy

Big Data: New data structures for a new concept of regulated manufacturing

Representing to ISPE-Spain, Pep and I we are presenting a seminar in the PaperLess Academy Event on 14-15 of April - 2015 in Barcelona.

Big Data is the reference to systems that manage large data sets in the context of information technology and communications. Nowadays vast amounts of information are continuously generated and stored in multiple different systems: external and internal hard drives, virtual disks, network storage, pen-drives, e-drives, etc. Right now 1400000 GB = 1400 TB per minute are transferred to Internet.

The huge amount of the generated electronic information is directly related to the ease with which it can be stored. Without a multitude of elements and storage devices that allow quick access and low cost, it would not make sense to create much data. This factor, coupled with the high technology and high degree of penetration of the ICT in to the society, has favored the avalanche of information produced by the different areas of reality that surrounds us.

Today many areas and professional activities have based a fundamental part of their work on managing large amounts of data. Academic simulation environments (engineering, meteorology, astrophysics, physics of matter, environmental sciences), scientific institutions aimed to healthcare (genomics, biomedical research, epidemiology) and many sectors of different non-scientific applications (police investigation, social networks , smart cities, financial systems, marketing) need to mine Giga-bytes of information in a short period of time to extract knowledge in real time. The concept of big-data is inherent into all these scenarios. More and more appear new sectors that require tools for the analysis of large amounts of bytes by second.


Which is the challenge for the pharmaceutical industry? How the regulated industries should adapt its structures to the new concept of data?


Event
Seminar content