Interview – Corrado Priami, COSBI (Bioinformatics Research Center, Italy) – Life Science R&D Big Data Leaders Forum 2014
Leading up to NextLevel Pharma’s 2nd Annual Life Science R&D Big Data Leaders Forum, we are conducting email interviews with selected members of our prestigious speaker panel to learn more about their thoughts on this vital issue.
*Opinions below are those only of the individual and do not reflect upon corporate strategy or positioning.
For more information regarding NextLevel Pharma’s 2nd Annual Life Science R&D Big Data Leaders Forum click here.
Corrado Priami, President, COSBI. COSBI is a bioinformatics research center, University of Trento, Italy.
NextLevel: What do you think makes the current Big Data challenge in Life Sciences R&D so daunting for pharma and medical device developers?
Corrado Priami:The main challenge I see is related to the integration of different data types rather than to the management of large data-sets. Omics technologies are producing a large amount of data at different levels of detail ranging from gene expression to gene products activities and concentrations. Integration methods are there, but none of them is uniformly accepted and suitable for any kind of study. Indeed it is well known that no model is good for everything. Here at COSBI we are putting a lot of efforts in integrative analysis of non-homogeneous data sets. Comprehensive views of the system at hand are fundamental to uncover the mechanistic details of the biological processes governing aetiology and progression of diseases and hence to identify strategy to recover a health physiological state of the cells.
NextLevel: Which trends have you seen in the ways in which data management and analytics are being implemented to ease the Big Data challenge?
CP: A decade ago the main focus was on producing and collecting all kinds of measures enabled by the new omics technologies for each biological process. Quite soon was clear that the devil is in the extraction of knowledge from data and bioinformatics moved its main activities from DB development to analysis methods. Nowadays a lot of analysis techniques have been developed and tested for single data sets and the current challenge is becoming integration of different analysis results. Another trend is related to scientific quality of analysis proved by repeatability of in-silico experiments and the visualization of this experiments. This is why at COSBI we are working with graphical designers to identify visualization strategies that allows immediate interpretation of big data sets.
NextLevel: How important do you think the big data management and analytics space is right now to enhance R&D efficiencies and break new ground?
Many other disciplines already experienced the move from one-lab work to highly collaborative, data-intensive research. The transition was always driven by computing support in analysis and visualization. I think it will be the same for Life Sciences and indeed we are already observing the dawn of this transition. I stress visualization as a main challenge. Indeed I have seen lot of extremely good software (also in other disciplines) that failed just because they were too difficult to use and understand.
NextLevel: What’s the best thing for you about working in Life Sciences R&D and Data Management functions right now?
Interdisciplinarity of research teams is the fundamental aspect to be successful. Although it is not easy to create multidisciplinary teams (at COSBI we needed more than one year to create a common language and common expectations between researchers from different fields), the current challenges of biological systems needs many skills at the same time and they cannot be found in a single person. These team helps also in identifying good visualization strategies because different backgrounds and sensibility works towards a compromise that makes all the different components understand the outcome of is-silico experiments.
NextLevel: Why is this Life Science R&D Big Data Leaders Forum event a good idea for people to attend in your eyes?
The way ahead is understanding and accepting the challenges I expressed so far and to collaboratively identify strategies and methodologies to avoid fragmentation of solutions and resources to enhance the research capacity of academy and industry. Good solutions for integrative analysis of multi-source, multi-level, heterogenous data sets can open new avenues leading to brilliant results and improved diagnosis and drugs.
For more information regarding NextLevel Pharma’s 2nd Annual Life Science R&D Big Data Leaders Forum click here.