If data is the currency of R&D, how do we recognise its value?

Analysis and visualization of internal and externally hosted data is critical to the on-going success of Pharma R&D as it searches for patterns, trends and sequences in the R&D processes to discover, develop and bring to market new drugs for unmet patient needs.

Data is the key currency for bio-pharmaceutical R&D. R&D generates, consumes, analyses and represents data for operational purposes as well as generating insights. The processes of R&D are data driven and should be clearly understood to provide clarity about the data backing the science and claims being made for medicines.

The importance of data provenance, governance, curation, sharing and tracking should be a cultural norm for all scientists within R&D. In the rush to new scientific advances, concerns of data management, controls and processes are sometimes viewed as of secondary importance.  Data without context is not useful and if used to make decisions, damaging. As the body of data grows, how does one understand and interpret how much governance is ‘good enough’?

Data analytics is a continuing strategic theme for the biopharmaceutical sector as the industry is faced with an explosion of biomedical data being generated and made available for R&D use. Along with the increasing volumes of publicly available data, new entrants have been observed in the life science industry, including non-traditional companies such as Facebook, Amazon and Google. How will the biopharmaceutical industry ensure that these new and exciting technologies will process these data intelligently?

Advances in data analytics do not appear to have reduced the effort required to prepare the data for use. A recent survey of data scientists^[1] suggests that data preparation is the most time consuming and least enjoyable aspect of their jobs. As the volumes and variety of data increase, the veracity, provenance, integrity – indeed the simple ‘usefulness’ of data becomes increasingly difficult to assess.

The focus of this PRISME forum Technical Meeting will be to explore classic and modern techniques and technologies that will aid biopharma R&D in collating, organizing, filtering, preparing and sharing data to provide the best opportunities to our scientists and operations in generating further value from our data – not least by collaboration.

A PRISME Forum Technical Meeting Advisory Committee (TMAC) has been established to provide guidance on agenda topics and appropriately qualified speakers. The committee members are listed below:

The PRISME Forum Technical Meeting Advisory Committee will be looking for qualified speakers to address relevant topics including:

1. New technologies enabling new ways of managing data relevant to bio-pharma R&D
2. Emerging trends in biopharma R&D / Healthcare IT data management and analytics investment
3. Data aggregation, distillation and visualization – including ‘omics’ and Real World Evidence
4. Knowledge management approaches including computational linguistics
5. Cross-company collaboration technologies
6. Cloud

^[1] http://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/#4b32a76f7f75