Clinical Trial Data and Informatics

16th Annual Pharmaceutical IT Congress

SPEAKER SPOTLIGHTS:

Clinical Trial Data and Informatics With technology permeating the market, there has been many advances in the clinical trials and informatics spaces. Marisa Cunha, Senior Biomedical Informatics Scientist at AstraZeneca and Abhindan Raghwan, Principal Scientist (Bioinformatics), Novartis shares their thoughts on where the market is heading and where their key priorities lie.

Marisa Cunha

Bioinformatics Senior Scientist, AstraZeneca

Abhindan Raghwan

Principal Scientist (Bioinformatics), Novartis

Q1: Clinical trial data and informatics has seen much change. How do you think the space will evolve over the next five years? MC: Over the next five years I expect to see more and more sophisticated decision support tools available to clinicians and other health professionals. Good decision support tools depend not only on complex informatics methods but also on good data, which is ultimately limited by the organisation’s culture. While the informatics methods for the clinical data acquisition, standardisation, monitoring and analysis are rapidly evolving, the analysis of the outcomes is often limited to the project

teams and data scientists. One of the reasons is that datasets are often not easy to combine. In order to obtain good data, a culture of data sharing and reuse should be promoted across a wide range of experts (not just limited to the data scientists). A shift in an organisation’s culture requires good planning and time to be effective. Over the last years we have observed a change in many organisations’ culture so hopefully we will start to see the benefits of it soon.

Q2: Within your own informatics research, what are your key priorities? MC: One of my duties is to facilitate informed decision-making. I provide tools that need to have the right context to aid users to achieve reliable interpretations. My key priorities are the delivery of accurate results and intuitive tools in a timely manner. To achieve this, I have to communicate with people with a variety of backgrounds. Actually, effective communication is another key priority.

AR: Pharma companies have access to a large body of historical data and one of the major challenges is exploiting this data to extract trends for future application. Spurred by major technological advances in the field of machine learning, the application of these algorithms to biologics research and life sciences in general represents the greatest opportunity in this field.

These experts will be presenting at the 16th Annual Pharmaceutical IT Congress this September in London as part of our PharmaTec Series. For more information on the event, please contact Angela at: [email protected]