The Power of Big Data Anaytics in Pharma [Infographic]

In this infographic experts provide insight on the opportunities that exist in big data analytics for Pharma and how pharma firms can capitalise on cracking open their data silos.

Attendee Profile- Data Analytics for Pharma Development

Here you can find a comprehensive attendee profile of who attends Data Analytics for Pharma Development forum. This list is comprised of all attending accounts and job titles of attendees 

Infographic:Latest Industry Trends 2019

Ahead of the 5th Annual Data Analytics for Pharma Development Forum 2019, taking place on 12-14 November in Munich, we conducted an industry wide survey.

In this infographic you will learn about the biggest challenges that are facing those using data analytics in their drug development, the strengths of using AI & Machine Learning, how the use of Real World Data can be improved and where the future lies in data analytics in pharma development with many more insights.

Download below to view the full infographic

Interview: The Impact of Data on Drug Development

Ahead of the 5th Annual Data Analytics for Pharma Development Forum (Munich, 12-14thNovember 2019), we asked Nigel Hughes, Scientific Director at Janssen, to have a chat with us about the role of data analytics in the pharmaceutical industry and the impact AI & Machine Learning, RWD/RWE, GDPR and clinical trials are having on drug development.

Does Big Data in Pharma = Big Money?

As of now, big data is not used as often and as well as it should be in the Pharmaceutical Industry.   Slowly the Industry is adopting data and analytics to improve itself.

Data usage could lead to accelerated drug discovery, better help patients and predict emergency rush hours.  To keep reading, download the PDF file. 

Artificial Intelligence set to Revolutionise Drug Discovery

Artificial Intelligence, Machine Learning and other technologies are expected to make the discovery and development of new pharmaceuticals quicker, cheaper and more effective. Download this article to hear experts insights from Leonardo Rodrigues, Senior Director, AI & Machine Learning at BERG Heath about how these tools will revolutionise drug development over the next decade and what the future of a drug discovery market looks like when driven by AI.

Infographic: Harnessing the power of data

While most industries are already benefiting from better use of dataanalytics, Pharma has been slow to innovate their business mode and adopt new technologies. Pharma R&D is stalling, there is a cap onproductivity and companies need to leverage data insights to move forwards. With insights from Larry Pickett, CEO, RxDataScience, this infographic provides a step-by-step guide to overcoming the key challenges faced in establishing and implementing a coherent data analytics strategy.

How to Create a Competitive Advantage with Big Data Analytics in Pharma

Nigel Hughes, Director Integrative Healthcare Informatics, Janssen R&D, takes a closer look at how access to external data is critical in today’s world and the ways data accessibility can provide pharmaceutical companies with a competitive advantage.

With large scale initiatives coming into practice, such as the European Medical Information Framework (EMIF), Hughes shares his top tips for implementing a project like this. Read this interview to find out the key opportunities and threats of utilising real world data and how the rise of personalised/ precision medicine will impact the use of data.

How Machine Learning and Artificial Intelligence can speed up the world of data processing

In this exclusive interview conducted ahead of this year’s forum for Data Analytics for Pharma Development, Paul Agapow, Health Informatics Director at AstraZeneca shares his views on the world of data, with a particular emphasise on how artificial intelligence (AI) can help analyse and interpret huge quantities of data at all stages of drug discovery and development. Paul also discusses the challenges of using Real World Data (RWD) and Real World Evidence (RWE) when data is not always easily accessible or specific.

Download our latest interview to get the answers to the following questions:

  1. How is RWD becoming increasingly attractive for research?
  2. What are the current challenges when using RWD/RWE?
  3. How do you foresee evolutions in different segments and types of RWD for different therapeutic areas?
  4. How and in what areas are ML and AI currently impacting drug discovery and development? What challenges need to be overcome to encourage wider adoption?
  5. How do you see Machine Learning and AI developing over the next 5 years and the impact it will have on drug discovery and development?

Best in Class Case Study with Allan Jordan

Allan Jordan strongly believes that while big data is important and can change pharma, it should not just be gathered without reason. There needs to be a purpose, and purpose is the main thing driving his latest project. 

The project in question is focused on exploiting genome sequencing efforts to discover new targets for cancer treatment. A huge opportunity for positive change. Download the Case Study to find out more.