The Impact of Real World Data

Steve Mott and Jane Juniper look at some of the potential real world data sources out there, as well as the impact this abundant resource can have on the pharmaceutical industry.

For life science companies investing heavily in research and development to find new cost effective medicines the investment choices are becoming much more complex.

Much has been written, from diverse perspectives, on the impact of the massive amounts of information becoming available from readily searchable databases, compiled from the information in individual patient medical records (“real world data”).

For any particular disease area there are a number of databases that can be used in discovery research. These can help identify targets for therapeutic intervention and enable development of molecules capable of therapeutic action on that target. These goals are supported by identification of genetic patterns in disease that are made possible by mapping the human genome. Decisions can now be augmented by a wealth of information on how that therapeutic molecule performs its task in everyday patient lives.

Access to databases with relevant information for research conducted by life science companies is an investment choice and the costs for licenses and contracts with the database providers a key strategic investment decision

The two areas where the data flow will directly affect research activity and contribute to the information used to make any strategic investment decision are:

  1. Epidemiological studies to identify disease causation, progression and the impact of particular treatment regimens over time and
  2. Safety and efficacy studies for any particular therapeutic molecule.

From the development perspective, greater visibility on disease prevalence in the community will help improve the mechanics of patient identification for potential participation in clinical trials. Access to databases with relevant information for research conducted by life science companies is an investment choice and the costs for licenses and contracts with the database providers a key strategic investment decision.

Meanwhile the science of informatics is also evolving fast, spawning a vast array of newly designed databases, search engines and analytics tools and techniques. An example could be the newly formed Clinical Practice Research Datalink. This is based on the UK’s long established General Practitioners Research Database derived from GP’s records comprising around 10% of UK patients). The CPRD aims to enable the linking of different databases (such as the Diabetes Register with the Office for National Statistics death register) to answer specific research questions for life science companies as a commercial service.  The goal of database linkage is to facilitate virtual research and development from observational studies using medical records (as opposed to running interventional trials in patients to collect data) so far as possible. 

Another example of data linkage capability with implications for use in wider research and development is the recent introduction of “IBM Watson”–a commercial supercomputer which has assimilated data from 1.5 million patient records, clinical trials and text from over 40 medical journals to provide an evidence platform for cancer diagnosis and therapy. 

Patients provide their own data on the effects of disease and specific treatment regimens to new types of databases designed and developed at PatientsLikeMe.  This is a further source of information that life science companies can access to refine their drug development.

Real world data and its usage will sit alongside methodological research progress, both of which will be key components of developing virtual research and development capability

Assessing the choice of databases to access and assimilate real world data will provide strategic challenges for life science companies.  In part this will be influenced by disease area and trial design. The role of clinical information and its usage in trial design is evolving as the science of information management evolves. The UK’s Medical Research Council has set up and funded eight centers (“Hubs”) for Trials Methodology Research to create a UK-wide, regionally distributed research resource to improve the design, conduct, analysis, interpretation, and reporting of clinical trials.

Real world data and its usage will sit alongside methodological research progress, both of which will be key components of developing virtual research and development capability.  An example of where the use of real world data has been used to improve the trial process to test a new medicine is the Salford LungStudy. It is a collaboration between industry, academia and the UK’s NHS in Salford the purpose of which is to test the safety and effectiveness of a new treatment for asthma and COPD, compared with standard medications used for these conditions. The initiative draws on Salford’s e-health records infrastructure, a clinical information system that provides a single, integrated electronic patient record across primary and secondary care. Patients are closely monitored over the course of the study, yet with minimal intrusion into their everyday lives. It has been described as a major advance in the way trials take place.

Monitoring patients for safety and efficacy in Salford illustrates one of the two key sources of data from patient records that can contribute to shaping research and development decisions as referred to above. Safety reporting, or pharmacovigilance, has long been a critical activity of healthcare delivery to patients and searchable data is increasingly appearing in pharmacovigilance databases which increase the evidence base of any medicine in use.

Scrutiny by physicians, regulators, payers and other third parties of such databases will provide the evidence base for determining the continued use of medicines. This will directly affect continued sales from which future research will be funded. For this reason an understanding of the increasing usage of real world data, its impact on current sales, and potential impact on future R&D capability of any life science company is critical.  

Integrating such data into the informatics systems that life science companies have developed over time is a big challenge. So also is the strategic question of how far informatics capabilities should be a core competence of the company? And if it is to be a core competence, how should a company ensure a supply of suitably trained and skilled informaticians to work effectively with the company’s staff in other functions such as regulatory, medical information, brand development and sales and marketing. The UK’s Medical Research Council along with other funders such as the Wellcome Trust have recently announced funding for a series of Health Information Research Centers to address this need but it will be a prevailing challenge for life science companies into the future.

Finding the most cost effective way of developing new medicines and navigating the sea of information to ensure effective strategic investments (and, in fact, a viable business model for the future based on an improved risk profile for decision making) will be the task of every life science company. The impact of real world data on research and development will be felt in various ways and it will be for every company to find its own particular strategy for investment based on its own strategic choices and competences.

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