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COLUMNS
Using real world evidence in the development of new medicine
Learn about the differences between real world data and real world evidence.
by Andrew Roddam and Sumitra Shantakumar

Traditional randomized controlled trials (RCTs) have long been thought of as the global standard in drug testing for efficacy and safety as well as in assessing the benefits to patients relative to prevailing standard treatments in the market.

Increasingly, there has been recognition amongst various stakeholders including regulators, healthcare providers, formulary decision makers and patients that RCTs, which generate evidence of efficacy, cannot alone inform the true value of a particular medicine in actual clinical practice. With the backdrop of increasing healthcare costs, drug makers will be required by payers, providers, and formularies to prove their new medicines are better value for money.

This is where access to, and the use of, Real World Data (RWD) and Real World Evidence (RWE) can help fill the gap and motivate drug makers to demonstrate the value of the new medicines they are developing in real world settings. Pharmaceutical companies have been developing RWD and RWE capabilities and operational models to help answer questions about the safety and effectiveness of new medicines in a more integrated and comprehensive way.

Real World Data (RWD) / Real World Evidence (RWE) and the value it adds

RWD refers to patient-level data generated under everyday conditions. Essentially, it is data derived from normal clinical practice and patient behaviour. RWD forms the basis for RWE, which is derived from RWD through analytics, observational studies, and pragmatic trials.

Whereas RCTs give evidence of efficacy and safety (the degree of benefit in ideal, controlled conditions), RWE informs effectiveness (the degree of benefit in everyday conditions) and safety in broader populations with greater power. The key difference, and this is where the value of RWE lies, is between efficacy and effectiveness. RWE studies permit real life behaviour to be possible, patients have co-morbidities and co-medications, as well as including patients with a range of disease severities which are typically excluded from RCTs due to the selective nature of the inclusion and exclusion criteria.

While RWE is more commonly used for post marketing safety surveillance and comparator studies looking at treatment effectiveness, RWE is increasingly used to support all phases of drug discovery and development, from new target selection based on deeper disease understanding to a more comprehensive assessment of the value of medicines in actual clinical settings. At the early phases of drug development, especially during clinical trials, RWD enables real time data analysis and examination of different hypotheses, which results in quicker insights and shorter time needed for decision making. Hence, the credible evidence derived from RWD forms a strong base from which a medicine’s future value can be reliably extrapolated.

Use of Real World Evidence (RWE) from digitally-enabled studies is catching on in Asia

At present, the use of RWE in Asia varies from country to country, with more real world studies being conducted in the West, especially the US and Europe. In Asia, some countries like Singapore are more advanced in this regard and have made efforts towards fully embracing RWD. In 2011, Singapore deployed the National Electronic Health Records system as part of its efforts to streamline medical data in a national electronic repository, with the aim to evolve its healthcare system to meet emerging challenges and changing needs.1

As a partner to these efforts, GSK is collaborating with Singapore Health Services and Duke-NUS Medical School to accelerate data integration and the digitisation of the medical records of asthma and chronic obstructive pulmonary disease patients across the SingHealth healthcare cluster.2 This is to fully realise the potential of electronic data in the care of patients with respiratory conditions, with the eventual aim to create an integrated real-time electronic health record system that will allow pragmatic clinical and health services trials to be conducted, in which patients’ care journeys are followed with minimal intrusion.

Barriers to systematic acceptance and uptake of Real World Evidence (RWE)

Despite the progress and promise of these initiatives, there remain challenges that need to be addressed before acceptance and uptake of RWE becomes more systematic, including the geographic coverage and completeness of data, quality of data, and concerns around patient consent and privacy as well as the ethical use of data.

At the same time, while there are many deep data on patients, these data sets are often siloed and linking them remains challenging. While RWD is increasingly stored in a digital format and accessible from sources like electronic health records, electronic claims data, as well as registry and observational study data sets which forms the foundation of research-ready RWD, other data such as genetics, biological and imaging data – while are often stored electronically – are not always linked to more accessible electronic medical record and claims datasets. Furthermore, direct patient feedback from diaries, remote sensor data, and validated outcome measures are captured in less structured ways and rarely linked to medical records.

Integration of these different data types, which can provide greater insights into treatment outcomes, requires prospective studies or collaborative efforts. Pragmatic Clinical Trials (PCTs) are designed to collect patient data under more usual clinical practice conditions and are therefore considered to be a type of RWE.

RWE is not a new concept, but one of the main reasons for the increased awareness of its utility is due to the 21st Century Cures Act, enacted into the US law in December 2016, which aims to accelerate the FDA drug and medical device approval processes by replacing some of the data requirements from clinical trials to observational data settings.3 While FDA has historically used RWE for post-approval studies and safety signal detection work, it is now also expanding the opportunity for RWE use, e.g., data requirements for label expansions.

In parallel, as more electronic data becomes available, national and private payers are increasingly enhancing their analytical capabilities to best utilize RWD in order to generate information to help manage care pathways more effectively. Greater adoption of RWE by pharmaceutical companies in the US, Europe and increasingly in Asia, is partly in reaction to an expansion of types of RWE that can be used for regulatory and payer discussions. This shift of utilization of RWE to enhance patient-centricity in all stages of the drug development process will ultimately benefit patients and consumers – helping them to do more, feel better and live longer.

References:

  1. Hospital and Healthcare Management. (n.d.). Singapore’s Journey to Build a National Electronic Health Record System. Retrieved from http://www.hhmglobal.com/knowledge-bank/articles/singapores-journey-to-build-a-national-electronic-health-record-system
  2. Duke-NUS (2017). SingHealth, Duke NUS and GSK to conduct large-scale big data study on asthma and COPD in Singapore. Retrieved from https://www.duke-nus.edu.sg/news/singhealth-duke-nus-and-gsk-conduct-large-scale-big-data-study-asthma-and-copd-singapore
  3. FDA (2017). Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices. Retrieved from https://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM513027.pdf
Dr Andrew Roddam is vice-president and head of epidemiology, RWE and digital clinical platform at GSK.
Dr Sumitra Shantakumar is regional real-world evidence and epidemiology lead for Asia-Pacific at GSK.

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EDITORS' CHOICE  
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APBN Editorial Calendar 2018
January:
Obesity / Outlook for 2018
February:
Searching for the fountain of youth
March:
Women in Science - Making a difference
April:
Digestive health in the 21st century - Trust your guts
May:
Dental health - The root to good health
June:
Cancer - Therapies and strategies for better patient outcomes
July:
Water management - Technologies for biotech and pharmaceutical industries
August:
Regenerative technology - Meat of the future
September:
Doctor Robot - The digital healthcare revolution
October:
Bones / Breast cancer
November:
Liver health / Top science research nations & institutions
December:
AIDS / Breakthrough of the year/Emerging trends
Editorial calendar is subjected to changes.
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