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  • decodeMR Team

Real-World Data and Real-World Evidence: Current status in the APAC region

(Focus-Singapore)


This interview was published in www.oncofocus.com on 04th July 2019


In the second post of the interview series, our team members, Raja Mukesh Dokala, Senior Manager and Khusnuma Begum, Senior Analyst discussed the current status of RWD in Singapore with Prof Teo Eng Kiong, HoD, Department of Gastroenterology and Chairman, Medical Board, Changi General Hospital, Singapore.




Prof Teo Eng Kiong

MBBS, M.Med (Int Med), FAMS, MRCP (UK), FRCP (Edin), FACP

HoD, Department of Gastroenterology and Chairman, Medical Board, Changi General Hospital




Real world data is essential because it reflects what really happens! It also helps us track how many patients cannot afford it (an expensive therapy) and what percent actually gets successfully treated.

Considering the rapidly transforming healthcare space, what are your views on the usage of Real-World Data (RWD) in healthcare decision-making?


In my view, RWD is undoubtedly something useful, but it must be updated periodically. There is a substantial difference between data available in books and data available online. So, if real-world data is available, it is best, if not then we must use mixed data based on the level of evidence and the kind of data available either online or in primary sources.


With the introduction of the 21st Century Cures Act in 2016, USFDA has an additional focus on using Real World Evidence (RWE) in regulatory decision-making. Coming to Singapore, how is the regulatory landscape evolving in terms of usage of RWE?


In Singapore, we make regulatory decisions depending on data available through randomized control trials. We get RWD in Phase 4 of a clinical trial, unlike observational data from a routine clinical trial. So, most of the time, real-world data will come in Phase 4 where it's a post-marketing kind of survey or post-marketing evaluation of the drug that we use at trial conditions probably as proof of treatment. Then we get back the population data to see the real efficacy or the compliance rate and other such parameters.


Do you see any specific area or specific indications where real-world data is used more compared to others?


Firstly, real-world data is important to understand to what extent drug accessibility is an issue. In my personal experience, where I am involved in Hepatitis C treatment, drug accessibility is a significant concern. Hepatitis C treatment is very costly. Though the clinical data showed excellent results, the real impact on society is not there because more than 90% to 95% of patients cannot afford it. So, it is available but not accessible. Even if you prescribe it to the patients, 95% of them cannot buy it because of the cost is beyond their reach. Real-world data would help us track how many patients cannot afford it and what percent actually gets successfully treated.


Another issue that can be tracked using real-world data is patient compliance. In Phase 2 or Phase 3 trials, the drug might have shown a good outcome, but in a real-world setting, the outcome may not be as good as that because it is challenging to achieve compliance. Real-world data is essential because it reflects what really happens.


How are the key stakeholders of the healthcare value chain responding to the use of real-world evidence in decision-making?


For a pharma company, if they want to increase the market share and if they are very confident with their product and to know more about its benefits, they conduct a post-marketing survey. They collect real-world data to show that the drug is as good as when it was in trial time.


The other one will be from a national level kind of database. For example - in Singapore, where Diabetes is a big problem, almost 1 in 4 or 1 in 5 people does get Diabetes. So that being a problem, it is a national agenda to make sure that Diabetes got under control, and under that consensus, there may be a national database that is being created, and then from there, we get real-world data. Thus, it is expensive to get real-world data, but I think sometimes the returns may be there and the returns may be different from different stakeholders' viewpoints - from the pharma viewpoint, from the national viewpoint, from the healthcare viewpoint.


What are the common sources of RWD? Are there any specific indications or areas in which RWD is utilized more in Singapore?


National databases, Disease registries, and some of the large institutions have their database or some demographic studies.


What are the key barriers to the increased use of RWD?


Cultural issues in the data, meaning certain things are peculiar to a population. So real-world data may not be applicable as we think it is, because for example it is well known across the world that the Japanese population is very compliant but if you use the same real-world data and you transfer it to maybe in Singapore, you may not get the same level of compliance rate. So, we have to be mindful of the cultural issues, population practices, and perceptions particular to the specific country/group from where the real-world data is acquired.


Another example is in India and Singapore, I would think that traditional medicine is a widespread practice, but if you go to the European side, I think traditional medicine is probably in the backseat. So, these are our population-specific characteristics which may be a challenge for the application of real-world data when collected in a particular population.


In terms of the collection of data and the difficulties, are there any issues on the technical front or privacy issues when we collect real-world data?


Most of this data is identified, coded, and from then crunched out as population data. So, this is again different from a trial where each patient reaction or response is taken as one count. Most of the population data will be average which again is a problem because when we are taking an average of data, you do allow data resolution, which is both a strength as well as a limitation of real-world data. Of course, in real-world data, there will be a lot of variation, a lot of con-founders that is why it is the real world, right? You should not correct them because that is what really happens in the real world. So, in my opinion, it just has to be interpreted without limitation in mind and then use for the best whatever the way we think it can help in making the decision.


In the U.S., draft guidance on the appropriate use of RWD in regulatory decision-making is expected to be published by 2021. Are there any such measures in the pipeline for Singapore?


Not that I am aware of. We still use data secured through a clinical trial or real-world publication, since we are bound to maintain the confidentiality of every patient adjunct with RWD.


Looking forward, what is the outlook for the usage of Real-World Data (RWD) in the future?


Well, the trend moving forward, is to look at real-world data to look at how effective drugs are and whether are they good value for money? There are problems present; it is challenging to combine real-world data (from different sources), it is not cheap always, sometimes you need a big database or, mega data to crunch. The value is there, mainly if applied to the bigger population. In specific populations, it is a lot more accurate than trials because trials have recruitment constraints. However, I must say that if real-world data is available, then we should use it. If not, use the next best available data rather than wait and depend on the fact that we must have real-world data to make a regulatory decision.​

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