Janssen believes RWE could realise an efficient, personalised and truly patient-centric healthcare system
Every day, everything we do generates an enormous amount of data. How best to analyse all this data and release the full potential of the insights it can offer is an issue the healthcare system is still struggling to work out.
At the Janssen Pharmaceutical Companies of Johnson & Johnson, we want to improve health outcomes by translating large-scale real world data (RWD) into evidence, and then using that evidence in an open and transparent manner to complement the results of randomised controlled trials (RCTs).
RCTs that are robust and well-devised can produce very high-quality data but may not always replicate the conditions patients experience outside of the clinic. RWD is captured from a variety of sources – such as disease registries, electronic medical records, health surveys, mobile apps and wearables – and can be transformed, via analytics, into insights or real world evidence (RWE).
RWE can help to shape clinical development plans and early drug discovery, optimise patient recruitment for RCTs and identify new areas of research. It can help us better understand disease and treatment pathways, assess the safety and effectiveness of newly-launched drugs, as used in the real world, and – ultimately – it will also be impactful on clinical practice and outcomes for patients.
The key to releasing the full potential of RWE is collaboration. If we can find ways of working together at scale; if data sharing across Europe – and the world – is incentivised, there’s a huge opportunity for RWE to help realise an efficient, personalised and truly patient-centric healthcare system.
One of the biggest drivers in our RWE strategy is to identify and use data sources of the highest possible quality. This often proves challenging, due to fragmented health systems and differing levels of investment in data platforms, so working with others is essential.
In Brazil, for example, in order to inform decision-making, Janssen partnered with Optum in the application of artificial intelligence to electronic health records (including unstructured physician notes), to estimate the proportion of patients with high risk non-metastatic castrate resistant prostate cancer. This project was executed with significant agility because it was based in electronic data sources.
We collaborated with the Karolinska Institute in Sweden and EPID Research in Finland on several large population-based studies of patients with a primary diagnosis of schizophrenia.
The studies included patients and their caregivers, and outcomes were comprehensive, based on long-term follow-up, and included endpoints impossible to measure in a randomised trial setting in the disease area, such as mortality. Most importantly, the studies revealed the enormous lifesaving benefits of treating patients with long-acting therapies
We have also partnered with Prospection – a data analytics and consulting company based in Australia – to develop and utilise multiple applications and tools, and we are leveraging those experiences to run a pilot project in Japan.
We aim to demonstrate the value and applicability of using RWE datasets like the Medical Data Vision (MDV) database for outcomes-based research, and advocate for improved access to other RWE datasets across the Asia Pacific region.
In Canada, we have secured partnerships with four provincial governments. These partnerships enable us to better understand the needs of payers, government stakeholders, KOLS and researchers, and co-create on mutually-beneficial RWE projects. As Canadian regulatory authorities (Health Canada) and the Canadian Agency for Drugs and Technologies in Health (CADTH) develop RWE frameworks, having the opportunity to provide input into RWE generation allows us to build credibility in the research, which is crucial when using the results in reimbursement submissions.
A common data model to increase use of existing RWD
We have a strong track record of working with partners across the healthcare system to explore new ways of leveraging data.
Janssen has actively supported open source data sharing platforms such as The Observational Medical Outcomes Partnership (OMOP) and The Observational Health Data Sciences and Informatics (OHDSI) programme.
OHDSI has developed several data analysis and visualisation tools and now represents over 1.2 billion patients in more than 20 countries via 60+ databases. All tools, methods and findings are shared publicly, and this transparency is crucial in joining the dots between the analysis of big data sets and actually improving patient care.
We have invested in a range of initiatives, including EHDEN (European Health Data & Evidence Network) and HONEUR (Haematology Outcomes Network in Europe), both of which are dedicated to optimising Europe’s health data collection landscape.
Launched in November 2018, EHDEN is a 22-partner consortium – 11 public, 11 pharmaceutical – co-led by Janssen under the framework of the Innovative Medicines Initiative (IMI2). Its mission is to develop a federated network of data centres that will promote stronger collaboration across Europe and enable all stakeholders to benefit from ‘big data’ research projects.
EHDEN is disease agnostic and, by 2024, aims to harmonise 100 million health records drawn from multiple data sources into a common, anonymised model.
Our own HONEUR project is also building a federated data network, but with a specific focus on haematology centres.
To protect patient privacy, HONEUR uses a similar federated approach as EMIF (European Medical Information Framework) and EHDEN: data in the network is de-identified and always remains with the participating institution. Furthermore, any potential research query must be approved by local clinicians before data can be accessed by an algorithm.
Both EHDEN and HONEUR use the OMOP common data model, developed by OHDSI, to ensure the clinical and biological vocabulary, as well as the structure of the data, are as homogeneous as possible across Europe’s understandably diverse data sets.
Enabling value-based healthcare
The existing reimbursement framework looks at value, evidence and cost in the short term, but is hard to apply to innovative treatments, and that’s where RWE can provide crucial insight.
If we are to move towards a value-based healthcare system that assesses the overall outcomes a medicine can achieve, then everyone – from patients and prescribers, to payers, policymakers and pharmaceutical companies – needs the analysis RWE can offer.
As regulatory authorities become increasingly interested in the application of RWE in support of their decision-making, there is another huge opportunity for collaboration on aspects such as structure, analytical methodology and ensuring quality of data.
The European Medicines Agency (EMA) has hosted various workshops on the use of RWE and, together with the European Union Heads of Medicines Agencies, has published a report (including a roadmap) on the use of ‘big data’.
In the US, the FDA has a broad, encompassing programme to understand how RWE can provide insights to support regulatory decision-making. Last December, the Agency released its RWE Framework and draft Guidance for Industry, for which Janssen provided robust and comprehensive comments on a broad range of issues.
Payers and Health Technology Assessment (HTA) bodies are also interested in better understanding the value of new treatments, so increasingly we are seeking to address their evidence needs with various methods of data generation.
Indeed, we are committed to collaborating with all parties to enable decision-making and ensure that patients who need these essential treatments the most, regardless of disease or geography, can access them when they need them.
Collaboration is the key
Working together to use RWE, and use it well, will mean we can break barriers – overcoming the obstacles of differing human and machine languages, uncovering new treatment options, and delivering smart, bespoke healthcare solutions.
And such solutions could have incredible value, reducing the cost to the healthcare system overall as more patients respond more positively, pay less to manage their disease and are freed to simply get on with their lives.
If we are to fully release the potential of real world evidence, collaboration is the key; an open sharing of data within an organised, coordinated ecosystem, so everyone – from patients and prescribers to payers and policymakers – can obtain the insights that will transform healthcare across the world.