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Science & tech

The real-world evidence revolution: how better research can improve patients’ lives

When Ravi Jandhyala’s son, Luca, was diagnosed with a rare disease, he experienced first-hand the challenges faced by those waiting for new orphan drug treatments. Ravi never accepted Luca’s diagnosis as an insurmountable challenge. Instead, he used his training and experience as a pharmaceutical physician to develop a new framework that helps pharmaceutical companies get more patients on the right medicines, sooner

By Ravi Jandhyala

A moment I’ll never forget

I still remember the first moment I received the news of Luca’s diagnosis shortly after he was born—it’s a moment rare parents never forget. I knew our lives were about to change in a major way, I just had no idea what that would mean.

Our first challenge was getting Luca on an appropriate treatment plan, but this seemed impossible, because he is the only patient worldwide who has been diagnosed with both of his conditions. As is often the case for people living with a rare disease, even the experts didn’t know how to help.

Throughout my career as a surgeon, I had helped thousands of patients, but in that instant, I learned what it’s like to feel truly powerless. However, I realised I was incredibly fortunate in having medical training and experience, and I decided to change specialties to an area where I could learn what I needed to help Luca: pharmaceutical medicine.

As a pharmaceutical physician, I would be able to lead and advise on the development of new treatments while helping pharmaceutical companies keep patients at the centre of their decision-making. Patient-centricity is a common buzzword, but it’s something the pharmaceutical industry can struggle with.

I didn’t realise it back then, but this decision would lead me to the position I’m in now, where I am not only able to help Luca but also the thousands of others living with rare disease worldwide.

My journey as a pharmaceutical physician

I entered the pharmaceutical industry at an exciting time, as people were beginning to recognise the power of real-world evidence. Real-world evidence is particularly important for rare disease patients as they are often excluded from clinical trials of new therapies, so their treatment options remain limited. As I engaged in pharmaceutical practice, I saw first-hand exactly how rare disease treatments fall through the gaps during drug development.

Rare disease treatments fall through these gaps in drug development pathways

  • inaccurate safety, efficacy and quality of life measurements
  • evidence fails to meet stakeholders’ unique needs
  • real-world evidence is generated after regulatory approval

The biggest problem was that pharmaceutical companies were frequently generating wrong or incomplete safety, efficacy and quality of life measurements. This can lead to delay or negative decisions during regulatory approval, pricing and reimbursement and evidence-based practice at the prescriber level.

For rare disease patients, unnecessary delays and negative decisions made incorrectly can mean avoidable clinical worsening, hospitalisation or even death.

During my practice, I was seeing new, life-changing treatments for populations with no existing alternatives being discontinued due to simple mistakes during real-world evidence generation. Even beyond helping Luca, I wanted to see the pharmaceutical industry do more to ensure that rare disease patients get the treatments they deserve. I knew there had to be a better way.

Overcoming rare disease with real-world evidence

I have spent the last six years conducting research to provide companies with the expertise they so desperately need. Pharmaceutical companies routinely use measurement tools to determine who can participate in clinical trials and how much those who are enrolled are affected by the treatment. Using inaccurate measurement tools may mean that too many or the wrong patients are excluded from clinical trials. Even worse, sometimes, it can mean that an underlying treatment effect is totally missed (Figure 1).

Figure 1: A simplified look at how the accuracy of measurement tools may determine whether a treatment effect is detected or missed. A and B represent distinct measurement tools capturing different quality of life characteristics. Generic tools are commonly used in rare diseases, often resulting in a scenario closer to A than B. This situation may also affect clinical trial recruitment and other important drug development decision-making.

My research centred on ways to solve the issue of inaccurate construct measurement. First, I wanted to develop a scientific means for determining how accurate existing measurement tools are. Then, I wanted to identify a method for creating accurate measurement tools.

Generating better evidence for drug development

As a result,  Neutral theory was born. Neutral theory describes the ideal construct measured with complete accuracy.1 Having this point of reference allows us to test and improve existing construct measures. In the case of rare disease, this often means creating new, disease-specific tools.


To create these tools, as well as many others, I developed the Jandhyala method.2 This is a method for observing expert consensus on what should be included in a tool, with experts ranging from patients to opinion leaders, academics and clinicians. It creates more accurate tools than existing consensus methods as it assesses proportional group awareness and rather than forcing consensus, it observes it.3

The Jandhyala method has already been used to create five measurement tools and patient registries in areas such as long Covid, hereditary transthyretin-mediated amyloidosis (ATTRv), triglyceride-induced pancreatitis and work-related quality of life. It has also been used to address priority research questions in medical affairs, pharmaceutical medicine and influenza vaccination

The right evidence for the right stakeholder…

Neutral theory and the Jandhyala method solved the issue of inaccurate construct measurement, but this wasn’t the only problem. Successful drug development requires a positive decision from each external stakeholder: regulators, payors and prescribers (Figure 2). However, these stakeholders each have different real-world evidence needs.

Figure 2: The medicine adoption model. For a medicine to reach patients, it must receive a positive decision at the regulator, payor and prescriber level via the provision of evidence to stakeholders, who have distinct needs.

I learned that new drug treatments were frequently delayed or received negative decisions because pharmaceutical companies weren’t providing the right evidence to stakeholders. There’s currently a 54% mismatch between stakeholders and pharma regarding what evidence needs to be provided.4

I developed the multiple-stakeholder approach to real-world evidence generation to address this issue.4 This helps pharmaceutical companies create strategically targeted medical plans with the distinct needs of each stakeholder in mind.

Even if a pharmaceutical company is aware of stakeholder needs, evidence availability can be a problem. Rare diseases are often under-researched, with fragmented and/or incomplete evidence bases. This means it’s harder for pharmaceutical companies to establish compelling evidence for stakeholders.

My approach solves this problem by establishing dedicated patient registries and core datasets. These data sources are created using the most accurate construct measurements, ensuring the highest quality evidence to facilitate drug development.

These solutions help pharmaceutical companies generate the right evidence, but a fundamental problem is that real-world evidence is currently being generated at the wrong time. Fortunately, this is perhaps the simplest problem to solve.

…At the right time

My research on the medicine adoption model has shown that initiating real-world evidence generation at Phase I and II could help new treatments reach patients 22% sooner.5 That’s approximately two years sooner for every drug development lifecycle, assuming the mean time of 10 years. When just 6 months can mean significant clinical worsening for rare disease patients, this incredibly simple solution has immense power to change lives for the better.

There are other benefits of generating real-world evidence in time for regulatory approval. We’ve shown that it tends to result in a broader population indicated for treatment, meaning that new treatments could reach more patients.6 In fact, by generating real-world evidence in time for regulatory approval, we estimate that 30% more patients could receive new treatments than if randomised controlled trial evidence is submitted alone (Figure 3).

Figure 3: Our 30/22 vision. Generating real-world evidence in time for regulatory approval could decrease the time it takes for medicines to reach patients (time to maximal adoption) and increase the number of patients who receive a medicine (depth of maximal adoption).

The Four Pillars Medicine Real-World Evidence Strategy

All this research has culminated in the Four Pillars Medicine Real-World Evidence Strategy, an end-to-end solution that helps pharmaceutical companies generate the right real-world evidence at the right time to help more patients, sooner.

The Four Pillars Medicine RWE Strategy implements Neutral theory (Pillar 1), the Jandhyala method (Pillar 2), the multiple stakeholder approach (Pillar 3) and the medicine adoption model (Pillar 4). Medialis Ltd., my medical affairs consultancy and contract research organisation, now implements this solution for pharmaceutical companies worldwide.

Using the Four Pillars Medicine RWE Strategy means that life-changing medicines could reach 22% more patients, 30% sooner by

  • developing more accurate construct measurement tools, patient registries and core datasets
  • generating targeted real-world evidence matched to all stakeholders’ needs
  • generating regulatory-grade real-world evidence in Phase I and II clinical trials

Getting more people living with rare disease on the right treatments, sooner

My mission began with my son, Luca, but now, Medialis Ltd. is a thriving medical affairs consultancy and contract research organisation specialising in real-world evidence generation for drug development.

We work with pharmaceutical companies to develop more accurate construct measures to facilitate the progression of treatments through the regulator, payor and prescriber. We also use these construct measures to establish core datasets and patient registries in rare diseases with fragmented and/or incomplete evidence bases.

It has been hugely inspiring working with my team to discover new insights, but our work hasn’t stopped there. We’re constantly creating new applications of the Jandhyala method to help pharma improve patients’ lives. But we can’t create the change the pharmaceutical industry needs on our own.

We want to get as many people involved in the real-world evidence revolution as possible. Whether that means signing up to our database to register your interest in participating in our ongoing research as a patient, clinician, academic or other expert, joining our Congress in 2023, following our LinkedIn or considering us for your next real-world evidence project, we’d love you to get involved.

For more information, please visit our website, Medialis.co.uk, read more about our research, or contact info@medialis.co.uk.

References

  1. Jandhyala R. Neutral theory: applicability and neutrality of using generic health-related quality of life tools in diseases or conditions where specific tools are available. BMC Medical Research Methodology. 2021;21(1):86. doi:10.1186/s12874-021-01279-w
  2. Jandhyala R. A novel method for observing proportional group awareness and consensus of items arising from list-generating questioning. Current Medical Research and Opinion. 2020;36(5):883-893. doi:10.1080/03007995.2020.1734920
  3. Jandhyala R. Delphi, non-RAND modified Delphi, RAND/UCLA appropriateness method and a novel group awareness and consensus methodology for consensus measurement: a systematic literature review. Curr Med Res Opin. 2020;36(11):1873-1887. doi:10.1080/03007995.2020.1816946
  4. Jandhyala R. The multiple stakeholder approach to real-world evidence (RWE) generation: observing multidisciplinary expert consensus on quality indicators of rare disease patient registries (RDRs). Current Medical Research and Opinion. 2021;37(7):1249-1257. doi:10.1080/03007995.2021.1927689
  5. Jandhyala R. A medicine adoption model for assessing the expected effects of additional real-world evidence (RWE) at product launch. Curr Med Res Opin. 2021;37(9):1645-1655. doi:10.1080/03007995.2021.1947218
  6. Jandhyala R. The effect of adding real-world evidence to regulatory submissions on the breadth of population indicated for rare disease medicine treatment by the European Medicines Agency. Journal of Pharmaceutical Policy and Practice. 2022;15(1):36. doi:10.1186/s40545-022-00433-z

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