Real-world evidence is being used by the health care sector to support the safe development of new medical interventions including devices, services and biopharmaceuticals. Before, it was only considered in the post-approval phase when bringing a new therapy to market, but now, it is being considered earlier in the clinical trial process. What is real-world evidence, how is it used, why is it important, and how can you start harnessing it?

What is Real World Evidence?

Evidence obtained from analyzing real-world data (RWD) is referred to as real-world evidence (RWE). To generate RWE, the RW data must be analyzed. Different statistical analysis can be done through modeling, or by performing a variety of different studies. Technology, like IBM’s Watson, can also be used for data analysis where it aggregates and reports on insights derived from multifaceted real-world data sets.

This real-world data comes from routine delivery of medical care. For example, RWD can come from clinical data such as electronic health records (EHRs) and electronic Case Report Forms (eCRFs). Patient generated data including medical charts, data gathered from mobile devices or wearables, and Patient Reported Outcomes (PRO). PROs are completed by patients and give researchers firsthand patient perspectives and an understanding of events that go on outside of appointments, operations, and hospital stays. Available public health data such as disease registries, prescription habits, and the use of healthcare services, can give data for the general population.  Lastly, cost data in the form of claims or billing activities can provide a monetary indicator for healthcare spending. Patient identity markers are expressly removed to maintain patient privacy. The RWE extracted from these data sources provide insight into elements that are not included in randomized clinical trials (RCT).

How is RWE used?

Real-world evidence enables researchers to assess the efficacy of medical treatments or interventions while considering other circumstances and variables not always accounted for with RCTs. A randomized controlled trial (RCT) enrolls a small subset of the population and examines how different groups react to a novel therapy in a controlled setting. While RCTs are considered ‘the gold standard’ in clinical testing, they are expensive and take a long time to complete. Rather than using RCTs alone, RWE can provide a more comprehensive insight of how a new treatment option will work in the “real world” and for a more diverse population. By supplementing RCTs with RWE, researchers can gain a better understanding of what works for different sub-populations.

RCT suffer from a narrow pool of trial participants and are not truly representative of the general population. Because RCTs have strict inclusion and exclusion criteria for enrollment, certain populations are expressly not represented in the trial, one such example is pregnant women. It is also the case that trials struggle to recruit candidates from certain ethnic populations, as is common for Hispanic communities. With a lack of diverse representation in clinical trials, the results from RCT do not consider all patient characteristics including age, gender, ethnicity, pregnancy, medical history, etc. However, using RWE can fill in some of these gaps.

Why is RWE important?

Real-world evidence can provide insights into how medicines work in certain patient subgroups that may not have been investigated in RCTs. RWE, for example, can allow researchers to investigate how novel medicines function in patients within specific age ranges, or specific socio-demographic groupings. Real-world evidence can also help researchers comprehend what occurs to a patient over the course of his or her life, not only during the RCT period, to assess the treatment’s effectiveness. How people use a product, what symptoms it does improve, side effects — all of that can be different from what is observed in a controlled trial in a clinic. The healthcare industry is constantly working on improving patient outcomes and reducing hospitalization rates. One way to achieve this is to work on more tailored therapies and personalized medicine. Because RWE insights are so valuable, the FDA employs real-world data and RWE to monitor post-market safety and adverse occurrences, and to support regulatory decisions.

RWE also helps improve healthcare decisions and is used in health economics and outcomes research (HEOR). HEOR measures the outcomes of healthcare interventions and the effect they have on patients to provide data and insights for healthcare decision makers. These decision makers include clinicians, governments, payers, health ministries, patients, to name a few. For these stakeholders, real-world data collection, analysis and reporting is essential.

How to collect and use RWE?

With so many varied data sources (clinical data, patient generated data, public health data, cost data) healthcare stakeholders may choose to use clinical trial and data science services. Evident IQ provides researchers with software to collect real-world data and can provide support to analyze RWD to generate and report on RWE.

As part of clinical trial data collection services, EvidentIQ offers eCRF Setup which simplifies electronic data collection forms, design branching questions, develop in-form and cross-form validations and edit checks to maximize data cleaning at the field level. They also provide configuration support for multilingual eCRF forms, and any localization support needed to configure the application workflow to align with the site’s local processes. Their Patient Reported Outcome (PRO) surveys collect a multitude of data points including treatment preference, quality of life, value of health, disease/treatment burden, and unmet needs. This data is then subject to sophisticated methodologies used to generate unique RWE. Data Linkage is one such method. Data Linkage helps match and merge records from different sources to get a richer dataset and more valuable evidence. EvidentIQ uses significant clinical data expertise, data science analysis, and access to Carenity patient platform, to successfully conduct state of the art data linkage studies. Their innovative data linkage capabilities combine unique self-patient reported data with biomarkers collected by a wearable/sensor through continuous monitoring, bringing RWE to the next level.

Real-world evidence is growing in popularity. Before it was only considered in the post-approval period, but now, it is being considered earlier in the clinical trial process. Using RWE at an early stage in treatment development is a critical consideration for healthcare stakeholders and is driving the trend of gathering more RWE and ultimately improving the safety and effectiveness of medical therapies.

Sources: 

https://veradigm.com/real-world-evidence/

https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence

https://www.arbormetrix.com/blog/9-ways-real-world-evidence-is-changing-healthcare/

https://vial.com/blog/articles/what-is-real-world-evidence-in-clinical-trials/?utm_source=organic

https://viseven.com/what-is-rwe-in-pharma/

https://servier.com/en/newsroom/folders/importance-real-world-studies/

https://rwe-navigator.eu/use-real-world-evidence/rwe-importance-in-medicine-development/

https://www.clinicalleader.com/doc/why-all-the-talk-about-real-world-evidence-0003

https://www.statnews.com/sponsor/2017/02/16/real-world-evidence-need-2/

https://www.ispor.org/heor-resources/about-heor

An evidence generation strategy is an advanced plan for generating evidence necessary for all the steps of the product life cycle. Traditionally, research follows consecutive steps which is more of a reactive process. Using an evidence generation strategy allows for proactive planning and execution of a holistic strategy.

What is evidence generation and what is it used for?

Evidence generation is multifaceted and includes various study designs and data sources. Typically, each department involved in the process (e.g., clinical development, medical affairs, and health economics and outcomes research (HEOR)) works in a siloed structure and independent from one another to come up with evidence to support their specific research topics.

Integrated evidence-generation plan (IEP) is a strategy used where the upfront research plan is developed specifically to find evidence to address the concerns of each stakeholder group (payers, clinicians, patients). Beyond simply proving if a therapy is effective and safe, pharmaceutical companies need to prove that the new treatment is addressing market gaps that the current products do not meet.

Each of these stakeholders have different needs and questions regarding new treatments. Payers, those who pay for the development of the treatment, want to ensure the final product has a value to the healthcare system and will prove to be profitable when launched. Clinicians look for evidence-based research to show how the new treatment is different from existing options. Patients need to know how the new treatment will meet their needs and solve their problems.

An IEP will pinpoint these motivations from each group and strategically set up testing to address each one. Considered in the planning are all functions, geographies, and the entirety of the life cycle to meet the needs of the various stakeholders. Demonstrating the economic, clinical and patient burden of a disease is a key need early in the development process and sets the stage to inform stakeholders regarding the potential value of a product.

Why it is important to have a plan early?

Early evidence-generation planning is key to allowing time to connect all the dots between functions and requirements. It is of vital importance when demonstrating value for the new treatment and it must be demonstrated throughout the lifecycle of the product (early development, clinical research, launch, and post approval) to understand the implications of how the product will address needs at each step along the way.

Impactful data points for each function team (medical, clinical, commercial) can be identified and a roadmap created to ensure the evidence-generation plan includes steps to achieve these data results which will add to the products overall value proposition. A cross-functional and early approach ensures the funding and required expertise is available at all stages.

What are the main steps where you could need evidence?

The ultimate goal of the treatment is to hit the market and provide a solution for the patient, add value to the healthcare community in the form of a differentiated treatment, while being profitable for the developer. Therefore, during the development of the product, it is beneficial to incorporate these factors into each stage of the product lifecycle.

In the early stages of development, there is a need to understand the current state of care for the target patient population. This includes conducting market research, literature reviews and developing a Health Economics and Outcomes Research (HEOR) strategy, identifying possible clinical trial designs, among other tasks that could benefit from evidence-generation. At this point in the product life cycle, the payer stakeholder is interested in the economic burden of disease in order to justify resources required to develop and adopt a new treatment.

During the clinical research and development stage is when patient trials and market access strategies start to be executed. Evidence generation collected from Randomized Clinical Trials (RCT) and patient reported outcomes (PRO) can be paired with Real World Evidence for proof of treatment effectiveness and differentiation of current on-the-market products. Clinicians will be most interested in the data that comes from this stage.

To launch a new product, a medical affairs team may use the evidence to inform their market access strategy and develop communications that target patient needs identified early on in the IEP. The launch stage is where the end prescriber and patient will be convinced of the value of the new treatment based on evidence leveraged through the marketing campaign.

The integrated evidence-generation plan utilizes the research results of all functions: market research, health economics and outcomes research, clinical trials, market access, patient-reported outcomes, literature reviews, etc, and combines them with the strategic objectives and ultimate value proposition. Be proactive with your go-to-market strategy, and plan in advance to address the needs of each stakeholder group. Along with a software suite for clinical trials, EvidentIQ offers the ability to run prospective and direct-to-patient studies with patient-reported outcomes through its Carenity Patient Platform. Carenity part of the EvidentIQ Group is a key partner to consider to support your data generation plan.

Take a look at our RWE offer.

Sources

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5047978/

https://www.openhealthgroup.com/news/17-01-2022/key-elements-of-a-real-world-evidence-generation-plan
https://marimacinsight.com/evidence-generation-strategy/
https://www.futuremedicine.com/doi/10.2217/cer-2017-0073
https://www.evidera.com/wp-content/uploads/2017/05/Strategic-Evidence-Generation-Planning-Product-Positioning.pdf
https://www.mckinsey.com/industries/life-sciences/our-insights/integrated-evidence-generation-a-paradigm-shift-in-biopharma

How to leverage data linkage to get better outcomes?

EvidentIQ, a leading clinical data science group, announced its partnership with Feel Therapeutics, a digital therapeutics US-based company. The alliance between these two visionaries of tech has resulted in the building of unique end-to-end solutions to link data and digitize clinical trials through a seamless patient journey supported by direct access to patients, best-in-class technologies and in-house data science expertise.

• What is Real-World Evidence and the different sources of Real-World Data?
• How to collect real-time physiological data 24/7 to monitor emotions, physical activity, and sleep quality: the example of Feel Therapeutics Data Monitoring and Digital Endpoint Discovery Platform
• How to efficiently collect self-reported outcomes?
• How to combine these two innovative data sources?

On May 12th our data linkage webinar took place. We showed you how innovative Real-World-Evidence generation can help to efficiently combine digital biomarkers and self-reported outcomes.

Access the replay! We will walk you through the new data linkage thanks to this partnership, combining best-in-class technologies and expertise of EvidentIQ and Feel Therapeutics.

Access the replay


Download the presentation

Contact us for more information: pro@carenity.com

Why collecting Real World Data is important to optimize clinical trials and get new medical product approved?

In clinical development, the traditional approach to demonstrate efficacy and safety of a new drug has always been in performing the traditional Randomized Clinical Trials (RCT) programs since this is considered by Regulatory Agencies as the best compromise to get sufficient, well-structured data from a subgroup of the future patient population in a reasonable time frame. However, these programs are highly cost-consuming and require the involvement of human resources (physicians, clinical research associates, etc.)

When a drug is assessed, Regulators and Health Technology Assessment (HTA) bodies require getting a far more extended set of data from a larger population and closer to normal life conditions. Having access to real life data enable to have a better understanding of disease and treatment burden, patient experiences, preferences to be able to establish how much the drug will cover unmet needs.

What is Real-World Data (RWD) and what are the different sources?

Real-world data is the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources, for example:

• Electronic health records (EHRs)
• Claims and billing activities
• Product and disease registries
• Patient-generated data including self-reported data entered by the patient or its relatives (e.g Patient-Reported Outcomes – PROs)
• Data gathered from other sources that can inform on health status, such as mobile devices.

What is Real-World Evidence (RWE)?

Real-world evidence is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD. RWE can be generated by different study designs or analyses, including but not limited to, randomized trials, including large simple trials, pragmatic trials, and observational studies (prospective and/or retrospective). RWE is increasingly used in drug development and evaluation as shown by the recent guidelines published by the FDA.

What is new in July 2021 FDA guidelines?

Since 2016, after the publication of the 21st century Cure Acts, the FDA is taking into account RWD for the evaluation of new drugs/medical devices, mostly to monitor post-marketing safety or support extension of indications.

In July 2021, the FDA published guidelines to illustrate the interest of implementing RWD during clinical development phase and not only at the end of that lengthy phase. There are many approaches from including RWD in the RCT up to implement specific trials in parallel to the pivotal program. RWE is not a substitute for RCTs but should be seen as complementary, each type of study design providing information the other cannot.

Due to long processes during new drug/medical device development, pharmaceutical companies should evaluate the best approach to collect data as early as possible. Indeed bringing patient perspective into clinical projects can accelerate clinical trials, save costs and ensure the success of new products. .

For Medical Devices, the FDA is also relying on RWE to support their decisions and to evaluate risk/benefit.

EMA (European Medicines Agencies) is also working with European National Agencies on a strategic plan for 2023 road map in favor of the use of RWE in clinical development considering the benefit of having access upfront to real world data.

Some examples to Illustrate how FDA rely on RWE to support regulatory decision-making:

In July 2021, U.S. Food and Drug Administration approved a new indication for Prograf (tacrolimus) based on an observational, non-interventional study providing real-world evidence (RWE) of effectiveness. FDA approved Prograf for use in combination with other immunosuppressant drugs to prevent organ rejection in adult and pediatric patients receiving lung transplantation.

In a more recent time, FDA has decided for the Pfizer-BioNTech COVID-19 Vaccine to allow for use of a single booster dose, to be administered at least six months after completion of the primary series in specific subset of population: the decision was partly based on real-world data on the vaccine’s effectiveness over a sustained period of time provided by both U.S. and international sources, including the CDC (Centers for Disease Control and Prevention), the UK and Israel.

How Carenity can help you?

Carenity, part of the EvidentIQ group, offers Real-World Evidence solutions to collect and analyze self-reported patient information (ePROs, patient preference information using Discrete-Choice Experiment designs, e-diaries, etc.).

Carenity relies on its global digital platform that engages more than 500,000 patients and caregivers in Europe and North America to conduct prospective non-interventional studies (cross-sectional and longitudinal designs). Theses observational studies can generate meaningful information about quality of life, disease and treatment burden, product effectiveness, patient preferences, etc.

Carenity supports its Life Sciences Industry clients at each step of the clinical development to ensure the success of patient recruitment and retention thanks to patient-centric decision-making:

• Target Product Profiles (TPP) definition
• Study design optimization and protocol evaluation
• Study feasibility assessment
• Endpoint optimization
• Test of patient materials (Informed Consent Form, Information notice, etc.) and patient services

Carenity also offers PatientLive®, a self-service platform to collect real-time patient insights. This unique solution allows to get fast answers from patients and caregivers and make better decisions via a quick poll (1-5 questions).

Contact us for more information: pro@carenity.com

Bibliography :

https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/submitting-documents-using-real-world-data-and-real-world-evidence-fda-drugs-and-biologics-guidance

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/use-real-world-evidence-support-regulatory-decision-making-medical-devices

https://www.fda.gov/drugs/drug-safety-and-availability/fda-approves-new-use-transplant-drug-based-real-world-evidence

https://www.fda.gov/news-events/press-announcements/fda-authorizes-booster-dose-pfizer-biontech-covid-19-vaccine-certain-populations

https://www.ema.europa.eu/en/about-us/how-we-work/big-data