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

We know that bringing the patient perspective at each step of the medical product life cycle is crucial to ensure the success of a new product. However, getting information directly reported by patients can be long and complex.

On October 28th our PatientLive webinar took place. We showed you how PatientLive® allows you to collect real-time patient insights at a fast pace, in order to help you make better strategic decisions with the help of real-life patient data.

This live session hosted by two of our finest industry specialists Emilie Pain, PatientLive Product Manager at EvidentIQ and Thierry Escudier, Strategic Consultant at DCRIPT, covered all you need to know about this innovative solution and how you can benefit from it.

What is PatientLive?

PatientLive® is a unique solution to get fast answers from patients and caregivers and make better decisions via a quick poll (1-5 questions).

This self-service platform gives you access to a community of 500,000 patients and caregivers in the US and Europe, so you can understand patient experience, test concepts of services, develop awareness campaigns, listen to patient preferences and thus create patient-centric solutions to fill unmet needs.

PatientLive® is available for 36 conditions. These conditions include immunology, respiratory conditions, endocrinology, gastroenterology, dermatology, oncology, etc.

Contact us for more information: patient-live@evidentiq.com

I’m Gilda Teissier, Marketing Director at EvidentIQ and I recently met with Emilie Pain, Data Scientist at Carenity, part of the EvidentIQ Group.

Whether to develop new products, services, design clinical trials or marketing strategies, first-hand access to patients and caregivers is increasingly becoming a cornerstone for life sciences industries.

By collaborating and engaging with patients in the decision-making process, health providers can make better decisions regarding a patient’s health. Therefore, having access to accurate information reported by patients and caregivers is essential to understand patient experience and be patient-centric, identify unmet needs in terms of products, services and information, test concepts of services and campaign messages, define Target Product Profiles, and optimize the design of clinical trials (study materials, endpoints, protocol assessment).

The only problem sometimes is that having access to this information can take time and a lot of resources. PatientLive® is a platform that responds to this by giving access to real-time Insights in a fast, autonomous and simple way.

Today I have the pleasure to interview Emilie Pain, PatientLive® Product Manager. She will help us understand better the need of patient-centric information and how PatientLive® helps us meet that in a quick and accurate way.

Gilda: Which are the main challenges of healthcare providers when it comes to access and use of patient information?

Emilie: Access to information directly reported by patients is long and complex for healthcare providers due to regulatory constraints. They need a third party that allows them to have quick access to patient insights on a regular basis to understand patient experience, to test new materials, and to listen to patient expectations and thus create patient-centric materials.

Gilda: What is PatientLive®?

Emilie: PatientLive® is a unique solution that allows customers to quickly survey an online community of 500,000 patients and caregivers in the US and Europe via quick polls (1 to 5 questions).

“PatientLive® is a unique solution that allows customers to quickly survey an online community of 500,000 patients and caregivers in the US and Europe via quick polls”

This tool, unique on the market, provides access to accurate patient insights in a compliant way. It also allows our customers to target specific patient profiles (country, condition, addition of a screener question).

The polls implemented through this platform allow quick and easy access to patient insights, which are complementary to traditional marketing surveys or real-world studies (non-interventional studies, preference studies, etc.) conducted by Carenity.

Gilda: Who is PatientLive® for?

Emilie: PatientLive® is a solution dedicated to the life sciences industry, such as pharmaceutical companies, biotech companies, medtechs or healthtechs companies. It can be of special interest to market research/business insights, commercial/marketing, patient engagement, medical affairs, market access, research and development, clinical development, and clinical operations teams.

Finally, it can also help consulting firms, market research agencies, and communication agencies to support the life sciences industry in their strategic decisions and actions.

This solution is available in the US and Europe (France, the United Kingdom, Germany, Spain and Italy).

Gilda: Which conditions can be targeted?

Emilie: PatientLive® is available for 36 conditions. These conditions include oncology, such as breast cancer or lung cancer, but also immunology (e.g. rheumatoid arthritis, multiple sclerosis, lupus), respiratory (e.g. Asthma, COPD), endocrinology (e.g. type 1 diabetes, type 2 diabetes, obesity), gastroenterology (e.g. Crohn’s disease), dermatology (e.g. psoriasis), etc. A detailed list can be found at the PatientLive’s site.

Gilda: How does it work?

Emilie: Once a customer has defined a topic, they can implement their poll on the platform.

PatientLive® offers the possibility to ask up to 5 questions per poll. There are 5 types of questions available: single choice, multiple choice, scale from 0 to 5, text field, numeric field and test of images/videos.

PatientLive® offers the possibility to ask up to 5 questions per poll.

They can also create a screener question to target a sub-population. A screener question is a question to which the answer must be either «Yes» or «No». For example, a screener question can be “Are you treated by insulin therapy?”. Only the respondents who choose «Yes» as answer are considered at the display of the results.

Once the poll has been created, a validation is made by the Carenity’s Data Science team before the poll goes live.

Then, invitations to participate are sent to patients and poll results are available once the first respondent has answered. 

Gilda: How much time does it take to obtain results and how are they delivered?

Emilie: The period can vary from 1 to 15 days, depending on the condition, the screening questions and the targeted number of respondents.

The results are available in real time on the site. Starting from the first responses customers can visualize the results thanks to our dashboard. Our customers also have the possibility to download the results (raw data, tables of results, or report) in real time.

Gilda: Can you give us a specific example of how the results can be integrated by pharmaceutical companies?  

Emilie: The results of a PatientLive® poll can be integrated by pharmaceutical companies through different ways, but one of the most concrete examples we have is from a poll we conducted among diabetic patients which evaluated a new advertising campaign and allowed our customer to adjust the wording of this campaign. I can also think of polls conducted to better understand patient experience (disease/treatment burden, quality of life), to identify patients’ unmet needs in terms of products, services and information, or to measure patients’ perception of products, devices or services.

Gilda: Are there any specificities in the use of the data by clinical teams or CROs?

Emilie: The results of a poll can support clinical teams in the definition of the Target Product Profile, in the evaluation of patient’s acceptance of the protocol evaluation parameters and flow chart, in the definition of study endpoints valuable from a patient perspective, in the optimization of the design of the clinical trial, etc. For instance, we have recently conducted a poll evaluating patient understanding of the information notice that was planned to be used on a clinical trial. It helped our customer clarify some parts of this information notice. 

Gilda: You previously mentioned that consulting firms, market research agencies, and communication agencies can also use PatientLive®. What are the type of polls they conduct?

Emilie: They mainly use our tool to differentiate their proposal and pitch by incorporating patient insights, to assess the feasibility of their studies, to optimize the design and the questionnaire of their patient studies, to generate patient insights to enrich their results and recommendations, and to test concepts of services or campaigns. To give a more specific example, a poll was conducted among breast cancer patients in order to evaluate the proportion per stage and thus the feasibility to conduct a study among metastatic breast cancer.  

Gilda: Thanks a lot for your time!

For more information about PatientLive® click here.