REAL WORLD EVIDENCE

Life Sciences

Insights from 2015 Industry Leaders

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Real World Evidence Lifecycle*

REAL WORLD DATA“The New Currency in Healthcare”

Real World Data (RWD) have become the bio/pharmaceutical industry’s treasure trove for information to inspire stakeholder decision-making. As an industry, professionals have increasingly been looking to RWD to not only assess the benefits and risks of new medicines in clinical and real world settings, but also as a way to advise healthcare reimbursement decisions worldwide.

In the past, real world data was collected only during the post-approval phase of clinical trials and within patient registries. However, the industry is experiencing a shift toward RWD collection earlier in the clinical trial process (as early as Phase II). Gone are the days of beginning to collect RWD after a product has been

approved; early data generation is especially critical in today’s market, given how saturated the healthcare marketplace is for many types of medications. New medicines in development undergo intense evaluation prior to regulatory approval. Instead of just being evaluated by the risk-benefit ratio of the medication, regulators and payers are increasingly assessing whether a new drug adds significant benefit over an established standard of care. In order to eventually achieve favorable placement on a payer’s formulary, the price of the product must also be justified by a correlated positive health outcome for the patient. Evidence collected in real-life settings are the only available source that can accurately answer these questions.

As data collection and storage capabilities continue to advance, RWD are less limited, which helps HEOR teams to fully capitalize on RWD to prove product value. In our technologically advanced world, we sit on the cusp of a golden era of access to digitized RWD, optimized by the adoption of electronic health records and the integration of clinical and biological information with other data, including registries, treatment databases, mobile platforms, social media and patient surveys (to name a few). Optimal use of RWD can provide a greater understanding of medicines and diseases, the impact on treatment standards and the long-term impact of medications on patient health.

RWD Intensifying Across Product Lifecycle

* IMS Health, “Real-World Insights. Real-World Impact.” www.imshealth.com

Illustrated by the graph, more evidence is required at every stage of product development growth and maturity than ever before. Anonymized patient-level data are becoming more accessible around the globe, allowing RWD to become the new currency in healthcare. The accessibility of data at all stages of development allow healthcare decisions to be more accurately informed by millions of patient experiences across the globe, all in real world settings. Using RWD, patients, healthcare providers and payers can better assess the value of treatments and services based on actual patient health outcomes and the total cost of care.

Who is utilizing RWD today?

• Clinical development teams: to design clinical trials based on actual treatment practices

• HEOR, epidemiology and drug safety researchers: to gain faster insights from richer patient databases

• Market access teams: to inform payers and HTAs with evidence of their product’s value

• Brand and franchise teams: to understand their markets, differentiate their products and improve stakeholder engagement

In addition, the “patient as a partner” is a new stakeholder that now must be critically engaged throughout the whole product lifecycle. Increasingly, payers are expressing that the voice of the patient will be a factor in decision making to help provide evidence that proves a superior product. As a result, bio/pharma teams are learning how patients can aid with the development of clinical tools and measurements through patient reported outcomes and voluntary patient data sharing.

As one can see, the benefits of fully utilizing RWD are immense for healthcare costs and patient health across the bio/pharmaceutical industry. However, RWD are also incredibly challenging. The data sources vary widely in quality, reliability and consistency, which requires a certain level of calculated risk when evaluating medicines. Additionally, the industry lacks policy solutions and full stakeholder cooperation.

This is what they have to say…

We had the opportunity to sit down with industry’s foremost RWD thought leaders. We asked them a variety of questions on the topic to better understand how bio/pharmaceutical teams can collaborate and capture data in an aggregated form to continue to improve the value of products in development with real world, real-time data.

In your experience, how is it beneficial to capitalize upon real world evidence to prove superior product value?In a value-based healthcare system demonstrating real world outcomes and comparative value will become the most important factor in driving market adoption. Without that, potentially great products will never leave the shelves. This is already becoming true for some payers, but will become much more true for providers who take on population risk.

Can you name two barriers of using real world data and the strategies to overcome them?Much real world data is often not being used for the purposes that it was intended, (e.g. billing data being used for outcomes); it’s not longitudinal at the patient level; it’s not representative of the population you want to understand and it’s not complete. The key strategies to overcoming these limitations are a greater focus on upfront planning for what is needed; what data are available and how can those data be supplemented with other data sources or primary collection to close the gaps.

The industry has called real world data “the new currency in healthcare.” Do you agree with this statement and if so, why or why not?What works in the real world is what every stakeholder, patient, provider, payer and manufacturer needs to know. In that way, I agree. But much of what we call real world data is not the right data to tell us what works. So, I’d qualify the statement with the “right” real world data.

Specifically in what ways do you anticipate big data value will increasingly become a driving force for a more sustainable healthcare system?The greatest opportunity for big data is that it will help healthcare systems make better decisions. Using novel big data capabilities, we are quickly becoming able to answer questions like which patient is most likely to be at risk for a fall, infection or readmission; who is most likely to benefit from a diabetes treatment program; which patient needs another scan to rule out a cancer or which patients should have an end of life discussion. These are important questions in a healthcare system where resources are inevitably constrained.

ABOUT DR. GLIKLICH...Dr. Rich Gliklich serves as an Executive in Residence at General Catalyst Partners where he leverages his operational experience and domain expertise to invest in and support businesses in the healthcare and life sciences industries. Prior to joining General Catalyst, Dr. Gliklich was President of the Outcome division of Quintiles. Prior to Quintiles, he was Founder, CEO and Chairman of Outcome, a health information and services company that served more than 3000 healthcare organizations and a majority of the global top 30 lifesciences companies. He led Outcome from its start as a spin-off from his Harvard affiliated research laboratory in 1998 through its acquisition by Quintiles in October 2011. In addition to his experience as an entrepreneur and executive, Dr. Gliklich is well known in the areas of outcomes and analytics. He is senior editor of the landmark publication by the U.S. Agency for Healthcare Research and Quality (AHRQ) handbook “Registries for Evaluating Patient Outcomes: A User’s Guide,” as well as PI for the national Outcome Measures Framework project and has led several key national and international efforts focused on evaluating the safety, effectiveness, value and quality of healthcare. Dr. Gliklich is also co-founder of Cyft, a revolutionary healthcare prediction platform. He is a graduate of Yale University and Harvard Medical School. In addition, he is also a surgeon and a chaired Professor at Harvard Medical School.

Rich Gliklich, M.D., Leffenfeld Professor, part time, Harvard Medical School; XIR, General Catalyst Partner

In your opinion, what is most important to working with payers, in regards to partnering around value demonstration, shared risk and pay for performance?We should work with them to agree to a value definition that makes sense in the quest to improve patient health, to make sure we are actually sharing the risk and it not only falls on the manufacturer and to have a clear definition of what is meant by performance.

Why do you think it is important to incorporate patient perceptions and experiences into clinical research? How does patient satisfaction lead to better HEOR evidence?Let me start with a quote from Professor Michael E. Porter at Harvard: “Today, value tends to be defined by what can be easily measured in our current misaligned structure, rather than what actually matters for patients.” As the patient is the ultimate end user of healthcare, I think their viewpoint should be included in the equation. Patient satisfaction complements other data to better understand the value based on HEOR evidence.

Can you define value and discuss the impact on collecting evidence for value generation?Value to me is defined as outcomes divided by costs. The challenge lies in the composition of the numerator “outcomes.” We have a tendency to only define outcomes as the result of efficacy, safety, tolerability and maybe add a quality component to include the patient perspective. The challenge is to determine the right proportion of each bucket and also question whether this really represents the patient perspective.

In your opinion, how do early access programs support or complement data gleaned from clinical trials?They may support the notion of effectiveness of an intervention in the real world, although somewhat biased towards the patients that are in urgent need of the treatment as opposed to patients that will receive the innovation post launch.

Bjorn Bolinder, Group Director, U.S. Health Services, Oncology, Bristol-Myers Squibb

ABOUT MR. BOLINDER...Bjorn Bolinder is an economist with 23 years of experience in the pharmaceutical industry, of which 18 years he dedicated to the health outcomes area, with responsibilities at affiliate, US and global level. Mr. Bolinder has broad therapeutic area knowledge, with the majority of experience in the diabetes, cardiovascular, CNS and Oncology areas.

Why do you think it is important to incorporate patient perceptions and experiences into clinical research? How does patient satisfaction lead to better HEOR evidence?Patients are the central focus of our research. It is critical for us to listen to them beyond the data points we are working to collect. Patient feedback and insights are changing the way we develop protocols, recruitment and retention strategies and develop positive experiences in our research programs.

The industry has called real world data “the new currency in healthcare.” Do you agree with this statement and if so, why or why not? Real world data is impacting the evidence we generate in research programs and late phase research stakeholders, including regulators, payers, providers and patients, want this data. This trend also appears to be expanding as we are now seeing real world evidence generation included in clinical development and patient support programs.

How does your organization currently capitalize on real world evidence to prove superior product value? What are your biggest challenges in reporting evidence to stakeholders?In order for Quintiles to improve our customers’ probability of success we are focused on combining our scientific and patient engagement expertise, proven global processes and operations and Quintiles Infosario technology together for real world and late phase research studies. This approach is enabling our customers to prove their products’ value and generate evidence for their stakeholders in novel ways that enhance patient engagement, retention and compliance.

John Reites, Senior Director, Health Engagement and Communications, Quintiles

ABOUT MR. REITES...John Reites is the Head of Product and Strategy for Quintiles Health Engagement & Communications. Mr. Reites is responsible for developing engagement innovations and patient-centered strategies to improve Quintiles’ customer’s probability of success. Mr. Reites is a speaker and author of various conference presentations, industry articles and peer-reviewed publications, providing subject matter expertise for direct-to-patient research, patient recruitment, patient communities, direct-to-patient late phase research and digital health approaches.

Mr. Reites has over 12 years global research experience conducting more than 150 programs spanning Phase I – IV studies and Commercial programs. His experience includes health research programs conducted in 52 countries reaching over 5,000 providers and 38,000 patients across various therapeutic areas. He provided oversight and development support for Quintiles patient communities of >3.4 million members in 7 countries including MediGuard.org and ClinicalResearch.com. He has also lead the development and execution of direct-to-patient research programs integrating ePRO, medical chart data, at-home labs and digital health devices.

Prior to his current role, he developed novel study design approaches and new business units from start-up to global scale within Quintiles. He has held multiple leadership positions within Clinical Operations, Global Project Management and Late Phase Research during his tenure.

The industry has called real world data “the new currency in healthcare.” Do you agree with this statement and if so, why or why not?Real world data will be the new currency — but what will it be worth to each organization? Unfortunately, it starts off as exhaust. The majority of real world data is captured as unstructured free text and the available structured data can be up to 80% inaccurate. The organizations that will thrive in a value-based economy will be those that are able to transform this byproduct of care into healthcare organizations’ most valuable asset.

Specifically, in what ways do you anticipate big data value will increasingly become a driving force for a more sustainable healthcare system?In a value-based world, it becomes critical to answer the three fundamental questions of improvement: 1) what are we doing; 2) to whom are we doing it and; 3) is it

working? The ability to begin to understand this is a prerequisite to progress and yet there’s not a healthcare delivery organization that can answer all three. If the term “big data” makes it popular to begin actually measuring what we’re doing, then I’m a huge big data advocate.

In your opinion, what are the most eminent ways patient considerations can impact: 1) trail design; 2) study participation; and 3) payer decisions?Healthcare is transitioning from a system that values outputs to a system that values outcomes. Outputs are finite transactions. Outcomes are product of a patients experience with each of healthcare’s dozens of stakeholders. In an outcomes-based model, the patient “owns” the outcome and therefore becomes the most valuable of all stakeholders. Organizations that recognize this and act accordingly will thrive.

Leonard D’Avolio, Ph.D., Director of Informatics, Ariadne Labs; Assistant Professor, Harvard Medical School; Co-Founder, Cyft

ABOUT DR. D’AVOLIO...Leonard D’Avolio, Ph.D., is the Director of the Informatics and Measurement Platform at Ariadne Labs. In this role, Dr. D’Avolio works across all project teams to design and develop infrastructure and methods that turn raw data into actionable knowledge and ideas into scalable solutions. This includes building programs and infrastructure, supporting an international project data capture and analysis, and developing software capable of detecting novel relationships across heterogeneous data sources.

Prior to his role at Ariadne Labs, he was head of a team he founded within the Department of Veterans Affairs. There he was responsible for the development of national programs such as the development of the VA’s genomic science infrastructure and the first randomized controlled trial embedded entirely within an electronic medical record system. He also developed several software programs to make data mining and natural language processing accessible to non-technical end users. He has also been an investigator on several projects funded by the Agency for Healthcare Research and Quality (AHRQ), Department of Defense, and the National Institutes of Health (NIH) focused on using information technology to improve the conduct of clinical science and care.

Dr. D’Avolio earned his Master’s Degree in Information Technology from the McCallum School of Business at Bentley University and his Ph.D., which brought him expertise in data mining and natural language processing, from the University of California, Los Angeles. Prior to obtaining his graduate degrees he spent several years in the software industry.

In your opinion, how do early access programs support or complement data gleaned from clinical trials?It is important to keep in mind that the primary purpose for an Expanded Access Program (or early access program) is to provide access to investigational products to patients with serious or life threatening conditions with limited alternative treatment options. These programs are often purposefully not designed with objectives to compliment the clinical trial data.

Manufacturers should carefully consider the collection of efficacy data in EAP design given the potential unintended consequences of such an approach.

Adverse drug reactions must of course be collected and if new safety signals present during the EAP, there could be implications to the marketing application that is presumably in process.

In the event that a post marketing patient assistance program/HUB is planned, the EAP could present an opportunity to collect information that will in turn inform the optimal design of such a program.

In your opinion, what are the most eminent ways patient considerations can impact: 1) trail design; 2) study participation; and 3) payer decisions?A patient-focused approach to trial design is essential to the success of the initiative to collect real world evidence. The study must accommodate the patient’s “usual care” experience, be conducive to unbiased evidence capture, and allow for optimal patient participation retention rates.

Aaron Berger, Project Director, UBC – An Express Scripts Company

ABOUT MR. BERGER...Mr. Berger joined the UBC team in 2003 and has since served in a range of diverse roles leveraging UBC global capabilities supporting the execution of per and post marketing product development programs, Expanded Access Program programs, REMS implementation, and Pharmacovigilance service delivery. Mr. Berger started his career at UBC as a CRA followed by a move to Project Management and now serves as a Project Director.

As a Project Director, Mr. Berger provides support and direction to UBC project teams conducting late stage studies, EAPs, registries and observational studies. He oversees multi-disciplinary project teams and assists them in meeting project timelines according to UBC quality standards and study contract specifications. He is also responsible for operations, budget oversight, and regulatory requirements throughout the duration of the project. Mr. Berger plays an integral role in the development and implementation of integrated solutions to the challenges manufacturers face as products travel through the development life cycle and commercialization. Mr. Berger received his Bachelor’s degree from the University of Kansas and holds the Project Management Professional credential.

In your experience, how is it beneficial to capitalize upon real world evidence to prove superior product value?At the conclusion of Phase III, important questions remain regarding the value of the product in the marketplace. There is significant value in collecting real world evidence to prove superior product value as treatment and reimbursement decisions may depend on showing effectiveness and safety in usual care. The ability to describe the burden of illness and economic, clinical and humanistic utility of a product in patients in usual care settings can demonstrate superior product value. It is important to first understand the payer perspective to determine what value messages matter and then determine the types of studies that should be conducted to generate real world evidence.

In your opinion, how do early access programs support or complement data gleaned from clinical trials?Early access programs (i.e., Compassionate Use, Expanded Access) which allow patients with no other appropriate treatment options to receive an investigational agent prior to market uptake, can provide valuable insight into future real world use. While patients in an early access program tend to be considered “sicker” than patients in clinical trials, evaluation of safety profiles (e.g., new safety signals) and effectiveness (e.g., progression free survival [PFS] and overall survival [OS]) can successfully be undertaken to provide insights into PFS and OS as well as adverse events that may not have been identified in the more homogeneous clinical trial populations. Early access programs can also supplement data collected in clinical trials since they may include patient populations that are not be fully represented in the clinical trials (physicians not included as investigators and patients excluded from clinical trials).

Can you name two barriers of using real world data and the strategies to overcome them?Two barriers that we normally face when dealing with real world data are data quality and selection bias.

Achieving robust data quality and completeness can be challenging in real world studies that do not interfere with usual medical care. In retrospective chart review studies, patient medical chart documentation may be conflicting, missing or incomplete. In prospective studies, patient survey data may be missing or incomplete depending on the mode, length and frequency of administration. Selection bias is an inherent risk wherein the patient population studied may not represent the target population of interest thereby lowering the value of data collected. Patients are randomly assigned to a treatment during a clinical trial in order to minimize bias between the groups being studied. In “real world” studies such as observational cohort studies, physicians prescribe the drug as per usual care, which may be outside of labeling, i.e., the patient characteristics, dosing or indication may differ from the approved label and the patient population that had been studied in the clinical trials.

In order to overcome these barriers, adequate planning must occur when designing the study. Even in the most hurried of situations, adequate planning is imperative. Most suitable data sources/study designs to answer the research questions need to be determined and the optimal design selected for ensuring data output will be of the highest quality possible. Obtaining study data from electronic medical records (EMRs) rather than paper records when possible and using an electronic data capture (EDC) system to facilitate data cleaning at time of entry are paramount. Ensuring the data collection tool/PROs used is as simple as possible to increase compliance and reduce burden on the site and the patient is also crucial. Having sites identify a sampling frame of the total potential eligible denominator population of interest and having an EDC system determine patient enrollment by random or sequential sampling will ensure that there is more oversight on patient sampling and a systematic process implemented similarly across all sites. While we cannot eliminate selection bias, collecting data at enrollment to characterize the patient population can allow for stratification and other analyses post-hoc to possibly control for confounding.

Dara Stein, MSc, Senior Research Scientist Value Demonstration Team, UBC – An Express Scripts Company

ABOUT MS. STEIN...Dara Stein, MSc, is a Senior Research Scientist for the Value Demonstration team within the Safety, Epidemiology, Registries and Risk Management (SERRM) Group, at United BioSource Corporation (UBC) in Montreal, Quebec. Ms. Stein holds a BSc in Human Kinetics from the University of Ottawa, and a MSc in Human Nutrition from McGill University. Prior to joining UBC, she worked as a Research Associate in the Division of Clinical Epidemiology of the Research Institute of the McGill University Health Centre.

Ms. Stein has experience designing and managing health services observational research studies including retrospective chart reviews and prospective and cross-sectional cohort studies. Ms. Stein has experience with various therapeutic areas including oncology, cardiovascular diseases, intensive care, peritonitis, hepatitis, and acute bleeding events. The research aims of studies Ms. Stein has worked on range from drug utilization, safety, burden of illness, and treatment patterns and resource utilization including direct and indirect cost of healthcare. Ms. Stein has experience with the design of over 15 multi-national chart review studies in various therapeutic areas. Ms. Stein has a keen interest in disease prevention and management as well as burden of illness evaluations.

What are five best practices for implementing organizational change to effectively generate value evidence? 1. Ability to develop strategic context for

value evidence; 2. Expertise in the design, execution and interpretation

of studies that provide such evidence; 3. An infrastructure that supports scientifically

rigorous research; 4. A prior intention to disclose results of research; 5. Direct application of such research to

reimbursement dossiers.

In your opinion, what is most important to working with payers, in regards to partnering around value demonstration, shared risk and pay for performance? Assessment of payer needs to properly value innovation and willingness to generate evidence of value in the payer’s environment. All else (e.g. subsequent risk sharing, etc.) derives from this effort.

The industry has called real world data “the new currency in healthcare.” Do you agree with this statement and if so, why or why not? It’s new in the sense that real world evidence of value has gained increasing recognition as important to the proper assessment of an innovation. It’s also new in the sense that informatics technology has advanced to the stage where real world data generation is both feasible and scientifically rigorous.

When hiring quality evidence teams, what are the biggest hurdles in regards to proper training?The demand for the competencies in this area is enormous and still growing. Therefore, competition for available talent is fierce. Potential employers are reluctant to provide on the job training since the need for these competencies is urgent.

How would you define the role of HEOR teams in generating real world evidence, PPO, clinical trials and HEOR data within a company’s internal organizational structure? HEOR staff are contributors to market access strategy and they derive the evidence of value, both adjunctive to clinical trials and embedded within trials (e.g., costs, resource use, clinical outcomes and patient reported outcomes).

In your opinion, what are the most eminent ways patient considerations can impact: 1) trail design; 2) study participation; and 3) payer decisions? 1. Trial design: trials capture measures that are relevant

to patients;

2. Study participation: trials enroll patient with a high unmet need and the promise of innovative therapies to address those needs;

3. Payer decisions: payers are incentivized to consider patient-specific measures in their reimbursement deliberations.

Gilbert J. L’Italien, Ph.D., Senior Director, Health Economics & Outcomes Research, Biogen; Adjunct Assistant Professor, Yale University School of Medicine

ABOUT DR. L’ITALIEN...Prior to his current HEOR role at Biogen, Dr. L’Italien has held roles of increasing responsibility within Bristol Myers Squibb Company (Executive Director) across multiple disease areas. Dr. L’Italien has led BMS initiatives for early dialogue with HTA, ranging from NICE consultation, EUnetHTA early dialogue and Adaptive Licensing (EMA-HTA) pilots. In 2003, he won the prestigious BMS Ondetti & Cushman Award for development of a database organization unique to the industry. Dr. L’Italien played a leading role in defining the metabolic value proposition for the antipsychotic drug, Abilify, and most recently led an initiative for CHMP qualification of imaging biomarkers in Alzheimer’s disease. In 2014, he led the development of an economic model which supported a favorable decision by the U.S. Preventative Task Force (USPTF) on reimbursement for universal screening of HCV. Prior to his Biogen and BMS/Yale roles, Dr. L’Italien was Director of Vascular Research at Massachusetts General Hospital and held a faculty appointment at Harvard Medical School.

Dr. L’Italien has further participated in advisory committees for several government institutions such as the Agency for Health Care Research and Quality (AHRQ), The CDC Foundation Viral Hepatitis Action Coalition (VHAC), the Multiple Sclerosis Outcome Assessments Consortium (MSOAC), the Alzheimer’s Disease Technical Working Group, Green Park Collaborative, and the Merit Review Committee for the Patient Centered Outcomes Research Institute (PCORI).

His major research interests include methodological enhancements to comparative effectiveness research, the application of HEOR to address regulatory, clinical development and reimbursement challenges. He is also a committed philanthropist and volunteer. Of note, he recently designed and led a 2-year field public health intervention that effectively treated 3,000 indigenous adults and children in rural Mexico to ameliorate the burden of soil transmitted helminthes (STH).

Medical Communications and Information Summit

November 5-6, 2015 San Francisco, CA

REAL WORLD EVIDENCEYour Next Opportunity to Learn More About

Expanded Access Programs

July 22-23, 2015 Washington, DC

Benefit-Risk Assessment and Decision Making Summit

August 6-7, 2015 Alexandria, PA

Evidence for Value-Based Programs

August 11-12, 2015 Boston, MA

Oncology Endpoints & QOL Assessments

November 2-3, 2015 Philadelphia, PA

Reimbursement and Access August 12-13, 2015 Philadelphia, PA

10th Annual Value Based Oncology Management

October 14-15, 2015 Chicago, IL

Life Sciences

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