ims health workshop world orphan drug congress

April 20-22, Washington, D.C.

Using real-world data to find undiagnosed patients with rare diseases

IMS Health Real-World Evidence Solutions

Speakers

Michel Denarié, MBA, Senior Principal, RWE Solutions, IMS Health

Nadea Leavitt, MSC, Engagement Manager, RWE Solutions, IMS Health

Leanne Li, MBA, Engagement Manager, RWE Solutions, IMS Health

Kelly Peters, VP, Customer Segments, RWE Solutions & Commercial Services, IMS Health

Dr John Rigg, PhD, Principal and Head of Predictive Analytics, IMS Health

Diana Wong, MBA, MSC, BSC, Principal, RWE Solutions, IMS Health

April 20, 9:00am - 12:00pm | Pre-Conference Workshop

World Orphan Drug Congress (WODC),

April 20-22, Washington D.C. 2

are seen before diagnosis3

before an accurate diagnosis3

7.3 physicians (avg.)

4.8 years (avg.)

1. Global GenesTM, https://globalgenes.org/rare-diseases-facts-statistics/ 2. Eurordis - Rare Diseases Europe. Survey of the delay in diagnosis for 8 rare diseases in Europe ('EURORDISCARE 2'). www.eurordis.org/IMG/pdf/Fact_Sheet_Eurordiscare2a.pdf

3. Engel PA, Bagal S, Broback M, Boice N. Physician and patient perceptions regarding physician training in rare diseases: The need for stronger educational initiatives for physicians. Journal of Rare Disorders, 2013; 1(2): 1-15

millionpeople su�er from a rare disease worldwide1

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of patients are misdiagnosed initially2

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Rare diseases are not so rare,but f inding those patients is taking too long

IMS Health brings more HOPE

to rare diseases su�erers

We use real-world data and advanced analytics to help diagnose those patients quickly

Under-diagnosis is a major barrier to the successful treatment of rare diseases. New tools leveraging real-world data and innovation in advanced analytics are creating opportunities for dramatic improvements in identifying hard-to-find patients.

The purpose of this workshop is to explore the ways in which real-world data (RWD) can be used to address the problem of under-diagnosis in rare diseases. The session will illustrate how companies worldwide are breaking new ground in understanding rare diseases through a variety of case studies. It will also include innovative ideas on how to build new engagement models with providers and payers to increase rare disease treatments.

Expect a highly interactive session with opportunity for audience members to ask questions and share their experience.

Using real-world data to find undiagnosed patients with rare diseases



Workshop Agenda: Using real-world data to find undiagnosed patients with rare diseasesApril 20, 9:00am – 12:00pm

9:00-9:10

Introduction – Using real-world data (RWD) to address the problem of under-diagnosis in rare diseases


9:10-9:40

Rare diseases are not that rare – How the expansion of large-scale RWD is helping to transform the landscape of rare diseases


9:40-10:30

How companies worldwide are breaking new ground in understanding rare diseases

Diana Wong, MBA, MSC, BSC, Principal, RWE Solutions, IMS Health Leanne Li, MBA, Engagement Manager, RWE Solutions, IMS Health

10:30-10:40

Coffee Break

10:40-11:20

Finding the needle in the haystack – Real-world data and predictive modelling helping to find patients with undiagnosed rare diseases


11:20-12:00

New engagement models with providers and payers to increase rare disease treatments

Dr John Rigg, PhD, Principal and Head of Predictive Analytics, IMS HealthKelly Peters, VP, Customer Segments, RWE Solutions & Commercial Services, IMS Health

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Click here to register your interest for the IMS Health workshop www.surveymonkey.com/r/7W7F7Y6

Click here to sign-up for the World Orphan Drug Congress

http://www.surveymonkey.com/r/7W7F7Y6

http://www.terrapinn.com/conference/world-orphan-drug-congress-usa/index.stm



9:00-9:10

Introduction – Using real-world data (RWD) to address the problem of under-diagnosis in rare diseases


There are 7,000 rare diseases identified with an estimated 350 million suffers worldwide, collectively the burden is considerable. This workshop will explore the ways in which real-world data (RWD) can be used to address the problem of under-diagnosis in rare diseases. The session will discuss examples of RWD, focusing on key data assets in the U.S. and Europe, including case studies to illustrate how these rich sources of data coupled with predictive analytics can be used to find undiagnosed patients. The workshop will also include novel ideas on how to build new engagement models with providers and payers to maximize patient-finding strategies.

9:10-9:40

Rare diseases are not that rare – How the expansion of large-scale RWD is helping to transform the landscape of rare diseases


Over the last decade, there has been a proliferation real-world data sources across the world, fueled by the computerization of pharmacies and the increased use of electronic medical record systems. This new data influx has given researchers new avenues to better understand incidence, prevalence, standard of care, and the overall patient journey.

In this section, we will explore what sources are available in the U.S. and across the world, from data providers as well as health authorities. Understanding these different types of RWD, their attributes, pitfalls and analytical challenges is critical in selecting the most appropriate RWD and applying it to the study of rare diseases.

30 20 10

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Detailed Agenda: Using real-world data to find undiagnosed patients with rare diseasesApril 20, 9:00am – 12:00pm



9:40-10:30

How companies worldwide are breaking new ground in understanding rare diseases

Diana Wong, MBA, MSC, BSC, Principal, RWE Solutions, IMS Health Leanne Li, MBA, Engagement Manager, RWE Solutions, IMS Health

As the importance of rare diseases continues to grow, IMS continues to leverage its longitudinal patient data assets to address manufacturers’ business and outcomes research questions. In this section of the workshop, we will present a variety of case studies spanning the U.S. and Europe, addressing different research objectives, notably:

• Sizing the addressable market for a pre-launch orphan drug, including the current standard of care for the diagnosed and treated population

• Understanding the frequency and distribution of health care costs for a rare disease, and the differential in total cost of care vs. common chronic conditions

• Identifying and segmenting the physicians likely to prescribe a new orphan drug based on historical prescription patterns and early product adoption

• Analyzing the burden of illness and epidemiological data

• Investigating care pathways and understanding the extent and effect of late diagnosis, as well as obstacles in the health care system preventing early diagnosis

10:40-11:20

Finding the needle in the haystack – Real-world data and predictive modelling helping to find patients with undiagnosed rare diseases


The path to a rare disease diagnosis can be long and frustrating for the patient, as well as costly for the healthcare system. With 7,000 known rare diseases, each inflicting a very small percentage of the U.S. population, Health Care Practitioners (HCPs) often do not have any experience with the rare condition of interest to properly diagnose it. This leads to ineffective symptomatic treatments, unnecessary surgical interventions and delayed proper diagnosis.

Raising awareness about rare diseases and a proper way to diagnose them is necessary to combat this challenge. This section will review how using IMS Health Real-World Data and advanced predictive modeling techniques can help identify undiagnosed patients, link them to their treating HCPs and provide a targeted, HIPAA-compliant and cost-effective way to raise disease awareness and speed up the time to diagnosis.

50 35 15

40 25 15




11:20-12:00

New engagement models with providers and payers to increase rare disease treatments

Dr John Rigg, PhD, Principal and Head of Predictive Analytics, IMS HealthKelly Peters, VP, Customer Segments, RWE Solutions & Commercial Services, IMS Health

While physician target lists may be the most obvious way for pharma to utilize output from a predictive model, is it necessarily the best way? This session will explore challenges with physician target lists, particularly the need for patient anonymity and the potentially low conversion rates (number of physicians contacted per new patient on treatment). Operating models, which may be more rewarding, including partnerships with providers and payers will be discussed as a potential alternative. These partnerships may involve developing the algorithm with named patients and clinician out-reach by trained healthcare professionals, resulting in a more direct and effective way to find undiagnosed patients.

Audience members will be encouraged to share their thoughts and experience. This final session of the workshop is intended to be especially interactive, with an emphasis on collaboratively identifying innovative solutions.

40 20 20


Click here to register your interest for the IMS Health workshop www.surveymonkey.com/r/7W7F7Y6

Click here to sign-up for the World Orphan Drug Congress

http://www.surveymonkey.com/r/7W7F7Y6

http://www.terrapinn.com/conference/world-orphan-drug-congress-usa/index.stm



Michel Denarié is a Sr Principal in the Real- World Evidence Solutions’ team, developing new offerings for IMS and helping clients solve an array of business issues by leveraging the full potential of longitudinal data across the globe. Specifically, he develops national and sub-national patient-centric offerings that analyze patient and treatment trends over time and improve sales force effectiveness strategies. Main functional experience: US and global longitudinal patient data.

Denarié’s experience in the pharmaceutical industry spans three decades and encompasses roles in sales, marketing, and product development. A frequent author and speaker, Denarié’s work has appeared in several trade & medical publications. Denarié earned an M.B.A. from the Colgate Darden Graduate School of Business Administration at the University of Virginia. He holds a B.S. in finance from American University in Washington, DC.


Presenters: Using real-world data to find undiagnosed patients with rare diseases

Nadea Leavitt is an Engagement Manager in the Real-World Evidence (RWE) department of IMS Health. Using longitudinal patient level data, she conducts and manages research engagements that help pharma clients answer an array of business questions, spanning from market opportunity assessment to launch preparation & tracking, to brand strategies post launch.

Nadea also leads the development of innovative offerings combining rich real-world data and predictive analytics to identify new opportunities and address challenging issues. This includes developing novel disease detection algorithms to find undiagnosed patients with rare diseases. Nadea is also leading IMS’s thought leadership on next-generation physician targeting strategies using advanced machine learning techniques. Nadea holds a B.A in Economics and an M.S. in Applied Statistics.


Leanne Li is an Engagement Manager in the Real-World Evidence (RWE) department of IMS Health.With extensive experience overseeing highly complex and customized consulting engagements, she leverages longitudinal patient level data assets, applies consultative problem solving skills, formulates analytical approaches, and presents conclusions and recommendations to help pharma clients tackle business challenges.

Her areas of expertise include source of business, market sizing, patient and physician segmentation, and adherence tracking, spanning various therapeutic markets such as Immunology, women’s health, and rare disease. Leanne holds a B.A in Diplomacy, a M.P.A. in Health Policy and Management and an M.B.A in Finance and Marketing.

Leanne Li, MBA, Engagement Manager, RWE Solutions, IMS Health



Presenters: Using real-world data to find undiagnosed patients with rare diseases

John Rigg, PhD heads-up the Predictive Analytics team in IMS Health’s Real-World Evidence Solutions. He develops innovative solutions to solve challenging problems using patient-level data using a variety of advanced statistical and machine learning methods. This encompasses applications such as clinical decision-support tools, risk stratification calculators, rare disease detection algorithms and physician targeting alerts.

John has over twenty years of experience developing predictive analytics solutions in life sciences, financial services and academia. He is regularly invited to deliver thought leadership presentations at universities, life science organizations and leading conferences. John has a PhD in Economics from Cambridge University and has held post-doctoral academic positions at the London School of Economics and the University of Essex.

Dr John Rigg, PhD, Principal and Head of Predictive Analytics, IMS Health

Diana is currently driving strategy and innovation initiatives to advance real-world evidence technologies at IMS Health globally. Diana also leads the Enriched Real-World Data Studies initiative and is building a solution that combines retrospective research with prospective data collection within a streamlined technology.

Prior to IMS Health, Diana worked as a management consultant on health care reform in the United States and Europe defining new roles for all health care stakeholders. Diana has a BScH specializing in biochemistry from Queen’s University, a MSc in type 2 diabetes research from the University of Toronto and MBA majoring in Health Sector studies from the Richard Ivey School of Business at the University of Western Ontario.

Diana Wong, MBA, MSC, BSC, Principal, RWE Solutions, IMS Health

Kelly Peters leads IMS Health’s Real-World Evidence (RWE) principal community, which guides the application of RWE in the U.S. operational processes (supporting pharma companies directly and their agencies of record, in addition to advocacy groups acting on behalf of the patients they serve).

With over 20 years of experience in the healthcare industry, Kelly specializes in provision of evidence-based operational guidance to marketing, sales, commercial operations, and business development client teams. She has hands-on experience in the use of RWE for the assessment of product potential, development of multi-channel operational plans tied to reaching that potential, and creation of diagnostic solutions across several therapeutic markets (spanning orphan drug categories through mainstream conditions that impact a broad base of patients).

Kelly Peters,VP, Customer Segments, RWE Solutions & Commercial Services, IMS Health



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Our Vision of an RWE EcosystemAn environment for building deeper insights to benefit the entire enterprise

Imagine a world where everyone can use the same fact base to understand what is really happening in healthcare. Add the ability to leverage advanced analytics, technology, data management approaches, data visualization and other innovations to bring relevant data together easily and accurately. You would then have the scientific evidence needed to support your products’ value proposition, safety, access and price. And you could use these insights to make better commercial decisions as well.



IMS Health Our Distinctive ApproachIMS Health has taken a holistic approach to real-world evidence (RWE) in pursuit of the most robust and insightful views of patient outcomes. With the breadth and depth of our capabilities, we are uniquely positioned to generate and use RWE globally. Applying the appropriate scientific and commercial lens and latest techniques to anonymous real-world data (RWD) is critical to realizing the value of RWE in healthcare decisions.

Real-World DataIdentify and access the most appropriate data sources while

ensuring patient privacy

• The broadest and deepest collection of scientifically-validated,

anonymous patient-level data assets complemented by custom

data sourcing

Technology-Enabled AnalyticsCreate consistent data models empowering analyses and leveraging

innovative technologies

• Extraction, analysis and visualization of RWD with IMS Health’s

E360™ technology suite

• Sophisticated data linkage and interpretation

Services and EngagementDevelop on RWE strategy and analyze RWD using scientific rigor,

clear governance, and advanced analytic and processing capabilities

• Strategic support

• Outcomes research, pharmacoepidemiology & drug safety

• Health economics & market access

• Market-level engagement

Technology- Enabled Analytics

Services and

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Real-World Data IMS HEALTH

REAL-WORLDEVIDENCE

SOLUTIONS

Leadership and innovation across the RWE spectrum


IMS Health Real-World Evidence Solutionsis based in 20 countries worldwide with regional headquarters in

[email protected]

www.imshealth.com/rwe

The Americas

One IMS DrivePlymouth Meeting,Pennsylvania 19462USA

Tel: +1 (484) 567 6461

Europe

210 Pentonville Road London N1 9JY United Kingdom

Tel: +44 (0) 20 3075 4800

Latin America

Insurgentes Sur # 2375 5th Floor Col.t Tizapan Mexico D.F.-C.P. 01090 Mexico

Tel: +52 55 5089 5205

Asia Pacific & Japan

8 Cross Street #21-01/02/03 Singapore 048424 Singapore

Tel: +65 6412 7365

Toranomon Towers Office 4-1-28 Toranomon Minato-ku Tokyo 105-0001 Japan

Tel: +81 3 5425 9541

©2016 IMS Health Incorporated and its affiliates. All rights reserved.

Trademarks are registered in the United States and in various other countries.

ims health workshop world orphan drug congress

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