Pharmaceutical Management Science Association

Revolutionize Healthcare Business Insights with Real World Data

January 12-13, 2017
Hilton San Diego Gaslamp Quarter
San Diego, California

Click on the title of each session to download the presentation.

Agenda

Thursday, January 12
7:00 am - 8:00 am	Breakfast
8:00 am - 9:30 am	Where Real World Data is Heading and Why It Matters to You JP Tsang, PhD & MBA (INSEAD), President, Bayser Shunmugam Mohan, Principal Consultant, Bayser More information Just yesterday, PLD was a new data asset primarily geared towards understanding patient journey, identifying sources of business, and measuring patient compliance and persistence. Identifying KOLs and mapping out referral patterns and spheres of influence were regarded as cutting edge as it required a mental shift from the patient as the object of the study to the patient as a mere thread that connects more important entities, namely, physicians. Patient-level claims data assets were so big compared with physician-level data assets they displaced (at least by one order of magnitude) that one had to be insane to suggest that this behemoth of data asset needed to be combined with yet other data assets to maximize insights that can be gleaned. How things have changed in the past 5 years! Today, patient-level data sources are routinely combined with all kinds of other data sources: other claims data assets, EMR's, registries, lab results, pharmacy and medical formulary data, patient demographics (including credit score, ethnicity, education level, and lifestyle segments), enhanced physician profile, and the list goes on. Why did that happen? For two reasons mainly. First, to achieve a larger footprint. Marrying two databases of different footprints obviously results in a database of a larger footprint. Second, to answer clinically more pointed questions. Case in point: What is the market share by line of therapy of a drug taken by a particular subpopulation of metastatic cancer patients. Claims data does not indicate line of therapy, nor does it indicate that the cancer is metastatic. We also see patient-level data assets deployed in ways we have not seen before. Normally, patient-level data provides data for analysis and analysis provides insights to act upon. These two tasks are distinct and take place sequentially. Lately, EMR's have been used not only to provide data for analysis, but also to identify physicians in real time and even take a shot at changing their prescription behavior. EMRs can now be programmed to fire pop-ups to physicians as soon as their patients fulfill pre-defined characteristics. The pop-up takes the physician to a web site that invites the physician to opt in, and if the physician consents, the physician grants the manufacturer the permission to target the physician. Another trend also worth noting is the site alert which owes its success to its real-time dimension. Replenishment signals coming from medicine cabinets located in physician group practices are meant to tell the GPO when to ship which products to which practices. These signals have been repurposed and are now dispatched to reps so they would know which physicians to call on the following day. How did we get there? There are essentially two forces at play. The first one is a tapestry of trends that have guided the marketplace. They include the rise of the EMR, explosion of the digital space along with the big data phenomenon, release by CMS of several databases in keeping with the Freedom of Information Act, monetization of data by any outfit that holds some kind of data. The second force has to do with the implications of the shift in emphasis from primary care drugs to specialty and orphan drugs. Sadly enough, data sharing has bucked the trend of openness. Manufacturers of specialty products in particular have gone to great lengths to ensure that the competition does not have access to their data. Interestingly, relentless data blocking has led to very creative ways to track the market. In this session we'll go over the two forces that gave birth to what we refer to as PLD 2.0, the tangle of creative combinations of databases to plug holes and answer clinically ever more complex questions. We'll pause and reflect on what PLD 2.0 may have in store for us, and conclude by taking a stab at what we believe constitutes a good data strategy moving forward.
9:30 am - 9:45 am	Break
9:45 am - 10:45 am	Next Generation Clinical Development Luke Dunlap, Sr. Principal, QuintilesIMS More information We all know what the challenges are in the industry: Increasing study complexity -- involving niche patient populations and tighter I/E criteria, sophisticated endpoints, and adaptive designs Fewer investigators taking part in research, and patient recruitment becoming even harder Protocol amendments -- which delay timelines and add costs Sites -- that are initiated but fail to recruit a patient, or under-enroll New and expanding data sources – which are difficult to identify and incorporate to improve development Different evidence requirements for regulators and payers By merging the “big data” access, technology and analytics with clinical trial capabilities, this allows us to replace the assumptions that are inherent in clinical development today - with much more credible pulls of real-life data. So we can replace those “pretty good guesses” (that we ourselves have relied on too) with real-world evidence. We will demonstrate through the use of case studies how to: Increase predictability – by creating study plans that are based on evidence, in order to mitigate the operational risks. Shorten timelines – through using data to help us select the right sites and recruit the right patients, so we can deliver best-in-class delivery timelines Maximize asset value – through helping you make decisions based on real insights, to generate evidence that is relevant to stakeholders, earlier in the process We will leverage four main cases studies to demonstrate how the inclusion of real-world data leads to better clinical trials. Those case studies will include: Multiple sclerosis trial feasibility in Europe US chronic heart disease trial recruitment US inflammatory bowel trial recruitment Diabetes global study feasibility and recruitment
10:45 am - 11:45 am	Understanding Variations in Care Using Public and RWE Data Bo Zhang, Vice President of Data Science, Twine Analytics Prasanna Sridharan, COO, Twine Analytics and CEO, 159 solutions More information Public data (incidence, utilization, census, open payment) integrated with claims data can provide compelling insights to understand how patients are treated. We leveraged big data technologies to procure, clean up, stitch together and analyze multiple data sources to identify local areas where patient care was not being delivered in an optimum manner.
11:45 am - 1:00 pm	Lunch
1:00 pm - 2:00 pm	Leveraging a Common Data Model to Speed Up Evidence-Based Decision-Making Priya Sapra, Chief Product Officer, SHYFT Analytics More information Perhaps no industry is drowning in data more than life sciences. This is especially true when considering Real World Evidence (RWE) data, which includes everything from physician utilization patterns to patient treatment options to drug effectiveness. Market estimates suggest big pharma spends more than $20 million annually on RWE data, but the industry is still struggling with how this impacts pharmacologic treatment on patients and the healthcare system and how a multitude of sources can be unified under a common model to drive normalized insights for real-world decision-making. This session will focus on: How the increase in data sources and the demand to leverage them for business benefit requires a common data model; How the translations of data in accurate and actionable insights requires comparative analytics and the right blend of business and technical acumen; How the derivation of analytics and dissemination of information requires a technology solution that can harness the power of RWE and broaden its use across the clinical-commercial continuum of an organization
2:00 pm - 3:15 pm	Data Aggregation Strategy for Complex Markets: Focus on Academic and Institutional Insights to Increase Coverage and Value Paul Cariola, Sr. Principal, QuintilesIMS More information The pharmaceutical industry is rapidly shifting towards specialty products in terms of promotion. With these specialty products, academic centers and IDNs become a greater portion of both sales and influence into overall distribution models. Gaining further insights into ever changing market dynamics, including disease specific utilization on treatment pathways in oncology, has become crucial in planning and implementing sales and marketing strategies. This presentation will provide a real world data application that demonstrates how use of data aggregation coupled with other information can provide powerful insights for marketing and sales implementation. To highlight the value of expanded data and insights for academic and IDN entities, a business case study will be presented. The case study will focus on scenarios demonstrating how data aggregation provides additional insight and action ability into challenged outlets of care from the historic perspective. This will evidence expanded insight into prescribing behavior for complex oncology markets and multi-indication products for insight and treatment sequencing can be used to effectively (and more accurately) rank physicians based on where in the treatment spectrum they prescribe a particular oncology drug. This information is paramount in tumor types with increased competition and complexities where understanding potential and performance at very detailed levels becomes increasingly important.
3:15 pm - 3:30 pm	Break
3:30 pm - 4:45 pm	Leveraging Predictive Analytics and Real-World Data to Address Challenging Problems in Health Care John Rigg, Sr. Principal, QuintilesIMS More information The expansion of real-world healthcare data coupled with innovation in advanced machine learning presents unique opportunities for using predictive analytics to gain deeper market insights, identify next best customers and design proactive solutions. In general, predictive analytics is helpful in: gaining a better understanding of the key drivers of a certain dynamic (ex. key predictors of non-adherence, disease, other medical outcome, etc.) predicting the impact of an event, and taking action prior to the occurrence of the event We will define predictive analytics, then showcase how it can be used with real-world data to find undiagnosed patients, predict non-adherence, and provide key treatment insights for clinical decision support tools. We will be sharing examples from several therapeutic areas such as neurology, ophthalmology, and rare diseases: Increasing Accuracy and Speed of Diagnosis: Do delays in diagnosis result in your brand’s under-penetration of the market? Disease Progression and Focused HCP Trigger Alerts: Are you interested in targeting the right HCP at the right time? Treatment Response Profiling: Will identifying patient segments that best respond to treatment help you differentiate your brand among payers and providers? Predictions for Non-Adherence: Would you like to understand the drivers of adherence and design interventions that help patients stay on treatment?
5:30 pm - 6:30 pm	Reception
Friday, January 13
7:30 am - 8:30 am	Breakfast
8:30 am - 9:30 am	Bringing the Patients Back In Sandy Balkin, Ph.D., Senior Director, Global Insights & Analytics, Sanofi US John Hartman, Ph.D., Head, Predictive Analytics, Phoenix Marketing International More information The ubiquitous volume/share framework can be profitably augmented with Anonymous Patient Level Data (APLD). In our research, we identify the relevant patient characteristics that drive choice and we associate these patient level variables with physicians. Thus we are able to isolate specific physician preferences in treatment net of the variation in the types of patients that they treat. It’s only by taking a close look at patient level data that we can uncover such HCP preferences in patient care. There are currently a number of sources of APLD and they have various strengths and weaknesses. We open our presentation with a review of three major datasets; we then note the relative advantages and disadvantages of each in the diabetes therapeutic area. While all three of the datasets provide the research with a wide array of patient characteristics on a massive volume of patients, each presents its distinct challenges in data integrity checking, temporal aggregation, coverage/projection and data staging. Once the patient typologies have been distilled, the data has been rolled up to the HCP level, the key drivers identified and has been temporally aggregated, then we can use a variety of dashboarding tools to present information to decision-makers.
9:30 am - 9:45 am	Break
9:45 am - 11:30 am	WORKSHOP: Deep Dive Into Real World Data Randy Risser, Principal, Axtria Sudeep Saha, Sr. Director, Axtria More information Take a deep dive into the essentials of Real Word Data in this informative session. Attendees will take part in hands-on exercises using patient level data. Exercises will focus on how to summarize and visualize longitudinal patient data using a ‘patient journey’ framework, and will have the group exploring data and defining business rules to generate insights about selected patient populations. We will focus on the most frequently encountered sources, including electronic health records, medical and Rx claims, and diagnostic testing data from labs. The workshop will address practical challenges such as setting up an environment for data access considering the daunting size of many RWE sources. We will discuss the ‘workbench’ required for RWE data sources and appropriate technologies for storing, blending, analysis and visualization. As RWE data sources are a significant cost, we will discuss how to make the most of this investment. This includes tips for demonstrating value quickly, removing barriers to data access and integrating the data into practical business applications. We’ll also share a powerful approach to problem solving that combines ‘deductive’ hypothesis-driven analysis with ‘inductive’ analysis that lets the data speak. Case examples will be presented from a practitioner’s perspective, covering: Defining objectives Specification of required data Developing an analysis plan Creating outputs When done properly, RWE becomes integrated into a broad range of analyses across the organization. We’ll leave you with a capability building blueprint that provides a template for developing your end-state vision and roadmap to get there.
11:30 am - 1:00 pm	Lunch
1:00 pm - 3:00 pm	WORKSHOP: Deep Dive Into Real World Data continued Randy Risser, Principal, Axtria Sudeep Saha, Sr. Director, Axtria More information Take a deep dive into the essentials of Real Word Data in this informative session. Attendees will take part in hands-on exercises using patient level data. Exercises will focus on how to summarize and visualize longitudinal patient data using a ‘patient journey’ framework, and will have the group exploring data and defining business rules to generate insights about selected patient populations. We will focus on the most frequently encountered sources, including electronic health records, medical and Rx claims, and diagnostic testing data from labs. The workshop will address practical challenges such as setting up an environment for data access considering the daunting size of many RWE sources. We will discuss the ‘workbench’ required for RWE data sources and appropriate technologies for storing, blending, analysis and visualization. As RWE data sources are a significant cost, we will discuss how to make the most of this investment. This includes tips for demonstrating value quickly, removing barriers to data access and integrating the data into practical business applications. We’ll also share a powerful approach to problem solving that combines ‘deductive’ hypothesis-driven analysis with ‘inductive’ analysis that lets the data speak. Case examples will be presented from a practitioner’s perspective, covering: Defining objectives Specification of required data Developing an analysis plan Creating outputs When done properly, RWE becomes integrated into a broad range of analyses across the organization. We’ll leave you with a capability building blueprint that provides a template for developing your end-state vision and roadmap to get there.
3:00 pm	Wrap Up

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Speakers

Sandy D. Balkin, Ph.D., Senior Director, Global Insights & Analytics, Sanofi US
Sandy D. Balkin, Ph.D. is Senior Director, Global Insights & Analytics with Sanofi. His responsibilities include the identification of opportunities and risks associated with commercial products, pipeline candidates and new business opportunities, leading the design and delivery of research uncovering unique and actionable customer-centric insights from large complex data sets, and for the identification, development and scaling of new data and analytic capabilities across the Company.

Sandy brings over 15 years of pharmaceutical industry experience building and leading forecasting and business analytic functions at companies including Pfizer, Boehringer-Ingelheim, and Aptus Health.


Paul Cariola, Senior Principal, Oncology Commercial Effectiveness, QuintilesIMS
Paul has more than eighteen years of experience in pharmaceutical marketing and marketing research, business development and consulting; with 11 years experience with QuintilesIMS (SDI) and more than 15 years of patient level data analytics. He is an expert in Oncology Data for use in sales, marketing and commercial strategy. Paul has executed numerous projects and client consulting in Oncology – with over 30 different tumor types and specialized solutions in complex market strategies and insights. Specific QuintilesIMS insights/client partnerships include pipeline analysis, sales targeting, KPI development, promotional evaluation, market entry strategies, licensing/partnership assessments, and RWE platform development and execution.

Paul holds a BS in Accounting and Risk Management from Temple University. He has been a guest speaker at multiple marketing, marketing sciences, and patient level data specific events. Prior to his time with QuintilesIMS, Paul managed the immunology market research group for Wyeth Pharmaceuticals with an emphasize on biologic analysis and multi channel markets.


Luke Dunlap, MS, Senior Principal, RWES, QuintilesIMS
Luke Dunlap is a Senior Principal in QuintilesIMS’s Real World Evidence Solutions practice based out of Plymouth Meeting, PA. Luke is a senior leader in the Products & Business Development team focused on the development of ground-breaking RWE products and services for QuintilesIMS’s Life Science, Payer, and Provider clients.

Luke combines a deep background in R&D research, drug development and regulatory approval with a passion for building information technology solutions that optimize research capabilities through the innovative use of technology. While entrepreneurial in nature, Luke is a trained research scientist with over 10 years of scientific research experience in both ophthalmology and infectious disease research,17 years of experience developing and executing informatics and data management strategies, and over 5 years of designing, building and executing scientific computing, cloud and big data analytic platforms.


John Hartman, Ph.D.Head, Predictive Analytics, Phoenix Marketing International
John is the Head of Predictive Analytics at Phoenix Marketing. Prior to his arrival at Phoenix, John built the customer channel optimization models for Boehringer-Ingelheim across all their major brands. And before joining Boehringer, he headed the advanced analytics teams at Observant LLC , Biovid and the Mattson-Jack Group.

John was also a Director of Research at Aetna, and in that capacity he constructed disease management studies of hypertension, depression, diabetes, vaccination and asthma. At Aetna, John led teams of programmers as well doctoral-level statisticians and pharmacists to provide business critical insight into issues of health economics, formulary status, compliance, pre-certification, fraud detection, and cost-containment. He was also a professor of sociology at Columbia University and was a core member of Columbia College, GSAS and Columbia’s School of International and Public Affairs. His research has been published in many referred journals , presented in national and international conferences and in dozen federal courts. John holds a Ph.D. in Sociology from Indiana University.


Shunmugam Mohan, Principal Consultant, Bayser
Shunmugam Mohan is a Principal Consultant with Bayser. He is fascinated with Specialty Pharma and is on his way to becoming an expert. Another of his interests is simulation and he recently developed an agent-based model in the urology field that forecasts sales while leveraging group practice dynamics. Shunmugam worked on several territory alignment projects and is always on the lookout for creative displays of multi-dimensional information. In the cardiovascular field, his recent contribution has been to build a potential assessment model of hospitals that incorporates geographic dynamics around the hospital. Prior to joining Bayser, Shunmugam worked in immune system modeling where he specialized in 3D texture analysis of multiple imaging modalities during his Masters in Electrical Engineering at the Ohio State University. He can be reached at (847) 679-8265 or This email address is being protected from spambots. You need JavaScript enabled to view it..


John Rigg ,PhD, Principal and Head of Predictive Analytics, Real-World Evidence Solutions, QuintilesIMS
John Rigg, PhD heads-up Predictive Analytics in QuintilesIMS’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 developing predictive analytics solutions in life sciences, financial services and academia.


Randy Risser, Principal, Axtria
Randy has over twenty years of consulting and client service experience, specializing in sales and marketing strategy, operations and execution. He has worked with clients in several industries including pharmaceuticals, financial services, insurance and energy. At Axtria, Randy leads the firm’s work in RWE and patient level analytics, in addition to overseeing relationships for several key client accounts. His clients include top pharmaceutical manufacturers, industry leaders in Oncology and innovative healthcare technology firms. Randy’s work focuses on helping his clients make better business decisions through data driven analytics. As one of Axtria’s founding Principals, Randy is devoted to firm building through enhancing Axtria’s capabilities, helping Axtria achieve continued leadership in analytics

Prior to Axtria, Randy was Vice President at ImpactRx, managing several of the company’s largest accounts. Randy’s responsibilities included developing innovative solutions using ImpactRx’ unique research methodology, growing business with existing clients, and building relationships with new clients. Randy worked as a strategy consultant for many years, including with Monitor Company, helping Fortune 500 clients across a variety of industries develop and implement marketing strategies. Randy has also been a Senior Engagement Manager with the consulting firm Mitchell Madison Group and an Associate Director of Promotion Planning at Health Products Research.

Randy received a B.S. from the University of Delaware and a M.S. in Applied Economics from the University of Minnesota.


Sudeep Saha, Sr. Director, Axtria
Sudeep has more than 11 years of experience in sales & marketing analytics, mgmt. consulting with global pharma and biotechnology clients. At Axtria, Sudeep has led and managed global engagements with clients across a range of sales/marketing engagements including promotion response, marketing mix optimization, ROI analysis, digital analytics, patient-level analytics, customer targeting, segmentation/alignment, call planning, etc.

Prior to joining Axtria, Sudeep worked with ZS Associates for 5 years with pharma clients across a range of functions in sales and marketing analytics including Incentive Compensation, Call Planning, Marketing Mix and Brand Strategy with various global pharma clients. Sudeep has worked with Aptus Health over the last 2 years across a range of analytics initiatives for campaign design, lift measurement, ROI analysis, etc. with stakeholders in Analytics, Account Management, Business Development, etc.

Sudeep has an MBA degree from Indian School of Business, specializing in Finance/Marketing. He also holds an undergraduate degree in Computer Science.


Priya Sapra, Chief Product Officer, SHYFT Analytics
Priya Sapra serves as the Chief Product Officer for SHYFT Analytics, an industry-leading cloud-based data management, analytics and insights organization based in Waltham, MA. At SHYFT, she leads the company’s overall vision and strategy for product innovation across the spectrum of clinical and commercial solutions for life sciences institutions.

Sapra has previously been part of five growing startup companies over the past 15 years, acting as a senior leader for the last three. Prior to SHYFT, she served as the Head of Analytics for Phreesia, a patient-centered health care technology company in New York, NY and Vice President of Quantitative Services for MedPanel, a research and consulting firm in Cambridge, MA.

Sapra earned her MBA in Entrepreneurship from Babson College as well as a Master’s degree in Epidemiology and Biostatistics from Boston University. She completed her undergraduate studies from Massachusetts Institute of Technology (MIT) in Biology and Literature.


Prasanna Sridharan, COO, Twine Analytics and CEO, 159 solutions
Prasanna Sridharan has twelve years of experience in bio-pharma consulting. He is currently COO of Twine Analytics, and also is the CEO & Founder of 159 solutions, providing data analytics and consulting to life sciences companies. He has extensive experience in solving sales and marketing business problems across product lifecycles leveraging secondary data. Prior to his current roles, he was the director of data strategy and analytics at AXESS oncology, and Oncology analytics lead at Genentech in their Marketing Sciences team, and a consultant at ZS Associates.


JP Tsang, PhD & MBA (INSEAD), President, Bayser
Jean-Patrick Tsang is the Founder and President of Bayser, a Chicago-based consulting firm dedicated to pharmaceuticals sales and marketing. JP is an expert in patient-level data and related analyses ranging from longitudinal analyses to hospital-retail spillover, KOL identification, influence mapping, referral networks, molecular targeting, promotion response, and the like. JP is also an expert in managed care and has worked on numerous managed care projects. JP publishes and talks on a regular basis and runs one-day tutorials several times a year. In a previous life, JP deployed Artificial Intelligence to automate the design of payloads for satellites, methaners, ethaners, and cruise-liners. JP earned a Ph.D. in Artificial Intelligence from Grenoble University and an MBA from INSEAD in France. He was the recipient of the 2015 PMSA Lifetime Achievement Award.


Bo Zhang, PhD, Vice President of Data Science, Twine Analytics
Bo Zhang has 20 years of experience combining the science and technology of Big Data to solve real world business problems. Currently, he serves as Vice President of Data Science at Twine Analytics. Prior to that, he was Chief Scientist at Opera Solutions (Big Data Analytics Firm) overseeing more than 50 data scientists working in Airline / Travel, Finance and Telecom. He was also the Lead Data Scientist at Fair Isaac building Machine learning models and Big Data profiling systems for credit card fraud detection. He received his PhD in Theoretical Physics and has an MS in Electrical Engineering.