Precision Medicine & Health Insurance Business Model Disruption? A Data& Evidence perspective

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1 Precision Medicine & Health Insurance Business Model Disruption? A Data& Evidence perspective December 12 th, 2017 Dr. Tim Wintermantel Real World Insights Lead, Switzerland Copyright 2017 IQVIA. All rights reserved.

2 Tech advancements provide opportunities to enhance and potentially disrupt the way value is generated and demonstrated More people connected with faster processors, faster broadband 4 billion internet users worldwide and growing 1 2 IQVIA with >530M global anonymous patient records. 20+ petabytes* of unique data Mind bogglingly vast amounts of digitized, connected data >150 exabyte* of health data and growing Technologies to unlock power of vast digitized, connected data Individualised diagnostic and therapeutic health technologies * 1 Petabyte = B 1 Exabyte = B 1

3 Combining Data with AI-enabled analytics is at the core of this change as they unlock unparalleled insights for all stakeholders Big data: capture diverse sets of real world data 1 *Machine learning, predictive analytics, natural language processing, other emerging AI approaches AI enabled Analytics Big data Unparalleled insights 2 3 AI enabled analytics Smart algorithms* to understand relationship between treatment design and outcomes Value generated or demonstrated for all stakeholders Patient: Receives right treatment at the right time Physician/Nurse: Treatment decision support Payers: Better budget management decisions, RWE enabled innovative contracting Pharma: R&D and commercial optimisation 2

4 For example, Predictive Analytics can identify new rare disease patients from the digital footprint of diagnosed patients 1 Identify patients with the disease and analyze their medical history PRIOR to the 1 st diagnosis of the disease Tests & Diagnostic Procedures Symptoms Comorbidities/ Misdiagnoses Specialist/ ER visits Treatments Demographics Age+ Medical history prior to 1 st diagnosis of disease Patient 1 st diagnosed with disease Patients with the disease Develop an algorithm to identify unique patterns of the disease in patients prediagnosis medical history 2 3 Find and target patients in the wider universe who are identified by the algorithm as potentially undiagnosed Patients identified by the algorithm Patients not identified by the algorithm 3

5 Table of Key theses Contents 1. We are not yet at the stage of true disruption which does not mean advanced analytics cannot generate tangible value in the current model 2. More health stakeholders (providers, payers, ) will require evidence and it will be evidence that wins 3. Patient-centricity will move from a buzzword to the center stage of health value demonstration 4

6 We are not yet at the stage of true disruption which does not mean advanced analytics cannot generate tangible value in the current model Rate of change Equilibrium Slow start Acceleration Disruption Pragmatic approach There are only a limited number of use cases that can realistically generate tangible value in the current model: Focus on value demonstration: enhance how you demonstrate value through big data and AI We are here Re-think how value will be generated, captured and shared: prepare to be part of the disruption of the future model Time 5

7 Treatment Response Profiling using Predictive analytics can profoundly change the way care is delivered Shows no predicted benefit of more than 10 doses Need: Predict optimal response for high burden treatment Machine learning: ~18,000 patients, multiple responses Goal: Treatment optimization tool to support physician-patient engagement IQVIA All rights reserved. Note: example above for illustration purposes; results will vary 6

8 Table of Key theses Contents 1. We are not yet at the stage of true disruption which does not mean advanced analytics cannot generate tangible value in the current model 2. More health stakeholders (providers, payers, ) will require evidence and it will be evidence that wins 3. Patient-centricity will move from a buzzword to the center stage of health value demonstration 7

9 The basic rules of the game for medicines will also apply for digital innovations if they aspire to be reimbursed. Yes Congrats! Does the offer cure a disease? Yes How much? How strong is the evidence? No Does it get you closer to a cure? No Does it make patient s journey easier? Is the evidence patient relevant? 8

10 Table of Key theses Contents 1. We are not yet at the stage of true disruption which does not mean advanced analytics cannot generate tangible value in the current model 2. More health stakeholders (providers, payers, ) will require evidence and it will be evidence that wins 3. Patient-centricity will move from a buzzword to the center stage of health value demonstration 9

11 Both the FDA and EMA have established mechanisms for capturing the patient voice in decision making Timeline of established agency guidelines for inclusion of patient perspectives Clinical Outcome Assessments (COAs) Reflection Paper On The Regulatory Guidance For The Use Of Healthrelated Quality Of Life (HRQL) Measures In The Evaluation Of Medicinal Products Guidance for Industry Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims COA Staff Team formed (f.k.a SEALD) for labeling review and patient-focused instrument assessment Guideline Endpoints used for relative effectiveness assessment of pharmaceuticals Health-Related Quality of Life and Utility Measures Value Frameworks for oncology Our observations Regulators actively supporting incorporation of the patient voice in regulatory decision-making Some Payers beginning to consider disease-specific COAs as differentiating Prescribers seeking COA robust evidence The field still needs to mature its methodologies and quality 10

12 As a consequence PRO-based labeling for drugs is gaining traction in the US and EU other interventions will follow Increase in PRO data included in drug labels Patient Reported Outcomes All Approved Drugs 11% of new products approved on PROs alone 16.5% of new products approved on PROs alone Oncology None submitted for PRO labeling 7.5% had PRO labeling (3 of 40) Oncology PROs are more common in EU value dossiers than in US, with 42% of oncology drugs approved by EMA having at least one PRO claim ( ) There is every reason to assume that stakeholder s will scrutinize digital health solutions along the same line patient-relevant improvements Source: Gnanasakthy A, A Review of Patient-Reported Outcome Labels in the United States:

13 1. We are not yet at the stage of true disruption which does not mean advanced analytics cannot generate tangible value in the current model Key Table theses& of consequences Contents While healthcare players are already in the race for the future business model, today s value opportunities should be seized 2. More health stakeholders (providers, payers, ) will require evidence and it will be evidence that wins Evidence generation strategies are key for a sustainable healthcare business model 3. Patient-centricity will move from a buzzword to the center of the evidence requirement Including the patient voice in the evidence strategy is both a chance and a necessity for any digital health solution 12

14 Please contact us for more information: Dr. Tim Wintermantel Senior Principal Head of Real World Insights, Switzerland Bernd Haas Vice President Technology Solutions, Central East and South Europe