Clinical Development - Current Trends and Challenges

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1 BIOTECH SUPPLY CHAIN ACADEMY October 8-9, 2012 Crowne Plaza, Foster City, CA Leveraging Technology to Transform the Clinical Trial Supply Chain Leon Wyszkowski : Fisher Clinical Supplies David Northrup : Accenture

2 Top ranked clinical trial supply chain pain points The Problems Remain the Same Short lead times Poor Clinical & supply team communication Protocol readiness / accuracy Inaccurate forecast Poor visibility Source: Tufts CSDD 2

3 3 What are we going to talk about today Technology in Clinical Development is evolving Fisher Clinical Services perspective Current biopharmaceutical supply chain landscape New ways to think about data visibility and collaboration Available technologies and an example

4 4 The sexy job in the next 10 years will be statisticians -- Hal Varian, Chief Economist at Google

5 Clinical Development is recognizing the strategic role of the clinical trial supply chain In an Accenture survey of Development Directors and Study Managers: 100% agreed clinical supply would be on their development critical path 100% highlighted supply as an important pre-marketing differentiator 90% cited drug supply as a key enabler of their development goals over the next 3 years In many instances, the Clinical Trial Supply Chain is facing up to these pressures from a position of weakness: High level of wastage Not exploiting the power of collaboration Disparate systems Expected to be available on-demand Cottage Industry Fragmented marketplace Industry wide opportunities 5 5

6 Acceleration in Clinical Development transformation is driving a change in clinical trial supply chains The Industry s Strategic Focus... is Driving Clinical Supply to. Analytics Data & information capabilities Collaboration Personalized medicines Patient focus Technology Recruitment Globalization Quality & Compliance Invest in system infrastructure Understand the customer and the patient Provide increased supply flexibility with reduced process lead-times, as the norm Deliver into ever expanding markets Achieve higher performance expectations Outsource, consolidate and integrate with the wider supplyside operation Focus on efficiency and standardization Adhere to stringent & evolving regulatory requirements 6

7 Complexity and Data Variability Supply Chain Systems Current State PROCESS API/MFG Inventory Packaging Distribution Site SAP Oracle SAP Oracle SAP Oracle IVRS (Multiple Providers) IVRS & E-Pro Systems JD Edwards JD Edwards JD Edwards Others Others Others SYSTEM Self-Developed Self-Developed Clinicopia Clin-Apps Self-Developed Clinicopia Clin-Apps Number of systems becomes more complex as innovators use both in-house and external capacity across supply chain Supply Chain professionals spend more time gathering data rather than analyzing it Broader trends on site performance, patient recruitment across therapeutic areas, and protocols are harder to detect 7

8 Current Solution Inventory Packaging Distribution Dispensing Customer System Returns Consumption Visibility to some parts of the Supply Chain to enable optimization Challenges: Not easy to bring on new systems All require a level of software development to connect to a data warehouse Some data is not transferred or system architecture does not allow for integration rules for data structure are not standard 8

9 Traditional view of my network Suppliers Customers Brand owner Logistics Services Providers Source: Gartner SC Conference

10 Extending beyond the 4 Walls Suppliers Customers Brand owner Logistics Services Providers Source: Gartner SC Conference

11 Data management might get a little more complicated Manufacturing Plant Item Russia Amsterdam Import hold Complaint Pooled Supplies Grant Supplies External Supplier Invoice BL# HJC PO # Kit number Quality Release Quality data Vendor Plant LIMS Dose Instructions Stability date Randomization Comparator Taiwan Batch Record Manual intervention Argentina Market External Supplier China Hub US Customs FDA Source: Gartner SC Conference

12 12 Future Information Solution How would data visibility with a single version of the truth impact your day-to-day life?

13 13 Example of technology solutions available today CMO Collaboration Analytics

14 Over the past 18 months Pfizer Moves Supply Chain to the Cloud a single version of the truth against which all stakeholders operate..allows supply chain network participants to be added or removed rapidly Financial Times, Sept 11,

15 15 Access to data creates opportunities for analytics Setting the Stage: What is Big Data? When the data size and performance requirements become significant design and decision factors for implementing a data management and analysis system. Roger Magoulas & Ben Lorica of O Reilly Media Data sets that are big enough to obscure underlying meaning or for which traditional methods of storing, accessing, and analyzing are breaking down (or simply getting too expensive). Practically speaking big data is also about adding unstructured or semi-structured data to the mix Or creating hybrid environments that perform while controlling cost.

16 Analytics capabilities drive improved decision making 16

17 17 which provides opportunities for improved business outcomes Big Data is top of mind for virtually every industry, impacting core business processes Resources Upstream Oil & Gas companies monitor 40K sensors per asset (combined with 4d seismic imagery) to drive real-time production operations and maintenance & reliability programs. Health Electronic health records, home health monitoring, telehealth, and new medical imaging devices drive data deluge in a connected health world. Public Sector USPS applies unique barcodes so it can seamlessly induct and account for postage. This results in ~1B pieces per day, scanned multiple times throughout the supply chain. Retail Emerging location based data, group purchasing and online leads allow Retailers to continuously listen, engage and act on customer intent across the purchasing cycle. Financial Services Communications Pioneers in Big Data, Capital Markets firms continue to innovate around low latency systems to unlock trading arbitrage opportunities. Mobile usage data for Service Providers unlock new business models and revenue streams from Outdoor Ad placement to medical adherence.

18 18 Summary To deliver enhanced patient outcomes, key components of business transformation emerge Analytics Clinical Data (via Collaborations) Data Integration Outcomes Visualization Mobility Key Components Data visibility: Increasing amounts of data will be available (e.g. via EMR, patient communities, digital aids, etc.), making data sourcing and preparation an essential foundation for the model. Data Integration: Raw data from many different sources will need to be consolidated and connected (e.g. via Master Data Management). Analytics: Predictive analytics must be developed to leverage data for proactive insights Mobility: Data and insights must be accessible to consumers, when and where they need it. Visualization: Data and insights are meaningless if they cannot be understood; Effective visualization is required to support insight development. Outcomes: All supporting components and capabilities must enable relevant, actionable insights in order to deliver improved patient outcomes.

19 Questions 19

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