CASE STUDIES:

LIFE SCIENCE EXPERIENCE

Moving Beyond the Data

TECHNOLOGY ASSESSMENT CASE STUDY:

IMPLEMENTATION AND ADOPTION OF A STATISTICAL COMPUTING ENvIRONMENT

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Implementation and Adoption of Statistical Computing Environment

About d-Wised-Wise Technologies, Inc. is a technology leader with the expertise to empower world-class life science and health-care organizations to resolve their business optimization challenges, helping them rapidly harness and leverage data, systems and processes to gain competitive advantage.

As one of North Carolinas’s fastest growing companies, with offices in the US in Research Triangle Park area of Raleigh, NC and in the UK in Marlborough, England, d-Wise offers product, service and consulting solutions that help clients clearly understand technology options, interconnect manual, disparate and point systems and implement best practices for robust, reliable, and compliant infrastructures that optimize data flow and business process.

d-Wise’s ten year history of tailoring solutions to meet individual client needs as well as delivering data integration, data warehousing and standards solutions within highly-regulated industries is rooted in extensive domain knowledge of SAS software, clinical drug development and clinical data standards like CDISC.

d-Wise solutions for clinical trial optimization, metadata management and clinical standards provide a solid foundation for extracting accurate business analytics to enable critical business decisions to be made rapidly and based on all the data.Within the healthcare arena, d-Wise provides data optimization for actuarial, quality, medical-management, and operational data marts and data warehouses as well as support for fraud detection using data-driven and repeatable processes.

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Implementation and Adoption of Statistical Computing Environment

d-Wise Technologies, Inc. Provides Strategic Support for the Implementation of a validated Statistical Computing Environment d-Wise Technologies, Inc. provided consulting services to a leading Pharmaceutical manufacturer to lead and support their implementation of a Statistical Computing Environment (SCE). The company was using SAS Drug Development (SDD) as a compliant data repository and platform for user access to their clinical research data. Enabling this environment included the implementation of new business processes, development of programming standards and programming validation, and the integration of currently used SDD software tools.

The SCE can be defined as “a data repository of source code, input data, and outputs with compliance features such as version-control of SCE elements, reusable programming ability, and links to the clinical data management system.” It serves as the foundation for documenting rigor in the analysis and reporting of clinical trial results in a compliant environment while increasing productivity and quality.

d-Wise is recognized as a leader in technology implementation based on their extensive knowledge of the clinical research workflow, the clinical systems architecture, and the integration of SCEs with other clinical systems,. d-Wise also understands the significant importance of user experience and change management when implementing technology and process change within an organization, and can provide expertise to spearhead the related tasks involved with technology adoption. The client also recognized that change management was integral to getting the best results from the SCE implementation.

During the initial discussions d-Wise noted these components (but did not limit the scope to only these) as key pieces of the SCE:

» Implementation of the SCE with SDD as the core technology

» Development of new business processes to optimize the adoption of the SDD within their organization

» Integration of existing key software tools with the SCE

» Implementation of programming standards, including the implementation of a new model for programming validation

d-Wise worked with the client to develop a preliminary implementation plan broken into four phases including:

1. Contract and Planning,

2. System Pilot,

3. Configuration and Validation, and

4. Production Rollout.

Each phase has an estimated duration, activities, prerequisites, and required assumptions. Additionally, the client also identified the need to engage both technology and process expertise to support all phases of the SCE implementation project including how to prioritize activities into an iterative project plan for implementation, and to address both the technical and change management activities. The client also indicated the need for subject matter experts to engage with them to do the ‘heavy lifting’ of the SCE implementation including defining best practices, system design, and process definition.

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Implementation and Adoption of Statistical Computing Environment

Overview of the SCE Implementation ScopeThe client identified the challenge and associated need to define a strategic implementation plan for the SCE. d-Wise guided the client through the process of determining which steps to take first, or in parallel, and how to iteratively develop and roll out processes to address the change management challenges. . Specifically d-Wise discussed their need for help in defining the scope and project priorities across the SCE Project initiatives described in earlier.

This plan, in order to be most effective, needed to be developed in incremental phases that are defined within short time intervals, and provide users with immediate benefit, while proactively addressing change management issues. These intervals allowed the project to be deployed iteratively optimizing project start up and streamlining the project

workflow to best meet the client’s timelines and project objectives.

SCE Project Assessmentd-Wise has extensive experience in developing strategic implementation plans that define priorities, dependencies, and timelines, balance budget, and show rapid and tangible benefits. The key is to develop an iterative process that targets quick wins and identifies the critical incremental pieces to tackle first. For example, the first step within the SCE implementation might only include the development of a standard hierarchy, user roles, and working guidelines for moving data in and out of the system. Essentially, the system might be used as a secure and compliant repository in the initial rollout leaving the code development workflow to be implemented as a follow up phase. The d-Wise implementation team worked closely with the client to define the key components of the SCE, and the priorities and associated iterations based on the critical stakeholder’s needs and SCE user community.

Collaborative MeetingsThe first step in defining the scope of the project was to engage in a kick off meeting facilitated by d-Wise. This meeting was organized to achieve three major tasks.

1. Review of the current status, including:

» Reviewing the status of the current environment including processes, technologies, tasks and user roles around both the current environment and the desired future SCE environment

» Assessing the client’s current programming standards, programming validation model, and process along with future state objectives for automation and implementation

Review and clarify the SCE Strategy documents provided by the client including the implementation plan, the list of requirements, and the process roadmap as well as the programming and validation process documents.

2. Defining a project plan which included

» defining the priorities and related iterations

» agreeing to a high level design

» and identifying the activities, resources, timelines, dependencies and potential risks for implementing each iteration.

3. At the end of these meetings, d-Wise was able to understand the current computing environment, user roles and responsibilities, the capabilities needed across the initiatives of the SCE Implementation strategy and the associated

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Implementation and Adoption of Statistical Computing Environment

priority of each initiative. With this understanding, d-Wise was in a position to recommend steps forward and to draft an implementation project plan for the SCE.

Strategic Implementation Plan for the SCEOnce d-Wise had a full understanding of the client’s needs, d-Wise developed a strategic implementation plan. This plan included the following components:

» Summary of findings of the existing environment including gaps and/or pains identified

» High level implementation process organized by project priorities into an iterative approach

» Description of each iteration including priorities tasks, deliverables, and timelines

» Definition of risks and a mitigation plan

» Identification of required resources, responsibilities, and level of effort

d-Wise and the client collaborated on finalizing the implementation plan with the goal of creating a well-defined, phased approach to the implementation. As mentioned earlier, this implementation plan informs and enables the definition of the SOW(s).

Note: While the objective is to provide a roadmap for implementation, the Strategic Implementation Plan is a dynamic document and is updated throughout the lifecycle of the SCE implementation.

SCE Pilot ProjectOur client identified the need to conduct a pilot implementation of SDD which is acting as the core component of the SCE. The pilot implementation designed, developed, and tested tools and processes to support the production implementation of the SCE. d-Wise highly recommended this approach and believes it is the first step to implementing an effective enterprise solution. Our experience indicates that a best practice for a pilot implementation is to ensure the implementation team focuses on creating a well-defined scope and timeline for the project that is related to specific tasks selected from the Strategic Implementation Plan.

Based on the existing implementation plan, the client ran a pilot project on a designated study allowing them to gain experience with the SDD system capabilities, and to determine the most suitable configuration for the production system.

In their document, The SCE Implementation Plan, the client states that the goals of the Pilot Project are to:

» Develop the most suitable configuration for production

» Coordinate the on-going development of department standards

» Identify requirements for customization of:

» SCE

» The programs to be installed in the SCE

» Interfaces between the SCE and other systems

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Implementation and Adoption of Statistical Computing Environment

d-Wise follows a high level iterative process for technology and/or process implementation which was presented to the client during the initial meeting. Based on conversations with the client and the review of their existing project documents, the process diagram below depicts the d-Wise process tailored to meet the client’s needs related to the implementation of the SCE. This section describes each step and the associated tasks, deliverables and estimated timelines.

d-Wise’s process tailored to meet the client’s needs related to the implementation of the SCE

InitiationPrior to initiating the process described below, the team had a project initiation meeting to develop a project plan specific to the SCE Pilot which will fall under the umbrella of the overall SCE Implementation Project Plan already created. The Pilot project plan outlined the objectives and deliverables, roles and responsibilities, meeting schedule, communication matrix, and decision making process. The project plan was approved by both the client team and d-Wise to ensure the implementation team understands their roles and responsibilities.

Deliverables: Pilot Project Plan

Define WorkflowsThe first step in the process was to define user workflows at a high level. This included a list of activities users would perform within the SCE; activities such as ‘loading data from external EDC’, ‘initiating a new study’, or ‘developing, testing, and validating SAS programs’. The majority of activities identified were extracted from the existing client documents and added or refined during the initial project meetings.

The team walked through the process that was included in the strategic implementation plan creating high level user workflows for each process and user role. In addition, the team began to assess the priority of each use case and the activities within those uses cases. This process helped define an iterative approach to implementing workflows and determining the associated functionality most important for the user community. The current use cases were reviewed

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Implementation and Adoption of Statistical Computing Environment

and updated based on review and discussions between d-Wise and the client. At the end of this step, the team prioritized the set of workflows and identified a critical subset that was included in the pilot implementation.

Deliverables: Workflow Use Cases

Design WorkflowsThe next step in the process was to design the workflows at a more granular level, identifying and defining each step within each workflow. This is analogous to developing use cases which will be used for testing later in the project. Each use case identified the user, each step the user should take to accomplish the task within the system, and any alternative flows that must be supported.

One important note here is that the use cases should be developed independent of the chosen technologies so the client focuses on developing a workflow that meets their needs and not developing workflows solely driven by the technology at hand. While this could lead to the client developing processes that replicate their existing processes, d-Wise validates that these workflows are designed with optimization and the selected technology in mind.

Deliverables: Workflow Diagrams and Prioritization

Map Workflow to SDDAfter the use cases were designed, each step in the use case workflow was mapped to SDD functionality. In some cases, multiple methods were identified and discussed to determine which component best met the client’s needs. In addition to identifying the SDD functionality that met the specific use case, process needs were identified and documented. This step helped identify where SOPs and working guidelines needed to be written later within the project.

This step also served to identify where gaps existed between the defined use cases for the SCE and theother client technologies that needed to interface with the SCE . During this step, the team determined how to address the identified gaps and whether they were to be filled by process, additional tools, or custom code/utilities. The team can then added the planning and development of additional processes and tools to the project plan.

Deliverables: Draft Functional Specifications

Install and Configure SDDIn parallel to the definition, design, and mapping of the workflows, the team worked with the software vendor to in-stall and configure a test SDD environment to support the SCE objectives. This environment was used to support the development of the use cases and prototyping exercise mentioned in the next section. d-Wise helped facilitate this process with the vendor to make sure it was completed in a timely fashion and in parallel to the completion of the workflow definition. The team must ensure those two activities are aligned so the next step in the process can proceed on schedule.

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Implementation and Adoption of Statistical Computing Environment

Deliverables: System Validation Plan, System Design Specification

Prototyping WorkflowsAfter the workflow definition is complete and the SCE is available for testing, the next critical step was to prototype each workflow. The team worked through each use case ensuring it met the business process and performance requirements as well as ad-hoc testing of the system and its capabilities. The goal of the team was to iterate through this prototyping exercise at least twice and possibly three times during this step. This prototyping will lead to refining of the workflows, use cases, and functional specifications as well as a better understanding of gaps and methods for resolving those gaps. Each of these documents was continuously updated during this process with the goal of delivering robust and complete workflows.

Deliverables: Prototyping Summary, Gap Assessment, final draft Workflow Definition, Use Cases, and final Functional Specifications

SOP/Working Guidelines DevelopmentDuring the entire process outlined above, the team began and iteratively updated SOP and working guideline documents. This was initiated as skeletons but eventually was populated as the pilot progressed. At the end of the Pilot, well defined draft SOPs and guidelines were available for the production implementation.

Deliverables: Final draft SOPs and Working Guidelines