a knowledge based collaborative model for the rapid integration of platforms, people and processes

A knowledge based collaborative model for the rapid integration of platforms, people and processes.Feb 19th 2010

Paul Fenton

Montrium Inc.

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Introduction

How we work today

Information and procedural silos• In today’s GxP landscape we have:

– Many individuals, groups and organizations working independently

– Many computerized systems working independently– Many different department or organization specific

processes

• All generate data and information which for the most part remains dislocated and underexploited

• This makes our working environment inefficient and costly

Lack of operational knowledge

• In a silo based model, it is difficult to gain cross system, cross functional knowledge

• We spend a lot of time transcribing, reconciling and collating data

• Often we do not have a clear picture of study progress at any one point in time, even less across programs of studies

• We do not fully exploit operational data (generated from automated system processes) and transform it into knowledge

The Challenge

• In todays R&D environment, our challenge is to:– Make better drug development decisions– Accelerate time to market– Increase organizational efficiencies and agility– Improve understanding and management of R&D

processes– Reduce cost– Reduce risk– Improve quality– Improve compliance

Meeting the Challenge..

• To meet the challenge we must break down organizational and procedural silos by:– Leveraging new technologies and work methods– Map out, re-engineer, automate and integrate

processes– Leverage and establish procedural and data

standards– Integrate computerized systems and data sources– Identify clear and measurable metrics and KPIs– Align and integrate the quality system with automated

processes

BPM and BI can help!

Definition of BPM

• Business process management (BPM) is a management approach focused on aligning all aspects of an organization

• It is a holistic management approach that promotes business effectiveness and efficiency while striving for innovation, flexibility, and integration with technology

• Is based on continuous improvement of processes

Source: Wikipedia

BPM technology elements

Definition of Business Intelligence

In 1958 Hans Peter Luhn, a computer scientist at IBM used the term business intelligence for the first time. He defined intelligence as: "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."

Definition of BI

• BI refers to skills, processes, technologies, applications and practices used to support decision making

• BI technologies provide historical, current, and predictive views of business operations

• BI is composed on reports, dashboards, metrics and analytical models

• BI is capable of transforming operational and business data into information and knowledge

BI Implementation

Top Critical Success Factors are:• Business driven methodology & project

management• Clear vision & planning• Committed management support & sponsorship• Data management & quality issues• Mapping the solutions to the user requirements• Performance considerations of the BI system• Robust & extensible framework

Source: Naveen K Vodapalli, 2009

Mapping out processes – High level to detailed

• We typically think of clinical trial organization as hierarchical

• Processes usually align to a particular level of hierarchy

• Processes can be high level and then drill down

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Identifying milestones and KPI

• Milestones are predefined events within a process or processes

• Milestones are calculated or non-calculated values based on one or many datapoints

• Milestones correspond to predefined key events or values within the various levels of the process maps

• Examples of Milestones would be:– IND Submission (Molecule Level)– Protocol Approval (Study Level)– FPFV (Site Level)

Identifying milestones and KPIs with process maps

• KPIs are key operational indicators which are calculated using information from processes, data and documents

• KPIs are calculated or non-calculated values based on one or many datapoints

• KPIs can be drilled in to to see underlying KPIs and data or rolled-up to see higher level KPIs

• Examples of KPIs would be:– Time between FPFV and DB Lock (study level)– Time between last query and DB lock (study level)– Time to query resolution (study, site level)– Number of queries by status (study / site) – Average protocol IRB approval time (site)

Identifying milestones and KPIs with process maps

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Identify data sources and integration points

• Data sources for KPIs and Milestones can come from:– Documents and document metadata– Procedures and procedural data (workflows)– Databases (EDC, CTMS, Safety etc.)– Project plans and manual metrics

• When thinking about data for KPIs and Milestones, it is important to identify unique data sources

• Establishment and use of standards is key to be able to integrate data sources and procedures

Integrating Processes through BPM

Building an operational knowledge model

Dashboards -

roll-up, drill-down, drill-in• By identifying key metrics, milestones and indicators at all

levels we are able to develop multi-dimensional dashboards

• These dashboards allow up to move up and down in our operational knowledge

• By adding a third dimension we are able to drill in both in terms of data but also time

• This model enables us to pin point key factors which have positive/negative impacts on our operations

Aligning with the QMS

• Implementing this approach often requires changes to components of the QMS

• When re-engineering processes try and break them down into clear steps, tasks, responsabilities and delvierable elements

• Clearly identify all interconnections on process maps• Re-engineer manual processes into automated

processes• Finally align these elements to your BPM and

collaborative environment

Recommended approach

1. Map out R&D process maps; remember high to low

2. Identify processes (SOPs) and interactions for each level and step

3. Identify people and organizations who intervene in each process and step

4. Identify data sources

5. Identify key metrics, milestones and KPIs

6. Identify technology elements

7. Define a scope for pilot project

8. Implement and improve

The light is at the end of the tunnel

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