1. Executive Summary
2. Introduction
2.1 Success is Not Automatic
2.2 Modern Manufacturing Concepts in Research
2.3 Communication in Research Organizations
2.4 The Postdiluvian Survivors
2.5 Changing Business Strategies
2.6 Summary
Part I - Process Optimization
3. Materials Management - Pitfalls and Bottlenecks
3.1 Compound Management Challenge
3.2 Solutions to Materials and Substance Handling
3.3 New Technologies Create Compound Overload
3.4 Bottlenecks and the "Hurry-Up-and-Wait"
Syndrome
3.5 Compound Management: The Hub of Drug
Research
3.6 A Typical Screening Procedure
3.7 Inventory Management Software: The Missing
Link
3.8 OPTIMA - A Compound Management Solution
3.9 Compound Management Solutions Drive Process
Improvement
3.10 Open And Integrated Operations
3.11 Conclusion
3.12 Summary
4. High Velocity Laboratory - Applying Manufacturing Process Techniques to Research
4.1 Research Applications of Manufacturing
Principles
4.2 Pipeline Velocity
4.3 Traditional Departmental Manufacturing
4.4 Cellular Manufacturing
4.5 Pull Systems
4.6 The Visual Factory
4.7 Process Analysis
4.8 From the Manufacturing Plant to the Discovery
Factory
5. High Throughput Target Discovery and Validation - Maximizing Productivity in Genomics
5.1 Industrialization of Target Identification and
Validation
5.2 The Structure of a Research Organization
5.3 Components of a Self-Learning Discovery Effort
5.4 The Old Paradigm of Disease Target Discovery
5.5 The New Paradigm of Disease Target Discovery
5.6 The New Paradigm of Target Validation and Lead
Generation
5.7 Academic Collaborations to Procure Technology
5.8 Challenges in the Post-Genomic Era
5.9 Building an Industrialized Target Discovery
Process
5.10 Integrated Information and Knowledge
Management Systems
5.11 Resource Allocation Management
5.12 Specific Goals of Production Teams
5.13 Industrialization of Later Stages in Drug
Discovery
6. An Operations Approach to Combinatorial Chemistry
6.1 The Task of Optimizing Combinatorial Chemistry
Operations
6.2 The Insatiable Demand for Chemical
Compounds
6.3 A Laundry List of Problems and Inefficiencies
6.4 The Need for Speed in Chemical Synthesis
6.5 Re-Organization: Separating Development and
Production
6.6 Protocol Development is the Rate Limiting Step
6.7 Quality Control for Chemical Libraries
6.8 High Quality Chemical Libraries
6.9 Combinatorial Chemistry is a Process
Development Function
6.10 Optimization of Lead Discovery Timeline
6.11 Full Automation vs. Partial Automation
6.12 Database Quality and Materials Management
6.13 Balancing Powers to Conduct R&D Quality
Control
6.14 Project Management: Organizational Buy-in
6.15 Follow-up Libraries
6.16 Reintegration of the Chemical Development
and Project Teams
6.17 Overcoming Cultural Obstacles to Productivity
6.18 The Future of Combinatorial Chemistry
7. Industrialization of Discovery Through Strategic R&D Alliances
7.1 Millennium's Vision
7.2 Multiple Areas of Discovery: Millennium's Family
of Companies
7.3 Discovery and Development Can be
Industrialized as a Process
7.4 Optimization from Discovery to Clinic
7.5 Strategic Alliances as a Financing Engine
7.6 Transforming Alliances
7.7 The Bayer Alliance
7.8 Industrialized Approach to Maximize Value
7.9 Criteria for Successful Alliances
7.10 The Monsanto Alliance
7.11 Conclusion
7.12 Question & Answers
8. Process Optimization Through the Implementation of Organizational Changes
8.1 Technological versus Organizational
Development Issues
8.2 Analysis of the Decision-Making Process During
R&D
8.3 Designing an Improved Discovery Template
8.4 Building Fully Integrated Teams
8.5 Strengthen Overall Management of the Process
8.6 Benefits Resulting from a Restructured R&D
Process
8.7 Key Success Factors for Performance
Improvement
8.8 Questions & Answers
Part II - Knowledge Management and Research Informatics
9. Design and Implementation of Knowledge Management Systems
9.1 The Concept of Knowledge Management
9.2 Communities as Networks of Communication
9.3 Communities are Defined by Geography or
Functionality
9.4 Member Cohesiveness and Organizational Reach
9.5 Case Study - Creating Incentives for Knowledge
Sharing in Larger Communities
9.6 User-Based Knowledge Management Systems
9.7 Knowledge Management Systems Have Many
Components
9.8 A Case Study of Knowledge Management Design
and Implementation
9.9 Definition of a Knowledge Lesson
9.10 Knowledge Management Process Design
9.11 Knowledge Management Enablers
9.12 Research Applications of Knowledge
Management Systems
9.13 A Five-Step Approach to Create Knowledge
Management Systems
9.14 Questions & Answers
10. Measuring Return on Knowledge
10.1 The Emerging Concept of Knowledge
Management
10.2 Focusing the Business to Leverage Knowledge
10.3 Monsanto's Company Structure
10.4 Drivers for Knowledge Management Systems
10.5 Staged Implementation from Pilot to
Enterprise
10.6 Application toward Domains of Increasing
Complexity
10.7 A Framework for Measuring Results
10.8 A Range of Implementations, Deliverables and
Metrics
10.9 Lessons Learned
10.10 Post-Implementation Issues
10.11 Questions & Answers
11. Integrated Information Systems for Global Collaborative Research
11.1 Effective Global Research IT Solutions
11.2 Competitive Advantage through Information
Management
11.3 Key Challenges Facing Research IT
Organizations
11.4 Key Principles of an IT Re-engineering
Strategy
11.5 Key Principles of Research IT Organizations
11.6 An Organizational Shift: Focusing on
Value-Added Activities
11.7 Coordinating Global Research
11.8 Settling on the Principles and Strategy of
Knowledge Management
11.9 Step One - Building the Foundation
11.10 Step Two - Adding Value
11.11 Lessons from Other Industries for Managing
the Supply Chain
11.12 The Research Supply Chain
11.13 Key Success Factors for a Globally Integrated
Research IT Environment
12. Using State-of-the Art IT Systems in Discovery
12.1 Dealing with the Quantum Jump in Amounts of
Data
12.2 Challenges in Discovery and Informatics
12.3 The Scale of the Data Deluge
12.4 Responses to Challenges in Discovery and
Informatics
12.5 Data Visualization
12.6 Enabling Technologies
13. Better Decision-Making Through Data-Mining and Visualization
13.1 Managing the Increasing Volume and
Complexity of Data
13.2 Moving from "Analog" to "Digital" Exchange of
Knowledge
13.3 Scalable Systems for Data Storage and
Analysis
13.4 Capturing Lessons and Knowledge
13.5 Evolution from Static Data Repositories to
Interactive Data-Mining and Visualization
13.6 MineSet as a Tool for Data-Mining and
Visualization
13.7 Building Predictive Models Using Visualization
of Data
13.8 Building Predictive Models
13.9 Applications of Data-Mining and Visualization
to Discovery Research
13.10 Visualization of Genomics Data
13.11 Visualization of Chemical Data
13.12 Visualization of Clinical Trial Data
13.13 Estimating Errors and Testing Assumptions in
Model Design
13.14 From Information Overload to Insight
Part III - Research Alliance Management
14. Collaborative Research - Project Management Across Corporate
Boundaries - Part I
14.1 Strategic Drivers for Collaborative Research
14.2 Finding Partners
14.3 Selecting Partners
14.4 Selecting the Research
14.4 Structuring the Collaboration
14.5 The Research Plan as a Cornerstone of the
Agreement
14.6 The Make-up and Responsibilities of the
Steering Committee
14.7 First Steps in Collaboration Management
14.8 Typical Agenda for the Initiation Meeting
14.9 Measuring the Success of a Collaboration
14.10 Alliance Management - Survey Results
14.11 Summary
Part II - Collaborative Research - Management of Internal and External Research Portfolios
14.12 Outside Collaboration Fosters Innovations
14.13 Commitment to Research and Partnering
Strategies to Strengthen the R&D Pipeline
14.14 High Attrition Rates and Long Development
Times
14.15 Trends Towards Increase in Strategic
Alliances
14.16 Strategic Objectives for Pfizer's Alliances
14.17 Identification and Valuation Methodologies
14.18 Pfizer's Alliances
14.19 Summary
14.20 Questions & Answers
15. Multi-Functional Alliance Management Teams
15.1 Why Alliance Management?
15.2 Increasing Collaborations Justify Alliance
Management
15.3 Keys to Alliance Success
15.4 Organizational Models for Alliance Management
15.5 Building Alliance Management into the
Contract
15.6 Choosing the Best Committee Structure
15.7 The Kick-Off
15.8 Institutionalization of Partnership Tools
15.9 HMR's Alliance Management Structures
15.10 Questions & Answers
16. Tools, Metrics & Techniques for Alliance Management
16.1 Common Issues in Alliance Management
16.2 Setting the Stage for Successful Alliances
16.3 Internal Preparations
16.4 Structural Issues Differ From Cultural Issues
16.5 Case Study - The Problem
16.6 Case Study - The Solution
16.7 Decision-Making Analysis
16.8 Reward Systems
16.9 Communication Within Alliances
16.10 Conflict Resolution
16.11 Anatomy of an Alliance
Part IV - Resource Allocation
17. Risk Management and Productivity in Clinical Development
Part I - Risk Management in Clinical Drug Development
17.1 The Clinical Discovery Stage
17.2 Risk Profile During Drug Development
17.3 A Process Performance Model for Clinical
Discovery
17.4 New Configurations During Early Clinical
Development
17.5 A Productivity Measure for Clinical Discovery
Part II - Modeling Resource Consumption and Probability of Clinical Success
17.6 Introduction
17.7 The Rationale for Process Modeling in R&D
17.8 Evolution of the R&D Process
17.9 Approaches to Modeling the R&D Process
17.10 Models to Estimate Resource Requirements
17.11 Useful Models for Decision-Making
17.12 Two Case Studies
17.13 Chemistry Resource Allocation Model
17.14 Models to Evaluate the Economic Impact of
Pulling Risk Forward
17.15 Conclusion
17.16 Questions & Answers
18. Creating Value via Better Resource Allocation
18.1 The Creative and the Analytical in
Decision-Making
18.2 Balanced Resource Allocation to Improve the
Decision-Making Process 298
18.3 Resource Constraints Require Difficult
Decisions
18.4 SmithKline Beecham's Approaches to Resource
Allocation
18.5 SmithKline Beecham's Approaches to Asset
Evaluation
18.6 Portfolio Management in a Smart Organization
18.7 Case Study: The Oncology Project
18.8 Increasing Shareholder Value from Portfolio
Investment
18.9 Organizational Buy-In
18.10 Effective Portfolio Management
