Decision Analysis and Portfolio Management in the Biopharma Industry
$89.95
A Practitioner’s Guide
Richard Bayney, Ph.D., and Jose Orellana
Hardcover, 7×10, 360 pages
ISBN: 978-1-60427-214-7
e-ISBN: 978-1-60427-869-9
July 2026
Available on backorder
Description
Biopharmaceutical R&D stands at a crossroads. Escalating development costs, persistent clinical attrition, heightened competitive pressures, mounting regulatory complexity, and uncertain commercial rewards have made “doing more with less” an inherently flawed strategy for success and sustainability. This one-of-a-kind book reframes the conversation, arguing that the true objective is not simply value creation, but value maximization under risk and uncertainty. By integrating decision analysis with enterprise portfolio management, it provides leaders with the intellectual and operational foundation required to make defensible, high-stakes investment decisions across drug discovery, clinical development, regulatory approval, and commercialization.
Grounded in decades of real-world experience, the book builds on CREOPM, first introduced in 2012, as a pragmatic and maturity-sensitive framework designed to embed analytical rigor, strategic clarity, and disciplined governance into the fabric of R&D organizations. Moving beyond weak data gathering resulting in single-point estimates and deterministic scorecards, it demonstrates how probabilistic modeling, efficient-frontier thinking, and integrated evaluation can transform portfolio construction from reactive budgeting to systematic value optimization. The result is a comprehensive roadmap for organizations seeking sustained competitiveness, transparent decision lineage, and measurable performance improvement in complex Biopharma environments.
Key Features
- Reinforces the applicability of CREOPM, a modular enterprise framework integrating categorization, risk analysis, evaluation, optimization, prioritization, and governance
- Applies efficient frontier principles from financial theory directly to Biopharma R&D portfolio investments
- Provides decision-tree–based valuation models using probabilistic metrics such as eNPV, eIRR, and utility-adjusted value
- Distinguishes operational execution risk from intrinsic scientific and clinical uncertainty and shows how to model both rigorously and defensibly
- Bridges the gap between decision analysis experts and executive governance committees with structured, traceable methodologies
- Designed for a broad audience, including portfolio practitioners, financial stewards, executives, strategists, entrepreneurs, and graduate-level students
About the author(s)
Richard Bayney is the President and Founder of Project & Portfolio Value Creation (PPVC), a specialized consulting boutique that delivers an integrated suite of services spanning executive education, decision-support analytics, asset valuation, and R&D portfolio strategy. PPVC’s work is grounded in rigorous applications of Decision Analysis, Risk Analysis, and Portfolio Management, and is applied across multiple innovation-driven sectors, including Biopharmaceuticals, Medical Devices and Diagnostics, Consumer Care, and Agriculture. Through this work, Richard advises organizations on aligning scientific uncertainty, regulatory risk, and capital allocation with long-term strategic and commercial objectives.
In parallel with his consulting practice, Richard has an extensive academic and professional speaking background. He has served as a lecturer at the University of Pennsylvania, where he taught graduate and executive courses in Decision Modeling and Project Portfolio Management. He is also a frequently invited speaker at industry forums, where he addresses topics such as decision and risk analysis, portfolio optimization, and strategic planning in drug development.
Richard brings more than four decades of industry and consulting experience to his work. He is a 23-year veteran of the Biopharma industry, having held roles at Merck, Bayer, Bristol-Myers Squibb, and Johnson & Johnson. In addition, he has spent 18 years in management consulting, working primarily with clients in the United States and Europe. Over the course of his career, he has built and led functions in Strategic Planning, Decision Analysis, and Portfolio Management, and has hands-on operational experience, including two years as an international project manager for a marketed cardiovascular therapy.
Earlier in his career, Richard spent a decade as a molecular biologist, conducting research on gene expression in drug detoxification systems and in the pathophysiology of Alzheimer’s disease. He has an M.Sc. and Ph.D. from the University of London, an MBA from Columbia University, and professional certification as a Project Management Professional (PMP) from the Project Management Institute.
Jose Orellana is a Senior Business Consultant and Quantitative Solutions Engineer at Lumivero with over 25 years of experience applying numerical modeling to high-stakes decision making. As a globally recognized expert in the DecisionTools Suite (@RISK, PrecisionTree, Evolver) and XLSTAT, Jose has advised organizations worldwide on navigating the inherent uncertainties of complex R&D cycles.
While his foundational expertise was forged in the demanding engineering environments of Schlumberger and P&G, his work now focuses on the “last mile” of decision analysis—the critical bridge between raw data and executive strategy. Leveraging a mastery of Python, machine learning, and traditional Monte Carlo simulation, Jose provides a robust framework for modeling the binary outcomes and long-tail risks characteristic of the pharmaceutical and life sciences sectors.
Jose holds a B.S. in Electrical Engineering from Cornell University, where he graduated Magna Cum Laude and was inducted into the Tau Beta Pi and Eta Kappa Nu honor societies. His interdisciplinary approach is further bolstered by a Data Analytics certification from UC Berkeley and a Diploma of Management from the Australian Institute of Management. He currently resides in Perth, Western Australia, with his wife and two teenage daughters.
Table of Contents
Chapter 1: Drug Research and Development Within an Evolving Industry
1.1 The Research & Development Funnel – The Impact of Risk, Cost, and Time to Productivity
1.2 The Valley of Clinical Death
1.3 The Stage Gate Review Process
Chapter 2: Scenario Analysis and Strategic Planning
2.1 Scenario Analysis as a Strategic Instrument Under Uncertainty
2.2 Core Concepts of Strategic Planning Under Uncertainty
Chapter 3: Decision Analysis and Portfolio Management
3.1 Introduction to Decision Analysis and Its Utility in Decision Making
3.2 Risk as a Quantitative Construct: Probability as the Common Language
3.3 Uncertainty – The Language of Outcomes
3.4 Decision Making Under Conditions of Risk and Uncertainty
3.5 Decision Framing and Data Integrity
3.6 Portfolio Management
3.7 Portfolio Selection
3.8 The Future of Enterprise Project Portfolio Management
Chapter 4: Project Categorization
Chapter 5: Risk Analysis
5.1 Conceptual Foundations of Risk and Uncertainty in Biopharmaceutical R&D
5.2 Project Risk
5.3 Program Risk
5.4 Portfolio Risk
Chapter 6: Integrated Evaluation
6.1 Key Financial Valuation Concepts
6.2 Anatomy of a Decision Tree
6.3 From Project Evaluation to Program Evaluation
6.4 Sensitivity Analysis to Decision Tree Parameters
6.5 Disease Sequencing: Maximizing Risk-adjusted Value for a Drug in Pursuit of Multiple Diseases
6.6 Bayesian Revision and the Value of Information from Early Clinical Trials
6.7 Integrated Valuation Based on Utility Value
Chapter 7: Portfolio Optimization
7.1 Key Concepts
7.2 The Efficient Frontier in Portfolio Selection
7.3 Application of Deterministic Single Objective Optimization for R&D Portfolio Selection
7.4 Application of Deterministic Multiple Objective Optimization for R&D Portfolio Selection
7.5 Application of Stochastic Optimization for R&D Portfolio Selection
Chapter 8: Project Prioritization
8.1 Comparison of Portfolio Selection by Prioritization and Optimization
8.2 Prioritization in Research: Challenges, Tensions, and Emerging Practice
8.3 A Matter of Weights – The Utility of AHP
Chapter 9: Best Practices in Portfolio Management
9.1 Key Concepts
9.2 Capability Maturity Model
9.3 Roles and Responsibilities in Decision Analysis and Portfolio Management
9.4 Portfolio Analysis and Presentation
9.5 Risk Management
9.6 Resource Management
9.7 Stakeholder Management
9.8 A Practical Approach to Improving Enterprise Portfolio Management Competencies
Chapter 10: Epilogue
Index
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