Quantitative Models in Life Science Business: From Value Creation to Business Processes (SpringerBriefs in Economics)

This open access book explores the field of life science business from a multidisciplinary perspective. Applying statistical, mathematical, game-theoretic, and data science tools to pharmaceutical and biotechnology business endeavors, the book describes value creation, value maintenance, and value realization in the life sciences as a sequence of processes using the quantitative language of applied mathematics. Written by experts from a variety of fields, the contributions illustrate the shift from a deterministic to a stochastic view of the processes involved, offering a new perspective on life sciences economics. The book covers topics such as valuing and managing intellectual property in life science, licensing in the pharmaceutical business, outsourcing pharmaceutical R&D, and stochastic modelling of a pharmaceutical supply chain. The book will appeal to scholars of economics and the life sciences, as well as to professionals in chemical and pharmaceutical industries. Preface Acknowledgments Contents *-1pc Value Creation and Managing Intellectual Property in the Life Science Industry Value Creation, Valuation and Business Models in the Pharmaceutical Sector 1 Value Principles in the Pharmaceutical Industry 2 Value Creation in the Pharmaceutical Industry 3 `Keeping Focus': The Traditional Value Token 4 `Extending Horizons': Innovation-Integration Across the Value Chain 5 Value Protection: Intellectual Property in the Life Sciences 5.1 Patent Evaluation 6 Modelling the Patent Value as a Stochastic Process 6.1 The Patent Life Model 6.2 Viewing a Generic Case 6.3 Interferon Beta 1a: A Real-World Case 7 The Future of Value and Valuation in Pharma References Limited Commercial Licensing Strategies: A Piecewise Deterministic Differential Game 1 Limited Commercial Licenses in the Pharmaceutical Industry 1.1 Probability of Issuing a CL 2 A Differential Game of Limited Commercial Licensing 2.1 Preliminaries 2.2 Profits and Sales in Each Regime 2.3 Switching Between Stages 2.4 The Problem 3 Solving the Model 4 Perspective References Partnership Models for R&D in the Pharmaceutical Industry 1 Introduction 2 The Problem of R&D Efficiency of Pharmaceutical Companies 2.1 Eroom's Law 2.2 Analysis of R&D Costs in the Pharmaceutical Sector 2.3 Analysis of Pipeline Drugs 3 New R&D Open Innovation Models for Pharmaceutical Companies 3.1 Mergers and Acquisitions 3.2 In-licensing Agreements 3.3 Outsourcing R&D Processes from CROs 3.4 R&D Collaborations 3.5 Public-Private Partnerships 3.6 Crowdsourcing 3.7 Innovation Centers 3.8 Open Source References *-1pc Modelling Specific Business Processes in the Life Science Industry Pharma Tender Processes: Modeling Auction Outcomes 1 Introduction 2 Pharmaceutical Tendering 2.1 Pharmaceutical Tendering Mechanism in Different Countries 2.2 Effect of Pharmaceutical Tendering 3 Tendering as Auction: Scope and Concept 3.1 Tender Versus Auction 3.2 Independent Private Value Auction 3.3 First Price Sealed Auction 3.4 Number of Bidders 4 Empirical Methods for Price Auction Estimation 4.1 Bidding Price Determinants Estimation with Reduced Form Approach 4.2 Structural Estimation of Auction Models 4.3 Quantile-Based Non-parametric Estimation of Private Value 5 Non-parametric Estimation on Observational Data 5.1 Dataset 5.2 Visualization and Descriptive Analysis 5.3 Assumptions Validation 5.4 Modeling and Estimation 5.5 Adjustments and Lessons Learned References Multi-Echelon Inventory Optimization Using Deep Reinforcement Learning 1 Introduction 2 Challenges of Multi-Echelon Inventory Management from an Optimization Perspective 3 Literature Review of Inventory Management 4 Reinforcement Learning for Inventory Management 4.1 Markov (Decision) Processes 5 Introduction to Reinforcement Learning 5.1 Value-Based Methods 5.2 Policy-Based Methods 5.3 Actor-Critic Methods 6 Evaluation 7 Discussion of Results 8 Outlook 9 Conclusions 10 Acronyms References *-1pc Specialized Quantitative Tools in the Life Science Industry An Invitation to Stochastic Differential Equations in Healthcare 1 Introduction 1.1 Brownian Motions 1.2 Ito's Integral and Solutions of Geometric Brownian Motions (GBM) 1.3 Existence of Solutions of Stochastic Differential Equations 2 Numerical Methods for SDEs 2.1 Euler–Maruyama Method 2.2 –Maruyama Methods 2.3 Stochastic Runge–Kutta Methods 3 A Numerical Evidence on PK/PD Models References Life Events that Cascade: An Excursion into DALY Computations 1 Introduction 2 The Hawkes–Cox Framework 2.1 The Choice of Kernel and the Rôle of δ 3 Dynkin's Formula 4 Theoretical Moments 4.1 The Moments of Counts in an Interval 4.2 The Covariance 5 Learning and Optimization 6 Synthetic Experiments 6.1 Calibration 7 Disability Adjusted Life Years 8 Concluding Remarks References