Related Experiment Videos
De-risking Biopharma Asset Acquisition: Towards a Quantitative Framework for Strategic Decision-making
Xiaotang Ma1, Zheng Lu2,3, Yating Zhao4
1Sanofi, Morristown, New Jersey, USA.
Abstract:
The impending patent cliff projected between 2028-2030 poses significant commercial and strategic challenges for innovative pharmaceutical and biotechnology companies. To sustain growth and maintain competitive positioning, organizations are increasingly relying on strategic mergers, acquisitions, and partnerships to replenish pipelines. However, systematic quantitative strategies and framework for asset evaluation remain limited. This review outlines how clinical pharmacology and pharmacometrics (CPP) can support asset evaluation and decision-making during the asset due diligence. First, CPP spans the entire drug development continuum, providing a quantitative framework for evaluating external assets, including pharmacological plausibility, dosing feasibility, and overall development risks. Second, Model-informed drug development (MIDD) approaches can be applied to predict human pharmacokinetics, inform dose selection, and estimate the probability of technical and regulatory success. Third, we examine the emerging role of artificial intelligence and machine learning in asset evaluation and portfolio decision-making, by discovering prognostic and predictive factors, and identifying the patient sub-group. We also introduce NewCo as an emerging drug-development and business model, where quantitative strategies may be deployed. Further, we address cognitive biases, such as confirmation bias and sunk cost fallacies that can influence acquisition outcomes. Importantly, we propose the development of a bias-aware, fit-for-purpose corporate template to integrate CPP and MIDD insights, standardize evaluation criteria, and support cross-functional decision-making during asset due diligence. Embedding quantitative and bias-mitigated CPP frameworks into due diligence workflows, can help identify high-value opportunities, de-risk development uncertainties, and accelerate delivery of innovative therapies to patients with unmet medical needs.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
Biopharmaceutical Factors Influencing Drug Product Design: Overview
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Pharmacodynamic Models: Overview
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.