Call for Chapters: Enhancing Pharmaceutical Transport, Logistics, and Supply Chain Resilience With Agentic AI

Editors

Blessing Takawira, University of Johannesburg, South Africa
Rose Luke, University of Johannesburg, South Africa

Call for Chapters

Proposals Submission Deadline: July 1, 2026
 Full Chapters Due: September 2, 2026
 Submission Date: September 2, 2026

Introduction

The global pharmaceutical industry operates within one of the most complex, regulated, and life-critical supply chain environments in existence. From the sourcing of active pharmaceutical ingredients (APIs) and excipients across multi-tier international supplier networks, to the last-mile cold-chain delivery of temperature-sensitive biologics, vaccines, and specialty medicines, every node in the pharmaceutical supply chain carries profound public health consequences. Systemic weaknesses in pharmaceutical transport, logistics, and supply chain management — whether caused by natural disasters, geopolitical disruptions, pandemics, regulatory failures, or demand surges — can directly translate into medicine shortages, patient harm, and loss of life. The COVID-19 pandemic starkly exposed these vulnerabilities, triggering unprecedented shortages of personal protective equipment, critical care medicines, and vaccines, and placing pharmaceutical supply chain resilience firmly at the top of global health policy and industry agendas. Against this backdrop, the rise of Agentic Artificial Intelligence (Agentic AI) represents a fundamental and transformative shift in how supply chain intelligence can be designed, deployed, and governed. Unlike earlier generations of AI tools — which primarily augmented human decision-making through dashboards, predictive analytics, and optimisation recommendations — Agentic AI systems are autonomous, goal-directed agents capable of perceiving their environment, reasoning under uncertainty, formulating multi-step plans, executing actions, and continuously learning and adapting without requiring constant human instruction. When embedded in pharmaceutical logistics and supply chain networks, Agentic AI agents can autonomously monitor cold-chain conditions, dynamically reroute shipments in response to disruptions, manage supplier negotiations, orchestrate cross-border compliance workflows, balance inventory across distribution networks, and coordinate demand forecasting across entire health systems — all in real time and at a scale that no human team could replicate. Yet the deployment of autonomous AI decision-making in an industry as consequential, regulated, and ethically complex as pharmaceuticals raises profound questions that transcend mere technical implementation. Who bears accountability when an AI agent makes a procurement decision that leads to a medicine stockout? How should regulators such as the FDA, EMA, or WHO approach the governance of autonomous systems operating within Good Distribution Practice (GDP) and Good Manufacturing Practice (GMP) frameworks? How can pharmaceutical companies ensure that Agentic AI systems are explainable, auditable, and free from algorithmic bias that may inadvertently exacerbate access inequities — particularly in low- and middle-income countries (LMICs)? What organisational capabilities, data architectures, and human-machine collaboration models are required to successfully integrate Agentic AI into existing pharmaceutical supply chain operations? This edited volume — Enhancing Pharmaceutical Transport, Logistics, and Supply Chain Resilience With Agentic AI — is designed to address these questions with scholarly rigour, empirical depth, and practical relevance. It brings together original research, theoretical frameworks, case studies, and policy perspectives from leading academics, industry experts, and policy practitioners worldwide to produce a comprehensive, multidisciplinary reference that advances both the academic frontier and the practical understanding of AI-driven pharmaceutical supply chain resilience.

Objective

This book intends to accomplish the following scholarly and practical objectives, each of which contributes meaningfully to and advances existing research at the intersection of pharmaceutical supply chain management, logistics, and Agentic AI: • To advance theoretical understanding of how Agentic AI architectures — including autonomous agents, multi-agent systems, and Large Language Model (LLM)-powered orchestration engines — can be applied to pharmaceutical transport, logistics, and supply chain management, thereby extending existing supply chain resilience theory into the domain of autonomous intelligence. • To document and critically analyse emerging empirical evidence on the performance, adoption barriers, enablers, and organisational impacts of Agentic AI deployments in real-world pharmaceutical supply chain settings, including both successes and failures. • To develop and consolidate frameworks, models, and conceptual tools that practitioners, researchers, and policymakers can apply to evaluate, design, and govern Agentic AI systems in pharmaceutical logistics contexts. • To examine the regulatory, ethical, and governance challenges associated with autonomous AI decision-making in a safety-critical, highly regulated industry — contributing to an emerging scholarly discourse on AI governance in life sciences. • To provide a globally representative and regionally diverse collection of perspectives, including contributions from emerging economies and low- and middle-income countries, ensuring that the book reflects the full spectrum of pharmaceutical supply chain challenges and AI adoption trajectories worldwide. • To bridge the gap between AI computer science and supply chain management scholarship, creating a cross-disciplinary resource that is accessible to, and useful for, both communities. • To serve as a definitive and authoritative reference work for academic libraries, research institutions, and industry organisations seeking cutting-edge, peer-reviewed knowledge on AI-driven pharmaceutical supply chain transformation — thereby contributing to IGI Global's mission of disseminating innovative research on emerging topics.

Target Audience

This publication is designed to serve a broad, multidisciplinary, and globally distributed readership. The research contained within will benefit the following primary and secondary audiences: • Academic Researchers and Doctoral Students — particularly those working in supply chain management, logistics, operations management, pharmaceutical sciences, health systems management, information systems, artificial intelligence, and business management. The book provides theoretical frameworks, empirical findings, and bibliographic resources that will support research at the cutting edge of these intersecting disciplines. • Pharmaceutical and Life Sciences Industry Professionals — including supply chain directors, logistics managers, procurement executives, regulatory affairs specialists, quality assurance professionals, and operations leaders at pharmaceutical manufacturers, distributors, Contract Development and Manufacturing Organisations (CDMOs), and third-party logistics providers (3PLs). These readers will gain practical insights into AI-enabled tools, implementation strategies, and real-world case studies directly applicable to their organisations. • Healthcare System Administrators and Public Health Officials — including hospital pharmacists, national medicines regulatory authorities, procurement agencies (such as UNICEF Supply Division and the Global Fund), and public health policymakers who are responsible for ensuring the uninterrupted supply of medicines and vaccines to patients, and who increasingly need to understand AI's role in health supply chain resilience. • Technology Developers and AI Solution Architects — including software engineers, data scientists, AI researchers, and product managers at technology companies developing Agentic AI platforms, digital supply chain solutions, and healthcare logistics systems, who require domain-specific knowledge of pharmaceutical supply chain requirements to build fit-for-purpose solutions. • Regulatory Bodies and Government Policymakers — at national and international levels, including staff at agencies such as the FDA, EMA, SAHPRA, WHO, and national health ministries, who are developing regulatory frameworks for AI in healthcare and pharmaceutical supply chains, and who need evidence-based policy-relevant research to inform their work. • University Libraries and Academic Institutions — seeking a comprehensive, up-to-date reference volume on AI-driven pharmaceutical supply chain management for their collections. The book's breadth of coverage across multiple disciplines makes it a high-value acquisition for libraries supporting health sciences, business, engineering, and computer science programmes. • Management Consultants and Industry Analysts — advising pharmaceutical and healthcare clients on digital transformation, supply chain resilience strategy, and AI adoption, who require access to the latest evidence-based research and conceptual models.

Recommended Topics

The following topics represent the broad thematic scope of this volume. Authors are welcome to address any of these areas or propose related topics that intersect with the book's central themes of Agentic AI, pharmaceutical logistics, supply chain resilience, and healthcare supply systems: Foundations and Frameworks • Conceptual frameworks for Agentic AI in pharmaceutical supply chain management • Distinguishing Agentic AI from conventional AI, machine learning, and automation in logistics • Multi-agent systems architecture for pharmaceutical supply chain coordination • Large Language Models (LLMs) and foundation models as cognitive engines for supply chain agents • Human-in-the-loop versus fully autonomous models for pharmaceutical decision-making • Supply chain resilience theory extended through the lens of autonomous AI Pharmaceutical Logistics and Transport Innovation • AI-driven dynamic route optimisation for pharmaceutical distribution networks • Autonomous cold-chain monitoring, temperature excursion detection, and real-time response • Drones, autonomous vehicles, and robotic systems for last-mile pharmaceutical delivery • Carrier selection, freight optimisation, and multimodal transport decisions using AI agents • Real-time shipment visibility, track-and-trace, and predictive estimated time of arrival (ETA) systems • Warehouse automation and autonomous inventory management in pharmaceutical distribution centres Supply Chain Resilience and Risk Management • Predictive disruption management: AI-driven anticipation and mitigation of supply chain shocks • AI-enabled supplier risk scoring, continuous monitoring, and autonomous procurement switching • Demand sensing, AI-driven inventory positioning, and prevention of medicine stockouts • Multi-tier supply chain mapping and risk visibility through autonomous data-gathering agents • Business continuity planning and supply chain recovery orchestration using Agentic AI • Case studies from COVID-19, natural disasters, and geopolitical disruptions Regulatory Compliance, Quality, and Governance • Autonomous GDP and GMP compliance monitoring in pharmaceutical distribution • Serialisation, track-and-trace, and anti-counterfeiting enhanced by Agentic AI • Regulatory frameworks for approving and overseeing autonomous AI in pharmaceutical supply chains • Data integrity, audit trails, and explainability requirements for regulated AI environments • Cross-border pharmaceutical logistics and AI-assisted customs and trade compliance • AI governance, accountability structures, and liability frameworks for autonomous supply chain agents Digitalisation, Data, and Technology Integration • Blockchain, Internet of Things (IoT), and digital twins as enablers of Agentic AI in pharmaceuticals • Data architectures and real-time pipelines supporting autonomous supply chain agents • Cloud and edge computing strategies for deploying Agentic AI in distributed logistics networks • Cybersecurity risks, resilience strategies, and threat modelling for AI-enabled pharmaceutical supply chains • ERP, WMS, and TMS integration challenges and opportunities for embedding Agentic AI • Interoperability standards and data-sharing ecosystems in pharmaceutical supply networks Ethics, Equity, and Human Factors • Ethical frameworks for autonomous AI decision-making in life-critical pharmaceutical supply chains • Accountability and liability when AI agents cause pharmaceutical supply chain failures • Algorithmic bias in pharmaceutical procurement, distribution, and allocation decisions • Workforce transformation: reskilling, job redesign, and human-AI collaboration in logistics • Patient safety, medicine access equity, and justice considerations in AI-automated distribution • Organisational change management and culture in AI-driven pharmaceutical supply chain transformation Emerging Markets, Global Health, and Special Contexts • Pharmaceutical supply chain resilience in low- and middle-income countries (LMICs) and the role of AI • Vaccine supply chain management in Africa and resource-constrained settings using AI • AI applications in humanitarian pharmaceutical logistics and emergency medicine distribution • Regional perspectives on Agentic AI adoption: Africa, Asia-Pacific, Latin America, the Middle East • Public-private partnership models for AI deployment in national pharmaceutical supply systems • AI-driven medicine supply optimisation for neglected tropical diseases and under-served populations Empirical Research, Case Studies, and Future Directions • Organisational case studies of Agentic AI pilots and deployments in pharmaceutical logistics • Quantitative studies on AI impact on pharmaceutical supply chain performance, cost, and service levels • Qualitative and mixed-methods studies on managerial adoption, barriers, and enablers of Agentic AI • Failure analysis: lessons from AI implementation challenges in pharmaceutical supply chains • Future scenarios and strategic roadmaps for AI-enabled pharmaceutical supply chain transformation • Comparative studies of AI adoption maturity across pharmaceutical companies, 3PLs, and health systems

Submission Procedure

Researchers and practitioners are invited to submit on or before July 1, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by July 15, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by September 2, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Enhancing Pharmaceutical Transport, Logistics, and Supply Chain Resilience With Agentic AI. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

July 1, 2026: Proposal Submission Deadline
July 15, 2026: Notification of Acceptance
September 2, 2026: Full Chapter Submission
October 7, 2026: Review Results Returned
November 4, 2026: Final Acceptance Notification
November 11, 2026: Final Chapter Submission

Inquiries

Blessing Takawira
University of Johannesburg
btakawira@uj.ac.za

Rose Luke
University of Johannesburg
rluke@uj.ac.za
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