From Reflection to Acceleration: Clinical Pharmacology’s 2025 Lessons and 2026 Opportunities

As we draw the curtain on 2025 and turn our gaze toward 2026, it is my pleasure to offer this year-in-review and forward-looking editorial on the evolving discipline of clinical pharmacology. The year 2025 has been pivotal for clinical pharmacology: a year when computational innovation, mechanistic modeling, and precision medicine coalesced to fundamentally re-shape drug development. Several themes dominated the landscape, both in our journal's publications and across the broader field. As we enter 2026, it is an opportune moment to reflect on the remarkable transformation clinical pharmacology has undergone in 2025, and to begin a conversation about the year ahead. Beginning with this issue, Clinical Pharmacology in Drug Development transitions to a continuous publication model. Rather than batching articles into discrete monthly issues, accepted manuscripts will now be published online immediately upon final preparation. This approach offers multiple advantages for our authors and readers: accelerated dissemination of findings and enhanced discoverability through earlier indexing. Continuous publication aligns with broader trends in scholarly communication toward real-time knowledge sharing.1 As digital platforms increasingly dominate academic publishing, the traditional issue-based model becomes less relevant to how researchers actually access and utilize the literature.2 We believe this transition will enhance the impact and accessibility of research published in our journal while maintaining the rigorous peer review standards that define Clinical Pharmacology in Drug Development. Model-informed drug development (MIDD) achieved demonstrable maturation in 2025.3 The publication by Sahasrabudhe and colleagues in Clinical Pharmacology & Therapeutics provided compelling quantitative evidence that systematic MIDD application yields average savings of approximately 10 months in development cycle time and $5 million per program.4 These are not theoretical projections but empirical findings from retrospective portfolio analysis that offer concrete validation of MIDD's value proposition. Physiologically based pharmacokinetic (PBPK) modeling, in particular, emerged as an indispensable tool. The FDA workshop on “Advances in PBPK Modeling and its Regulatory Utility for Oral Drug Product Development,” summarized by Cheng et al.5 highlighted both the successes and persistent challenges in utilizing PBPK for generic drug development and bioequivalence assessments. Our own journal contributed important work in this area. Studies examining pharmacokinetic variability across special populations, drug–drug interactions, and first-in-human dose escalation protocols published throughout 2025 in Clinical Pharmacology in Drug Development exemplified the practical application of quantitative pharmacology principles to real-world drug development challenges. Perhaps no development in 2025 has captured the imagination (as well as scrutiny) of our field more than the integration of artificial intelligence (AI) and machine learning (ML) into drug development workflows. The FDA's landmark guidance document “Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products,” published in January 2025, marked a pivotal moment in regulatory acceptance of these technologies.6 This guidance established a risk-based credibility assessment framework that balances innovation with the need for robust validation. The tangible impact of AI on drug development timelines has begun to materialize.7 AI is transitioning from a theoretical concept to an institutional reality, as evidenced by major pharmaceutical companies embedding “lab-in-the-loop” methodologies that iteratively combine experimental data with ML algorithms to accelerate target identification and lead optimization.8 However, as Kant et al.9 appropriately cautioned, significant challenges remain regarding algorithmic interpretability, data quality requirements, and potential computational biases. As clinical pharmacologists, we have a responsibility to ensure that AI applications are validated against robust clinical endpoints and do not merely optimize surrogate measures. The integration of AI must enhance, not replace, mechanistic understanding of drug action. The promise of pharmacogenomics is finally achieving meaningful clinical traction. In 2025, we witnessed several countries, including Singapore and Thailand, implement national-level HLA-B*15:02 screening programs prior to carbamazepine initiation, dramatically reducing severe cutaneous adverse reactions.10 The integration of multi-omics data with advanced computational models continued to evolve. Zhuang's analysis in Frontiers in Medicine explored how genomics, transcriptomics, proteomics, and metabolomics can be synthesized with AI approaches to provide more comprehensive understanding of drug response variability.11 The Clinical Genome Resource (ClinGen) Pharmacogenomics Working Group's frameworks for evaluating gene–drug clinical validity represent critical infrastructure for translating genomic insights into practice.12 However, significant disparities persist in pharmacogenomic implementation across healthcare systems, and harmonization of international policies remains an urgent priority. As we move into 2026 and the future, we must embrace the polygenic complexity of most drug response phenotypes. The integration of real-world evidence with pharmacogenomic analysis will be essential to refine treatment protocols continuously and reduce the trial-and-error approach that still characterizes much of clinical prescribing. Clinical pharmacology in 2025 demonstrated remarkable progress in translating computational innovation and mechanistic understanding into tangible improvements in drug development efficiency and patient care. The convergence of AI, MIDD, and precision medicine represents not merely incremental advancement but a fundamental transformation in therapeutic optimization. As we enter 2026, our responsibility is to ensure that these powerful tools are applied with scientific rigor, ethical consideration, and unwavering focus on patient benefit. The challenges are substantial. We must remain vigilant about data quality, algorithmic transparency, equitable access, and regulatory harmonization. However, our collective commitment to advancing rational, evidence-based optimization of drug therapy is also formidable. I draw your attention to Kruse and colleagues' perspective in the European Journal of Clinical Pharmacology, which provided valuable insights into how clinical pharmacology shapes the drug development journey, emphasizing the discipline's central role in modern pharmaceutical science.13 Their analysis highlighted that clinical pharmacology information accounts for up to 50% of drug label content, a testament to the field's fundamental importance. The transition to continuous publication in Clinical Pharmacology in Drug Development signifies our commitment to keeping pace with the field's rapid evolution. We will continue to provide a unique forum for early-phase research, first-in-human studies, and negative findings that contribute essential knowledge to the drug development enterprise. The future of clinical pharmacology is not about choosing between traditional approaches and emerging technologies, but rather about thoughtfully integrating these capabilities to serve our fundamental mission: ensuring that the right patient receives the right drug at the right dose at the right time. That mission guides our work in 2026 and beyond. To the many clinical pharmacologists working in industry, academia, regulatory agencies, and contract research organizations around the world: you are the unsung heroes of drug development. You translate the science of drug behavior into dosing strategy, you shape the safe recruitment of first-in-human subjects, you navigate the complexity of drug–drug interactions, you harness modeling to optimize trials, and ultimately you help ensure that medicines achieve their promise with the right dose, for the right patient, at the right time. In this era of rapid change with novel modalities, AI/ML, global trials, and precision dosing, your expertise remains needed more than ever. Let us continue to push boundaries while preserving foundational rigor, sound PK/PD principles, robust study design, transparent reporting, and ethical conduct. I extend my heartfelt thanks to the many authors, reviewers, and readers of Clinical Pharmacology in Drug Development. Your contributions keep the journal vibrant and the discipline advancing. Thank you for your continued trust and for choosing Clinical Pharmacology in Drug Development as your publication home. As we embark on 2026, let us embrace the opportunities ahead: faster dissemination, richer modeling tools, broader global engagement, and deeper patient-centeredness. I wish you all a happy, healthy, and productive New Year. May it bring new insights, collaborations, and breakthroughs. We look forward to your continued contributions to Clinical Pharmacology in Drug Development and to the advancement of the field. Happy 2026! The author declares no conflicts of interest. No funding was obtained for this work. Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.