Issue 1 Volume 15 (2026)

Biopharmaceutical manufacturing processes evolve through scale changes, equipment replacement, raw-material variation, site transfers, analytical modernization, process intensification, and post-approval optimization. Conventional comparability plans are commonly structured around a defined change and a prespecified evidence package, but repeated and interacting changes can fragment product knowledge across development and commercial lifecycles. This article proposes a living comparability proto

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Living, biohybrid, and self-propelled drug carriers seek to overcome limitations of conventional nanomedicine by incorporating active movement, biological sensing, endogenous homing, externally directed navigation, or locally triggered release. Their defining opportunities arise from coupling pharmaceutical payloads to microorganisms, mammalian cells, cell-derived membranes, biological vesicles, chemically reactive micromotors, or externally guided microdevices. However, technological novelty fr

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Pharmacogenomic decisions are commonly anchored to inherited variation, yet the functional consequences of genotype may change as medications, inflammation, organ function, disease severity, adherence, and treatment priorities evolve. This article proposes a Pharmacogenomic Digital Twin for Counterfactual Therapy Selection as an original, non-empirical architecture for representing these interacting determinants over time. The proposed twin separates relatively stable genomic information from ti

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Comparative efficacy trials have historically served as visible clinical confirmation within biosimilar development, but their incremental scientific value has become increasingly contested as analytical characterization, functional testing, pharmacokinetic comparison, pharmacodynamic biomarkers, and immunogenicity assessment have become more sensitive. This critical evidence review evaluates whether comparative efficacy trials still resolve uncertainties that materially affect biosimilar develo

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Pharmaceutical dosage forms are conventionally designed around predetermined release profiles, even though the physiological conditions governing dissolution, transport, absorption, clearance, tissue access, and therapeutic need can change during use. Stimuli-responsive materials partly address this mismatch, but a material reaction to pH, glucose, enzymes, reactive oxygen species, or another cue does not by itself establish reliable patient-state interpretation or safe adaptation. This article

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Quantitative structure–activity relationship models are commonly developed as bounded predictive artefacts, yet their evidential conditions may continue to change after deployment. Incoming compounds can occupy unfamiliar chemical space, assay procedures and biological contexts can alter endpoint meaning, labels can be corrected or reinterpreted, molecular representations and software environments can change, and prediction consequences can expand beyond the original context of use. Treating the

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Nanocarriers designed to alter their behavior in response to biological conditions create a safety problem that extends beyond conventional formulation quality and passive targeting. Their sensed inputs may influence transport, surface exposure, cellular entry, intracellular trafficking, or payload release, allowing uncertainty at one stage to propagate into later and potentially irreversible actions. This Original Governance and Control Theory Article proposes a navigation constitution for orga

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Generative artificial intelligence can retrieve, reorganize, and synthesize formulation knowledge, but fluent output is not equivalent to the situated expertise required to design a pharmaceutical product. Formulation decisions depend on dosage-form purpose, material attributes, excipient functionality, compatibility, stability, process conditions, scale, bioavailability, patient needs, and the quality of supporting evidence. This article develops an original, non-empirical governance architectu

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Foundation models are increasingly presented as reusable computational infrastructures for molecular property prediction, compound generation, reaction modelling, biological representation learning, and pharmacoinformatics. Their relevance to quantitative structure–activity relationship modelling, however, cannot be inferred from pretraining scale or benchmark performance alone. This scoping review maps how foundation-model concepts are defined, trained, adapted, transferred, grounded, calibrate

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Pharmacogenomics has traditionally translated inherited variation into treatment guidance through individual genes or compact variant panels. This framework remains clinically important but incompletely represents drug response when many variants, treatment exposures, disease states, concomitant medicines, environmental influences, and population-specific genomic structures act together. This evidence-mapping review examines how polygenic information is being developed and evaluated for precisio

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Molecular dynamics can characterize conformational ensembles, energy landscapes, ligand-recognition pathways, allosteric transitions, and molecular mechanisms relevant to pharmaceutical research, but conventional trajectories frequently undersample rare events and slow collective motions. Enhanced-sampling methods address this limitation through biased potentials, generalized ensembles, replica exchange, pathway sampling, adaptive trajectory generation, or learned collective variables. This syst

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Molecular simulation can characterize conformational ensembles, energy landscapes, ligand interactions, and transition pathways, yet an individual simulation remains a conditional representation rather than a continuously updated molecular counterpart. This article proposes an original mechanistic digital-twin architecture for drug–target dynamics that separates latent molecular state, intervention, physical time, evidence-update time, decision horizon, and observation. The architecture links a

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