Issue 4 Volume 14 (2025)

Pharmaceutical concepts commonly advance through discovery and development by completing predefined activities, entering formal phases, or satisfying locally defined technical milestones. These events are operationally useful but do not necessarily demonstrate that the supporting evidence is reproducible, biologically relevant, manufacturable, clinically interpretable, or adequate for the next consequential decision. This Original Translation-Readiness Architecture Article proposes a Translation

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Individualized dosing is frequently presented as a problem of estimating an appropriate dose from patient covariates, drug concentrations, and population pharmacokinetic or pharmacodynamic models. This framing is incomplete when patient information is missing or delayed, exposure–response relationships are uncertain, efficacy and toxicity objectives conflict, and treatment must be revised as the patient’s condition changes. This article develops an original decision-theoretic framework for organ

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Pharmacovigilance systems can detect unusual patterns of reported adverse events, yet statistical prominence does not establish that a medicine caused the observed harm. Disproportionality measures, spontaneous reports, observational associations, case narratives, mechanistic findings, and computational predictions each address different questions and remain vulnerable to distinct biases. This Original Causal Safety Architecture Article proposes a traceable signal-to-causality evidence architect

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Clinical pharmacokinetic and pharmacodynamic modelling can support precision therapeutics by connecting dose, exposure, response, patient characteristics, and uncertainty. However, a model that describes observed data adequately may still provide unreliable individual predictions or unsuitable dose recommendations when its parameters are non-identifiable, its evaluation is restricted to development data, or its assumptions do not transfer across populations and clinical settings. This methodolog

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Population-average safety estimates can obscure clinically important differences in drug harm because patients differ in baseline susceptibility, realized exposure, biological response, concomitant treatment, and the probability that an adverse outcome will be observed or reported. This Original Subgroup-Safety Framework Article proposes a multidimensional architecture for detecting and evaluating heterogeneous drug harm across age, sex, pregnancy, physiological state, comorbidity, frailty, orga

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Pharmacovigilance evidence is progressively transformed as source reports are received, linked, coded, interpreted, analyzed, corrected, and translated into safety conclusions. Existing systems frequently preserve the resulting records without preserving a complete, inspectable account of how each assertion, exposure estimate, contextual judgment, analytical result, and conclusion was derived. This article proposes an adverse-event provenance graph as an original conceptual architecture for link

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Modern pharmacovigilance increasingly combines spontaneous reports with electronic health records, administrative claims, registries, distributed data networks, active monitoring, natural-language processing, and machine-learning methods. Yet the evidentiary roles of these approaches are often conflated: signal generation may be treated as causal assessment, computational performance as operational utility, and implementation activity as evidence of improved patient safety. This umbrella review

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Promising pharmaceutical technologies frequently demonstrate reproducible technical performance under laboratory conditions yet fail to progress toward patient-relevant clinical use. Such attrition is often attributed to isolated scientific, regulatory, financial, or operational obstacles, obscuring the relationships through which weaknesses in one domain propagate across development. This Original Failure-Mechanism Framework Article proposes a multidimensional architecture for explaining transl

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Pharmaceutical innovation frequently generates compelling mechanistic, computational, preclinical, or technological findings that do not progress into reproducible, manufacturable, clinically useful, and sustainably implemented products. This systematic review examined how evidence maturity, reproducibility, external validation, manufacturing feasibility, clinical relevance, and implementation conditions jointly shape pharmaceutical translation. A protocol-driven review design was used, with pre

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Population pharmacokinetic and pharmacodynamic models commonly support inference by relating dose, exposure, response, and patient characteristics, yet their application during clinical care can become problematic when treatment, physiology, disease severity, observation intensity, and clinical decisions change together. This article develops an original longitudinal modelling framework that treats clinical PK/PD as a coupled system of biological states, treatment events, observation processes,

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