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Advanced drug delivery systems have long promised to transform therapy by improving biodistribution, reducing toxicity, enabling intracellular delivery, extending exposure, and opening therapeutic spaces that conventional dosage forms cannot reach. Yet the field remains marked by a persistent translation paradox: thousands of sophisticated carrier systems are reported in the literature, while only a small fraction progress into durable clinical products. This gap is usually explained through biological complexity, manufacturing difficulty, regulatory uncertainty, or inadequate preclinical models. This critical perspective proposes that these explanations, although important, are incomplete. A deeper systemic factor is technological lock-in, defined here as the self-reinforcing dominance of specific drug delivery platforms that shape what researchers, funders, manufacturers, regulators, and companies consider technically feasible and translationally credible. Once a platform accumulates expertise, protocols, supply chains, regulatory familiarity, and publication momentum, alternatives may struggle to compete even when they offer potentially superior solutions. The central argument is that technological lock-in contributes to translational failure by narrowing the drug delivery imagination. Instead of asking which delivery architecture is best suited to a given biological, clinical, manufacturing, and regulatory problem, the field often asks how an incumbent platform can be modified to fit yet another therapeutic challenge. This platform-first logic can lead to repeated optimisation of familiar systems while more disruptive or simpler design spaces remain underexplored. The article critically examines the assumptions that sustain dominant platforms in advanced drug delivery. These assumptions include beliefs that increasing carrier complexity necessarily improves therapeutic performance, that certain materials possess broad translational privilege, that murine and in vitro models can adequately predict human outcomes, and that incremental optimisation is less risky than platform diversification. The perspective argues that these assumptions are not merely technical claims but institutional habits that stabilise lock-in. The proposed conceptual model links critical assumptions, technological lock-in, platform dependency, innovation constraint, and translational failure in a self-reinforcing cycle. In this model, failure does not necessarily disrupt dominant platforms; paradoxically, it may intensify dependence on them because they remain the most familiar, fundable, publishable, manufacturable, and regulatable options. Five tables structure the analysis by summarising translational failure evidence, critical assumptions, failure mechanisms, lock-in case examples, and the proposed model. Breaking technological lock-in requires more than improving individual formulations. It requires deliberate diversification of platform portfolios, stronger interrogation of inherited assumptions, translational assessment that rewards fit-for-purpose simplicity, and innovation policies that lower the cost of exploring alternative delivery architectures. A more resilient advanced drug delivery ecosystem should treat platform diversity not as inefficiency, but as insurance against repeated translational failure.