Chemical noise and signal fidelity in stimuli-responsive drug delivery systems

Stimuli-responsive systems for drug delivery have been developed for the purpose of delivering drugs in a controlled manner through the use of chemical or biological signals. However, these systems are typically referred to as selective and precise; however, in biological systems, there are multiple factors that create chemical variability (i.e., extrinsic stimuli such as temperature, pH, and time). Because there is a chemical variance in the biological environment, it will be possible to introduce chemical noise that will distort, suppress, or incorrectly trigger the desired therapeutic response. In this article, the notion of signal fidelity is introduced as a quantitative chemical parameter to describe how accurately external stimuli are translated into therapeutic responses. Signal fidelity is defined in terms of measurable descriptors including kinetic selectivity (ratio of desired to competing reaction rates), activation variability (distribution of activation across carrier populations), and temporal precision (dispersion in activation time). These parameters provide a framework for quantitatively evaluating the reliability of SRS under chemically noisy biological conditions. In addition to examining sources of chemical noise, how well the signal has been processed or yielded to the therapeutic effect, and the limitations of existing design approaches, the authors propose that responsive drug delivery systems can be considered as chemical signal processing challenges. The authors present the management and understanding of noise, as opposed to ignoring it, as one of the major hurdles that will face the development of the next generation of therapeutic products. Importantly, the concepts discussed in this review are grounded in a wide range of experimental observations reported in the literature, including heterogeneous activation kinetics, stochastic drug release behavior, diffusion-limited transport, and single-entity variability in responsive systems. Rather than proposing a purely hypothetical framework, this work synthesizes these experimentally observed phenomena into a unified perspective to better interpret and design stimuli-responsive drug delivery systems.