Biomimetic photonic crystals transduce subtle structural and refractive-index changes into measurable optical signals, offering dynamic sensing capabilities beyond conventional endpoint detection. This review examines how these materials can move beyond static endpoint readouts toward dynamic and reliable detection in complex biological samples. To clarify how dynamic detection is achieved, this review organizes the discussion around two complementary aspects. The first aspect focuses on material-level responses, which are classified by the location and mechanism of the change into bulk-phase response, pore-mediated mass transport, and interfacial recognition. The second aspect addresses system-level readout, which records these changes through spatially resolved imaging or time-resolved spectral acquisition. Three major challenges to reliable detection are then analyzed, including ambiguous signal attribution, material hysteresis and drift, and matrix interference from non-target components. A four-tier framework for reliability assessment is proposed, encompassing signal attribution, dynamic stability, sample adaptability, and method comparison. Finally, future directions are discussed in terms of recyclable dynamic materials, physics-constrained algorithm-assisted design with digital calibration, and integrated platforms that combine sample handling, internal referencing, and time-series readout for real-sample analysis.