Spike-based neural networks have been shown to hold more computational power than other architectures and their integration into mainstream computing is projected to herald a new age for information technology. Implementation using a flexible Thin Organic Large Area Electronics TOLAE process is a promising low cost way to integrate neuromorphic circuits into sensors, however its feasibility has never been demonstrated. Here we simulate spiking neuron circuits based on the characteristics of a gravure printed scalable organic thin film transistor technology. We then explore the variability of the parameters to show how much variation the circuits can support. Our results demonstrate the feasibility of OTFT technologies for spiking neuromorphic hardware.