Personalised synthetic speech can enhance communication for Augmentative and Alternative Communication (AAC) users, but achieving high-quality, speaker-specific voices depends on various factors such as the condition causing speech loss, and availability of recorded speech. Recent advancements in large-scale zero-shot TTS models may change the data requirements, as they have the potential to adapt to a wider range of inputs. This paper explores the potential of these pretrained models in various data availability scenarios, from extensive spontaneous speech to minimal or no unaffected speech. We evaluate a state-of-the-art TTS system on a case study involving a stroke survivor with dysarthria, leveraging both typical and atypical speech data. Additionally, we introduce a novel interactive approach using dysarthric speech as an audio prompt to enable user-guided prosody adaptation.