Vector Space Biosciences, Inc. focuses on context-controlled NLP/NLU (Natural Language Processing/Understanding) and feature engineering for hidden relationship detection in data related to space biosciences. Our platform powers advanced approaches in Artificial Intelligence (AI) and Machine Learning (ML) using experimental and formal language models including well-known models such as OpenAI"s GPT-3 (2020), Google"s BERT (2018), word2vec (2013) combined with experimental methods developed at Lawrence Berkeley National Laboratory (2008) Biosciences division. To establish a lunar base or go to Mars, understanding how to protect and repair the human body during spaceflight is required. Vector Space Biosciences, Inc., (SBIO), designs, develops and launches biological CubeSats for the purpose of generating and interpreting unique datasets related to microgravity and radiation. This leads to the development of countermeasures against diseases associated to stressors connected to protecting and repairing the human body during spaceflight. This includes using a network of scientific data engineering pipelines for building targeted language models (LM) resulting in real-time datasets and advanced visualizations of the language models, which power Artificial Intelligence (AI) operations in space biosciences, biotechnology and pharmaceutical development.