In this presentation, I will showcase a particular aspect of my work, which focuses on the development of accessible tools aimed at enhancing open science practices and ensuring reproducibility within the research community. I'll start by discussing my paper published in Nature, a collaborative effort involving numerous researchers. This paper highlights our commitment to advancing open science and reproducibility by using innovative tools. I'll continue to present my ongoing project concerning the Robustify Python library, designed for comprehensive multiversal analysis. Additionally, I'll outline my contributions to developing computationally efficient individual synthetic control methods, which are poised to significantly enhance research methodologies by allowing to apply this methodology to increasingly large datasets.