The insulin-like growth factor 1 receptor (IGF1R) is a crucial receptor tyrosine kinase involved in cellular growth, survival, and metabolism. Abnormal overexpression and activation are common in various cancers and contribute to tumor development and resistance to treatment. The STRING database was used to analyze the protein-protein interaction network of IGF1R and was visualized using Cytoscape to identify the key associated proteins. We assessed IGF1R and its associated protein expression levels across pan-cancer types and compared them to healthy controls using a TNMplot and cBioPortal. The objective of this study was to identify novel, low-toxicity inhibitors targeting the IGF1R and its associated proteins (e.g., AKT1 and EGFR) with better pharmacokinetic profiles for effective cancer treatment, including brain cancer. We screened 693 million drug-like compounds and selected the top 400 for toxicity analysis using ProTox-II, which identified 83 nontoxic candidates. These were categorized as either blood-brain barrier (BBB) permeant or impermeant. Molecular docking studies with AutoDock Vina 4.1 were performed on 17 target proteins, including IGF1R, with the top three compounds. Subsequently, molecular dynamics simulations using Desmond were conducted on the two most promising candidates: two BBB permeants and two impermeants. Our study identified six nontoxic IGF1R inhibitors and 16 other target protein inhibitors. Docking and MD simulations confirmed the potential of these compounds in targeted therapies. Notably, both BBB-permeant and -impermeant compounds in complex with the target proteins showed stability over 50 and 400 ns molecular simulation experiments, highlighting their potential in cancer therapy and suggesting the need for further in vitro and in vivo validation.