According to the results of the bioequivalence analysis carried out in this study, RMP formulations A, B, C and D were not within the acceptable range and only formulation E passed the bioequivalence criteria of 80-125%. In comparison, four-test INH formulations (A, B, C and D) were bioequivalent to the corresponding single-drug formulation, while product E failed in the bioequivalence criteria.

Screening for drug compounds that exhibit therapeutic properties in the treatment of various disease remain a challenge even after considerable advancements in biomedical research. Here we introduce an integrated platform that exploits gene expression compendia generated from drug-treated cell lines and primary tumor tissue to identify therapeutic candidates that can be used in the treatment of acute myeloid leukemia (AML). Our framework combines these data with patient survival information to identify potential candidates that presumably have significant impact on AML patient survival. We use a Drug Regulatory Score (DRS) to measure the similarity between drug-induced cell line and patient tumor gene expression profiles, and show that these computed scores are highly correlated with in vitro metrics of pharmacological activity. Furthermore, we conducted several in vivo validation experiments of our potential candidate drugs in AML mouse models to demonstrate the accuracy of our in silico predictions.