BACKGROUND AND OBJECTIVE: Considered as one of the most recurrent types of liver malignancy, Hepatocellular Carcinoma (HCC) needs to be assessed in a non-invasive way. The objective of the current study is to develop prediction models for Chronic Hepatitis C (CHC)-related HCC using machine learning techniques.

METHODS: A dataset, for 4423 CHC patients, was investigated to identify the significant parameters for predicting HCC presence. In this study, several machine learning techniques (Classification and regression tree, alternating decision tree, reduce pruning error tree and linear regression algorithm) were used to build HCC classification models for prediction of HCC presence.

RESULTS: Age, alpha-fetoprotein (AFP), alkaline phosphate (ALP), albumin, and total bilirubin attributes were statistically found to be associated with HCC presence. Several HCC classification models were constructed using several machine learning algorithms. The proposed HCC classification models provide adequate area under the receiver operating characteristic curve (AUROC) and high accuracy of HCC diagnosis. AUROC ranges between 95.5% and 99%, plus overall accuracy between 93.2% and 95.6%.

CONCLUSION: Models with simplistic factors have the power to predict the existence of HCC with outstanding performance.

The work aimed to improve both absorption and hepatic availability of sofosbuvir. Bilosomes and galactose-anchored bilosomes were investigated as potential nanocarriers for this purpose. Sofosbuvir is a class III drug with high solubility and low permeability. Thus, the drug entrapment into lipid-based galactose-anchored carriers would enhance drug permeability and improve its liver availability. The galactosylated taurocholate was designed and synthesized based on molecular docking studies, where both galactose and taurocholate molecules were connected in a way to avoid affecting crucial interactions and avoid steric clashes with their cellular uptake receptors. The suggested nano-carriers were prepared using a thin-film hydration technique with sodium taurocholate and span 60 as stabilizers. The prepared formulae were statistically optimized using a central composite design. The optimized plain and galactosylated formulae, composed of SAA to drug ratio of 1:1 w/w and sodium taurocholate to span ratio of 10:1 w/w, have a vesicular size, zeta potential and entrapment efficiency in the range of 140-150 nm, -50 mV and 85%, respectively. The optimized formulae were lyophilized to increase their physical stability and facilitate accurate drug dosing. In vivo results showed that Sofosbuvir availability in the liver was significantly increased after oral administration of the plain and the galactosylated bilosomal formulae when compared to the oral drug solution with relative targeting efficiencies (RTIs) of 1.51 and 3.66, respectively. These findings confirmed the hypothesis of considering the galactosylated bilosomes a promising nanocarrier to efficiently target sofosbuvir to the liver.