Characteristics of hepatitis C virus resistance in an international cohort after a decade of direct-acting antivirals

Background & Aims: Direct-acting antiviral (DAA) regimens provide a cure in >95% of patients with chronic HCV infection. However, in some patients in whom therapy fails, resistance-associated substitutions (RASs) can develop, limiting retreatment options and risking onward resistant virus transmission. In this study, we evaluated RAS prevalence and distribution, including novel NS5A RASs and clinical factors associated with RAS selection, among patients who experienced DAA treatment failure. Methods: SHARED is an international consortium of clinicians and scientists studying HCV drug resistance. HCV sequence linked metadata from 3,355 patients were collected from 22 countries. NS3, NS5A, and NS5B RASs in virologic failures, including novel NS5A substitutions, were examined. Associations of clinical and demographic characteristics with RAS selection were investigated. Results: The frequency of RASs increased from its natural prevalence following DAA exposure: 37% to 60% in NS3, 29% to 80% in NS5A, 15% to 22% in NS5B for sofosbuvir, and 24% to 37% in NS5B for dasabuvir. Among 730 virologic failures, most were treated with first-generation DAAs, 94% had drug resistance in ≥1 DAA class: 31% single-class resistance, 42% dual-class resistance (predominantly against protease and NS5A inhibitors), and 21% triple-class resistance. Distinct patterns containing ≥2 highly resistant RASs were common. New potential NS5A RASs and adaptive changes were identified in genotypes 1a, 3, and 4. Following DAA failure, RAS selection was more frequent in older people with cirrhosis and those infected with genotypes 1b and 4. Conclusions: Drug resistance in HCV is frequent after DAA treatment failure. Previously unrecognized substitutions continue to emerge and remain uncharacterized. Lay summary: Although direct-acting antiviral medications effectively cure hepatitis C in most patients, sometimes treatment selects for resistant viruses, causing antiviral drugs to be either ineffective or only partially effective. Multidrug resistance is common in patients for whom DAA treatment fails. Older patients and patients with advanced liver diseases are more likely to select drug-resistant viruses. Collective efforts from international communities and governments are needed to develop an optimal approach to managing drug resistance and preventing the transmission of resistant viruses

Evaluation of matrix tablets based on Eudragit®E100/Carbopol®971P combinations for controlled release and improved compaction properties of water Soluble Model Drug Paracetamol

The purpose of this work was to investigate the influence of Eudragit®E100 polymer in modifying the release rates and compaction properties of water soluble model drug paracetamol from Carbopol®971P NF polymer matrix tablets prepared by direct compression. The effects of the ratio of the two polymers, the total polymeric content, and the tablets mechanical strength on paracetamol release rates were investigated. Dissolution studies were conducted using USP XX Π rotating paddle apparatus at 50 rpm and 37°C at three different stages (pH 1.2, 4.8, and 6.8). Results showed that the polymers combination improved significantly the compaction properties of paracetamol tablets as evident by the higher crushing strengths (8.3 ± 0.4 Kp) compared to polymer-free tablets (3.4 ± 0.2 Kp) at intermediate compression pressure of 490 MPa. When combined with Carbopol®971P NF, Eudragit®E100 was found to be capable of extending paracetamol release for more than 12 h compared to 1 h for polymers-free tablets. The combined polymers were able to control paracetamol release in a pH independent pattern. The f2 (similarity factor) analysis showed that the ratio between the polymers and the total polymer concentration exhibited significant impact on drug release rates. In conclusion, Eudragit®E100 when combined with Carbopol®971P NF was capable of improving the compaction and sustained release properties of paracetamol. Korsmeyer–Peppas model was found to be the most suitable for fitting drug release data. The polymer combinations can potentially be used to control the release rates of highly water soluble drugs