Atorvastatin added to interferon beta for relapsing multiple sclerosis: a randomized controlled trial

Statins have anti-inflammatory and immunomodulatory properties in addition to lipid-lowering effects. The present study evaluated the effect of atorvastatin added to interferon beta-1b in multiple sclerosis (MS) in a multicenter, randomized, parallel-group, rater-blinded study performed in eight Swiss hospitals. Seventy-seven patients with relapsing-remitting MS started interferon beta-1b every other day. After 3 months, they were randomized 1:1 to receive atorvastatin 40 mg/day or not in addition to interferon beta-1b until month 15. The primary endpoint was the proportion of patients with new lesions on T2-weighted images at month 15 compared to baseline at month three. At study end, the proportion of patients with new lesions on T2-weighted images was equal in both groups (odds ratio 1.14; 95 % CI 0.36-3.56; p = 0.81). All predefined secondary endpoints including number of new lesions and total lesion volume on T2-weighted images, total number of new Gd-enhancing lesions on T1-weighted images, total brain volume, volume of grey matter, volume of white matter, EDSS, MSFC, relapse rate, time to first relapse, number of relapse-free patients and neutralizing antibodies did not show any significant differences (all p values >0.1). Transient elevations of liver enzymes were more frequent with atorvastatin (p = 0.02). In conclusion, atorvastatin 40 mg/day in addition to interferon beta-1b did not have a beneficial effect on relapsing-remitting MS compared to interferon beta-1b monotherapy over a 12-month period.

Genetic variation in the PNPLA3 gene is associated with alcoholic liver injury in caucasians

A recent genome-wide study revealed an association between variation in the PNPLA3 gene and liver fat content. In addition, the PNPLA3 single-nucleotide polymorphism rs738409 (M148I) was reported to be associated with advanced alcoholic liver disease in alcohol-dependent individuals of Mestizo descent. We therefore evaluated the impact of rs738409 on the manifestation of alcoholic liver disease in two independent German cohorts. Genotype and allele frequencies of rs738409 (M148I) were determined in 1,043 alcoholic patients with or without alcoholic liver injury and in 376 at-risk drinkers from a population-based cohort. Relative to alcoholic patients without liver damage (n = 439), rs738409 genotype GG was strongly overrepresented in patients with alcoholic liver cirrhosis (n = 210; OR 2.79; P(genotype) = 1.2 × 10(-5) ; P(allelic) = 1.6 × 10(-6) ) and in alcoholic patients without cirrhosis but with elevated alanine aminotransferase levels (n = 219; OR 2.33; P(genotype) = 0.0085; P(allelic) = 0.0042). The latter, biochemically defined association was confirmed in an independent population-based cohort of at-risk drinkers with a median alcohol intake of 300 g/week (OR 4.75; P(genotype) = 0.040; P(allelic) = 0.022), and for aspartate aminotransferase (AST) levels. Frequencies of allele PNPLA3 rs738409(G) in individuals with steatosis and normal alanine aminotransferase (ALT) and AST levels were lower than in alcoholics without steatosis and normal ALT/AST (P(combined) = 0.03). The population attributable risk of cirrhosis in alcoholic carriers of allele PNPLA3 rs738409(G) was estimated at 26.6%. CONCLUSION: Genotype PNPLA3 rs738409(GG) is associated with alcoholic liver cirrhosis and elevated aminotransferase levels in alcoholic Caucasians.

Proposal on How To Conduct a Biopharmaceutical Process Failure Mode and Effect Analysis (FMEA) as a Risk Assessment Tool

With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.