Stability analysis using mixed models: A critique of tolerance interval methods and a probabilistic solution.

Recently, tolerance interval approaches to the calculation of a shelf life of a drug product have been proposed in the literature. These address the belief that shelf life should be related to control of a certain proportion of batches being out of specification. We question the appropriateness of the tolerance interval approach.

Residue-Specific Impact of EDTA and Methionine on Protein Oxidation in Biotherapeutics Formulations Using an Integrated Biotherapeutics Drug Product Development Workflow.

The rational design and selection of formulation composition to meet molecule-specific and product-specific needs are critical for biotherapeutics development to ensure physical and chemical stability. This work, based on three antibody-based (mAb) proteins (mAbA, mAbB, and mAbC), evaluates residue-specific impact of EDTA and methionine on protein oxidation, using an integrated biotherapeutics drug product development workflow. This workflow includes statistical experimental design, high-throughput experimental automation and execution, structure-based in silico modeling, inferential statistical analysis, and enhanced interactive data visualization of large datasets.

The current state of Bayesian methods in nonclinical pharmaceutical statistics: Survey results and recommendations from the DIA/ASA-BIOP Nonclinical Bayesian Working Group.

The use of Bayesian methods to support pharmaceutical product development has grown in recent years. In clinical statistics, the drive to provide faster access for patients to medical treatments has led to a heightened focus by industry and regulatory authorities on innovative clinical trial designs, including those that apply Bayesian methods. In nonclinical statistics, Bayesian applications have also made advances.

Reduced scale model qualification of 5-L and 250-ml bioreactors using multivariant visualization and Bayesian inferential methods.

A novel method for the qualification of reduced scale models (RSMs) was illustrated using data from both a 250-ml advanced microscale bioreactor (ambr) and a 5-L bioreactor RSM for a 2,000-L manufacturing scale process using a CHO cell line to produce a recombinant monoclonal antibody. The example study showed how the method was used to identify process performance attributes and product quality attributes that capture important aspects of the RSM qualification process. The method uses two novel statistical approaches: multivariate dimension reduction and data visualization techniques, via partial least squares discriminant analysis (PLS-DA), and Bayesian multivariate linear modeling for inferential analysis.

The Use of Bayesian Hierarchical Logistic Regression in the Development of a Modular Viral Inactivation Claim.

Low pH inactivation of enveloped viruses has historically been shown to be an effective viral inactivation step in biopharmaceutical manufacturing. To date, most statistical analyses supporting modular low pH viral inactivation claims have used descriptive statistical analyses, which in many cases do not allow for probabilistic characterization of future experimental log reduction values (LRVs). Using Bayesian hierarchical logistic regression modeling, probability statements regarding the likelihood of successful low pH viral inactivation based on only certain process parameter settings can be derived.

Connecting Our Gut Feeling and How Our Gut Feels: The Role of Well-being Attributes in Irritable Bowel Syndrome.

Background/aims: There is a close relationship between the mind and gut in the pathogenesis of functional bowel disorders. Common psychological disturbances such as depression and anxiety are not uncommon in those with irritable bowel syndrome (IBS). There is little research investigating the role of positive psychology and gastrointestinal (GI) conditions.