Good Manufacturing Practices (GMP) manufacturing of advanced therapy medicinal products: a novel tailored model for optimizing performance and estimating costs

Background aimsAdvanced therapy medicinal products (ATMP) have gained considerable attention in academia due to their therapeutic potential. Good Manufacturing Practice (GMP) principles ensure the quality and sterility of manufacturing these products. We developed a model for estimating the manufacturing costs of cell therapy products and optimizing the performance of academic GMP-facilities.MethodsThe “Clean-Room Technology Assessment Technique” (CTAT) was tested prospectively in the GMP facility of BCRT, Berlin, Germany, then retrospectively in the GMP facility of the University of California-Davis, California, USA. CTAT is a two-level model: level one identifies operational (core) processes and measures their fixed costs; level two identifies production (supporting) processes and measures their variable costs. The model comprises several tools to measure and optimize performance of these processes. Manufacturing costs were itemized using adjusted micro-costing system.ResultsCTAT identified GMP activities with strong correlation to the manufacturing process of cell-based products. Building best practice standards allowed for performance improvement and elimination of human errors. The model also demonstrated the unidirectional dependencies that may exist among the core GMP activities. When compared to traditional business models, the CTAT assessment resulted in a more accurate allocation of annual expenses. The estimated expenses were used to set a fee structure for both GMP facilities. A mathematical equation was also developed to provide the final product cost.ConclusionsCTAT can be a useful tool in estimating accurate costs for the ATMPs manufactured in an optimized GMP process. These estimates are useful when analyzing the cost-effectiveness of these novel interventions.     

Complete Mitochondrial DNA Sequences of the Threadfin Cichlid (Petrochromis trewavasae) and the Blunthead Cichlid (Tropheus moorii) and Patterns of Mitochondrial Genome Evolution in Cichlid Fishes

The cichlid fishes of the East African Great Lakes represent a model especially suited to study adaptive radiation and speciation. With several African cichlid genome projects being in progress, a promising set of closely related genomes is emerging, which is expected to serve as a valuable data base to solve questions on genotype-phenotype relations. The mitochondrial (mt) genomes presented here are the first results of the assembly and annotation process for two closely related but eco-morphologically highly distinct Lake Tanganyika cichlids, Petrochromis trewavasae and Tropheus moorii. The genomic sequences comprise 16,588 bp (P. trewavasae) and 16,590 bp (T. moorii), and exhibit the typical mitochondrial structure, with 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes, and a non-coding control region. Analyses confirmed that the two species are very closely related with an overall sequence similarity of 96%. We analyzed the newly generated sequences in the phylogenetic context of 21 published labroid fish mitochondrial genomes. Consistent with other vertebrates, the D-loop region was found to evolve faster than protein-coding genes, which in turn are followed by the rRNAs; the tRNAs vary greatly in the rate of sequence evolution, but on average evolve the slowest. Within the group of coding genes, ND6 evolves most rapidly. Codon usage is similar among examined cichlid tribes and labroid families; although a slight shift in usage patterns down the gene tree could be observed. Despite having a clearly different nucleotide composition, ND6 showed a similar codon usage. C-terminal ends of Cox1 exhibit variations, where the varying number of amino acids is related to the structure of the obtained phylogenetic tree. This variation may be of functional relevance for Cox1 synthesis.     

207-nm UV Light - A Promising Tool for Safe Low-Cost Reduction of Surgical Site Infections. I: In Vitro Studies

Background

0.5% to 10% of clean surgeries result in surgical-site infections, and attempts to reduce this rate have had limited success. Germicidal UV lamps, with a broad wavelength spectrum from 200 to 400 nm are an effective bactericidal option against drug-resistant and drug-sensitive bacteria, but represent a health hazard to patient and staff. By contrast, because of its limited penetration, ∼200 nm far-UVC light is predicted to be effective in killing bacteria, but without the human health hazards to skin and eyes associated with conventional germicidal UV exposure.

Aims

The aim of this work was to test the biophysically-based hypothesis that ∼200 nm UV light is significantly cytotoxic to bacteria, but minimally cytotoxic or mutagenic to human cells either isolated or within tissues.

Methods

A Kr-Br excimer lamp was used, which produces 207-nm UV light, with a filter to remove higher-wavelength components. Comparisons were made with results from a conventional broad spectrum 254-nm UV germicidal lamp. First, cell inactivation vs. UV fluence data were generated for methicillin-resistant S. aureus (MRSA) bacteria and also for normal human fibroblasts. Second, yields of the main UV-associated pre-mutagenic DNA lesions (cyclobutane pyrimidine dimers and 6-4 photoproducts) were measured, for both UV radiations incident on 3-D human skin tissue.

Results

We found that 207-nm UV light kills MRSA efficiently but, unlike conventional germicidal UV lamps, produces little cell killing in human cells. In a 3-D human skin model, 207-nm UV light produced almost no pre-mutagenic UV-associated DNA lesions, in contrast to significant yields induced by a conventional germicidal UV lamp.

Conclusions

As predicted based on biophysical considerations, 207-nm light kills bacteria efficiently but does not appear to be significantly cytotoxic or mutagenic to human cells. Used appropriately, 207-nm light may have the potential for safely and inexpensively reducing surgical-site infection rates, including those of drug-resistant origin.     

Forward Modeling of Fluctuating Dietary 13C Signals to Validate 13C Turnover Models of Milk and Milk Components from a Diet-Switch Experiment

Isotopic variation of food stuffs propagates through trophic systems. But, this variation is dampened in each trophic step, due to buffering effects of metabolic and storage pools. Thus, understanding of isotopic variation in trophic systems requires knowledge of isotopic turnover. In animals, turnover is usually quantified in diet-switch experiments in controlled conditions. Such experiments usually involve changes in diet chemical composition, which may affect turnover. Furthermore, it is uncertain if diet-switch based turnover models are applicable under conditions with randomly fluctuating dietary input signals. Here, we investigate if turnover information derived from diet-switch experiments with dairy cows can predict the isotopic composition of metabolic products (milk, milk components and feces) under natural fluctuations of dietary isotope and chemical composition. First, a diet-switch from a C₃-grass/maize diet to a pure C₃-grass diet was used to quantify carbon turnover in whole milk, lactose, casein, milk fat and feces. Data were analyzed with a compartmental mixed effects model, which allowed for multiple pools and intra-population variability, and included a delay between feed ingestion and first tracer appearance in outputs. The delay for milk components and whole milk was ∼12 h, and that of feces ∼20 h. The half-life (t_½) for carbon in the feces was 9 h, while lactose, casein and milk fat had a t_½ of 10, 18 and 19 h. The ¹³C kinetics of whole milk revealed two pools, a fast pool with a t_½ of 10 h (likely representing lactose), and a slower pool with a t_½ of 21 h (likely including casein and milk fat). The diet-switch based turnover information provided a precise prediction (RMSE ∼0.2 ‰) of the natural ¹³C fluctuations in outputs during a 30 days-long period when cows ingested a pure C3 grass with naturally fluctuating isotope composition.     

Organic acid profile of isovaleric acidemia: a comprehensive metabolomics approach

Isovaleric acidemia (IVA, MIM 248600) can be a severe and potentially life-threatening disease in affected neonates, but with a positive prognosis on treatment for some phenotypes. This study presents the first application of metabolomics to evaluate the metabolite profiles derived from urine samples of untreated and treated IVA patients as well as of obligate heterozygotes. All IVA patients carried the same homozygous c.367 G > A nucleotide change in exon 4 of the IVD gene but manifested phenotypic diversity. Concurrent class analysis (CONCA) was used to compare all the metabolites from the original complete data set obtained from the three case and two control groups used in this investigation. This application of CONCA has not been reported previously, and is used here to compare four different modes of scaling of all metabolites. The variables important in discrimination from the CONCA thus enabled the recognition of different metabolic patterns encapsulated within the data sets that would not have been revealed by using only one mode of scaling. Application of multivariate and univariate analyses disclosed 11 important metabolites that distinguished untreated IVA from controls. These included well-established diagnostic biomarkers of IVA, endogenous detoxification markers, and 3-hydroxycaproic acid, an indicator of ketosis, but not reported previously for this disease. Nine metabolites were identified that reflected the effect of treatment of IVA. They included detoxification products and indicators related to the high carbohydrate and low protein diet which formed the hallmark of the treatment. This investigation also provides the first comparative metabolite profile for heterozygotes of this inherited metabolic disorder. The detection of informative metabolites in even very low concentrations in all three experimental groups highlights the potential advantage of the holistic mode of analysis of inherited metabolic diseases in a metabolomics investigation.     

Molecular interactions of alcohols with zeolite BEA and MOR frameworks

Zeolites can adsorb small organic molecules such as alcohols from a fermentation broth. Also in the zeolite-catalyzed conversion of alcohols to biofuels, biochemicals, or gasoline, adsorption is the first step. Several studies have investigated the adsorption of alcohols in different zeolites experimentally, but computational investigations in this field have mostly been restricted to zeolite MFI. In this study, the adsorption of C1–C4 alcohols in BEA and MOR was investigated using density functional theory (DFT). Calculated adsorption geometries and the corresponding energies of the designed cluster models were comparable to periodic calculations, and the adsorption energies were in the same range as the corresponding computational and experimental values reported in the literature for zeolite MFI. Thus, BEA and MOR may be good adsorption materials for alcohols in the field of downstream processing and catalysis. Aside from the DFT calculations, adsorption isotherms were determined experimentally in this study from aqueous solutions. For BEA, the adsorption of significant amounts of alcohol from aqueous solution was observed experimentally. In contrast, MOR was loaded with only a very small amount of alcohol. Although differences were found between the affinities obtained from gas-phase DFT calculations and those observed experimentally in aqueous solution, the computational data presented here represent molecular level information on the geometries and energies of C1–C4 alcohols adsorbed in zeolites BEA and MOR. This knowledge should prove very useful in the design of zeolite materials intended for use in adsorption and catalytic processes, as it allows adsorption behavior to be predicted via judiciously designed computational models.     

Direct Correlation of the Organic Solar Cell Device Performance to the In‐Depth Distribution of Highly Ordered Polymer Domains in Polymer/Fullerene Films

This study correlates the device performance of organic solar cells and the electronic charge transport within polymer/fullerene films, directly to the optical order of the polymer. The optical order was measured by spectroscopic ellipsometry and evaluated by our previously derived model. We were able to determine the in‐depth distribution of higher and lower ordered poly(3‐hexylthiophene) (P3HT) domains within an [6,6]‐phenyl‐C₆₁‐butyric acid methyl ester (PCBM) matrix. The over the film thickness integrated volume fraction of highly ordered P3HT domains could be directly correlated to the corresponding solar cell device performance. We are able to describe various thermally annealing conditions between room‐temperature and 200 °C.