Particle Property Characterization and Data Curation for Effective Powder Property Modeling in the Pharmaceutical Industry.

Computational modeling, machine learning, and statistical data analysis are increasingly utilized to mitigate chemistry, manufacturing, and control failures related to particle properties in solid dosage form manufacture. Advances in particle characterization techniques and computational approaches provide unprecedented opportunities to explore relationships between particle morphology and drug product manufacturability. Achieving this, however, has numerous challenges such as producing and appropriately curating robust particle size and shape data. Addressing these challenges requires a harmonized strategy from material sampling practices, characterization technique selection, and data curation to provide data sets which are informative on material properties. Herein, common sources of error in particle characterization and data compression are reviewed, and a proposal for providing robust particle morphology (size and shape) data to support modeling efforts, approaches for data curation, and the outlook for modeling particle properties are discussed.

Ni-Catalyzed C-H Functionalization in the Formation of a Complex Heterocycle: Synthesis of the Potent JAK2 Inhibitor BMS-911543.

BMS-911543 is a complex pyrrolopyridine investigated as a potential treatment for myeloproliferative disorders. The development of a short and efficient synthesis of this molecule is described. During the course of our studies, a Ni-mediated C-N bond formation was invented, which enabled the rapid construction of the highly substituted 2-aminopyridine core. The synthesis of this complex, nitrogen-rich heterocycle was accomplished in only eight steps starting from readily available materials.

Microbiome-based risk prediction in incident heart failure: a community challenge.

Heart failure (HF) is a major public health problem. Early identification of at-risk individuals could allow for interventions that reduce morbidity or mortality. The community-based FINRISK Microbiome DREAM challenge (synapse.org/finrisk) evaluated the use of machine learning approaches on shotgun metagenomics data obtained from fecal samples to predict incident HF risk over 15 years in a population cohort of 7231 Finnish adults (FINRISK 2002, n=559 incident HF cases). Challenge participants used synthetic data for model training and testing. Final models submitted by seven teams were evaluated in the real data. The two highest-scoring models were both based on Cox regression but used different feature selection approaches. We aggregated their predictions to create an ensemble model. Additionally, we refined the models after the DREAM challenge by eliminating phylum information. Models were also evaluated at intermediate timepoints and they predicted 10-year incident HF more accurately than models for 5- or 15-year incidence. We found that bacterial species, especially those linked to inflammation, are predictive of incident HF. This highlights the role of the gut microbiome as a potential driver of inflammation in HF pathophysiology. Our results provide insights into potential modeling strategies of microbiome data in prospective cohort studies. Overall, this study provides evidence that incorporating microbiome information into incident risk models can provide important biological insights into the pathogenesis of HF.

Improving CT accuracy in the diagnosis of COVID-19 in a hospital setting.

OBJECTIVE: This study aimed to improve the accuracy of CT for detection of COVID-19-associated pneumonia and to identify patient subgroups who might benefit most from CT imaging. METHODS: A total of 269 patients who underwent CT for suspected COVID-19 were included in this retrospective analysis. COVID-19 was confirmed by reverse-transcription-polymerase-chain-reaction. Basic demographics (age and sex) and initial vital parameters (O2-saturation, respiratory rate, and body temperature) were recorded. Generalized mixed models were used to calculate the accuracy of vital parameters for detection of COVID-19 and to evaluate the diagnostic accuracy of CT. A clinical score based on vital parameters, age, and sex was established to estimate the pretest probability of COVID-19 and used to define low, intermediate, and high risk groups. A p-value of <0.05 was considered statistically significant. RESULTS: The sole use of vital parameters for the prediction of COVID-19 was inferior to CT. After correction for confounders, such as age and sex, CT showed a sensitivity of 0.86, specificity of 0.78, and positive predictive value of 0.36. In the subgroup analysis based on pretest probability, positive predictive value and sensitivity increased to 0.53 and 0.89 in the high-risk group, while specificity was reduced to 0.68. In the low-risk group, sensitivity and positive predictive value decreased to 0.76 and 0.33 with a specificity of 0.83. The negative predictive value remained high (0.94 and 0.97) in both groups. CONCLUSIONS: The accuracy of CT for the detection of COVID-19 might be increased by selecting patients with a high-pretest probability of COVID-19.

Microfluidic preparative free-flow isoelectric focusing in a triangular channel: system development and characterization.

A preparative scale free-flow IEF device is developed and characterized with the aim of addressing needs of molecular biologists working with protein samples on the milligrams and milliliters scale. A triangular-shape separation channel facilitates the establishment of the pH gradient with a corresponding increase in separation efficiency and decrease in focusing time compared with that in a regular rectangular channel. Functionalized, ion-permeable poly(acrylamide) gel membranes are sandwiched between PDMS and glass layers to both isolate the electrode buffers from the central separation channel and also to selectively adjust the voltage efficiency across the separation channel to achieve high electric field separation. The 50 x 70 mm device is fabricated by soft lithography and has 24 outlets evenly spaced across a pH gradient between pH 4 and 10. This preparative free-flow IEF system is investigated and optimized for both aqueous and denaturing conditions with respect to the electric field and potential efficiency and with consideration of Joule-heating removal. Energy distribution across the functionalized polyacrylamide gel is investigated and controlled to adjust the potential efficiency between 15 and 80% across the triangular separation channel. The device is able to achieve constant electric fields high as 370+/-20 V/cm through the entire triangular channel given the separation voltage of 1800 V, enabling separation of five fluorescent pI markers as a demonstration example.

Cascaded free-flow isoelectric focusing for improved focusing speed and resolution.

This work presents the first implementation of cascaded stages for a microfabricated free-flow isoelectric focusing (FF-IEF) device. Both analytical and computational models for IEF suggest device performance will be improved by utilizing multiple stages to reduce device residence time. These models are shown to be applicable by using focusing of small IEF markers as a demonstration. We also show focusing of fluorescently tagged proteins under different channel geometries, with the most efficient focusing occurring in the cascaded design, as predicted by theory. An additional aim of this work is to demonstrate the compatibility of cascaded FF-IEF with common bioanalytical tools. As an example, outlet fractions from cascaded FF-IEF were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Processing of whole cell lysate followed by immunoblotting for cell signaling markers demonstrates the reduction of albumin from samples, as well as the enrichment of apoptotic markers.

Micro free-flow IEF enhanced by active cooling and functionalized gels.

Rapid free-flow IEF is achieved in a microfluidic device by separating the electrodes from the focusing region with porous buffer regions. Moving the electrodes outside enables the use of large electric fields without the detrimental effects of bubble formation in the active region. The anode and cathode porous buffer regions, which are formed by acrylamide functionalized with immobilized pH groups, allow ion transport while providing buffering capacity. Thermoelectric cooling mitigates the effects of Joule heating on sample focusing at high field strengths (approximately 500 V/cm). This localized cooling was observed to increase device performance. Rapid focusing of low-molecular-weight p/ markers and Protein G-mouse IgG complexes demonstrate the versatility of the technique. Simulations provide insight into and predict device performance based on a well-defined sample composition.