Mass distributions of the system 136Xe + 208Pb at laboratory energies around the Coulomb barrier:A candidate reaction for the production of neutron-rich nuclei at N = 126

Reaction products from the system 136Xe + 208Pb at 136Xe ions laboratory energies of 700, 870, and 1020 MeV were studied by two-body kinematics and by a catcher-foil activity analysis to explore the theoretically proposed suitability of such reaction as a means to produce neutron-rich nuclei in the neutron shell closure N = 126. Cross sections for products heavier than 208Pb were measured and were found sensibly larger than new theoretical predictions. Transfers of up to 16 nucleons from Xe to Pb were observed

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies

ABSTRACTBiologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration–time curve (AUC0–672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL