Bristol-Myers Squibb (Germany)

Automated microbial detection systems are becoming increasingly essential in pharmaceutical manufacturing to enhance efficiency, accuracy, and compliance with Good Manufacturing Practice (GMP) standards. The APAS Independence System, developed by Clever Culture Systems, was evaluated at Bristol Myers Squibb (BMS) to assess its suitability for environmental monitoring applications. The APAS system is capable of automated plate counting of both 55 mm and 90 mm plates, following an offline incubation at routine EM parameters. The study compared APAS automated colony counts to traditional manual counts for compendial strains and environmental monitoring samples across multiple weeks of EM sampling. Performance metrics for both plate sizes were analyzed, such as accuracy, precision, false negative and false positive rates, and robustness. The APAS system demonstrated high accuracy (≥70%) and reliability for most tested organisms. Therefore, the system is being implemented for GMP use, with a validation approach that combines vendor validation of the Artificial Intelligence with site specific instrument qualification. This evaluation provides insight into the capabilities and limitations of automated colony detection, informing future digitalization strategies in microbiological quality control.

Objectives:To assess and evaluate various jaw pathologies their nature, location, size, extent and effect on surrounding structures by CT.Methods:In total, 29 subjects of jaw pathologies and traumatic injuries of maxillofacial complex were subjected to CT.Results:showed characteristic and distinct features for various pathologies. Fisher exact test was applied to compare consistency of features like matrix, margins, density, and number.Conclusion:CT plays a crucial role in depicting the exact extensions of pathologies and its relation to adjacent anatomical structures in all possible directions.

The discovery of KRAS G12C inactive state inhibitors represented a significant advancement in the field of precision oncology. While inactive state inhibition shows promise in patients, Switch II (SWII)-binding inhibitors targeting both inactive and active states remain an underdeveloped therapeutic modality. Here, we describe the discovery of such KRAS G12C dual inhibitors that bind the SWII allosteric site using a chemically differentiated warhead to covalently modify boththe KRAS G12C inactive and active states. Co-crystal structures reveal that these inhibitors perturb a key water-mediated hydrogen bonding network and trigger allosteric remodeling of the GTP-bound protein surface and SWI that prevents binding to downstream effectors. Consistent with simultaneous targeting of the active and inactive states, dual inhibitors provide rapid covalent target engagement and suppression of MAPK signaling. However, they demonstrate similar efficacy in cellular and in vivo modelswhen compared to inactive state-selective ones despite faster target inactivation. Furthermore, both inhibitor classes show similar cellular efficacy in the presence of growth factors that drive KRAS, wt NRAS, and wt HRAS to the active state. These data provide the first detailed account of targeting both the active and inactive states of KRAS G12C and highlight the absence of a mechanistic advantage in contexts dependent on prolonged target inhibition.

Catalytic reactions involving multiple cycles are common in many key organic transformations. We report a detailed mechanistic analysis of one such network of "nested" cycles, the Ni-catalyzed cross-coupling of alkyl sulfonyl hydrazides with (hetero)aryl halides, employing a battery of techniques, including Temperature Scanning Reaction (TSR) calorimetry coupled with Reaction Progress Kinetic Analysis (RPKA), quantitative NMR time-course analysis, kinetic modeling, linear free energy analysis, and density functional theory (DFT) quantum chemical calculations. TSR/RPKA studies yield the simultaneous determination of the thermodynamic enthalpy of the reaction, the kinetic rate law, and the activation parameters (ΔH‡, ΔS‡, ΔG‡), for the rate-determining step. Expanding the analysis to the coupling of an array of electron-poor and electron-rich sulfonyl hydrazides (each readily accessible on the decagram scale) with a range of (hetero)aryl halide coupling partners introduces the concept of "kinetics matching," and demonstrates that optimal yields may be obtained when the reactivities of the separate cycles are tuned to work in unison. These requirements for reaction networks involving nested catalytic cycles are showcased by several real-world examples. Our work highlights the predictive power of this kinetics-focused mechanistic approach, which may be extended to other nested catalytic networks to select appropriate catalyst and substrate combinations for optimal outcomes.

The application of chemical transformations to substrates that surpass the scope of the original method for either steric or electronic reasons can often lead to failure. The chances of succeeding in reoptimizing that method can vary and are increased when the existing method is well-defined in terms of critical parameters and mechanism. As part of efforts to develop a sustainable and scalable synthesis of a functionalized indole intermediate en route to the TLR7/8 antagonist afimetoran, reoptimization of a previously developed (phenoxyimine)nickel-catalyzed C(sp2)–C(sp3) Suzuki–Miyaura coupling led to conditions which presented significant advantages over the alternatives in terms of purity and yield. When combined with a nickel-catalyzed borylation, a streamlined two-step telescope was demonstrated which shows the potential for successful and rapid extension of existing methodologies to challenging substrates when starting reoptimization from a mechanistically well-defined starting point.

Accurately measuring compound binding affinities is key to driving the pharmaceutical development process. Rigorous physics-based in silico approaches, particularly alchemical free energy methods, have become a gold standard tool for estimating compound affinity changes. Here we present the results of a large-scale pre-competitive collaborative assessment of relative binding free energy (RBFE) calculations generated by 15 pharmaceutical companies. We evaluate an open-source and MIT licensed RBFE Protocol from the Open Free Energy (OpenFE) ecosystem across both public and blinded private datasets, encompassing over 1,700 ligands in total. For the public dataset, the weighted RMSE across the 58 systems was 1.73 [1.53, 1.96] kcal/mol, with 10 of the systems reaching sub-kcal/mol accuracy. For the private dataset, the weighted RMSE across the 37 systems was 2.44 [1.94, 3.06] kcal/mol, with only 2 of the systems reaching sub-kcal/mol accuracy, reflecting the increased complexity of real-world drug discovery. The protocols performance was system-dependent, with no single dominant error source, indicating that accuracy is primarily influenced by input quality and transformation type. Overall, these benchmark results are encouraging and indicate that OpenFE is ready for large-scale industrial applications, with an "out-of-the-box" accuracy that approaches that of commercial solutions. While comparison against published FEP+ results, which were obtained after manual parameter optimization, shows comparable ranking statistics, a gap remains in error statistics, for which we outline possible paths toward improvement. The protocol meets key criteria required for production use in an industrial setting: it shows robust performance, generates reproducible results, and achieves both sufficient throughput and rapid convergence.