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Current practices for QSP model assessment: an IQ consortium survey.
No full textQuantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions
Use of the bacterial reverse mutation assay to predict carcinogenicity of N-nitrosamines.
No full textUnder ICH M7, impurities are assessed using the bacterial reverse mutation assay (i.e., Ames test) when predicted positive using in silico methodologies followed by expert review. N-Nitrosamines (NAs) have been of recent concern as impurities in pharmaceuticals, mainly because of their potential to be highly potent mutagenic carcinogens in rodent bioassays. The purpose of this analysis was to determine the sensitivity of the Ames assay to predict the carcinogenic outcome with curated proprietary Vitic (n = 131) and Leadscope (n = 70) databases. NAs were selected if they had corresponding rodent carcinogenicity assays. Overall, the sensitivity/specificity of the Ames assay was 93-97% and 55-86%, respectively. The sensitivity of the Ames assay was not significantly impacted by plate incorporation (84-89%) versus preincubation (82-89%). Sensitivity was not significantly different between use of rat and hamster liver induced S9 (80-93% versus 77-96%). The sensitivity of the Ames is high when using DMSO as a solvent (87-88%). Based on the analysis of these databases, the Ames assay conducted under OECD 471 guidelines is highly sensitive for detecting the carcinogenic hazards of NAs
Large-scale functional epigenomic screens reveal cancer lineage-specific regulation of YAP responsive elements
No full textYAP and TAZ are potent transcriptional co-factors engaging TEAD proteins downstream of Hippo signaling. Malignant pleural mesothelioma (MPM) and uveal melanoma (UM) are distinct cancer lineages bearing different genetic aberrations that ultimately lead to YAP activation. Here we use MPM and UM as prototypical cancers displaying, respectively, Hippo-dependent and -independent YAP activation to demonstrate that, while YAP is essential in both diseases, its interaction with TEAD is dispensable in UM, potentially limiting the application of TEAD inhibitors. Large scale functional epigenomic screens of YAP regulatory elements in MPM and UM reveal: 1) lineage-specific enhancers controlling broad oncogene dependencies (e.g., MYC) in both diseases, 2) rewiring of MAPK transcriptional regulatory networks in MPM, translating into synergistic efficacy of TEAD and MAPK inhibitors and 3) enrichment of melanocytic master regulators at functional YREs in UM. Our work prompts the design of tailored therapeutic strategies to inhibit YAP signaling in specific cancers
Predicting Bile and Lipid Interaction for Drug Substances.
No full textPredicting biopharmaceutical characteristics and food effects for drug substances may substantially leverage rational formulation outcomes. We established a bile and lipid interaction prediction model for new drug substances and further explored the model for the prediction of bile-related food effects. One hundred and forty-one drugs were categorized as bile and/or lipid interacting and noninteracting drugs using 1H nuclear magnetic resonance (NMR) spectroscopy. Quantitative structure-property relationship modeling with molecular descriptors was applied to predict a drug's interaction with bile and/or lipids. Bile interaction, for example, was indicated by two descriptors characterizing polarity and lipophilicity with a high balanced accuracy of 0.8. Furthermore, the predicted bile interaction correlated with a positive food effect. Reliable prediction of drug substance interaction with lipids required four molecular descriptors with a balanced accuracy of 0.7. These described a drug's shape, lipophilicity, aromaticity, and hydrogen bond acceptor capability. In conclusion, reliable models might be found through drug libraries characterized for bile interaction by NMR. Furthermore, there is potential for predicting bile-related positive food effects
Ring replacement recommender: Ring modifications that lead consistently to improved biological activity
No full textAnalysis of structure-activity data from a large corpus of medicinal chemistry literature identified a set of ring replacements that lead consistently to improved biological activity. A database of these replacements for 245 common heterocyclic rings is provided. Based on the analysis of the whole data set a 80 diverse substituted rings are suggested to be used in an early stage of hit optimization and design of focused libraries with the goal to explore structure-activity relationships and quickly improve the biological activity of the explored series. An easy to use Ring Replacement Recommender web tool allowing medicinal chemists to interactively explore the recommended ring substitution is available at https://bit.ly/ringreplacement
Opinion on Not Terminating Control Animals in the Recovery Phase of Non-rodent Toxicology Studies
No full textNonclinical toxicology studies required to support human clinical trials of new drug candidates are generally conducted in a rodent and a non-rodent species. These studies typically contain a vehicle control group and low, intermediate, and high dose test article treatment groups. In addition, a dosing-free recovery phase is sometimes included in toxicity studies to demonstrate reversibility of toxicities observed during the dosing phase and may include additional animals in the vehicle control and one or more dose groups. Typically, reversibility is determined by comparing the test article-related changes in the dosing phase animals to concurrent recovery phase animals at the same dose level. Therefore, for interpretation of reversibility, it is not always essential to terminate the recovery vehicle control animals. In the absence of recovery vehicle control tissues, the pathologist’s experience, historical control database, digital or glass slide repositories, or literature can be used to interpret the findings in the context of background pathology of the species/strain/age. Therefore, in most studies, the default approach could be not to terminate recovery vehicle control animals. This manuscript provides opinions on scenarios that may or may not necessitate termination of recovery phase vehicle control animals in nonclinical toxicology studies involving dogs and nonhuman primates
Analytically-speaking-podcast podcast "sometimes negative results turn out to be the most interesting ones": Adrian Clarke interviewed by Dwight Stoll.
No full textAnalytically Speaking podcast from LCGC, episode 6 ""sometimes negative results turn out to be the most interesting ones" , with Adrian Clarke interviewed by Dwight Stoll. addresses important issues in separation science. Topics include, how strated in science, my current role, responsibilities and scientific interests. new analytical techniques, methods, and approaches; the latest trends; advances in instrument and
software technology; recent papers in the scientific literature and their applicability; challenges and solutions for pharmaceutical analysis
People of TM: Video Gregori Gerebtzoff
No full textThe video will be used for an external social media engagement campaign on platforms like linked-in, facebook etc. featruing stories of people in TM. No IP related content
Comparing algorithms for characterizing treatment effect heterogeneity in randomized trials.
No full textThe identification and estimation of heterogeneous treatment effects in biomedical clinical trials are challenging, because trials are typically planned to assess the treatment effect in the overall trial population. Nevertheless, the identification of how the treatment effect may vary across subgroups is of major importance for drug development. In this work, we review some existing simulation work and perform a simulation study to evaluate recent methods for identifying and estimating the heterogeneous treatments effects using various metrics and scenarios relevant for drug development. Our focus is not only on a comparison of the methods in general, but on how well these methods perform in simulation scenarios that reflect real clinical trials. We provide the R package benchtm that can be used to simulate synthetic biomarker distributions based on real clinical trial data and to create interpretable scenarios to benchmark methods for identification and estimation of treatment effect heterogeneity
Cover art to "25 years of small molecule optimization at Novartis: A retrospective analysis of chemical series evolution"
No full textIn the internal Novartis compound databases, a set of ~3000 chemical series has been retrospectively reconstructed. Using the registration dates of the compounds, the evolution over time of structural properties, ADMET and target activities during optimization of the compounds has been analyzed, which revealed multiple trends. Furthermore, general properties of the chemical series and their inter-relations are investigated