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Multicellular dynamics of zonal liver regeneration mapped in space and time.
No full textIn this issue, Ben-Moshe et al. (2022) use spatiotemporally resolved single-cell and spatial transcriptomic profiling to dissect the multicellular dynamics enabling zonal liver regeneration. They highlight how pan-zonal compensatory hepatocyte proliferation, transient reprogramming of peri-injury hepatocytes, and concerted zonated action of different liver cell types orchestrate the healing process
Discovery of MAP855, an efficacious and selective MEK1/2 inhibitor with ATP-competitive mode of action
No full textMutations in MEK1/2 have been described as a resistance mechanism to BRAF/MEK inhibitor treatment. We report the discovery of a novel ATP-competitive MEK inhibitor with efficacy in wildtype (WT) and mutant MEK models. Starting from a HTS hit, we obtained selective, cellularly active compounds that showed equipotent inhibition of WT MEK and a panel of MEK mutant cell lines. Using a structure-based approach, the optimisation addressed the liabilities by systematic analysis of molecular matched pairs (MMP) and ligand conformation. Addition of only 3 heavy atoms to early tool com-pound 6 removed Cyp3A4 liabilities and increased cellular potency by 100-fold, while reducing logP by 5 units. Profiling of MAP855, compound 30 in PK-PD and efficacy studies in BRAF-mutant models showed comparable efficacy to clinical MEK inhibitors. Compound 30 is a novel highly potent and selective MEK1 kinase inhibitor with equipotent inhibition of WT and mutant MEK whose drug like properties allow further investigation in the mutant MEK setting upon BRAF/MEK therapy
Machine Learning in Chemoinformatics and Medicinal Chemistry.
No full textIn chemoinformatics and medicinal chemistry, machine learning has evolved into an important approach. In recent years, increasing computational resources and new deep learning algorithms have put machine learning onto a new level, addressing previously unmet challenges in pharmaceutical research. In silico approaches for compound activity predictions, de novo design, and reaction modeling have been further advanced by new algorithmic developments and the emergence of big data in the field. Herein, novel applications of machine learning and deep learning in chemoinformatics and medicinal chemistry are reviewed. Opportunities and challenges for new methods and applications are discussed, placing emphasis on proper baseline comparisons, robust validation methodologies, and new applicability domains. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates
A composite endpoint for acceptability evaluation of oral drug formulations in the pediatric population
No full textIntroduction: A medicine’s acceptability is likely to have significant impact on pediatric compliance. EMA and FDA guidance on this topic ask for investigation of acceptability. Although palatability and deglutition are denoted as elements of acceptability, the impact of both on acceptability remains unclear as an unambiguous definition of acceptability is lacking. Actually, globally applied standards for acceptability definition, testing methodology and assessment criteria do not exist. A definition of acceptability establishing a composite endpoint that combines deglutition and palatability in different age groups is presented here.
Methods: This composite acceptability endpoint is based on validated assessment methods for deglutition and palatability in children of different age groups with different galenic placebo formulations, in line with criteria EMA proposed for assessing acceptability in children from newborn to 18 years. Data from two studies investigating mini-tablets, oblong tablets, orodispersible films and syrup were used to investigate the validity, expediency and applicability of the suggested composite acceptability assessment tool.
Results: The new composite endpoint is highly suitable and efficient to distinguish preferences of oral formulations: Mini-tablets and oblong tablets were significantly better accepted than syrup and orodispersible film.
Conclusion: Since the suggested acceptability criterion takes both deglutition and palatability into account as composite endpoint, it is highly sensitive to detect acceptability differences between oral formulations. It is a well-defined, valid approach, which particularly meets regulatory requirements in an appropriate and comprehensive manner and may in future serve as an easy, standardized method to assess and compare acceptability of pediatric formulations with active substances
Impact of diabetes status on immunogenicity of trivalent inactivated influenza vaccine in older adults
No full textIndividuals with type 2 diabetes mellitus experience high rates of influenza virus infection and complications. We compared the magnitude and duration of serologic response to trivalent influenza vaccine in adults aged 50–80 with and without type2 diabetes mellitus. Serologic response to influenza vaccination was similar in both groups: greater fold-increases in antibody titer occurred among participants with lower pre-vaccination antibody titers. Waning of antibody titers was not influenced by diabetes status
A Mucin-Deficient Ocular Surface Mimetic Platform for Interrogating Drug Effects on Biolubrication, Anti-Adhesion Properties, and Barrier Functionality
No full textDry eye disease (DED) affects more than 100 million people worldwide, causing significant patient discomfort and imposing a multi-billion-dollar burden on global health care systems. In DED patients, the natural biolubrication process that facilitates pain-free blinking goes awry due to an imbalance of lipid, aqueous medium, and mucin in the tear film, resulting in ocular surface damage. Identifying strategies to reduce adhesion and shear stresses between the ocular surface and the conjunctival cells lining the inside of the eyelid during blink cycles is a promising approach to improve the signs and symptoms of DED. However, current preclinical models for screening ocular lubricants rely on scarce, heterogeneous tissue samples or model substrates that do not capture the complex biochemical and biophysical cues present at the ocular surface. To recapitulate the hierarchical architecture and phenotype of the ocular interface for preclinical drug screening, we developed an in vitro mucin-deficient DED model platform that mimics the complexity of the ocular interface and investigated its utility in biolubrication, anti adhesion, and barrier protection studies using recombinant human lubricin, a promising investigational therapy for DED. The biomimetic platform recapitulated the pathological changes in biolubrication, adhesion, and barrier functionality often observed in mucin-deficient DED patients and demonstrated that recombinant human lubricin can reverse the damage induced by mucin loss in a dose- and conformation-dependent manner. Taken together, these results highlight the potential of the platform—and recombinant human lubricin—in advancing the standard of care for mucin deficient DED patients
High-content cellular screen image analysis benchmark study
No full textRecent development of novel methods based on deep neural networks has transformed how high-content microscopy cellular images are analyzed. Nonetheless, it is still a challenge to identify cellular phenotypic changes caused by chemical or genetic treatments and to elucidate the relationships among treatments in an unsupervised manner, due to the large data volume, high phenotypic complexity and the presence of a priori unknown phenotypes. Here we benchmarked five deep neural network methods and two feature engineering methods on a well-characterized public data set. In contrast to previous benchmarking efforts, the manual annotations were not provided to the methods, but rather used as evaluation criteria afterwards. The seven methods individually performed feature extraction or representation learning from cellular images, and were consistently evaluated for downstream phenotype prediction and clustering tasks. We identified the strengths of individual methods across evaluation metrics, and further examined the biological concepts of features automatically learned by deep neural networks
Adipocyte-specific deletion of the oxygen-sensor PHD2 sustains elevated energy expenditure at thermoneutrality
No full textEnhancing brown adipose tissue (BAT) function to combat metabolic disease is a promising therapeutic strategy. A major obstacle to this strategy is that a thermoneutral environment, relevant to most modern human living conditions, deactivates functional BAT. We showed that we can overcome the dormancy of BAT at thermoneutrality by inhibiting the main oxygen sensor HIF-prolyl hydroxylase, PHD2, specifically in adipocytes. Mice lacking adipocyte PHD2 (P2KOad) and housed at thermoneutrality maintained greater BAT mass, UCP1 protein expression and higher energy expenditure. PHD2-deficiency facilitated higher sensitivity to b3-adrenergic stimulation. The elevated energy expenditure of P2KOadmice was sustained after a high-fat-feeding challenge at thermoneutrality. Mouse brown adipocytes treated with a pan-PHD inhibitor (PHDi), exhibited higher Ucp1mRNA and protein levels, effects that were abolished by antagonising the canonical PHD2 substrate, Hypoxia-inducible factor (HIF)-2a. Induction of UCP1mRNA expression by PHDi, was also confirmed in human adipocytes isolated from obese individuals. Human serum proteomics analysis of 5457 participants in the deeply phenotyped Age, Gene and Environment Study revealed that serum PHD2 (aka EGLN1) associates with increased risk of metabolic disease. Our data suggest adipose–selective PHD2 inhibition as a novel therapeutic strategy for metabolic disease and identify serum PHD2 as a potential biomarker
Open channel for external industry technology providers to centrally upload technology offers to a Novartis web portal.
No full textIn order to channel technologies offered by external industry partners Novartis is now having a tool called "digitalbrain" that enables having channels. A "Channel" is a broader canal to contact Novartis in a structured/channeled way.
Channel will be published on: https://digitalbrain.novartis.com/
The channel content/info is attached to the PPT including also screenshots on how it will look like