7196 research outputs found
Sort by
Translational Modeling of Anticancer Efficacy to Predict Clinical Outcomes in a First-in-Human Phase 1 Study of MDM2 Inhibitor HDM201
No full textWe report on a retrospective model-based assessment of the predictive value of translating antitumor drug activity from in vivo experiments to a phase I clinical study in cancer patients treated with the MDM2 inhibitor, HDM201. Tumor growth inhibition models were developed describing the longitudinal tumor size data in human-derived osteosarcoma xenograft rats and in 96 solid tumor patients under different HDM201 treatment schedules. The model structure describing both datasets captures the delayed drug effect on tumor growth via a series of signal transduction compartments, including a resistance component. The models assumed a drug-killing effect on both sensitive and resistant cells and parameterized to estimate two tumor static plasma drug concentrations for sensitive (TSCS) and resistant cells (TSCR). No change of TSCS and TSCR with schedule was observed, implying that antitumor activity for HDM201 is independent of treatment schedule. Preclinical and clinical model-derived TSCR were comparable (48 ng/mL vs. 74 ng/mL) and demonstrating TSCR as a translatable metric for antitumor activity in clinic. Schedule independency was further substantiated from modeling of clinical serum growth differentiation factor-15 (GDF-15) as a downstream marker of p53 pathway activation. Equivalent cumulative induction of GDF-15 was achieved across schedules when normalized to an equivalent total dose. These findings allow for evaluation of optimal dosing schedules by maximizing the total dose per treatment cycle while mitigating safety risk with periods of drug holiday. This approach helped guide a phase I dose escalation study in the selection of an optimal dose and schedule for HDM201
Engineering an omega-Transaminase for the Efficient Production of a Chiral Sacubitril Precursor
No full textAn omega-transaminase was engineered for the efficient production of a chiral precursor to sacubitril, (2R,4S)-5-([1,1'-biphenyl]-4-yl)-4-amino-2-methylpentanoic acid, a key component in the blockbuster heart failure drug Entresto®. Starting from an enzyme with trace activity and preference for the undesired diastereoisomer, eleven rounds of enzyme evolution were performed. The resultant variant, CDX-043, showed high productivity giving 90% conversion at 75 g/L substrate concentration with 1% enzyme loading with respect to the substrate in 24 h and without the use of an organic co-solvent. The product diastereomeric purity towards the desired (2R,4S)-stereoisomer was > 99.9:0.1 d.r. This variant also exhibited high process robustness and could tolerate reaction temperatures up to 65 °C and isopropylamine concentrations of at least 2 M. A structural analysis of the enzyme variants gave insight into how the mutations affected activity and selectivity. This new enzyme variant allows for the efficient and cost-effective production of sacubitril at large scale
Learning to Extend Molecular Scaffolds with Structural Motifs
No full textRecent advancements in deep learning based modelling of molecules promise to accelerate in silico drug discovery. There is a plethora of generative models available, which build molecules either atom-by-atom and bond-by-bond or fragment-by fragment. Apart from property-driven generation, many drug discovery projects also require a fixed scaffold to be present in the generated molecule, and incorporating that constraint has been recently explored. In this work, we present a new graph based model that learns to extend a given partial graph by flexibly choosing between adding individual atoms and entire fragments. Our model does not assume access to a predefined vocabulary of scaffolds; instead, extending a scaffold is implemented by using it as the initial partial graph. This is only possible because our model does not depend on generation history, and has been trained to generate molecules using a variety of generation orders. We show that using a randomized generation order is necessary for good performance when extending scaffolds, and that results are further improved when increasing motif vocabulary size
Structure-based design of selective LONP1 inhibitors for probing in vitro biology
No full textLONP1 is an AAA+ protease that maintains mitochondrial homeostasis by removing damaged or misfolded proteins. Elevated activity and expression of LONP1 promotes cancer cell proliferation and resistance to apoptosis-inducing reagents. Despite the importance of LONP1 in human biology and disease, very few LONP1 inhibitors have been described in the literature. Herein, we report the development of selective boronic acid-based LONP1 inhibitors using structure based drug design as well as the first structures of human LONP1 bound to various inhibitors. Our efforts led to several nanomolar LONP1 inhibitors with little to no activity against the 20S proteasome that serve as tool compounds to investigate LONP1 biology
Cardiotoxic Potential of Hydroxychloroquine, Chloroquine and Azithromycin in adult Human Primary Cardiomyocytes.
No full textBackground
Clinical communications regarding the efficacy and cardiac safety of Hydroxychloroquine (HCQ), Chloroquine (CQ) alone or in combination with Azithromycin (AZ) in patients with Covid-19 provided conflicting evidence. Although these drugs in general have a good safety record, however, if this is true for patients with COVID-19 is unknown.
.
Methods
We studied both pro-arrhythmic potential as well as inotropic effect of HCQ, CQ and AZ in paced adult human primary cardiomyocytes in vitro, assessing drug concentrations, the effects of electrolyte changes and elevated temperature that are prevalent risk factors among hospitalized COVID-19 patients.
Results
Concentration-dependent pro-arrhythmia and negative inotropic potential risks of HCQ started within the therapeutic free exposure range (0.1 - 0.3 µM) and were found to be less pronounced compared to CQ. AZ co-administration with HCQ not only altered the pro-arrhythmia profile of HCQ, but also attenuated the negative inotropic effect of HCQ due to mechanisms that need further evaluation. Hypokalemia caused significant indices of pro-arrhythmia at the lower limit of HCQ therapeutic exposure tested, but exposure to high level of Mg2+ significantly reduced all markers of pro-arrhythmia associated with HCQ treatment. When cardiomyocytes were subjected to elevated temperature pro-arrhythmia was observed that was not increased by therapeutic exposure levels of HCQ.
Conclusions
Our data indicate that high exposures levels of HCQ should be avoided. The clinical environment (e.g., elevated temperature, electrolyte changes) associated with severe COVID-19 modulates cardiotoxicity, reinforces the clinical advice to maintain high normal levels of K+ and Mg2+. These results emphasizes the need to assess drugs under the disease-specific conditions
Evaluation of protein kinase D auto-phosphorylation as biomarker for NLRP3 inflammasome activation.
No full textThe NLRP3 inflammasome is a critical component of sterile inflammation, which is involved in many diseases. However, there is currently no known proximal biomarker for measuring NLRP3 activation in pathological conditions. Protein kinase D (PKD) has emerged as an important NLRP3 kinase that catalyzes the release of a phosphorylated NLRP3 species that is competent for inflammasome complex assembly.To explore the potential for PKD activation to serve as a selective biomarker of the NLRP3 pathway, we tested various stimulatory conditions in THP-1 and U937 cell lines, probing the inflammasome space beyond NLRP3. We analyzed the correlation between PKD activation (monitored by its auto-phosphorylation) and functional inflammasome readouts.PKD activation/auto-phosphorylation always preceded cleavage of caspase-1 and gasdermin D, and treatment with the PKD inhibitor CRT0066101 could block NLRP3 inflammasome assembly and interleukin-1β production. Conversely, blocking NLRP3 either genetically or using the MCC950 inhibitor prevented PKD auto-phosphorylation, indicating a bidirectional functional crosstalk between NLRP3 and PKD. Further assessments of the pyrin and NLRC4 pathways, however, revealed that PKD auto-phosphorylation can be triggered by a broad range of stimuli unrelated to NLRP3 inflammasome assembly.Although PKD and NLRP3 become functionally interconnected during NLRP3 activation, the promiscuous reactivity of PKD challenges its potential use for tracing the NLRP3 inflammasome pathway
Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study.
No full textWith the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies
Immunogenicity Risk Assessment for Multi-specific Therapeutics.
No full textThe objective of this manuscript is to provide the reader with a hypothetical case study to present an immunogenicity risk assessment for a multi-specific therapeutic as part of Investigational New Drug (IND) application. In order to provide context for the bioanalytical strategies used to support the multi-specific therapeutic presented herein, the introduction focuses on known immunogenicity risk factors. The subsequent hypothetical case study applies these principles to a specific example HC-12, based loosely on anti-TNFα and anti-IL-17A bispecific molecules previously in development, structured as an example immunogenicity risk assessment for submission to health authorities. The risk of higher incidence and safety impact of anti-drug antibodies (ADA) due to large protein complexes is explored in the context of multi-specificity and multi-valency of the therapeutic in combination with the oligomeric forms of the targets
Evaluation of the humoral response to viral-based Gene Therapy Modalities using Total Antibody assays
No full textThe number of viral vector-based gene therapies (GTx) continues to grow with 2 products (Zolgensma® and Luxturna®) approved in the US as of March 2021. To date, one of the most commonly used vectors are adeno-associated virus (AAV) based. The pre-existing humoral immunity against AAV (anti-AAV antibodies) has been well described and is expected as a consequence of endogenous AAV infections. High prevalence of anti-AAV antibodies may present a barrier to successful AAV transduction and hence negatively impact clinical efficacy and may also result in Adverse Events (AEs) as a consequence of the formation of large immune complexes. Patients may be screened for the presence of anti-AAV antibodies, including neutralizing (NAb) and total binding antibodies (TAb) prior to treatment with the GTx. Recommendations for the development and validation of anti-AAV NAb detection methods has been presented elsewhere. This manuscript covers considerations related to anti-AAV TAb detecting protocols, including the benefits of the use of TAb methods, selection of assay controls and reagents, and parameters critical to monitoring assay performance. This manuscript was authored by a group of scientists involved in GTx development representing 11 companies. It is our intent to provide recommendations and guidance to industrial sponsors and academic laboratories working on viral vector based GTx modalities with the goal of achieving a more consistent approach to anti-AAV TAb assessment
Scaling Down Large-Scale Thawing of Monoclonal Antibody Solutions: 3D Temperature Profiles, Changes in Concentration, and Density Gradients.
No full textScale-down devices (SDD) are designed to simulate large-scale thawing of protein drug substance, but require only a fraction of the material. To evaluate the performance of a new SDD that aims to predict thawing in large-scale 2 L bottles, we characterised 3D temperature profiles and changes in concentration and density in comparison to 125 mL and 2 L bottles. Differences in diffusion between a monoclonal antibody (mAb) and histidine buffer after thawing were examined.Temperature profiles at six distinct positions were recorded with type T thermocouples. Size-exclusion chromatography allowed quantification of mAb and histidine. Polysorbate 80 was quantified using a fluorescent dye assay. In addition, the solution's density at different locations in bottles and the SDD was identified.The temperature profiles in the SDD and the large-scale 2 L bottle during thawing were similar. Significant concentration gradients were detected in the 2 L bottle leading to marked density gradients. The SDD slightly overestimated the dilution in the top region and the maximum concentrations at the bottom. Fast diffusion resulted in rapid equilibration of histidine.The innovative SDD allows a realistic characterisation and helps to understand thawing processes of mAb solutions in large-scale 2 L bottles. Only a fraction of material is needed to gain insights into the thawing behaviour that is associated with several possible detrimental limitations