A multi-scale modeling framework for individualized, spatiotemporal prediction of drug effects and toxicological risk

International audienceIn this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy

Application of a genome-based predictive CHO model for increased mAb production and Glycosylation control

Monoclonal antibody therapeutics continue to grow in both number and market share with recent forecasts of global sales reaching ~$125MM by 2020. Most mAb products currently on the market are produced using cultured mammalian cells, typically Chinese Hamster Ovary (CHO) cells, which provide the necessary post-translational modifications to make the antibody efficacious. Many post-translational modifications such as the oligosaccharide profile are considered critical quality attributes (CQAs) that must be tightly controlled throughout the manufacturing process to ensure product safety and effectiveness. Therefore, the ability to predict how cell culture media components, including potential contaminants like trace metals, will affect product formation and glycosylation is important from both a process development and process control viewpoint. A detailed genome-based, predictive CHO model from the Insilico Cells™ library was adapted by the reconstruction software Insilico Discovery™ for a representative fed-batch process through a collaborative effort leveraging the computational and experimental expertise of two companies. The final, compartmentalized network model contained 1900 reactions (including transport reactions), 1300 compounds and contains stoichiometric descriptions of anabolic pathways for amino acids, lipids and carbohydrate species. The genome-scale model was constrained using several assumptions on the cell physiology and then used to compute time-resolved flux distributions by the software module Insilico Inspector™. The Insilico Designer™ module was then used to subsequently reduce the large model to a computationally manageable reduced model able to describe all flux distributions using 5 flux modes, of which 4 combined several metabolic functions and one is independently responsible for product synthesis. Using Insilico Designer™, the kinetic parameters of the reduced model were estimated by fitting the model-predicted metabolite concentrations to the experimentally determined values. The calibrated model was able to properly describe the time-dependent trajectories of biomass, product and most metabolites. Simulations using the reduced model were run and a media composition predicted to improve mAb production was identified and experimentally verified. Furthermore, experiments probing the effects of trace metals on product glycosylation were used to extend the model’s glycosylation predictability. The ability to identify both metabolic signatures, as well as media components, that correlate to specific glycan profiles will allow for fine-tuning of desired CQAs and enable more robust control strategies in upstream processes

Infections after kidney transplantation: A comparison of mTOR‐Is and CNIs as basic immunosuppressants. A systematic review and meta‐analysis

Background Side effects of the immunosuppressive therapy after solid organ transplantation are well known. Recently, significant benefits were shown for mTOR‐Is with respect to certain viral infections in comparison with CNIs. However, reported total incidences of infections under mTOR‐Is vs CNIs are usually not different. This raises the question to additional differences between these immunosuppressants regarding development and incidence of infections. Methods The current literature was searched for prospective randomized controlled trials in renal transplantation. There were 954 trials screened of which 19 could be included (9861 pts.). The 1‐year incidence of infections, patient and graft survival were assessed in meta‐analyses. Results Meta‐analysis on 1‐year incidence of infections showed a significant benefit of an mTOR‐I based therapy when combined with a CNI vs CNI‐based therapy alone (OR 0.76). There was no difference between mTOR‐I w/o CNI and CNI therapy (OR 0.97). For pneumonia, a significant disadvantage was seen only for mTOR‐I monotherapy compared to CNI's (OR 2.09). The incidence of CMV infections was significantly reduced under mTOR‐I therapy (combination with CNI: OR 0.30; mTOR w/o CNI: OR: 0.46). There was no significant difference between mTOR‐I and CNI therapy with respect to patient survival (mTOR‐I w/o CNI vs CNI: OR 1.22; mTOR‐I with CNI vs CNI: OR 0.86). Graft survival was negatively affected by mTOR‐I monotherapy (OR 1.52) but not when combined with a CNI (OR 0.97). Conclusion Following renal transplantation the incidence of infections is lower when mTOR‐Is are combined with a CNI compared to a standard CNI therapy. Pneumonia occurs more often under mTOR‐I w/o CNI

A systems biology approach to dynamic modeling and inter-subject variability of statin pharmacokinetics in human hepatocytes

A dynamic model for the biotransformation of atorvastatin has been developed using quantitative metabolite measurements in primary human hepatocytes. The model comprises kinetics for transport processes and metabolic enzymes as well as population liver expression data allowing us to assess the impact of inter-individual variability of concentrations of key proteins. Application of computational tools for parameter sensitivity analysis enabled us to considerably improve the validity of the model and to create a consistent framework for precise computer-aided simulations in toxicology

Patterns of HER-2/neu Amplification and Overexpression in Primary and Metastatic Breast Cancer

Background: Only 25% of patients with HER-2/neu-positive metastatic breast tumors respond favorably to trastuzamab (Herceptin) treatment. We hypothesized that a high failure rate of patients on trastuzamab could result if some of the metastases were HER-2 negative and these metastases ultimately determine the course of the disease. Methods: We used tissue microarrays (TMAs) containing four samples each from 196 lymph node-negative primary tumors, 196 lymph node-positive primary tumors, and three different lymph node metastases from each lymph node-positive tumor to estimate HER-2 gene amplification by fluorescence in situ hybridization (FISH) and Her-2 protein overexpression by immunohistochemistry (IHC). Results: FISH and IHC analyses gave the same result with respect to HER-2 status for 93.7% of the tissues contained in the TMAs. Tissue samples were, therefore, considered to be HER-2 positive if they were positive for either HER-2 DNA amplification or Her-2 protein expression and HER-2 negative if both FISH and IHC gave a negative result. The HER-2 status of lymph node-positive primary tumors was maintained in the majority of their metastases. For HER-2-positive primary tumors, 77% (95% confidence interval [CI] = 59% to 90%) had entirely HER-2-positive metastases, 6.5% (95% CI = 8% to 21%) had entirely HER-2-negative metastases, and 16.3% (95% CI = 5% to 34%) had a mixture of HER-2-positive and HER-2-negative metastases. For HER-2-negative primary tumors, 95% (95% CI = 88% to 98%) had metastases that were entirely negative for HER-2. Conclusions: Our data suggest that differences in HER-2 expression between primary tumors and their lymph node metastases cannot explain the high fraction of nonresponders to trastuzamab therap

Detecting Activation of Ribosomal Protein S6 Kinase by Complementary DNA and Tissue Microarray Analysis

Background: Studies by comparative genomic hybridization (CGH) have shown that chromosomal region 17q23 is amplified in up to 20% of primary breast cancers. We used microarray analyses to measure the expression levels of genes in this region and to explore their prognostic importance. Methods: A microarray that contained 4209 complementary DNA (cDNA) clones was used to identify genes that are overexpressed in the MCF-7 breast cancer cell line as compared with normal mammary tissue. Fluorescence in situ hybridization was used to analyze the copy number of one overexpressed gene, ribosomal protein S6 kinase (S6K), and to localize it to the 17q23 region. Northern and western blot analyses were used to measure S6K gene and protein expression, and an enzymatic assay was used to measure S6K activity. Tumor tissue microarray analysis was used to study amplification of S6K and the HER-2 oncogene, another 17q-linked gene, and the relationship between amplification and prognosis was analyzed. The Kaplan-Meier method was used for data analysis, and the log-rank test was used for statistical analysis. All P values are two-sided. Results: S6K was amplified and highly overexpressed in MCF-7 cells relative to normal mammary epithelium, and protein expression and enzyme activity were increased. S6K was amplified in 59 (8.8%) of 668 primary breast tumors, and a statistically significant association between amplification and poor prognosis (P = .0021) was observed. Amplification of both S6K and HER-2 implied particularly poor survival (P = .0001). Conclusions: The combination of CGH information with cDNA and tissue microarray analyses can be used to identify amplified and overexpressed genes and to evaluate the clinical implications of such genes and genomic rearrangements. S6K is likely to be one of the genes at 17q23 that is amplified during oncogenesis and may adversely affect the prognosis of patients with this amplificatio

Extending the coherence time of spin defects in hBN enables advanced qubit control and quantum sensing

Spin defects in hexagonal Boron Nitride (hBN) attract increasing interest for quantum technology since they represent optically-addressable qubits in a van der Waals material. In particular, negatively-charged boron vacancy centers (${V_B}^-$) in hBN have shown promise as sensors of temperature, pressure, and static magnetic fields. However, the short spin coherence time of this defect currently limits its scope for quantum technology. Here, we apply dynamical decoupling techniques to suppress magnetic noise and extend the spin coherence time by nearly two orders of magnitude, approaching the fundamental $T_1$ relaxation limit. Based on this improvement, we demonstrate advanced spin control and a set of quantum sensing protocols to detect electromagnetic signals in the MHz range with sub-Hz resolution. This work lays the foundation for nanoscale sensing using spin defects in an exfoliable material and opens a promising path to quantum sensors and quantum networks integrated into ultra-thin structures

Stimulated resonant inelastic X-ray scattering in a solid

When materials are exposed to X-ray pulses with sufficiently high intensity, various nonlinear effects can occur. The most fundamental one consists of stimulated electronic decays after resonant absorption of X-rays. Such stimulated decays enhance the number of emitted photons and the emission direction is confined to that of the stimulating incident photons which clone themselves in the process. Here we report the observation of stimulated resonant elastic (REXS) and inelastic (RIXS) X-ray scattering near the cobalt L3 edge in solid Co/Pd multilayer samples. We observe an enhancement of order 106 of the stimulated over the conventional spontaneous RIXS signal into the small acceptance angle of the RIXS spectrometer. We also find that in solids both stimulated REXS and RIXS spectra contain contributions from inelastic electron scattering processes, even for ultrashort 5 fs pulses. Our results reveal the potential and caveats of the development of stimulated RIXS in condensed matter