scholarly journals Computational Approaches for Supporting Combination Therapy in the Post-Aducanumab Era in Alzheimer’s Disease

2021 ◽  
pp. 1-12
Author(s):  
Hugo Geerts ◽  
Piet van der Graaf
Keyword(s):  
Combination Therapy ◽  
Checkpoint Inhibitors ◽  
Surrogate Marker ◽  
Data Driven ◽  
Therapeutic Modalities ◽  
Multi Scale ◽  
Large Databases ◽  
In Silico Modeling ◽  
Amyloid Load ◽  
Accelerated Approval

With the approval of aducanumab on the “Accelerated Approval Pathway” and the recognition of amyloid load as a surrogate marker, new successful therapeutic approaches will be driven by combination therapy as was the case in oncology after the launch of immune checkpoint inhibitors. However, the sheer number of therapeutic combinations substantially complicates the search for optimal combinations. Data-driven approaches based on large databases or electronic health records can identify optimal combinations and often using artificial intelligence or machine learning to crunch through many possible combinations but are limited to the pharmacology of existing marketed drugs and are highly dependent upon the quality of the training sets. Knowledge-driven in silico modeling approaches use multi-scale biophysically realistic models of neuroanatomy, physiology, and pathology and can be personalized with individual patient comedications, disease state, and genotypes to create ‘virtual twin patients’. Such models simulate effects on action potential dynamics of anatomically informed neuronal circuits driving functional clinical readouts. Informed by data-driven approaches this knowledge-driven modeling could systematically and quantitatively simulate all possible target combinations for a maximal synergistic effect on a clinically relevant functional outcomer. This approach seamlessly integrates pharmacokinetic modeling of different therapeutic modalities. A crucial requirement to constrain the parameters is the access to preferably anonymized individual patient data from completed clinical trials with various selective compounds. We believe that the combination of data- and knowledge driven modeling could be a game changer to find a cure for this devastating disease that affects the most complex organ of the universe.

Potential predictive marker of treatment effectiveness in patients with osteopenic syndrome after surgical menopause

GYNECOLOGY ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 39-42
Author(s):  
Yansiiat Z. Zaydieva ◽  
Elena V. Kruchinina ◽  
Olga S. Gorenkova ◽  
Elena Yu. Polyakova ◽  
Elena N. Kareva ◽  
...  
Keyword(s):  
Vitamin D ◽  
Combination Therapy ◽  
Vitamin D Receptor ◽  
Surrogate Marker ◽  
Predictive Marker ◽  
Expression Level ◽  
Mineral Density ◽  
Vitamin D Receptors ◽  
Surgical Menopause

Introduction. Patients with surgical menopause have a risk for osteopenic syndrome (OS). Menopausal hormone therapy (MHT) in combination with calcium and vitamin D promotes increase in bone mineral density (BMD). The expression level of vitamin D receptor in mononuclear fraction cells (MNFC) of blood can be considered as a predictive marker of effectiveness of OS therapy. Aim. To search a molecular predictive marker of the effectiveness of OS treatment. Materials and methods. The study included 100 women aged 4055 years with a duration of surgical menopause from 12 months to 6 years. The criterion for including patients in the study was the absence of contraindications to the use of MHT. The subject of the study was the determination of BMD by dual-energy X-ray absorptiometry, polymerase chain reaction diagnostics of the level of expression of vitamin D genes, estradiol and progesterone receptors, determination of 25-OH vitamin D in the blood. Results. Analysis of 12-month OS therapy effectiveness evaluated with a surrogate marker BMD. The increase in BMD up to 34% per year was treated as absence of negative dynamics, more than 4% per year as positive one. Significant effect of combination therapy compared with MHT on BMD in patients with surgical menopause with a low baseline level of BMD (due to hypovitaminosis D) is associated with the anti-inflammatory, bone-protective effect of vitamin D. In both groups of patients not responding; to the prescribed therapy we were able to conduct a comparative analysis of expression level of the target molecules in the MNFC before the start of treatment. The efficacy of MHT and combination therapy for BMD disorders is positively associated with the expression level of vitamin D receptors in MNFC before treatment. Therefore, the vitDR mRNA level is a potential predictive marker of the effectiveness of OS treatment. The expression levels of nuclear estradiol beta receptor and membrane receptor for progesterone in MNFC before treatment showed an upward trend in women responding to therapy. Conclusion. The expression level of the vitamin D receptor in MNFC of blood is significantly lower in the group of women with no/insufficient effect on 12-month combined therapy. This indicator can be considered as a predictive marker of the effectiveness of OS therapy.

Hyaluronan based Multifunctional Nano-carriers for Combination Cancer Therapy

2020 ◽  
Vol 20 ◽  
Author(s):  
Menghan Gao ◽  
Hong Deng ◽  
Weiqi Zhang
Keyword(s):  
Cancer Therapy ◽  
Combination Therapy ◽  
Cancer Cells ◽  
Drug Loading ◽  
Tumor Therapy ◽  
Drug Carriers ◽  
Functional Sites ◽  
Therapeutic Modalities ◽  
Combination Cancer Therapy ◽  
Targeting Strategy

: Hyaluronan (HA) is a natural linear polysaccharide that has excellent hydrophilicity, biocompatibility, biodegradability, and low immunogenicity, making it one of the most attractive biopolymers used for biomedical researches and applications. Due to the multiple functional sites on HA and its intrinsic affinity for CD44, a receptor highly expressed on various cancer cells, HA has been widely engineered to construct different drug-loading nanoparticles (NPs) for CD44- targeted anti-tumor therapy. When a cocktail of drugs is co-loaded in HA NP, a multifunctional nano-carriers could be obtained, which features as a highly effective and self-targeting strategy to combat the cancers with CD44 overexpression. The HA-based multidrug nano-carriers can be a combination of different drugs, various therapeutic modalities, or the integration of therapy and diagnostics (theranostics). Up to now, there are many types of HA-based multidrug nano-carriers constructed by different formulation strategies including drug co-conjugates, micelles, nano-gels and hybrid NP of HA and so on. This multidrug nano-carrier takes the full advantages of HA as NP matrix, drug carriers and targeting ligand, representing a simplified and biocompatible platform to realize the targeted and synergistic combination therapy against the cancers. In this review, recent progresses about HA-based multidrug nano-carriers for combination cancer therapy are summarized and its potential challenges for translational applications have been discussed.

scholarly journals Checkpoint inhibitor induced hepatitis and the relation with liver metastasis and outcome in advanced melanoma patients

2021 ◽  
Author(s):  
Maaike Biewenga ◽  
Monique K. van der Kooij ◽  
Michel W. J. M. Wouters ◽  
Maureen J. B. Aarts ◽  
Franchette W. P. J. van den Berkmortel ◽  
...  
Keyword(s):  
Overall Survival ◽  
Liver Metastasis ◽  
Combination Therapy ◽  
Real World ◽  
Cytotoxic T Lymphocyte ◽  
Checkpoint Inhibitor ◽  
Checkpoint Inhibitors ◽  
Progression Free Survival ◽  
Negative Effect ◽  
Melanoma Patients

Abstract Background Checkpoint inhibitor-induced hepatitis is an immune-related adverse event of programmed cell death protein 1 (PD-1) inhibition, cytotoxic T-lymphocyte associated 4 (CTLA-4) inhibition or the combination of both. Aim of this study was to assess whether checkpoint inhibitor-induced hepatitis is related to liver metastasis and outcome in a real-world nationwide cohort. Methods Data from the prospective nationwide Dutch Melanoma Treatment Registry (DMTR) was used to analyze incidence, risk factors of checkpoint inhibitor-induced grade 3–4 hepatitis and outcome. Results 2561 advanced cutaneous melanoma patients received 3111 treatments with checkpoint inhibitors between May 2012 and January 2019. Severe hepatitis occurred in 30/1620 (1.8%) patients treated with PD-1 inhibitors, in 29/1105 (2.6%) patients treated with ipilimumab and in 80/386 (20.7%) patients treated with combination therapy. Patients with hepatitis had a similar prevalence of liver metastasis compared to patients without hepatitis (32% vs. 27%; p = 0.58 for PD-1 inhibitors; 42% vs. 29%; p = 0.16 for ipilimumab; 38% vs. 43%; p = 0.50 for combination therapy). There was no difference in median progression free and overall survival between patients with and without hepatitis (6.0 months vs. 5.4 months progression-free survival; p = 0.61; 17.0 vs. 16.2 months overall survival; p = 0.44). Conclusion Incidence of hepatitis in a real-world cohort is 1.8% for PD-1 inhibitor, 2.6% for ipilimumab and 20.7% for combination therapy. Checkpoint inhibitor-induced hepatitis had no relation with liver metastasis and had no negative effect on the outcome.

scholarly journals Immune checkpoint inhibitor combination therapies very frequently induce secondary adrenal insufficiency

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Katsunori Manaka ◽  
Junichiro Sato ◽  
Maki Takeuchi ◽  
Kousuke Watanabe ◽  
Hidenori Kage ◽  
...  
Keyword(s):  
Combination Therapy ◽  
Adrenal Insufficiency ◽  
Cancer Patients ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Delayed Diagnosis ◽  
Secondary Adrenal Insufficiency ◽  
Acth Deficiency ◽  
Life Threatening ◽  
Inhibitor Combination

AbstractImmune checkpoint inhibitors (ICIs) are potent therapeutic options for many types of advanced cancer. The expansion of ICIs use however has led to an increase in immune-related adverse events (irAEs). Secondary adrenal insufficiency (AI) can be life-threatening especially in patients with delayed diagnosis. We retrospectively investigated secondary AI in ICI-treated patients. A total of 373 cancer patients treated with ICIs were included and evaluated. An adrenocorticotropic hormone (ACTH) deficiency was described in 13 patients. Among 24 patients with a combination of nivolumab and ipilimumab therapy, 7 patients (29%) developed secondary AI in a median time of 8 weeks during the combination therapy and 2 of 15 patients (13%) developed isolated ACTH deficiency during maintenance nivolumab monotherapy following the combination therapy. More than half of the patients (4/7) with a combination therapy-induced multiple anterior hormone deficiencies was diagnosed as secondary AI based on regular ACTH and cortisol tests with slight subjective symptoms. Secondary AI can arise frequently and rapidly in cancer patients receiving a combination ICI therapy, and thus we speculate active surveillance of AI using regular ACTH and cortisol tests during the combination therapy might be useful for avoiding life-threatening conditions due to secondary AI.

scholarly journals Pan-Cancer Analysis Identifies Liver Metastases as Negative Predictive Factor for Immune Checkpoint Inhibitors Treatment Outcome

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiao-Juan Chen ◽  
Aiqun Ren ◽  
Liang Zheng ◽  
En-Dian Zheng ◽  
Tao Jiang
Keyword(s):  
Combination Therapy ◽  
Liver Metastases ◽  
Predictive Factor ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Intrinsic Resistance ◽  
The Impact ◽  
Pan Cancer ◽  
Negative Predictive Factor

This study aimed to investigate the predictive value of liver metastases (LM) in patients with various advanced cancers received immune-checkpoint inhibitors (ICIs). First, clinical and survival data from a published cohort of 1,661 patients who received ICIs therapy were downloaded and analyzed. Second, a retrospective review of 182 patients with advanced non-small-cell lung cancer (NSCLC) who received PD-1/PD-L1 monotherapy was identified. Third, a meta-analysis of published trials was performed to explore the impact of LM on the efficacy of anti-PD-1/PD-L1 based therapy in advanced lung cancers. Pan-cancer analysis revealed that patients with LM had significantly shorter overall survival (OS) than those without LM (10 vs. 20 months; P < 0.0001). Subgroup analysis showed that the presence of LM was associated with markedly shorter OS than those without LM in ICI monotherapy group (P < 0.0001), but it did not reach the statistical significance in ICI-based combination therapy (P = 0.0815). In NSCLC, the presence of LM was associated with significantly inferior treatment outcomes in both pan-cancer and real-world cohort. Interestingly, ICI-based monotherapy and combination therapy could simultaneously prolong progression-free survival (PFS) and OS than chemotherapy in patients without LM. However, ICI-based monotherapy could not prolong PFS than chemotherapy in patients with LM while ICI-based combination therapy could dramatically prolong both PFS and OS. Together, these findings suggested that the presence of LM was the negative predictive factor in cancer patients received ICIs monotherapy, especially in NSCLC. ICI-based combination therapy might overcome the intrinsic resistance of LM to ICIs while the optimal combinatorial strategies remain under further investigation.

Uncertainty Quantification in Metallic Additive Manufacturing Through Data-Driven Modelling Based on Multi-Scale Multi-Physics Models and Limited Experiment Data

2020 ◽  
Author(s):  
Zhuo Wang ◽  
Chen Jiang ◽  
Mark F. Horstemeyer ◽  
Zhen Hu ◽  
Lei Chen
Keyword(s):  
Temperature Field ◽  
Additive Manufacturing ◽  
Uncertainty Quantification ◽  
Surrogate Modeling ◽  
Data Driven ◽  
Modeling Framework ◽  
High Quality ◽  
Experimental Calibration ◽  
Multi Scale ◽  
Metallic Additive

Abstract One of significant challenges in the metallic additive manufacturing (AM) is the presence of many sources of uncertainty that leads to variability in microstructure and properties of AM parts. Consequently, it is extremely challenging to repeat the manufacturing of a high-quality product in mass production. A trial-and-error approach usually needs to be employed to attain a product with high quality. To achieve a comprehensive uncertainty quantification (UQ) study of AM processes, we present a physics-informed data-driven modeling framework, in which multi-level data-driven surrogate models are constructed based on extensive computational data obtained by multi-scale multi-physical AM models. It starts with computationally inexpensive metamodels, followed by experimental calibration of as-built metamodels and then efficient UQ analysis of AM process. For illustration purpose, this study specifically uses the thermal level of AM process as an example, by choosing the temperature field and melt pool as quantity of interest. We have clearly showed the surrogate modeling in the presence of high-dimensional response (e.g. temperature field) during AM process, and illustrated the parameter calibration and model correction of an as-built surrogate model for reliable uncertainty quantification. The experimental calibration especially takes advantage of the high-quality AM benchmark data from National Institute of Standards and Technology (NIST). This study demonstrates the potential of the proposed data-driven UQ framework for efficiently investigating uncertainty propagation from process parameters to material microstructures, and then to macro-level mechanical properties through a combination of advanced AM multi-physics simulations, data-driven surrogate modeling and experimental calibration.

On the use of the data- and physics-driven approaches for quasi-geostrophic double-gyre problem: application of Genetic Programming

2021 ◽  
Author(s):  
Elnaz Naghibi ◽  
Elnaz Naghibi ◽  
Sergey Karabasov ◽  
Vassili Toropov ◽  
Vasily Gryazev
Keyword(s):  
Genetic Programming ◽  
Data Driven ◽  
Time Signal ◽  
Reduced Order ◽  
Multi Scale ◽  
Data Driven Approach ◽  
Auto Correlation Function ◽  
Gyre Circulation ◽  
Proper Orthogonal ◽  
Double Gyre

<p>In this study, we investigate Genetic Programming as a data-driven approach to reconstruct eddy-resolved simulations of the double-gyre problem. Stemming from Genetic Algorithms, Genetic Programming is a method of symbolic regression which can be used to extract temporal or spatial functionalities from simulation snapshots.  The double-gyre circulation is simulated by a stratified quasi-geostrophic model which is solved using high-resolution CABARET scheme. The simulation results are compressed using proper orthogonal decomposition and the time variant coefficients of the reduced-order model are fed into a Genetic Programming code. Due to the multi-scale nature of double-gyre problem, we decompose the time signal into a meandering and a fluctuating component. We next explore the parameter space of objective functions in Genetic Programming to capture the two components separately. The data-driven predictions are cross-compared with original double-gyre signal in terms of statistical moments such as variance and auto-correlation function.</p><p> </p>

scholarly journals Immune Checkpoint Inhibitors for Brain Metastases: A Primer for Neurosurgeons

Neurosurgery ◽  
2020 ◽  
Vol 87 (3) ◽  
pp. E281-E288
Author(s):  
Elisa Aquilanti ◽  
Priscilla K Brastianos
Keyword(s):  
Brain Metastases ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Cytotoxic T Lymphocyte ◽  
Checkpoint Inhibitors ◽  
Standard Of Care ◽  
Nonsmall Cell Lung Cancer ◽  
Immune Recognition ◽  
Therapeutic Modalities ◽  
Programmed Death 1

Abstract Immune checkpoint inhibitors enhance immune recognition of tumors by interfering with the cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) and programmed death 1 (PD1) pathways. In the past decade, these agents brought significant improvements to the prognostic outlook of patients with metastatic cancers. Recent data from retrospective analyses and a few prospective studies suggest that checkpoint inhibitors have activity against brain metastases from melanoma and nonsmall cell lung cancer, as single agents or in combination with radiotherapy. Some studies reported intracranial response rates that were comparable with systemic ones. In this review, we provide a comprehensive summary of clinical data supporting the use of anti-CTLA4 and anti-PD1 agents in brain metastases. We also touch upon specific considerations on the assessment of intracranial responses in patients and immunotherapy-specific toxicities. We conclude that a subset of patients with brain metastases benefit from the addition of checkpoint inhibitors to standard of care therapeutic modalities, including radiotherapy and surgery.

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