A critical evaluation of methods to interpret drug combinations.
Ontology highlight
ABSTRACT:
SUBMITTER: Twarog NR
PROVIDER: S-EPMC7083968 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Publications
A critical evaluation of methods to interpret drug combinations.
Twarog Nathaniel R NR Connelly Michele M Shelat Anang A AA
Scientific reports 20200320 1
Combination therapy is increasingly central to modern medicine. Yet reliable analysis of combination studies remains an open challenge. Previous work suggests that common methods of combination analysis are too susceptible to noise to support robust scientific conclusions. In this paper, we use simulated and real-world combination datasets to demonstrate that traditional index methods are unstable and biased by pharmacological and experimental conditions, whereas response-surface approaches such ...[more]
Similar Datasets
Project description:During polychemotherapy, cytotoxic drugs are given in combinations to enhance their anti-tumor effectiveness. For most drug combinations, underlying signaling mechanisms responsible for positive drug-drug interactions remain elusive. Here, we prove a decisive role for the Bcl-2 family member NOXA to mediate cell death by certain drug combinations, even if drugs were combined which acted independently from NOXA, when given alone. In proof-of-principle studies, betulinic acid, doxorubicin and vincristine induced cell death in a p53- and NOXA-independent pathway involving mitochondrial pore formation, release of cytochrome c and caspase activation. In contrast, when betulinic acid was combined with either doxorubicine or vincristine, cell death signaling changed considerably; the drug combinations clearly depended on both p53 and NOXA. Similarly and of high clinical relevance, in patient-derived childhood acute leukemia samples the drug combinations, but not the single drugs depended on p53 and NOXA, as shown by RNA interference studies in patient-derived cells. Our data emphasize that NOXA represents an important target molecule for combinations of drugs that alone do not target NOXA. NOXA might have a special role in regulating apoptosis sensitivity in the complex interplay of polychemotherapy. Deciphering the differences in signaling of single drugs and drug combinations might enable designing highly effective novel polychemotherapy regimens.
| S-EPMC3388227 | biostudies-literature
Project description:Lyme disease, caused by Borrelia burgdorferi, is the most common vector-borne disease in USA, and 10-20% of patients will develop persistent symptoms despite treatment ("post-treatment Lyme disease syndrome"). B. burgdorferi persisters, which are not killed by the current antibiotics for Lyme disease, are considered one possible cause. Disulfiram has shown to be active against B. burgdorferi, but its activity against persistent forms is not well characterized. We assessed disulfiram as single drug and in combinations against stationary-phase B. burgdorferi culture enriched with persisters. Disulfiram was not very effective in the drug exposure experiment (survival rate (SR) 46.3%) or in combinations. Clarithromycin (SR 41.1%) and nitroxoline (SR 37.5%) were equally effective when compared to the current Lyme antibiotic cefuroxime (SR 36.8%) and more active than disulfiram. Cefuroxime + clarithromycin (SR 25.9%) and cefuroxime + nitroxoline (SR 27.5%) were significantly more active than cefuroxime + disulfiram (SR 41.7%). When replacing disulfiram with clarithromycin or nitroxoline in three-drug combinations, bacterial viability decreased significantly and subculture studies showed that combinations with these two drugs (cefuroxime + clarithromycin/nitroxoline + furazolidone/nitazoxanide) inhibited the regrowth, while disulfiram combinations did not (cefuroxime + disulfiram + furazolidone/nitazoxanide). Thus, clarithromycin and nitroxoline should be further assessed to determine their role as potential treatment alternatives in the future.
| S-EPMC7559458 | biostudies-literature
Project description:Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks. Furthermore, there is a need for automated methods to apply to large numbers of varied hyperspectral data sets containing multiple overlapping peaks, and thus methods ideally suitable for diverse tasks. To investigate these issues, we implemented three novel resolution enhancement methods based on pseudospectra, over-deconvolution, and peak fitting to evaluate them along with three extant methods: node narrowing, blind deconvolution, and the general-purpose peak fitting program Fityk. We first applied the methods to varied synthetic spectra, each consisting of nine overlapping Voigt profile peaks. Improved spectral resolution was evaluated based on several criteria including the separation of overlapping peaks and the preservation of true peak intensities in resolution-enhanced spectra. We then investigated the efficacy of these methods to improve the resolution of measured Raman spectra. High resolution spectra of glucose acquired with a narrow spectrometer slit were compared to ones using a wide slit that degraded the spectral resolution. We also determined the effects of the different resolution enhancement methods on 2D-COS and on chemical contrast image generation from mammalian cell spectra. We conclude with a discussion of the particular benefits, drawbacks, and potential of these methods. Our efforts provided insight into the need for effective resolution enhancement approaches, the feasibility of these methods for automation, the nature of the problems currently limiting their use, and in particular those aspects that need improvement.
| S-EPMC8750138 | biostudies-literature
Project description:In the field of photocatalysis, the fabrication of black titania is a booming topic, as it offers a system with improved solar light harvesting properties and increased overall efficiency. The darkening of white TiO2 powders can be ascribed to surface hydroxylation, oxygen vacancies, Ti3+ centres, or a combination thereof. A handful of studies suggests these defects can be conveniently introduced by acoustic cavitation, generated during sonochemical treatment of pristine TiO2 powders. In reproducing these studies, P25 TiO2 samples were ultrasonicated for various hours with a power density of 8000 W/L, resulting in powders that indeed became gradually darker with increasing sonication time. However, HAADF-STEM revealed that extensive erosion of the sonotrode tip took place and contaminated the samples, which appeared to be the primary reason for the observed colour change. This was confirmed by UV-Vis DRS and DRIFTS, that showed no significant alteration of the catalyst surface after sonication. EPR measurements showed that only an insignificant fraction of Ti3+ centres were produced, far less than in a TiO2 sample that was chemically reduced with NaBH4. No evidence of the presence oxygen vacancies could be found. The enhanced photocatalytic activities of ultrasonicated materials reported in literature can therefore not be ascribed to the synthesis of actual black (defected) TiO2, but rather to specific changes in morphology as a result of acoustic cavitation. Also, this study underlines the importance of considering probe erosion in sonochemical catalyst synthesis, which is an unavoidable side effect that can have an important impact on the catalyst appearance, properties and performance.
| S-EPMC10518725 | biostudies-literature
Project description:ObjectivesPrescription drug monitoring programs (PDMPs) are state-based databases that contain information about controlled substance prescriptions dispensed by pharmacies. Many states now mandate PDMP use by prescribers, despite unclear effectiveness. We hypothesize that it is possible to improve the interpretability, and hence effectiveness, of PDMPs by enhancing them.MethodsThis was a real-time simulation of an enhanced PDMP. Fifty practicing physicians (25 primary care, 25 emergency medicine) were randomized to see three cases with a standard profile or an enhanced profile that included graphical representation of prescriptions and identified risky prescribing patterns. After a two-month washout period, participants were placed in the opposite group.ResultsPhysicians presented with the enhanced profile were more likely to correctly identify patients with multiple providers (97.0% vs. 85.8%, p = 0.002), overlapping opioid and benzodiazepine prescriptions (94.7% vs. 87.5%, p = 0.03), overlapping opioid prescriptions (89.5% vs. 70.8%, p < 0.01), high daily dosages of opioids (99.2% vs. 25.0%, p = 0.02), and traveling to distant pharmacies (79.7% vs. 2.5%, p < 0.01). There was no difference in interpretation time for the three cases (standard profile 657.3 s vs. enhanced profile 686.3 s, p = 0.31).ConclusionsA simulated PDMP with graphical displays and interpretation of findings was, for this cohort of emergency physicians and primary care physicians, associated with an increased ability to determine high-risk features on PDMP profiles.
| S-EPMC6737934 | biostudies-literature
Project description:Recent technological and methodological developments have enabled the use of array-based DNA methylation data to call copy number variants (CNVs). ChAMP, Conumee, and cnAnalysis450k are popular methods currently used to call CNVs using methylation data. However, so far, no studies have analyzed the reliability of these methods using real samples. Data from a cohort of individuals with genotype and DNA methylation data generated using the HumanMethylation450 and MethylationEPIC BeadChips were used to assess the consistency between the CNV calls generated by methylation and genotype data. We also took advantage of repeated measures of methylation data collected from the same individuals to compare the reliability of CNVs called by ChAMP, Conumee, and cnAnalysis450k for both the methylation arrays. ChAMP identified more CNVs than Conumee and cnAnalysis450k for both the arrays and, as a consequence, had a higher overlap (~62%) with the calls from the genotype data. However, all methods had relatively low reliability. For the MethylationEPIC array, Conumee had the highest reliability (57.6%), whereas for the HumanMethylation450 array, cnAnalysis450k had the highest reliability (43.0%). Overall, the MethylationEPIC array provided significant gains in reliability for CNV calling over the HumanMethylation450 array but not for overlap with CNVs called using genotype data.
| S-EPMC7028453 | biostudies-literature
Project description:Current cancer therapy includes a variety of strategies that can comprise only one type of treatment or a combination of multiple treatments. Chemotherapy is still the gold standard for cancer therapy, though sometimes associated with undesired side effects and the development of drug resistance. For this reason, drug combination is an approach that has been proposed to overcome the problems related to monotherapy and several studies have already demonstrated the superiority of combined therapies compared to monotherapy. The main goal when designing and evaluating drug combinations is to achieve synergistic effects by demonstrating that the combined effects are greatly superior to the expected from the additive effects of the single drugs, allowing for dosage reduction and therefore decreasing toxicity. Nevertheless, synergism quantification is not a simple task due to the different definitions of additivity and over the years several reference models have been proposed based on different assumptions and with different mathematical frameworks. In this review, we begin to cover the available treatment options for cancer therapy, with emphasis on the importance of drug combinations in cancer therapy. We next describe the classical reference models that have been proposed for synergism evaluation, usually classified as effect-based and dose-effect based methods, with a brief analysis of the current limitations of these models. We also describe here the novel methods for the accurate quantification of drug interactions in combined treatments. At the end of this manuscript, we covered some of the most recent preclinical and clinical combination studies that reflect the importance of the appropriate, accurate and precise application of the concepts and methodologies here described for the evaluation of synergism.
| S-EPMC9127325 | biostudies-literature
Project description:BackgroundTargeted therapies have greatly improved cancer patient prognosis. For instance, chronic myeloid leukemia is now well treated with imatinib, a tyrosine kinase inhibitor. Around 80% of the patients reach complete remission. However, despite its great efficiency, some patients are resistant to the drug. This heterogeneity in the response might be associated with pharmacokinetic parameters, varying between individuals because of genetic variants. To assess this issue, next-generation sequencing of large panels of genes can be performed from patient samples. However, the common problem in pharmacogenetic studies is the availability of samples, often limited. In the end, large sequencing data are obtained from small sample sizes; therefore, classical statistical analyses cannot be applied to identify interesting targets. To overcome this concern, here, we described original and underused statistical methods to analyze large sequencing data from a restricted number of samples.ResultsTo evaluate the relevance of our method, 48 genes involved in pharmacokinetics were sequenced by next-generation sequencing from 24 chronic myeloid leukemia patients, either sensitive or resistant to imatinib treatment. Using a graphical representation, from 708 identified polymorphisms, a reduced list of 115 candidates was obtained. Then, by analyzing each gene and the distribution of variant alleles, several candidates were highlighted such as UGT1A9, PTPN22, and ERCC5. These genes were already associated with the transport, the metabolism, and even the sensitivity to imatinib in previous studies.ConclusionsThese relevant tests are great alternatives to inferential statistics not applicable to next-generation sequencing experiments performed on small sample sizes. These approaches permit to reduce the number of targets and find good candidates for further treatment sensitivity studies.
| S-EPMC6717342 | biostudies-literature
Project description:OBJECTIVES:The objectives of this mixed-methods study were to assess the uptake, sustainability and influence of the Footprints Project. SETTING:Twenty-two-bed university-affiliated ICU in Hamilton, Canada. PARTICIPANTS:ICU patients admitted and their families, as well as clinicians. INTERVENTIONS:We developed a personalised patient Footprints Form and Whiteboard to facilitate holistic, patient-centred care, to inform clinical encounters, and to create deeper connections among patients, families and clinicians. OUTCOME MEASURES:We conducted 3 audits to examine uptake and sustainability. We conducted semi-structured interviews with 10 clinicians, and held 5 focus groups with 25 clinicians; and we interviewed 5 patients and 13 family representatives of 5 patients who survived and 5 who died in the ICU. Transcripts were analysed using qualitative content analysis. RESULTS:The Footprints Project facilitated holistic, patient-centred care by setting the stage for patient and family experience, motivating the patient and humanising the patient for clinicians. Through informing clinical encounters, Footprints helped clinicians initiate more personal conversations, foster deeper connections and guide treatment. Professional practice influences included more focused attention on the patient, enhanced interdisciplinary communication and changes in community culture. Initially used in 15.8% of patients (audit A), uptake increased to 51.4% in audit B, and was sustained at 57.8% in audit C. CONCLUSIONS:By sharing valuable personal information about patients before and beyond their illness on individualised whiteboards at each bedside, the Footprints Project fosters humanism in critical care practice.
| S-EPMC6830601 | biostudies-literature
Project description:Preclinical experimental models of pathological aggressive behavior are a sorely understudied and difficult research area.How valid, reliable, productive, and informative are the most frequently used animal models of excessive aggressive behavior?The rationale, key methodological features, supporting data, and arguments as well as their disadvantages and limitations of the most frequently used animal models for excessive aggressive behavior are summarized and their validity and reliability are evaluated.Excessive aggressive behavior is validly and reliably seen in (1) a proportion of feral-derived rats and selectively bred mice; (2) rats with compromised adrenal function resulting in a hypoglucocorticoid state; (3) a significant minority of mice, rats, and monkeys after consumption of a moderate dose of alcohol; and (4) resident animals of various species after social instigation. Limitations of these procedures include restrictive animal research regulations, the requirement of expertise in surgical, pharmacological, and behavioral techniques, and the behaviorally impoverished mouse strains that are used in molecular genetics research. Promising recent initiatives for novel experimental models include aggressive behaviors that are evoked by optogenetic stimulation and induced by the manipulation of early social experiences such as isolation rearing or social stress.One of the most significant challenges for animal models of excessive, potentially abnormal aggressive behavior is the characterization of distinctive neurobiological mechanisms that differ from those governing species-typical aggressive behavior. Identifying novel targets for effective intervention requires increased understanding of the distinctive molecular, cellular, and circuit mechanisms for each type of abnormal aggressive behavior.
| S-EPMC3595336 | biostudies-literature