[Show abstract][Hide abstract] ABSTRACT: We describe a protocol for the discovery of synergistic drug combinations for the treatment of disease. Synergistic drug combinations lead to the use of drugs at lower doses, which reduces side effects and can potentially lead to reduced drug resistance, while being clinically more effective than the individual drugs. To cope with the extremely large search space for these combinations, we developed an efficient combinatorial drug screening method called the Feedback System Control (FSC) technique. Starting with a broad selection of drugs, the method follows an iterative approach of experimental testing in a relevant bioassay and analysis of the results by FSC. First, the protocol uses a cell viability assay to generate broad dose-response curves to assess the efficacy of individual compounds. These curves are then used to guide the dosage input of each drug to be tested in combination. Data from applied drug combinations are input into the differential evolution (DE) algorithm, which predicts new combinations to be tested in vitro. This process identifies optimal drug-dose combinations, while saving orders of magnitude in experimental effort. The complete optimization process is estimated to take ∼4 weeks. FSC does not require insight into the disease mechanism, and it has therefore been applied to find combination therapies for many different pathologies, including cancer and infectious diseases, and it has also been used in organ transplantation.
[Show abstract][Hide abstract] ABSTRACT: The development of clean, sustainable alternative energy sources is increasingly important. One promising alternative to depleting fuel reserves is algae-based biodiesel fuel, which is both non-toxic and renewable. Despite the tremendous potential of algae-based biodiesel fuel, it has not yet been profitable because of the high cost per unit area of large cultivation. We present a novel application of Orthogonal Array Composite Designs (OACDs) to optimize lipid production of a cell-free system for algae. An OACD consists of a two-level fractional factorial design and a three-level orthogonal array. We start with an initial screening experiment based on six chemicals using an OACD with 50 runs. Based on this experiment, two chemical compounds were removed and a follow-up 25-run OACD with four chemicals was performed. Our analysis shows that only three chemicals – nitrogen, magnesium, and phosphate – are essential for lipid accumulation, and a range of optimum combinations of these three chemicals is identified. The lipid accumulation for these three chemical combinations is substantially higher in comparison to the commercial medium, which contains 16 chemicals and soil water. This leads to a reduced cost of the chemical medium and increased efficiency of biodiesel production from the algal-based cell-free system, which can be used to significantly expand the use of biodiesel as a viable alternative to fossil fuels. Copyright
No preview · Article · Sep 2015 · Quality and Reliability Engineering
[Show abstract][Hide abstract] ABSTRACT: A major key to improvement of cancer therapy is the combination of drugs. Mixing drugs that already exist on the market may offer an attractive alternative. Here we report on a new model-based streamlined feedback system control (s-FSC) method, based on a design of experiment approach, for rapidly finding optimal drug mixtures with minimal experimental effort. We tested combinations in an in vitro assay for the viability of a renal cell adenocarcinoma (RCC) cell line, 786-O. An iterative cycle of in vitro testing and s-FSC analysis was repeated a few times until an optimal low dose combination was reached. Starting with ten drugs that target parallel pathways known to play a role in the development and progression of RCC, we identified the best overall drug combination, being a mixture of four drugs (axitinib, erlotinib, dasatinib and AZD4547) at low doses, inhibiting 90% of cell viability. The removal of AZD4547 from the optimized drug combination resulted in 80% of cell viability inhibition, while still maintaining the synergistic interaction. These optimized drug combinations were significantly more potent than monotherapies of all individual drugs.
Full-text · Article · Aug 2015 · Scientific Reports
[Show abstract][Hide abstract] ABSTRACT: Therapeutic outcomes of combination chemotherapy have not significantly advanced during the past decades. This has been attributed to the formidable challenges of optimizing drug combinations. Testing a matrix of all possible combinations of doses and agents in a single cell line is unfeasible due to the virtually infinite number of possibilities. We utilized the Feedback System Control (FSC) platform, a phenotype oriented approach to test 100 options among 15,625 possible combinations in four rounds of assaying to identify an optimal tri-drug combination in eight distinct chemoresistant bladder cancer cell lines. This combination killed between 82.86% and 99.52% of BCa cells, but only 47.47% of the immortalized benign bladder epithelial cells. Preclinical in vivo verification revealed its markedly enhanced anti-tumor efficacy as compared to its bi- or mono-drug components in cell line-derived tumor xenografts. The collective response of these pathways to component drugs was both cell type- and drug type specific. However, the entire spectrum of pathways triggered by the tri-drug regimen was similar in all four cancer cell lines, explaining its broad spectrum killing of BCa lines, which did not occur with its component drugs. Our findings here suggest that the FSC platform holdspromise for optimization of anti-cancer combination chemotherapy.
Full-text · Article · Jun 2015 · Scientific Reports
[Show abstract][Hide abstract] ABSTRACT: Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.
Electronic supplementary material
The online version of this article (doi:10.1007/s10456-015-9462-9) contains supplementary material, which is available to authorized users.
[Show abstract][Hide abstract] ABSTRACT: Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. The expression of glucose transporter isoform 1, a key factor in transporting glucose into cancer cells, is overexpressed in several human cancers, including HCC. In addition, this has been shown to correlate with a higher proliferation index and more advanced stages in HCC, suggesting that inhibition of glucose metabolism is a promising therapeutic strategy. Our study used high-content screening (HCS) for compounds that target glucose metabolism and effect cell death in HCC cells. Specifically, we showed that a fluorescent 2-deoxyglucose analog, 2-[N-(7-nitrobenz-2- oxa-1,3-diazol-4-yl)amino]-2-deoxyglucose, and CellTrace Calcein Red-Orange AM can be used reliably as readouts for glucose uptake and proliferative index, respectively, to identify drug candidates that simultaneously reduce glucose uptake and induce cell death in HCC cells. Thus, fluorescent glucose uptake bioprobes can be implemented in HCS assays to identify previously unknown regulators of glucose metabolism in HCC. In addition, our study also employs the use of feedback system control (FSC.II), a platform that optimizes the combinations of drugs identified through HCS. The coordinated use of HCS and FSC.II can improve the development of drug combinations and uncover previously unidentified signaling pathways that govern HCC as well as other cancers.
No preview · Article · Mar 2015 · Journal of the Association for Laboratory Automation
[Show abstract][Hide abstract] ABSTRACT: Combination chemotherapy can mediate drug synergy to improve treatment efficacy against a broad spectrum of cancers. However, conventional multi-drug regimens are often additively determined, which have long been believed to enable good cancer-killing efficiency but are insufficient to address the nonlinearity in dosing. Despite improved clinical outcomes by combination treatment, multi-objective combination optimization, which takes into account tumor heterogeneity and balance of efficacy and toxicity, remains challenging given the sheer magnitude of the combinatorial dosing space. To enhance the properties of the therapeutic agents, the field of nanomedicine has realized novel drug delivery platforms that can enhance therapeutic efficacy and safety. However, optimal combination design that incorporates nanomedicine agents still faces the same hurdles as unmodified drug administration. The work reported here applied a powerful phenotypically-driven platform, termed Feedback System Control (FSC), that systematically and rapidly converges upon a combination consisting of three nanodiamond-modified drugs and one unmodified drug that is simultaneously optimized for efficacy against multiple breast cancer cell lines and safety against multiple control cell lines. Specifically, the therapeutic window achieved from an optimally efficacious and safe nanomedicine combination was markedly higher compared to that of an optimized unmodified drug combination and nanodiamond monotherapy or unmodified drug administration. The phenotypically-driven foundation of FSC implementation does not require any cellular signaling pathway data, and innately accounts for population heterogeneity and non-linear biological processes. Therefore, FSC is a broadly-applicable platform for both nanotechnology-modified and unmodified therapeutic optimization that represents a promising path towards phenotypic personalized medicine (PPM).
[Show abstract][Hide abstract] ABSTRACT: We have succeeded in developing hollow branching structure in vitro commonly observed in lung airway using primary lung airway epithelial cells. Cell concentration gradient is the key factor that determines production of the branching cellular structures, as optimization of this component removes the need for heterotypic culture. The higher cell concentration leads to the more production of morphogens and increases the growth rate of cells. However, homogeneous high cell concentration does not make a branching structure. Branching requires sufficient space in which cells can grow from a high concentration toward a low concentration. Simulation performed using a reaction-diffusion model revealed that long-range inhibition prevents cells from branching when they are homogeneously spread in culture environments, while short-range activation from neighboring cells leads to positive feedback. Thus, a high cell concentration gradient is required to make branching structures. Spatial distributions of morphogens, such as BMP-4, play important roles in the pattern formation. This simple yet robust system provides an optimal platform for the further study and understanding of branching mechanisms in the lung airway, and will facilitate chemical and genetic studies of lung morphogenesis programs.
[Show abstract][Hide abstract] ABSTRACT: The challenge in creating an effective combinatorial treatment lies in the inability to screen through a huge number of possible drug combinations. To address the challenge, we introduce PROPHECY, a data-driven search engine for the selection of drugs in combinatorial cancer therapeutics. The user provides the genetic profile, e.g. mutations in cancer cell lines or primary cells, and PROPHECY will select optimal drug combinations from a comprehensive library of existing drugs to meet clinical objectives. The decision making is accomplished by comparing the efficacy of drug combinations with in silico drug screening. Predictive module of the in silico screening is trained with a comprehensive database of drug screening experiment to recognize high order interactions of drug targets and disease genes in a protein-protein interaction network (PPI). The prediction of drug efficacy is based on systematic view of proteomic scale data, so can accurately reflect drug efficacy and elucidate interactions of drug targets and disease genes in de novo drug combinations. Unlike currently predominant approach of reductionistic drug development, PROPHECY can fully take into account the synergy between multiple drugs and predict the most effective multi-target treatment against drug resistant cancer cells.
[Show abstract][Hide abstract] ABSTRACT: Stem cell-based disease modeling presents unique opportunities for mechanistic elucidation and therapeutic targeting. The stable induction of fate-specific differentiation is an essential prerequisite for stem cell-based strategy. Bone morphogenetic protein 2 (BMP-2) initiates receptor-regulated Smad phosphorylation, leading to the osteogenic differentiation of mesenchymal stromal/stem cells (MSC) in vitro; however, it requires supra-physiological concentrations, presenting a bottleneck problem for large-scale drug screening. Here, we report the use of a double-objective feedback system control (FSC) with a differential evolution (DE) algorithm to identify osteogenic cocktails of extrinsic factors. Cocktails containing significantly reduced doses of BMP-2 in combination with physiologically relevant doses of dexamethasone, ascorbic acid, beta-glycerophosphate, heparin, retinoic acid and vitamin D achieved accelerated in vitro mineralization of mouse and human MSC. These results provide insight into constructive approaches of FSC to determine the applicable functional and physiological environment for MSC in disease modeling, drug screening and tissue engineering.
Full-text · Article · Dec 2013 · Scientific Reports
[Show abstract][Hide abstract] ABSTRACT: Recent experimental work has described an elegant pattern of branching in the development of the lung. Multiple forms of branching have been identified, including side branching and tip bifurcation. A particularly interesting feature is the phenomenon of 'orthogonal rotation of the branching plane'. The lung must fill 3D space with the essentially 2D phenomenon of branching. It accomplishes this by rotating the branching plane by 90 degrees with each generation. The mechanisms underlying this rotation are not understood. In general, the programs that underlie branching have been hypothetically attributed to genetic 'subroutines' under the control of a 'global master routine' to invoke particular subroutines at the proper time and location, but the mechanisms of these routines are not known. Here, we demonstrate that fundamental mechanisms, the reaction and diffusion of biochemical morphogens, can create these patterns. We used a Partial Differential Equation model that postulates 3 morphogens, which we identify with specific molecules in lung development. We found that cascades of branching events, including side branching, tip splitting and orthogonal rotation of the branching plane, all emerge immediately from the model, without further assumptions. In addition, we found that one branching mode can be easily switched to another, by increasing or decreasing the values of key parameters. This shows how a 'global master routine' could work by the alteration of a single parameter. Being able to simulate cascades of branching events is necessary to understand the critical features of branching, such as orthogonal rotation of the branching plane between successive generations, and branching mode switch during lung development. Thus, our model provides a paradigm for how genes could possibly act to produce spatial structures. Our low-dimensional model gives a qualitative understanding of how generic physiological mechanisms can produce branching phenomena, and how the system can switch from one branching pattern to another using low-dimensional 'control knobs'. The model provides a number of testable predictions, some of which have already been observed (though not explained) in experimental work.
Full-text · Article · Nov 2013 · The Journal of Physiology
[Show abstract][Hide abstract] ABSTRACT: Flexible integration of a microfluidic system comprising pumps, valves, and microchannels was realized by an optoelectronic reconfigurable microchannels (OERM) technique. Projecting a low light fluidic device pattern—e.g., pumps, valves, and channels—onto an OERM platform generates Joule heating and melts the substrate in the bright area on the platform; thus, the fluidic system can be reconfigured by changing the projected light pattern. Hexadecane was used as the substrate of the microfluidic system. The volume change of hexadecane during the liquid–solid phase transition was utilized to generate pumping pressure. The system can pump nanoliters of water within several seconds.
No preview · Article · Oct 2013 · Applied Physics Letters
[Show abstract][Hide abstract] ABSTRACT: Combination therapy was found to be more effective in treating cancer, as it reduces the risk of relapse due to drug resistance and can more effectively modulate the genome. To uncover potential combinations, direct screening can be challenging, as the number of possibility The challenge, however, in creating a sucessful combinatorial treatment lies in the inability to screen through a huge number of possible combinations. We introduce PROPHECY (Predictive Optimization of Pharmaceutical Efficacy), a data-driven search engine for the selection of drugs in combinatorial cancer therapeutics. The user provides the genetic profile, e.g. mutations in cancer cell lines or primary cells, and PROPHECY will select optimal drug combinations from a comprehensive library of existing drugs to meet clinical objectives. The decision making is accomplished by comparing the efficacy of drug combinations with in silico screening. The predictive module of the in silico screening is trained with a comprehensive database of drug screening experiments to recognize high-order interactions of drug targets and disease genes in a protein-protein interaction network (PPI). The prediction of drug efficacy is based on a systematic view of proteomic scale data, so can accurately reflect drug efficacy and elucidate interactions of drug targets and disease genes in de novo drug combinations. Unlike other recent approaches of reductionistic drug development, PROPHECY can fully acknowledge the synergy between multiple drugs and predict the most effective multi-target treatment against drug resistant cancer cells.
[Show abstract][Hide abstract] ABSTRACT: The detection of bacterial pathogens plays an important role in many biomedical applications, including clinical diagnostics, food and water safety, and biosecurity. Most current bacterial detection technologies, however, are unsuitable for use in resource-limited settings where the highest disease burdens often exist. Thus, there is an urgent need to develop portable, user-friendly biosensors capable of rapid detection of multiple pathogens in situ. We report a microfluidic chip for multiplexed detection of bacterial cells that uses antimicrobial peptides (AMPs) with species-specific targeting and binding capabilities. The AMPs are immobilized onto an electrical impedance microsensor array and serve as biorecognition elements for bacterial cell detection. Characterization of peptide immobilization on the sensors revealed robust surface binding via cysteine-gold interactions and vertical alignment relative to the sensor surface. Samples containing Streptococcus mutans and Pseudomonas aeruginosa were loaded in the chip, and both microorganisms were detected at minimum concentrations of 10(5) cfu/mL within 25 min. Measurements performed in a variety of solutions revealed that high-conductivity solutions produced the largest impedance values. By integrating a highly specific bacterial cell capture scheme with rapid electrical detection, this device demonstrates great potential as a next-generation, point-of-care diagnostic platform for the detection of disease-causing pathogenic agents.
No preview · Article · Jul 2013 · Journal of the Association for Laboratory Automation
[Show abstract][Hide abstract] ABSTRACT: We present a compact mobile phone platform for rapid, quantitative biomolecular detection. This system consists of an embedded circuit for signal processing and data analysis, and disposable microfluidic chips for fluidic handling and biosensing. Capillary flow is employed for sample loading, processing, and pumping to enhance operational portability and simplicity. Graphical step-by-step instructions displayed on the phone assists the operator through the detection process. After the completion of each measurement, the results are displayed on the screen for immediate assessment and the data is automatically saved to the phone's memory for future analysis and transmission. Validation of this device was carried out by detecting Plasmodium falciparum histidine-rich protein 2 (PfHRP2), an important biomarker for malaria, with a lower limit of detection of 16 ng mL(-1) in human serum. The simple detection process can be carried out with two loading steps and takes 15 min to complete each measurement. Due to its compact size and high performance, this device offers immense potential as a widely accessible, point-of-care diagnostic platform, especially in remote and rural areas. In addition to its impact on global healthcare, this technology is relevant to other important applications including food safety, environmental monitoring and biosecurity.
[Show abstract][Hide abstract] ABSTRACT: Identifying potent drug combination from a herbal mixture is usually quite challenging, due to a large number of possible trials. Using an engineering approach of the feedback system control (FSC) scheme, we identified the potential best combinations of four flavonoids, including formononetin, ononin, calycosin, and calycosin-7-O- β -D-glucoside deriving from Astragali Radix (AR; Huangqi), which provided the best biological action at minimal doses. Out of more than one thousand possible combinations, only tens of trials were required to optimize the flavonoid combinations that stimulated a maximal transcriptional activity of hypoxia response element (HRE), a critical regulator for erythropoietin (EPO) transcription, in cultured human embryonic kidney fibroblast (HEK293T). By using FSC scheme, 90% of the work and time can be saved, and the optimized flavonoid combinations increased the HRE mediated transcriptional activity by ~3-fold as compared with individual flavonoid, while the amount of flavonoids was reduced by ~10-fold. Our study suggests that the optimized combination of flavonoids may have strong effect in activating the regulatory element of erythropoietin at very low dosage, which may be used as new source of natural hematopoietic agent. The present work also indicates that the FSC scheme is able to serve as an efficient and model-free approach to optimize the drug combination of different ingredients within a herbal decoction.
Full-text · Article · Apr 2013 · Evidence-based Complementary and Alternative Medicine
[Show abstract][Hide abstract] ABSTRACT: We introduce a new biosensing platform for rapid protein detection that combines one of the simplest methods for biomolecular concentration, coffee ring formation, with a sensitive aptamer-based optical detection scheme. In this approach, aptamer beacons are utilized for signal transduction where a fluorescence signal is emitted in the presence of the target molecule. Signal amplification is achieved by concentrating aptamer-target complexes within liquid droplets, resulting in the formation of coffee ring "spots". Surfaces with various chemical coatings were utilized to investigate the correlation between surface hydrophobicity, concentration efficiency and signal amplification. Based on our results, we found that the increase in coffee ring diameter with larger droplet volumes is independent of surface hydrophobicity. Furthermore, we show that highly hydrophobic surfaces produce enhanced particle concentration, via coffee ring formation, resulting in signal intensities 6-fold greater than those on hydrophilic surfaces. To validate this biosensing platform for the detection of clinical samples, we detected α-thrombin in human serum and 4x diluted whole blood. Based on our results, coffee ring spots produced detection signals 40x larger than samples in liquid droplets. Additionally, this biosensor exhibits a lower limit of detection of 2 ng/mL (54 pM) in serum, and 4 ng/mL (105 pM) in blood. Based on its simplicity and high performance, this platform demonstrates immense potential as an inexpensive diagnostic tool for the detection of disease biomarkers, particularly for use in developing countries that lack the resources and facilities required for conventional biodetection practices.
[Show abstract][Hide abstract] ABSTRACT: During the last two decades, the manufacturing techniques of microfluidics-based devices have been phenomenally advanced, offering unlimited potential for bio-medical technologies. However, the direct applications of these technologies toward diagnostics and therapeutics are still far from maturity. The present challenges lay at the interfaces between the engineering systems and the biocomplex systems. A precisely designed engineering system with narrow dynamic range is hard to seamlessly integrate with the adaptive biological system in order to achieve the design goals. These differences remain as the roadblock between two fundamentally non-compatible systems. This paper will not extensively review the existing microfluidic sensors and actuators; rather, we will discuss the sources of the gaps for integration. We will also introduce system interface technologies for bridging the differences to lead toward paradigm shifts in diagnostics and therapeutics.