A computational tumor growth model experience based on molecular dynamics point of view using deep cellular automata.

Cancer, as identified by the World Health Organization, stands as the second leading cause of death globally. Its intricate nature makes it challenging to study solely based on biological knowledge, often leading to expensive research endeavors. While tremendous strides have been made in understanding cancer, gaps remain, especially in predicting tumor behavior across various stages. The integration of artificial intelligence in oncology research has accelerated our insights into tumor behavior, right from its genesis to metastasis. Nevertheless, there's a pressing need for a holistic understanding of the interactions between cancer cells, their microenvironment, and their subsequent interplay with the broader body environment. In this landscape, deep learning emerges as a potent tool with its multifaceted applications in diverse scientific challenges. Motivated by this, our study presents a novel approach to modeling cancer tumor growth from a molecular dynamics' perspective, harnessing the capabilities of deep-learning cellular automata. This not only facilitates a microscopic examination of tumor behavior and growth but also delves deeper into its overarching behavioral patterns. Our work primarily focused on evaluating the developed tumor growth model through the proposed network, followed by a rigorous compatibility check with traditional mathematical tumor growth models using R and Matlab software. The outcomes notably aligned with the Gompertz growth model, accentuating the robustness of our approach. Our validated model stands out by offering adaptability to diverse tumor growth datasets, positioning itself as a valuable tool for predictions and further research.

Non-Fourier Bioheat Transfer Analysis in Brain Tissue During Interstitial Laser Ablation: Analysis of Multiple Influential Factors.

This work presents the dual-phase lag-based non-Fourier bioheat transfer model of brain tissue subjected to interstitial laser ablation. The finite element method has been utilized to predict the brain tissue's temperature distributions and ablation volumes. A sensitivity analysis has been conducted to quantify the effect of variations in the input laser power, treatment time, laser fiber diameter, laser wavelength, and non-Fourier phase lags. Notably, in this work, the temperature-dependent thermal properties of brain tissue have been considered. The developed model has been validated by comparing the temperature obtained from the numerical and ex vivo brain tissue during interstitial laser ablation. The ex vivo brain model has been further extended to in vivo settings by incorporating the blood perfusion effects. The results of the systematic analysis highlight the importance of considering temperature-dependent thermal properties of the brain tissue, non-Fourier behavior, and microvascular perfusion effects in the computational models for accurate predictions of the treatment outcomes during interstitial laser ablation, thereby minimizing the damage to surrounding healthy tissue. The developed model and parametric analysis reported in this study would assist in a more accurate and precise prediction of the temperature distribution, thus allowing to optimize the thermal dosage during laser therapy in the brain.

Vitamin B12 Deficiency and the Nervous System: Beyond Metabolic Decompensation-Comparing Biological Models and Gaining New Insights into Molecular and Cellular Mechanisms.

Vitamin B12 (VitB12) is a micronutrient and acts as a cofactor for fundamental biochemical reactions: the synthesis of succinyl-CoA from methylmalonyl-CoA and biotin, and the synthesis of methionine from folic acid and homocysteine. VitB12 deficiency can determine a wide range of diseases, including nervous system impairments. Although clinical evidence shows a direct role of VitB12 in neuronal homeostasis, the molecular mechanisms are yet to be characterized in depth. Earlier investigations focused on exploring the biochemical shifts resulting from a deficiency in the function of VitB12 as a coenzyme, while more recent studies propose a broader mechanism, encompassing changes at the molecular/cellular levels. Here, we explore existing study models employed to investigate the role of VitB12 in the nervous system, including the challenges inherent in replicating deficiency/supplementation in experimental settings. Moreover, we discuss the potential biochemical alterations and ensuing mechanisms that might be modified at the molecular/cellular level (such as epigenetic modifications or changes in lysosomal activity). We also address the role of VitB12 deficiency in initiating processes that contribute to nervous system deterioration, including ROS accumulation, inflammation, and demyelination. Consequently, a complex biological landscape emerges, requiring further investigative efforts to grasp the intricacies involved and identify potential therapeutic targets.

Advances in screening hyperthermic nanomedicines in 3D tumor models.

Hyperthermic nanomedicines are particularly relevant for tackling human cancer, providing a valuable alternative to conventional therapeutics. The early-stage preclinical performance evaluation of such anti-cancer treatments is conventionally performed in flat 2D cell cultures that do not mimic the volumetric heat transfer occurring in human tumors. Recently, improvements in bioengineered 3D in vitro models have unlocked the opportunity to recapitulate major tumor microenvironment hallmarks and generate highly informative readouts that can contribute to accelerating the discovery and validation of efficient hyperthermic treatments. Leveraging on this, herein we aim to showcase the potential of engineered physiomimetic 3D tumor models for evaluating the preclinical efficacy of hyperthermic nanomedicines, featuring the main advantages and design considerations under diverse testing scenarios. The most recent applications of 3D tumor models for screening photo- and/or magnetic nanomedicines will be discussed, either as standalone systems or in combinatorial approaches with other anti-cancer therapeutics. We envision that breakthroughs toward developing multi-functional 3D platforms for hyperthermia onset and follow-up will contribute to a more expedited discovery of top-performing hyperthermic therapies in a preclinical setting before their in vivo screening.

Population dynamics of a stoichiometric aquatic tri-trophic level model with fear effect.

In this paper, a stoichiometric aquatic tri-trophic level model is proposed and analyzed, which incorporates the effect of light and phosphorus, as well as the fear effect in predator-prey interactions. The analysis of the model includes the dissipativity and the existence and stability of equilibria. The influence of environmental factors and fear effect on the dynamics of the system is particularly investigated. The key findings reveal that the coexistence of populations is positively influenced by an appropriate level of light intensity and/or the dissolved phosphorus input concentration; however, excessive levels of phosphorus input can disrupt the system, leading to chaotic behaviors. Furthermore, it is found that the fear effect can stabilize the system and promote the chances of population coexistence.

Generalized thermomechanical interaction in two-dimensional skin tissue using eigenvalues approach.

The aim of this work is to analytically study the thermo-mechanical response of two-dimensional skin tissues when subjected to instantaneous heating. A complete understanding of the heat transfer process and the associated thermal and mechanical effects on the patient's skin tissues is critical to ensuring the effective applications of thermal therapy techniques and procedures. The surface boundary of the half-space undergoes a heat flux characterized by an exponentially decaying pulse, while maintaining a condition of zero traction. The utilization of Laplace and Fourier transformations is employed, and the resulting formulations are then applied to human tissues undergoing regional hyperthermia treatment for cancer therapy. To perform the inversion process for Laplace and Fourier transforms, a numerical programming method based on Stehfest numerical inverse method is employed. The findings demonstrate that blood perfusion rate and thermal relaxation time significantly influence all the analyzed distributions. Numerical findings suggest that thermo-mechanical waves propagate through skin tissue over finite distances, which helps mitigate the unrealistic predictions made by the Pennes' model.

Influence of different heat transfer models on therapeutic temperature prediction and heat-induced damage during magnetic hyperthermia.

Magnetic hyperthermia regulates the therapeutic temperature within a specific range to damage malignant cells after exposing the magnetic nanoparticles inside tumor tissue to an alternating magnetic field. The therapeutic temperature of living tissues can be generally predicted using Pennes' bio-heat equation after ignoring both the inhomogeneity of biological structure and the microstructural responses. Although various of the bio-heat transfer models proposed in literature fix these shortages, there is still a lack of a comprehensive report on investigating the discrepancy for different models when applied in the magnetic hyperthermia context. This study compares four different bio-heat equations in terms of the therapeutic temperature distribution and the heat-induced damage situation for a proposed geometric model, which is established based on computed tomography images of a tumor bearing mouse. The therapeutic temperature is also used as an index to evaluate the effect of two key relaxation times for the phase lag behavior on bio-heat transfer. Moreover, this work evaluates the effects of two blood perfusion rates on both the treatment temperature and the cumulative equivalent heating minutes at 43 °C. Numerical analysis results reveal that relaxation times for phase-lag behavior as well as the porosity for living tissues directly affect the therapeutic temperature variation and ultimately the thermal damage for the malignant tissue during magnetic hyperthermia. The dual-phase-lag equation can be converted into Pennes' equation and simple-phase-lag equation when relaxation times meet specific conditions during the process of heat transfer. In addition, different blood perfusion rates can result in an amplitude discrepancy for treatment temperature, but this parameter does not change the characteristics of thermal propagation during therapy.

ASAS-NANP symposium: mathematical modeling in animal nutrition: agent-based modeling for livestock systems: the mechanics of development and application.

Over the last three decades, agent-based modeling/model (ABM) has been one of the most powerful and valuable simulation-based decision modeling techniques used to study the complex dynamic interactions between animals and their environment. ABM is a relatively new modeling technique in the animal research arena, with immense potential for routine decision-making in livestock systems. We describe ABM's fundamental characteristics for developing intelligent modeling systems, exemplify its use for livestock production, and describe commonly used software for designing and developing ABM. After that, we discuss several aspects of the developmental mechanics of an ABM, including (1) how livestock researchers can conceptualize and design a model, (2) the main components of an ABM, (3) different statistical methods of analyzing the outputs, and (4) verification, validation, and replication of an ABM. Then, we perform an overall analysis of the utilities of ABM in different subsystems of the livestock systems ranging from epidemiological prediction to nutritional management to livestock market dynamics. Finally, we discuss the concept of hybrid intelligent models (i.e., merging real-time data streams with intelligent ABM), which have applications in artificial intelligence-based decision-making for precision livestock farming. ABM captures individual agents' characteristics, interactions, and the emergent properties that arise from these interactions; thus, animal scientists can benefit from ABM in multiple ways, including understanding system-level outcomes, analyzing agent behaviors, exploring different scenarios, and evaluating policy interventions. Several platforms for building ABM exist (e.g., NetLogo, Repast J, and AnyLogic), but they have unique features making one more suitable for solving specific problems. The strengths of ABM can be combined with other modeling approaches, including artificial intelligence, allowing researchers to advance our understanding further and contribute to sustainable livestock management practices. There are many ways to develop and apply mathematical models in livestock production that might assist with sustainable development. However, users must be experienced when choosing the appropriate modeling technique and computer platform (i.e., modeling development tool) that will facilitate the adoption of mathematical models by certifying that the model is field-ready and versatile enough for untrained users.

Agent-based modeling (ABM) is a well-known simulation technique that decision-makers of livestock systems can use to develop holistic, long-term, and well-informed decisions. This modeling technique facilitates the investigation of complex systems of different individuals, given its capability to simulate individual agents, their specific characteristics, and their inherent capacity to memorize individuals' past behaviors. Livestock systems are complex systems involving multiple stakeholders with collaborative and sometimes competing interests; thus, ABM might aid in achieving sustainability goals of interest to livestock systems. The modeling processes involved in developing a generic ABM and its utilities are described, so that livestock researchers can build multiple models customized for their research needs. We discuss numerous software platforms that livestock systems modelers can utilize towards this goal. A brief overview of the state-of-the-art ABM developed by different domain experts researching livestock systems was done so that decision modelers working in the field can use those models to conceptualize and design their models for their specific research needs. We also made a case for hybridizing the ABM with real-time data streaming technology to support precision livestock sensor initiatives to enhance the utility of agent-based models for real-time decision-making.

Influence of thermal relaxation time on thermomechanical interactions in biological tissue during hyperthermia treatment.

This study presents an analytical analysis of thermo-mechanical interactions within living tissues using a generalized biothermoelastic model with one thermal relaxation time. Utilizing Laplace transforms and associated techniques, we investigate the response of living tissue to a pulse boundary heat flux that decays exponentially on a traction-free surface. Through detailed graphical illustrations, we elucidate the influence of key parameters such as thermal relaxation time, blood perfusion rate, and the characteristic time of the pulsing heat flux on temperature distribution, displacement, and thermal strain. Our results are presented through comprehensive graphical representations. Furthermore, a parametric analysis is conducted to guide the selection of optimal design factors, enhancing the accuracy of hyperthermia treatments.

Hyperthermia therapy of cancerous tumor sitting in breast via analytical fractional model.

The heat transfer in bi-layer spherical composite region representing a cancerous tumor embedded in a homogenous muscle tissue (Andra et al., 1999; Yu and Jiang, 2019) is modeled by means of fractional energy equations with additional interface boundary constrictions. This hyperthermia problem was explored before in literature with proper hyperthermia experimental parameters and numerical simulations were later on devised by substituting the integer order energy model with the fractional order one. In order to match the experimental data to the fractional model, the order of fractional derivative was determined after a laborious inverse solution scheme. Here, we obtain exact analytical solutions to the fractional hyperthermia problem which is shown to be controlled by four thermal parameters corresponding to each fractional order derivative. The spatio-temporal distribution of temperature within the tumor-tissue medium is then studied via the closed-form solutions. From the solutions, the anomalous heat diffusion process for early and late exposure times is detected. The best derivative of fractional order is eventually determined by matching the experimental temperature to analytically derived one here. Excellent agreement with the numerically fitted fractional value is observed. The present approach is eventually extended to a more realistic situation in which the perfusion of blood relative to tumor and skin zone is taken into account. The presented analytical expressions are further beneficial to elaborately alternate the optimized operational thermal parameters of desire during a hyperthermia treatment of different kind tumors.

Numerical simulation of burn injuries with temperature-dependent thermal conductivity and metabolism under different surface heat sources.

In the present paper, the phenomena of heat transport inside human forearm tissue are studied through a one-dimensional nonlinear bioheat transfer model under the influence of various boundary and interface conditions. In this study, we considered temperature-dependent thermal conductivity and metabolic heat to predict temperature distribution inside the forearm tissue. We have studied the temperature distribution inside inner tissue and bone because it has been found that burn injuries are mostly affected by layer thickness. The temperature distribution inside human forearm tissue is analyzed using the finite difference and bvp4c numerical techniques. To examine the accuracy of present numerical code, we compare the obtained numerical result with the exact analytical result in a specific case and find an excellent agreement with the exact results. We also validated our present numerical code with a hybrid scheme based on Runge-Kutta (4,5) and finite difference technique and found it in good compliance. From the obtained results, we observed that the homogeneous heat flux has a greater impact on the temperature at the outer surface of the skin, but the sinusoidal heat flux has a greater impact on the temperature of the subcutaneous layer and inner tissue. It is found that there is no burn injury in the first type of heat source (Tw=44°C), but it may occur in the second and third types of heat sources. It has been observed that by raising the blood perfusion rate and reducing the values of reference metabolic heat, coefficient of thermal conductivity, and heat fluxes, we can manage and reduce burn injuries and achieve hyperthermia temperature.

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning System.

BACKGROUND: Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it is important to measure cellular or genetic features as a function of position along a zonal axis. While it is possible to manually count, characterize, and locate features in relation to the zonal axis, it is labor-intensive and difficult to do manually while maintaining precision and accuracy. METHODS: We addressed this challenge by developing a deep-learning-based quantification method called the "Tissue Positioning System" (TPS), which can automatically analyze zonation in the liver lobule as a model system. FINDINGS: By using algorithms that identified vessels, classified vessels, and segmented zones based on the relative position along the portal vein to central vein axis, TPS was able to spatially quantify gene expression in mice with zone specific reporters. INTERPRETATION: TPS could discern expression differences between zonal reporter strains, ages, and disease states. TPS could also reveal the zonal distribution of cells previously thought to be positioned randomly. The design principles of TPS could be generalized to other tissues to explore the biology of zonation. FUNDING: CPRIT (RP190208, RP220614, RP230330) and NIH (P30CA142543, R01AA028791, R01CA251928, R01DK1253961, R01GM140012, 1R01GM141519, 1R01DE030656, 1U01CA249245). The Pollack Foundation, Simmons Comprehensive Cancer Center Cancer & Obesity Translational Pilot Award, and the Emerging Leader Award from the Mark Foundation For Cancer Research (#21-003-ELA).

The cooling effect of blood flow during hyperthermia treatment.

The amount and duration of the applied heat in hyperthermia treatment are critical for cancer survivors. The challenge is to use a mechanism dealing with the tumor cells only while keeping healthy tissues unharmed. The aim of this paper is to predict the blood temperature distribution in main dimensions during hyperthermia process by deriving a new analytical solution of unsteady flow that adequately covers the cooling factor. We adopted a separation of variable method to solve the bio-heat transfer problem of unsteady blood flow. The solution is similar to Pennes' equation, except that it is for blood rather than tissue. We also performed computational simulations with varied flow conditions and thermal energy transports. The blood cooling effects were calculated with vessel's diameter, tumor's zone length, pulsating period and flow velocity. The cooling rate rises by around 133% if the tumor zone's length is extended four times the diameter of 0.5 (mm), but it is seemingly fixed with this distance if the diameter is equal or larger than 4 (mm). Likewise, the temporal variations of temperature disappear if the blood vessel has a diameter of 4 (mm) or more. Pre-heating or post-cooling techniques perform effectively given the theoretical solution; under particular conditions, the reduction percentages of the cooling effect are between 130% and 200%, respectively.

Physiologically based pharmacokinetic (PBPK) modelling of oral drug absorption in older adults - an AGePOP review.

The older population consisting of persons aged 65 years or older is the fastest-growing population group and also the major consumer of pharmaceutical products. Due to the heterogenous ageing process, this age group shows high interindividual variability in the dose-exposure-response relationship and, thus, a prediction of drug safety and efficacy is challenging. Although physiologically based pharmacokinetic (PBPK) modelling is a well-established tool to inform and confirm drug dosing strategies during drug development for special population groups, age-related changes in absorption are poorly accounted for in current PBPK models. The purpose of this review is to summarise the current state-of-knowledge in terms of physiological changes with increasing age that can influence the oral absorption of dosage forms. The capacity of common PBPK platforms to incorporate these changes and describe the older population is also discussed, as well as the implications of extrinsic factors such as drug-drug interactions associated with polypharmacy on the model development process. The future potential of this field will rely on addressing the gaps identified in this article, which can subsequently supplement in-vitro and in-vivo data for more robust decision-making on the adequacy of the formulation for use in older adults and inform pharmacotherapy.

Inversion of spatio-temporal distribution heat flux and reconstruction of transient temperature field of three-layered skin tissue during hyperthermia.

Hyperthermia (for example, high-intensity focused ultrasound, laser, radio-frequency) of cancerous cells from in vitro to in vivo requires accurately obtaining the heat distribution induced by external heating into the three-layered skin tissue. Obtaining the boundary heat flux into the three-layered skin tissue is a necessary condition to realize the measurement of tissue heat distribution. Considering the complexity of multiple boundary heat fluxes in spatio-temporal distribution, this study proposes an inversion scheme to predict the spatio-temporal distribution of multiple boundary heat fluxes into the three-layered skin tissue. In the inversion scheme, a multivariable prediction model is established to solve the spatio-temporal coupling problem between the inversed boundary heat flux and measurement temperature information. Furthermore, based on the dependence between the predicted temperature and inversed boundary heat flux, the inversion system is constructed to realize the simultaneous optimization inversion of multiple boundary heat fluxes in spatio-temporal distribution. To examine the feasibility and effectiveness of inversion scheme, numerical experiments are carried out to discuss the influence of future time steps and measurement errors on the inversion results of boundary heat flux. In addition, the transient temperature field of three-layered skin tissue is reconstructed by inversed boundary heat flux, which could provide an economical, effective, and non-invasive solution for the measurement of thermal field of three-layered skin tissue during hyperthermia.

Impact of Grape Seed Powder and Black Tea Brew on Lipid Digestion-An In Vitro Co-Digestion Study with Real Foods.

Effects of two foods with bioactive constituents (black tea brew, BTB and grape seed powder, GSP) on lipid digestibility was studied. Lipolysis inhibitory effect of these foods was examined using two test foods (cream and baked beef) with highly different fatty acid (FA) composition. Digestion simulations were performed either using both gastric and pancreatic lipase, or only with pancreatic lipase according to the Infogest protocol. Lipid digestibility was assessed based on the bioaccessible FAs. Results showed the triacylglycerols containing short- and medium-chain FAs (SCFA and MCFA) are non-preferred substrates for pancreatic lipase; however, this is not characteristic for GL. Our findings suggest that both GSP and BTB primarily affect the lipolysis of SCFAs and MCFAs, because the dispreference of pancreatic lipase towards these substrates was further enhanced as a result of co-digestion. Interestingly, GSP and BTB similarly resulted in significant decrease in lipolysis for cream (containing milk fat having a diverse FA profile), whereas they were ineffective in influencing the digestion of beef fat, having simpler FA profile. It highlights that the characteristics of the dietary fat source of a meal can be a key determinant on the observed extent of lipolysis when co-digested with foods with bioactive constituents.

Hollow-fibre system model of tuberculosis reproducibility and performance specifications for best practice in drug and combination therapy development.

BACKGROUND: The hollow-fibre system model of tuberculosis (HFS-TB) has been endorsed by regulators; however, application of HFS-TB requires a thorough understanding of intra- and inter-team variability, statistical power and quality controls. METHODS: Three teams evaluated regimens matching those in the Rapid Evaluation of Moxifloxacin in Tuberculosis (REMoxTB) study, plus two high-dose rifampicin/pyrazinamide/moxifloxacin regimens, administered daily for up to 28 or 56 days against Mycobacterium tuberculosis (Mtb) under log-phase growth, intracellular growth or semidormant growth under acidic conditions. Target inoculum and pharmacokinetic parameters were pre-specified, and the accuracy and bias at achieving these calculated using percent coefficient of variation (%CV) at each sampling point and two-way analysis of variance (ANOVA). RESULTS: A total of 10 530 individual drug concentrations, and 1026 individual cfu counts were measured. The accuracy in achieving intended inoculum was >98%, and >88% for pharmacokinetic exposures. The 95% CI for the bias crossed zero in all cases. ANOVA revealed that the team effect accounted for <1% of variation in log10 cfu/mL at each timepoint. The %CV in kill slopes for each regimen and different Mtb metabolic populations was 5.10% (95% CI: 3.36%-6.85%). All REMoxTB arms exhibited nearly identical kill slopes whereas high dose regimens were 33% faster. Sample size analysis revealed that at least three replicate HFS-TB units are needed to identify >20% difference in slope, with a power of >99%. CONCLUSIONS: HFS-TB is a highly tractable tool for choosing combination regimens with little variability between teams, and between replicates.

The Importance of Subcellular Structures to the Modeling of Biological Cells in the Context of Computational Bioelectromagnetics Simulations.

Numerical investigation of the interaction of electromagnetic fields with eukaryotic cells requires specifically adapted computer models. Virtual microdosimetry, used to investigate exposure, requires volumetric cell models, which are numerically challenging. For this reason, a method is presented here to determine the current and volumetric loss densities occurring in single cells and their distinct compartments in a spatially accurate manner as a first step toward multicellular models within the microstructure of tissue layers. To achieve this, 3D models of the electromagnetic exposure of generic eukaryotic cells of different shape (i.e. spherical and ellipsoidal) and internal complexity (i.e. different organelles) are performed in a virtual, finite element method-based capacitor experiment in the frequency range from 10 Hz to 100 GHz. In this context, the spectral response of the current and loss distribution within the cell compartments is investigated and any effects that occur are attributed either to the dispersive material properties of these compartments or to the geometric characteristics of the cell model investigated in each case. In these investigations, the cell is represented as an anisotropic body with an internal distributed membrane system of low conductivity that mimics the endoplasmic reticulum in a simplified manner. This will be used to determine which details of the cell interior need to be modeled, how the electric field and the current density will be distributed in this region, and where the electromagnetic energy is absorbed in the microstructure regarding electromagnetic microdosimetry. Results show that for 5 G frequencies, membranes make a significant contribution to the absorption losses. © 2023 The Authors. Bioelectromagnetics published by Wiley Periodicals LLC on behalf of Bioelectromagnetics Society.

A novel strategy for dynamic modeling of genome-scale interaction networks.

MOTIVATION: The recent availability of omics data allows the construction of holistic maps of interactions between numerous role-playing biomolecules. However, these networks are often static, ignoring the dynamic behavior of biological processes. On the other hand, dynamic models are commonly constructed on small scales. Hence, the construction of large-scale dynamic models that can quantitatively predict the time-course cellular behaviors remains a big challenge. RESULTS: In this study, a pipeline is proposed for the automatic construction of large-scale dynamic models. The pipeline uses a list of biomolecules and their time-course trajectories in a given phenomenon as input. First, the interaction network of the biomolecules is constructed. To state the underlying molecular events of each interaction, it is translated into a map of biochemical reactions. Next, to define the kinetics of the reactions, an ordinary differential equation (ODE) is generated for each involved biomolecule. Finally, the parameters of the ODE system are estimated by a novel large-scale parameter approximation method. The high performance of the pipeline is demonstrated by modeling the response of a colorectal cancer cell line to different chemotherapy regimens. In conclusion, Systematic Protein Association Dynamic ANalyzer constructs genome-scale dynamic models, filling the gap between large-scale static and small-scale dynamic modeling strategies. This simulation approach allows for holistic quantitative predictions which are critical for the simulation of therapeutic interventions in precision medicine. AVAILABILITY AND IMPLEMENTATION: Detailed information about the constructed large-scale model of colorectal cancer is available in supplementary data. The SPADAN toolbox source code is also available on GitHub (https://github.com/PooyaBorzou/SPADAN). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.