In silico modeling for the risk assessment of toxicity in cells

Chaudhry, Qasim Ali; Abbas, Amna; Noor, Ayesha; Asif, Muqaddas

doi:10.1016/j.camwa.2018.09.006

“…( 6), was solved through discretising the cross section of a fibre into annuli (see Figure 2B and the Technical Supplementary Information). The model is solved using a finite volume method (FVM) discretization, for examples of this form of discretization in cancer growth and treatment see [51][52][53][54][55][56][57][58][59].…”

Section: Model Of Gemcitabinementioning

confidence: 99%

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model

Jenner

¹

,

Kelly

²

,

Dallaston

³

et al. 2022

Preprint

View full text Add to dashboard Cite

The prognosis for pancreatic ductal adenocarcinoma (PDAC) patients has not significantly improved in the past 3 decades, highlighting the need for more effective treatment approaches. Poor patient outcomes and lack of response to therapy can be attributed, in part, to the dense, fibrotic nature of PDAC tumours, which impedes the uptake of systemically administered drugs. Wet-spun alginate fibres loaded with the chemotherapeutic agent gemcitabine have been developed as a potential tool for overcoming the physical and biological barriers presented by the PDAC tumour microenvironment and deliver high concentrations of drug to the tumour directly over an extended period of time. While exciting, the practicality, safety, and effectiveness of these devices in a clinical setting requires further investigation. Furthermore, an in-depth assessment of the drug-release rate from these devices needs to be undertaken to determine whether an optimal release profile exists. Using a hybrid computational model (agent-based model and partial differential equation system), we developed a simulation of pancreatic tumour growth and response to treatment with gemcitabine loaded alginate fibres. The model was calibrated using in vitro and in vivo data and simulated using a finite volume method discretization. We then used the model to compare different intratumoural implantation protocols and gemcitabine-release rates. In our model, the primary driver of pancreatic tumour growth was the rate of tumour cell division and degree of extracellular matrix deposition. We were able to demonstrate that intratumoural placement of gemcitabine loaded fibres was more effective than peritumoural placement. Additionally, we found that an exponential gemcitabine release rate would improve the tumour response to fibres placed peritumourally. Altogether, the model developed here is a tool that can be used to investigate other drug delivery devices to improve the arsenal of treatments available for PDAC and other difficult-to-treat cancers in the future.Author SummaryPancreatic cancer has a dismal prognosis with a median survival of 3-5 months for untreated disease. The treatment of pancreatic cancer is challenging due to the dense nature of pancreatic tumours which impedes retention of drug at the tumour site. As such, systemic administration of chemotherapies, such as gemcitabine, has a limited efficacy. To overcome this, sustained-release devices have been proposed. These devices are injected locally and release drug slowly over time, providing a concentrated local, sustained drug concentration. To investigate the possible efficacy of these devices, we developed a mathematical model that would allow us to probe treatment perturbations in silico. We modelled the individual cancer cells and their growth and death from gemcitabine loaded into the sustained delivery devices. Our platform allows future investigations for these devices to be run in silico so that we may better understand the forms of the drug release-profile that are necessary for optimal treatment.

show abstract

“…In particular, the diffusion of drug within the fibre, Eq (2), was solved through discretising the cross section of a fibre into annuli (see Fig 2B and S1 Technical Supplementary Information). The model is solved using a finite volume method (FVM) discretisation, for examples of this form of discretisation in cancer growth and treatment see [62][63][64][65][66][67][68][69][70]. As part of the investigations of these fibres in this work, we chose to quantify the impact of varying the drug release profile to a constant release, exponential release, or sigmoidal release profiles.…”

mentioning

confidence: 99%

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model

Jenner

¹

,

Kelly

²

,

Dallaston

³

et al. 2023

View full text Add to dashboard Cite

The prognosis for pancreatic ductal adenocarcinoma (PDAC) patients has not significantly improved in the past 3 decades, highlighting the need for more effective treatment approaches. Poor patient outcomes and lack of response to therapy can be attributed, in part, to a lack of uptake of perfusion of systemically administered chemotherapeutic drugs into the tumour. Wet-spun alginate fibres loaded with the chemotherapeutic agent gemcitabine have been developed as a potential tool for overcoming the barriers in delivery of systemically administrated drugs to the PDAC tumour microenvironment by delivering high concentrations of drug to the tumour directly over an extended period. While exciting, the practicality, safety, and effectiveness of these devices in a clinical setting requires further investigation. Furthermore, an in-depth assessment of the drug-release rate from these devices needs to be undertaken to determine whether an optimal release profile exists. Using a hybrid computational model (agent-based model and partial differential equation system), we developed a simulation of pancreatic tumour growth and response to treatment with gemcitabine loaded alginate fibres. The model was calibrated using in vitro and in vivo data and simulated using a finite volume method discretisation. We then used the model to compare different intratumoural implantation protocols and gemcitabine-release rates. In our model, the primary driver of pancreatic tumour growth was the rate of tumour cell division. We were able to demonstrate that intratumoural placement of gemcitabine loaded fibres was more effective than peritumoural placement. Additionally, we quantified the efficacy of different release profiles from the implanted fibres that have not yet been tested experimentally. Altogether, the model developed here is a tool that can be used to investigate other drug delivery devices to improve the arsenal of treatments available for PDAC and other difficult-to-treat cancers in the future.

show abstract

Quantitative analysis of cancer risk assessment in a mammalian cell with the inclusion of mitochondria

Khalid

¹

,

Chaudhry

²

2019

Computers & Mathematics with Applications

View full text Add to dashboard Cite

In silico modeling for the risk assessment of toxicity in cells

Cited by 6 publications

References 14 publications

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model

Quantitative analysis of cancer risk assessment in a mammalian cell with the inclusion of mitochondria

Contact Info

Product

Resources

About