INTRODUCTION:

5-Fluorouracil (5-FU) is one of the oldest chemotherapeutic drugs, and is still widely used for the treatment of many solid tumor malignancies such as colorectal, breast and head and neck cancer^1,2. As it has been postulated, 5-FU, an antimetabolite, acquires its cytotoxic profile primarily through its inhibition of thymidylate synthase and incorporation of its metabolites into RNA and DNA, effectively interfering with nucleic acids synthesis and function³. In spite of its extensive usage and effectiveness curing metastatic colorectal cancer, the clinical usage of 5-FU remains complicated by both the pharmacokinetic and pharmacodynamic differences between patients^4,5.

Thus, the efficacy and toxicity of 5-FU are connected with its pharmacokinetics which may greatly vary according to genetic and environmental factors⁶. The activity of DPD, the chief enzyme for the catabolism of 5-FU, is one of the key barometers that determine the rate of metabolism of 5-FU⁷. DPD, encoded by DPYD gene, is reported to metabolize about 80-85% of 5-FU to the inactive product dihydrofluorouracil⁸. Therefore, changes in DPD activity affect plasma concentrations of 5-FU and its safety and toxic effects.

DPD, which refers to a lower or complete lack of DPD enzyme activity, is estimated to occur in 3-5% of people of the population⁹. This genetic polymorphism result in severe and even potential lethal toxic effects when normal doses of 5-FU is administered¹⁰. These patients can have an increased risk of myelosuppression, mucositides, neurotoxicity, and in serious cases may die due to higher exposure to 5-FU when they are partially or completely deficient in DPD^11,12. The clinical relevance of DPD deficiency in 5-FU based chemotherapy has been a topic of perennial interest and several researchers have shown that deficiency leads to high toxicity rates and poor drug tolerance^13,14.

The realization of the role of DPD deficiency in the metabolism of 5-FU has prompted many researches to explore ways on adjustment of the individual dosage regimens based on DPD activity¹⁵. These efforts are coupled with a paradigm shift in oncology through precision medicine: the development of an individualized medical treatment plan designed to optimize the therapeutic benefit, while minimizing associated toxicity, based on genetic variables^16,32.

Pharmacometric simulations have emerged as a valuable tool in optimizing drug dosing Pharmacometric simulations are fast becoming useful in determining the right dosage regimens, especially for drugs having small Therapeutic Window like 5-FU^17,18,19,34. These pharmacokinetic simulations can combine the concept of modeling with addressable patient characteristics in order to accurately replicate drug exposure and therefore inform dose modification to achieve the best therapeutic endpoints with the least possible toxicity²⁰. The use of pharmacometrics in oncology has recently been growing increased with several works that have shown that pharmacometrics can contribute to the definition of new dosing regimens for several chemotherapeutic agents ^21,22.

Pharmacometric strategies as part of dose individualization of 5-FU in patients are well documented especially with regard to the measure at pharmacokinetic level such like AUC²³. As a sum drug concentration response vs time graph the AUC has been found to reflect the efficacy and toxicity of a dosing regimen of more complex drugs like 5-FU²⁴. Earlier works set a therapeutic AUC window of 20-30mg.h/l for 5-FU; apparent efficacy levels at below the therapeutic range were predicted, whereas any toxicity levels beyond the range were also predicted^25,26.

Pharmacokinetic modeling that can enhance the dosing of 5-FU combined with therapeutic drug monitoring in managing the drug combination have being practiced and documented to have enhanced treatment outcomes. Gamelin et al showed in a significant study that local dose adjustment according to pharmacokinetic follow-up should be significantly superior to conventional dosing concerning and objective response rate, trend toward longer survival and toxicity. Subsequent work has supported these refinements with other research emphasizing the possible advantages of using pharmacokinetically-driven dosing of 5-FU based chemotherapy.

However, the best management of risk linked to 5-FU administration in patient with DPD deficiency is still a matter of further research and discussion. Whereas, some guidelines support the strategy of genotyping DPYD at admission to disclose the patients at high risk of severe toxicity, others prefer storing genetic data along with phenotypic assessment of DPD activity^31,35-37. The pharmacometric models for DPD deficiency that would fully reflect clinical reality could help to better individualize 5-FU doses for these patients.

Consequently, the present study seeks to fill this knowledge gap through the use of pharmacometric simulations in order to assess the effect of DPD deficiency on the pharmacokinetics of 5-FU. To this end, we built a one-compartment open model for intravenous infusion administration to poss the AUC of normal DPD activity and DPD-deficient populations. This strategy makes it possible to assess pharmacokinetic profiles of candidate compounds in a large number of virtual patients – a benefit that yields substantive data on disparities between the genders.

Furthermore, we aimed to propose an optimal 5-FU dosage regimen for DPD-deficient patients based on these simulations, with the goal of achieving target AUC values within the established therapeutic range of 20-30 mg.h/l. By simulating dose adjustments and their impact on AUC, we sought to develop a rational, pharmacokinetically guided approach to dose reduction in DPD-deficient patients that balances efficacy and safety considerations.

This study augments the current literature regarding the application of pharmacokinetic modeling and TDM in oncology practice. In using the following strategies in 5-FU dosing especially for patient with DPD deficiency, we hope to manipulate the therapeutic index of the drug in an attempt to obtain better cancer therapeutic end result.

The study results could be useful to clinicians and improve existing or create new sets of directives concerning 5-FU treatment for patients with or at risk for DPD deficiency. Furthermore, the approach used in this study can act as a guide when conducting other studies on other CIs that have huge pharmacokinetic variability like the present chemotherapeutic drug.

Thus, the current work can be considered as a contribution towards achieving the goal of precision oncology. In order to positively impact the safety and efficacy of cancer chemotherapy as part of an emerging era of personalized treatment³⁰, this study seeks to employ pharmacometric simulations of 5-FU dosing in patients with DPD deficiency.

METHODOLOGY:

Ethical Approval:

The study uses PopPK models of 5-FU, adjusted pharmacokinetic parameter for DPD deficient group, particularly CL to generate a representative population for analysis. No real-time patient or patient-specific information was used, allowing no requirement of ethical approval for the study.

Simulation Methodology:

The study aimed to explore the potential association between DPD deficient activity for 5-FU in its pharmacokinetics to do the dosage adjustments for the DPD Deficient population group. Monte Carlo simulations were conducted using Pumas.ai ²⁷, a cloud-based software that operates on Julia Hub in the programming language Julia to derive expected plasma concentrations for both normal and DPD deficient scenarios and calculation of AUC (0-∞) as well.

CL is calculated as 101.1 l/h using the formula Cl = Dose/AUC, based on the dose and AUC given in the literature ²⁸ for an Indian population. This Cl of 101.1 l/hr is considered for normal DPD activity patients and the literature supports that there is a 30% reduction in the Cl value for the patients with deficient DPD activity, so for DPD deficient activity population Cl is reduced 30% and calculated as 70.77 l/h. There is no effect on Vd for DPD deficient, so the reported 12 l is used for both normal and DPD deficient for the simulation of time vs plasma concentration data for both groups.

The rate process was quantified using pharmacokinetic equations of the one-compartment open model following intravenous infusion administration. Input values for predefined parameters and clearance models were given based on literature estimates²⁸. A dosage regimen of 400 mg/m² and 2400mg/m² was employed in Pumas.ai to estimate the observed concentrations (DV) and the CONC derived from the model. Dosage regimen of 640mg followed by 3840mg was considered for simulation, accounting for the BSA of 1.6 m². The defined model was used to simulate 1000 virtual patients in each population such as normal and DPD deficient population groups having different inputs in the CL of 101.1 l/h and 70.77 l/h accounting 30% reduction of Cl in DPD deficient population group.

Subject-specific pharmacokinetic values were estimated using pumas.ai and used to improve the decision on the dosing of 5-FU in DPD deficient population group. The simulations were conducted by collecting samples virtually at every 2 hours for 48 hours and the simulated time vs plasma concentration profile was extracted into .csv file. Then using the simulated time vs plasma concentration profile, AUC (0-∞) was calculated using pumas.ai

Box plots were made and the AUC (0-∞) were then analysed relative to the therapeutic window of 5-FU, which falls between 20-30mg.h/l. Using these results, the percentage dose needs to be reduced for DPD deficient population was calculated based on its therapeutic window. The dose was reduced accordingly and the simulations were re-run with calculated new dose. The unpaired t-Test between before and after dose adjustment in DPD deficient group was done to show the statistical significance (p<0.001) in AUC (0-∞). Respectable AUC(0-∞) values found regarding each regimen produced a box plot data which was determined from the most effective regimen.

RESULTS:

As indicated in Table 1, time vs plasma concentration data of 5-FU were simulated for total of 1,000 patients over a 48-hour period, with an initial dosage of 640mg followed by 3,840mg administered to both normal and DPD deficient population group. The simulated data used to calculate AUC (0-∞), this AUC (0-∞) data revealed a 37.25% difference in AUC (0-∞) between the normal population and DPD deficient population before dosage adjustment. Consequently, the dosage was reduced by 37.25%, resulting in a new dose of 2,410 mg, which was subsequently simulated for time vs plasma concentration and then calculated the new AUC (0-∞) for the adjusted dose, Table 1 also indicates the inputs necessary for the simulation of time vs plasma concentration data of 5-FU after dose adjustment. The simulated data for these adjusted doses, yield new mean AUC (0-∞) of 24.84mg.h/l, comfortably within the target AUC (0-∞) range of 20-30mg.h/l, providing critical insights into the pharmacokinetics of 5FU following dosage modifications.

The mean and SD of AUC (0-∞) prior to and post dosage adjustment of 5-Fluorouracil in normal population and DPD deficient population are depicted in Table 2. The unpaired t-Test between before and after dose adjustment in DPD deficient group shows that they are statistically significant, p<0.001 in AUC (0-∞). A satisfactory decrease in the AUC (0-∞) was confirmed thereby reducing the risk of toxicity.

Table 2: Comparison of the Mean ± SD of simulated AUC (0-∞) prior to and post dosage adjustment

AUC (0-∞)	Normal population	DPD Deficient activity population
Prior dosage adjustment	29.14 ± 39.35	42.46 ± 55.46
Post dosage adjustment	29.14 ± 39.35	24.84 ± 24.40

By using the AUC (0-∞) data from normal and DPD deficient data, box plots were plotted to compare between groups, Figure 1 represents the box plot between the normal and DPD deficient group prior to dosage adjustment, where the mean of normal group is 29.14mg.h/l and the DPD deficient group is 43.46 mg.h/l clearly represents the mean of DPD deficient group not lies in the therapeutic range of 20- 30mg.h/l, whereas in figure 2 represents the box plots of the groups after dose adjustment, where the mean AUC (0-∞) of DPD deficient group falls within the therapeutic range i.e., 24.84mg.h/l.

Figure 1: Mean AUC (0-∞) of 5- fluorouracil in Normal population and DPD deficient population prior dosage adjustment

Figure 2: Mean AUC (0-∞) of 5- fluorouracil in normal population and DPD deficient population post dosage adjustment

DISCUSSION:

A pharmacometric approach to do these simulations was performed to determine the pharmacokinetics of 5-FU in DPD deficient population and to propose an optimal dosing regimen for the DPD deficiency population. These results bring an importance to have personalized dosing strategies in oncology, especially in the case of DPD deficient patients. The simulations conducted during the current research clearly demonstrate a significant difference between AUC (0-∞) values of DPD normal and DPD deficient patients after the standard administration of 5-FU at dosages 400mg/m² followed by 2400mg/m². Much higher AUC(0-∞) values reported in the DPD deficient population signify the significant role of this deficiency enzyme in 5-FU metabolism. This finding is in accord with previous clinical observations and case reports of severe toxicity in DPD deficient patients who are receiving the standard 5-FU doses.⁷. The 37.25% dose intensification in the DPD deficient group, so that the target AUC (0-∞) of 20-30mg.h/l can be attained, brings to the fore the critical impact of DPD deficiency on the pharmacokinetics of 5-FU. Such a high dose adjustment justifies the risk of throwing all patients on the same scale and points out the pre-treatment potential value of gene testing with 5-FU. Therapeutic AUC values were achieved in both populations after dose adjustment, with an important demonstration of feasibility and importance of personalized dosing strategy. The adjusted dose of 400mg/m² followed by 1500mg/m² (total 2410mg) differed considerably from standard dosing protocols for DPD-deficient patients. This study findings support routine DPD genotyping or phenotyping before commencing 5-FU treatment. Doing so may possibly avoid serious adverse toxicity in DPD-deficient patients¹¹. The authors further stress that there is a need for flexible dosing protocols through which the dosing strategy would be flexed according to the DPD status of the patient. The oncology departments should think of standardizing the algorithms for the doses to be given for those in whom DPD deficiency may occur. Although our simulations provide a solid basis for dose adjustment, incorporation of TDM into clinical practice may fine-tune the dosing in an individual. The strategy of repeatedly monitoring plasma concentrations of 5-FU really could allow a real-time adjustment of the dose, striving as best as possible to move that balance between efficacy and toxicity.²³ Healthcare providers should therefore educate patients on the role of DPD testing and future personalized dosing. This could improve compliance with treatment and further involve the patient in their care²⁹. The pharmacometric simulations of this study allow the exploration of dosing strategies in a high number of virtual patients without actually submitting actual patients to potential risks. The approach is of excellent value for drugs whose dosing problems are somewhat similar to the case of rare genetic variations, such as DPD deficiency, under which the conduction of large-scale clinical trials may be quite difficult. However, limitations of such a simulation-based approach must not be forgotten. Despite being built on literatures derived pharmacokinetic parameters, all potential variability that would be present in actual patient populations may not have been captured. Co-medications, comorbidities, and different degrees of DPD deficiency can influence 5-FU pharmacokinetics in ways our model has not accounted for fully. Future directions, should be focused on validating the recommended dosing regimen in DPD deficient patients with prospective real time patients and to do TDM for confirmation of their safety and efficacy. Also, further expansion of genetic profiling with other variations in metabolism pathways of 5-FU may more precisely determine the dosing strategies based on individual needs³³. While likely integrating the DPD status with other factors of prediction, including age, sex, and body composition, may lead to more accurate dosing algorithms, an economic analysis from the comparison of cost-effectiveness between routine DPD testing and personalized dosing versus standard approaches may be quite insightful in the healthcare policy. Finally, the principles and methodologies used in this study should be extrapolated to other fluoropyrimidine drugs also metabolized by DPD to further extend the impact of such research on treatment strategies for cancer.

CONCLUSION:

This study shows that when DPD- deficient patients receive an initial dosing regimen of 400mg/m² followed by 2400mg/m², the AUC (0-∞) of the drug is much higher than that of patients with normal DPD activity. which suggests that dose adjustment in patients with DPD deficiency may help to reduce toxicity. A dose reduction by 37.25% was needed to achieve mean AUC (0-∞) within the therapeutic window of 20-30mg.h/l at steady state. Both DPD-deficient and normal DPD activity patients had comparable normal AUC values after the dose was adjusted to 400mg/m² followed by 1500mg/m² (2410mg) and emphasize the finding of dosing for DPD-deficient patients to achieve both adequate therapeutic effects and toxicity.

CONFLICTS OF INTEREST:

All authors declare that they have no conflict of interest

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Received on 19.11.2024 Revised on 11.05.2025

Accepted on 18.07.2025 Published on 01.12.2025

Available online from December 06, 2025

Research J. Pharmacy and Technology. 2025;18(12):6059-6064.

DOI: 10.52711/0974-360X.2025.00876

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

Parameter	Normal population	DPD Deficient activity population (Prior)	DPD Deficient activity population (Post)
Total no. of simulated patients	1000	1000	1000
Dose of 5-FU (mg)	640mg followed by 3840mg	640mg followed by 3840mg	640mg followed by 2410mg
Plasma concentration time points (mg/l)	0-48hrs	0-48hrs	0-48hrs
Clearance (l/h)	101.1	70.17	70.17
Volume (l)	12	12	12