Predicting Clinical Pharmacokinetics of Docetaxel in Cancer Patients Using an Advanced Kinetic Approach

Abstract

The pharmacokinetics of the commonly used chemotherapeutic drug, docetaxel varies significantly between individuals which makes it difficult to determine the best dosage and treatment outcomes for cancer patients. This study explores a data-driven, patient-specific approach to develop a predictive model for personalized therapy. Clinical data from different published studies were gathered and using this data, synthetic dataset was generated to reflect real-world interpatient variability in pharmacokinetic parameters such as, clearance, volume of distribution and area under the curve (AUC), along with other patient factors and clinical characteristics such as, age, gender, weight, cancer type and organ function. After generating synthetic dataset, this dataset was then validated using Python libraries, which enables exploratory data analysis (EDA) and visualization to evaluate biological possibility and clinical significance. Pharmacokinetic patterns were confirmed through correlation analyses, which includes strong inverse relationship between clearance and AUC, and positive correlation between Vd, weight and body surface area. Different predictive models were developed, such as Linear Regression model, Random Forest model, Gradient Boosting model and SVR, to predict AUC from patient-specific variables. Among all of these predictive models, Gradient Boosting model showed the best performance, R² is 0.83, which demonstrates that this model provides feasibility for using synthetic dataset and advanced analytics for the prediction of individualized dosing. This study demonstrates how pharmacokinetic research can benefit from the integration of artificial intelligence and synthetic data to aid in decision making. It strengthens the position of clinical pharmacists in personalized medicine and lays the groundwork for the creation of future instruments that can improve the safety and effectiveness of chemotherapy based on docetaxel.