Machine-Learning Exploration of Exposure-Effect Relationships of Cisplatin in Head and Neck Cancer Patients.

BACKGROUND: Cisplatin is a pivotal drug in the treatment of head and neck cancer, and personalized dosage should help the preservation of an optimal toxicity-efficacy ratio. METHODS: We analyzed the exposure-effect relationships of 80 adult patients with head and neck cancers and treated with standard Cisplatin-based regimen administered as three-hour infusion. Individual pharmacokinetics (PK) parameters of Cisplatin were identified using a Bayesian approach. Nephrotoxicity and ototoxicity were considered as typical Cisplatin-related toxicities according to Common Terminology Criteria for Adverse Events (CTCAE) standards. Efficacy was evaluated based upon Response Evaluation Criteria in Solid Tumors (RECIST) criteria. Up to nine different machine-learning algorithms were tested to decipher the exposure-effect relationships with Cisplatin. RESULTS: The generalized linear model was the best algorithm with an accuracy of 0.71, a recall of 0.55 and a precision of 0.75. Among the various metrics for exposure (i.e., maximal concentration (Cmax), area-under-the-curve (AUC), trough levels), Cmax, comprising a range between 2.4 and 4.1 µg/mL, was the best one to be considered. When comparing a consequent, model-informed dosage with the standard dosage in 20 new patients, our strategy would have led to a reduced dosage in patients who would eventually prove to have severe toxicities while increasing dosage in patients with progressive disease. CONCLUSION: Determining a target Cmax could pave the way for PK-guided precision dosage with Cisplatin given as three-hour infusion.

An Investigation of O-Demethyl Tramadol/Tramadol Ratio for Cytochrome P450 2D6 Phenotyping: The CYTRAM Study.

Cytochrome P450 2D6 (CYP2D6) gene polymorphisms influence the exposure to tramadol (T) and its pharmacologically active metabolite, O-demethyl tramadol (O-dT). Tramadol has been considered as a candidate probe drug for CYP2D6 phenotyping. The objective of the CYTRAM study was to investigate the value of plasma O-dT/T ratio for CYP2D6 phenotyping. European adult patients who received IV tramadol after surgery were included. CYP2D6 genotyping was performed and subjects were classified as extensive (EM), intermediate (IM), poor (PM), or ultra-rapid (UM) CYP2D6 metabolizers. Plasma concentrations of tramadol and O-dT were determined at 24 h and 48 h. The relationship between O-dT/T ratio and CYP2D6 phenotype was examined in both a learning and a validation group. Genotype data were obtained in 301 patients, including 23 PM (8%), 117 IM (39%), 154 EM (51%), and 7 UM (2%). Tramadol trough concentrations at 24 h were available in 297 patients. Mean value of O-dT/T ratio was significantly lower in PM than in non-PM individuals (0.061 ± 0.031 versus 0.178 ± 0.09, p < 0.01). However, large overlap was observed in the distributions of O-dT/T ratio between groups. Statistical models based on O-dT/T ratio failed to identify CYP2D6 phenotype with acceptable sensitivity and specificity. Those results suggest that tramadol is not an adequate probe drug for CYP2D6 phenotyping.

Implementation of Model-Based Dose Adjustment of Tobramycin in Adult Patients with Cystic Fibrosis.

Therapeutic drug monitoring (TDM) of tobramycin is widely performed in patients with cystic fibrosis (CF), but little is known about the value of model-informed precision dosing (MIPD) in this setting. We aim at reporting our experience with tobramycin MIPD in adult patients with CF. We analyzed data from adult patients with CF who received IV tobramycin and had model-guided TDM during the first year of implementation of MIPD. The predictive performance of a pharmacokinetic (PK) model was assessed. Observed maximal (Cmax) and minimal (Cmin) concentrations after initial dosing were compared with target values. We compared the initial doses and adjusted doses after model-based TDM, as well as renal function at the beginning and end of therapy. A total of 78 tobramycin courses were administered in 61 patients. After initial dosing set by physicians (mean, 9.2 ± 1.4 mg/kg), 68.8% of patients did not achieve the target Cmax ≥ 30 mg/L. The PK model fit the data very well, with a median absolute percentage error of 4.9%. MIPD was associated with a significant increase in tobramycin doses (p < 0.001) without significant change in renal function. Model-based dose suggestions were wellaccepted by the physicians and the expected target attainment for Cmax was 83%. To conclude, the implementation of MIPD was effective in changing prescribing practice and was not associated with nephrotoxic events in adult patients with CF.

How a Patient Personalised Clinical Pharmacy Programme Can Secure Therapeutic Care in an Orthogeriatric Care Pathway (5P Project)?

BACKGROUND: A new model was developed for integrating a personalised clinical pharmacy programme (5P project) into the orthogeriatric care pathway. OBJECTIVE: To secure the therapeutic care of orthogeriatric patients. DESIGN AND SETTING: Prospective descriptive study in a multisite teaching hospital from June 2019 to January 2020. SUBJECTS: Patients aged ≥75 years admitted for hip fracture. METHODS: A prescription review was performed for all patients at inclusion. Other clinical pharmacy activities (additional prescription review, pharmaceutical interviews, medication reconciliation) were dedicated to "high-risk" patients. Potential medication errors (ME), either pharmaceutical interventions (PI) or unintentional discrepancies (UID), were recorded. The potential clinical impact of PI was evaluated by a pluriprofessional expert panel using a validated tool. RESULTS: In the 455 patients included, 955 potential ME were detected, that is ≥1 potential ME for 324/455 (71%) patients. In acute care, 561 PI were formulated during prescription review for 440/455 (97%) patients and 348/561 (62%) were accepted by physicians. Medication reconciliation was performed for 213 patients, 316 UID were identified. In rehabilitation units, a second prescription review was performed for 112/122 (92%) "high-risk" patients, leading to 61 PI. The clinical impact was evaluated for 519/622 (83%) PI. A consensus was obtained for 310/519 (60%) PI: 147/310 (47%) were rated as having minor clinical impact, 138/310 (45%) moderate, 22/310 (7%) major, 2/310 (0.6%) vital, and 1/310 (0.3%) null. CONCLUSION: The 5P project secured the orthogeriatric care pathway by detecting a great number of potential ME, including PI mostly considered as having a significant clinical impact.

Population Pharmacokinetic Modeling and Dosing Simulations of Tobramycin in Pediatric Patients with Cystic Fibrosis.

Initial dosing and dose adjustment of intravenous tobramycin in children with cystic fibrosis (CF) is challenging. The objectives of this study were to develop nonparametric population pharmacokinetic (PK) models of tobramycin in children with CF to be used for dosage design and model-guided therapeutic drug monitoring. We performed a retrospective analysis of tobramycin PK data in our children's CF center. The Pmetrics package was used for nonparametric population PK analysis and dosing simulations. Both the ratios of maximal concentration to the MIC (Cmax/MIC) and daily area under the concentration-time curve to the MIC (AUC24/MIC) were considered efficacy targets. Trough concentration (Cmin) was considered the safety target. A total of 2,884 tobramycin concentrations collected in 195 patients over 9 years were analyzed. A two-compartment model including total body weight, body surface area, and creatinine clearance as covariates best described the data. A simpler model was also derived for implementation in the BestDose software to perform Bayesian dose adjustment. Both models were externally validated. PK/pharmacodynamics (PD) simulations with the final model suggest that an initial dose of tobramycin of 15 to 17.5 mg/kg/day was necessary to achieve Cmax/MICs of ≥10 for MICs up to 2 mg/liter in most patients. The AUC24/MIC target was associated with higher dosage requirements and higher Cmin. A daily dose of 12.5 mg/kg would optimize both efficacy and safety target attainment. We recommend performing tobramycin therapeutic drug monitoring (TDM), model-based dose adjustment, and MIC determination to individualize intravenous tobramycin therapy in children with CF.

Quantitative Prediction of Interactions Mediated by Transporters and Cytochromes: Application to Organic Anion Transporting Polypeptides, Breast Cancer Resistance Protein and Cytochrome 2C8.

BACKGROUND: The in vivo mechanistic static model (IMSM) is an effective method to predict the magnitude of drug-drug interactions (DDIs) mediated by cytochromes. OBJECTIVE: The aim of this study was to extend the IMSM paradigm to DDIs mediated by organic anion transporting polypeptide (OATP) 1Bs, breast cancer resistance protein (BCRP) and cytochrome 2C8. METHODS: First, a generic model for this kind of interaction was established, and a literature search was then conducted to retrieve the area under the concentration-time curve (AUC) ratio of a large set of DDIs involving OATP1B1, OATP1B3, BCRP and cytochromes 2C8 or 3A4. The model was fitted to the data to estimate the characteristic parameters (contribution ratios [CRs] and inhibition or induction potencies [IXs]) by nonlinear regression, and the model was qualified by external validation on a different dataset. Lastly, the model was used to identify the risks of overexposure by DDIs of this type. RESULTS: A total of 27 substrates, 26 inhibitors, 3 inducers and 3 genetic variants were considered in the regression analysis. The number of observations (AUC ratios, denoted as Robs) was 101. Forty-six CRs and 47 IXs were estimated. The proportions of predictions within 0.67- to 1.5-fold and 0.5- to twofold Robs were 90% and 99%, respectively, for the internal validation, and 78% and 96%, respectively, for the external validation. The median fold-error was 1.03 (the ideal value is 1). The interquartile range of fold-error was 0.31, and the relative standard error of parameter estimates was, at most, 17%. CONCLUSIONS: The IMSM approach was successfully extended to DDIs mediated by OATP1Bs, BCRP and cytochromes 2C8 or 3A4. The method revealed good predictive performances by internal and external validation.

Prediction of docetaxel toxicity in older cancer patients: a Bayesian network approach.

Chemotherapy is an essential therapy in the fight against cancer. Polypathology and polymedication are often encountered in elderly patients, making this population especially at risk for adverse drug reactions, and particularly with cytotoxic drugs. The objective of this study was to build a model to predict high-grade toxicity in elderly patients treated with docetaxel. Data from the trial TAX-108 have been used to create the model. The variable to predict was the occurrence of grade 3 or 4 toxicity. The explanatory variables entered in the model were anthropometric and biological characteristics of patients at inclusion; fragility criteria (SMAF, CIRS-G, performance status); location of the primary tumor; chemotherapy history, radiotherapy or surgery; weekly dose of docetaxel, cumulative dose administered. A Bayesian network model was developed using a global search procedure and an Expectation-Maximization algorithm. A 10-fold cross-validation was performed. A toxicity of grade 3 or higher was observed in 54% of patients. The variables providing the most information were the primary site (19.4%), the dose per course (17.5%), and albuminemia (13.1%). The area under the curve of the model obtained after cross-validation was 74 ± 1.4%. The model built allows classifying correctly 71.21 ± 0.9% of patients in our sample in the cross-validation procedure. The sensitivity and specificity of the model were 75 and 67%, respectively, and the positive and negative predictive values were 73 and 69%. The encouraging results from this first study show that Bayesian networks could help assess the benefit-risk ratio of chemotherapy in elderly patients.