Randomized study of individualized pharmacokinetically-guided dosing of paclitaxel compared with body-surface area dosing in Chinese patients with advanced non-small cell lung cancer

From Prospective Evaluation to Practice: Model-Informed Dose Optimization in Oncology

One dose does not fit all, especially in oncolytic drugs, where side effects and therapy failures highlight the need for personalized dosing approaches. In recent years, the quest to apply model-informed precision dosing to oncology drugs has gained significant momentum, reflecting its potential to revolutionize patient care by tailoring treatments to individual pharmacokinetic profiles. Despite this progress, model-informed precision dosing has not (yet) become widely integrated into routine clinical care. We aimed to explain model-informed precision dosing from a clinical viewpoint while addressing all prospective model-informed precision dosing implementation and validation studies in the field of oncology. We identified 16 different drugs for which prospective model-informed precision dosing validation/implementation has been performed. Although these studies are mostly focused on attaining adequate drug exposures and reducing inter-individual variability, improved clinical outcomes after performing model-informed precision dosing were shown for busulfan, and high-dose methotrexate. Toxicities were significantly reduced for busulfan and cyclophosphamide treatment. In contrast, for carboplatin, for which model-informed precision dosing has been used in the Calvert formula, no prospective validation on outcomes was deemed necessary as the therapeutic window had been extensively validated. Model-informed precision dosing has shown to be of added value in oncology and is expected to significantly change dosing regimens in the future.

Therapeutic drug monitoring in anticancer agents: perspectives of Australian medical oncologists

BACKGROUND

In the development of anticancer agents for solid tumours, body surface area continues to be used to personalise dosing despite minimal evidence for its use over other dosing strategies. With the development of tyrosine kinase inhibitors and other oral targeted anticancer agents, dosing using therapeutic drug monitoring (TDM) is now utilised in many health systems but has had limited uptake in Australia.

AIM

To determine attitudes and barriers to the implementation of TDM among Australian oncologists.

METHODS

A comprehensive questionnaire was developed by the Dutch Pharmacology Oncology Group from semistructured interviews of stakeholders. Seventy-nine questions across seven domains were developed with three free-text responses. This was rationalised to 17 questions with three free-text responses for Australian medical oncologists who identified limited experience with TDM.

RESULTS

Fifty-seven responses were received, with 49 clinicians (86%) identifying limited experience of performing TDM in daily practice. Clinicians were positive (62-91% agree/strongly agree across seven questions) about the advantages of TDM. There was a mixed response for cost-effectiveness and scientific evidence being a barrier to implementation, but strong agreement that prospective studies were needed (75% agreed or strongly agreed); that national treatment guidelines would enable practice (80%) and that a 'pharmacology of oncolytics' education programme would be useful (96%) to provide knowledge for dose individualisation.

CONCLUSION

Despite the limited experience of TDM in oncology in Australia, medical oncologists appear positive about the potential benefit to their patients. We have identified three barriers to implementation that could be targeted for increased adoption of TDM in oncology in Australia.

Using maximum plasma concentration (Cmax) to personalize taxane treatment and reduce toxicity

Taxanes are a widely used class of anticancer agents that play a vital role in the treatment of a variety of cancers. However, toxicity remains a major concern of using taxane drugs as some toxicities are highly prevalent, they can not only adversely affect patient prognosis but also compromise the overall treatment plan. Among all kinds of factors that associated with taxane toxicity, taxane exposure has been extensively studied, with different pharmacokinetic (PK) parameters being used as toxicity predictors. Compared to other widely used predictors such as the area under the drug plasma concentration curve versus time (AUC) and time above threshold plasma drug concentration, maximum plasma concentration (Cmax) is easier to collect and shows promise for use in clinical practice. In this article, we review the previous research on using Cmax to predict taxane treatment outcomes. While Cmax and toxicity have been extensively studied, research on the relationship between Cmax and efficacy is lacking. Most of the articles find a positive relationship between Cmax and toxicity but several articles have contradictory findings. Future clinical trials are needed to validate the relationship between Cmax and treatment outcome and determine whether Cmax can serve as a useful surrogate endpoint of taxane treatment efficacy.

Paclitaxel therapeutic drug monitoring - International association of therapeutic drug monitoring and clinical toxicology recommendations

Paclitaxel, one of the most frequently used anticancer drugs, is dosed by body surface area, which leads to substantial inter-individual variability in systemic drug exposure. We evaluated clinical evidence regarding the scientific rationale and clinical benefit of individualized paclitaxel dosing based on measured systemic concentrations, known as therapeutic drug monitoring (TDM). In retrospective studies, higher systemic exposure is associated with greater toxicity and efficacy of paclitaxel treatment across several disease types and dosing regimens. In prospective trials, TDM reduces variability in systemic exposure, and has been demonstrated to reduce toxicity while retaining treatment efficacy for 3-weekly dosing in patients with advanced non-small cell lung cancer. Despite the demonstrated benefits of paclitaxel TDM, clinical adoption has been limited due to the challenges with sample collection and analysis. Based on our review, we strongly recommend TDM for patients receiving every 3-week paclitaxel in combination with a platinum agent for advanced NSCLC, due to the prospectively demonstrated clinical benefits, and find moderate evidence to recommend TDM for paclitaxel 3-hour infusions for other tumor types and preliminary evidence suggesting potential usefulness for paclitaxel administered by 1-hour infusions.

Paclitaxel and Therapeutic Drug Monitoring with Microsampling in Clinical Practice

Paclitaxel is an anticancer agent efficacious in various tumors. There is large interindividual variability in drug plasma concentrations resulting in a wide variability in observed toxicity in patients. Studies have shown the time the concentration of paclitaxel exceeds 0.05 µM is a predictive parameter of toxicity, making dose individualization potentially useful in reducing the adverse effects. To determine paclitaxel drug concentration, a venous blood sample collected 24 h following the end of infusion is required, often inconvenient for patients. Alternatively, using a microsampling device for self-sampling would facilitate paclitaxel monitoring regardless of the patient's location. We investigated the feasibility of collecting venous and capillary samples (using a Mitra® device) from cancer patients to determine the paclitaxel concentrations. The relationship between the venous plasma and whole blood and venous and capillary blood (on Mitra®) paclitaxel concentrations, defined by a Passing-Bablok regression, were 0.8433 and 0.8569, respectively. Demonstrating a clinically acceptable relationship between plasma and whole blood paclitaxel concentration would reduce the need to establish new target concentrations in whole blood. However, in this study, comparison of venous and capillary blood using Mitra® for sampling displayed wide confidence intervals suggesting the results from the plasma and whole blood on this device may not be interchangeable.

Evolution of predictive risk factor analysis for chemotherapy-related toxicity

The causes of variation in toxicity to the same treatment regimen among seemingly similar patients remain largely unknown. There was tremendous optimism that the patient's germline genome would be strongly predictive of treatment-related toxicity and could be used to personalize treatment and improve therapeutic outcomes. However, there has been limited success in discovering robust pharmacogenetic predictors of treatment-related toxicity and even less progress in translating the few validated predictors into clinical practice. It is apparent that identification of toxicity predictors that can be used to predict and prevent treatment-related toxicity will require thinking beyond germline genomics. To that end, we propose an integrated biomarker discovery approach that recognizes that a patient's toxicity risk is determined by the cumulative effects of a broad range of "omic" and non-omic factors. This commentary describes the limited success in discovering and translating clinical and pharmacogenetic toxicity predictors into clinical practice. We illustrate the evolution of cancer toxicity biomarker discovery and translation through studies of taxane-induced peripheral neuropathy, which is one of the most common and debilitating side effects of cancer treatment. We then discuss the opportunities for discovering non-genomic (e.g., metabolomic, lipidomic, transcriptomic, proteomic, microbiomic, medical, behavioral, environmental) and integrated biomarkers that may be more strongly predictive of toxicity risk and the potential challenges with translating integrated biomarkers into clinical practice. This integrated biomarker discovery approach may circumvent some of the major limitations in toxicity biomarker science and move precision oncology treatment forward so that patients receive maximum treatment benefit with minimal toxicity.

Cost-effectiveness analysis of toripalimab plus chemotherapy versus chemotherapy alone for advanced non-small cell lung cancer in China

Background

Toripalimab is the first domestic anti-tumor programmed death 1 antibody marketed in China. The CHOICE-01 trial (identifier: NCT03856411) demonstrated that toripalimab plus chemotherapy can significantly improve the clinical outcomes of advanced non-small cell lung cancer (NSCLC) patients. However, whether it is cost-effective remains unknown. Given the high cost of combination therapy, a cost-effectiveness analysis of toripalimab plus chemotherapy (TC) versus chemotherapy alone (PC) for the first-line treatment of patients with advanced NSCLC is required.

Methods

A partitioned survival model was adopted to predict the course of disease in advanced NSCLC patients on TC or PC from the perspective of the Chinese healthcare system over a 10-year horizon. The survival data were obtained from the CHOICE-01 clinical trial. Cost and utility values were obtained from local hospitals and kinds of literature. Based on these parameters, the incremental cost-effectiveness ratio (ICER) of TC vs. PC was measured, and one-way sensitivity analyses, probabilistic sensitivity analyses (PSA), and scenario analyses were performed to assess the robustness of the model.

Results

In the base case, TC was associated with an incremental cost of $18510 and an incremental quality-adjusted life year (QALY) of 0.57 compared with PC, resulting in an ICER of $32237/QALY which was lower than the willingness to pay (WTP) threshold ($37654/QALY), TC was cost-effective. The health utility value of progression-free survival, the price of toripalimab, and the cost of best supportive care were factors that significantly influenced the ICER, but no change in any of them could change the model result. TC showed a 90% probability of being a cost-effective option at a WTP threshold of $37,654/QALY. In the 20 and 30-year time horizons, the results remained unchanged and TC remained cost-effective when the second-line treatment was switched to docetaxel.

Conclusion

At a WTP threshold of $37,654 per QALY, TC was cost-effective compared to PC for patients with advanced NSCLC in China.

Clinical Decision Support for Precision Dosing: Opportunities for Enhanced Equity and Inclusion in Health Care

Precision dosing aims to tailor doses to individual patients with the goal of improving treatment efficacy and avoiding toxicity. Clinical decision support software (CDSS) plays a crucial role in mediating this process, translating knowledge derived from clinical trials and real-world data (RWD) into actionable insights for clinicians to use at the point of care. However, not all patient populations are proportionally represented in clinical trials and other data sources that inform CDSS tools, limiting the applicability of these tools for underrepresented populations. Here, we review some of the limitations of existing CDSS tools and discuss methods for overcoming these gaps. We discuss considerations for study design and modeling to create more inclusive CDSS, particularly with an eye toward better incorporation of biological indicators in place of race, ethnicity, or sex. We also review inclusive practices for collection of these demographic data, during both study design and in software user interface design. Because of the role CDSS plays in both recording routine clinical care data and disseminating knowledge derived from data, CDSS presents a promising opportunity to continuously improve precision dosing algorithms using RWD to better reflect the diversity of patient populations.

The correlation between paclitaxel chemotoxicity and the plasma albumin level in cancer patients

WHAT IS KNOWN AND OBJECTIVE

The aim of this study was to evaluate the pharmacokinetics of paclitaxel in cancer patients with hypoalbuminemia following paclitaxel-containing chemotherapy and to provide a reference for the prevention of adverse events (AEs) after paclitaxel administration.

METHODS

Peripheral blood was collected from cancer patients treated with paclitaxel. The plasma concentration of paclitaxel was determined by ultra-high performance liquid chromatography after 24 ± 8 h of chemotherapy, and individual paclitaxel time above a threshold concentration of 0.05 μmol/L (T_c>0.05 ) was calculated using the population pharmacokinetic model. Haematological and non-haematological toxicities were monitored after chemotherapy, and the correlation between different chemotherapy toxicities and T_c>0.05 was evaluated using the Prism software.

RESULTS AND DISCUSSION

The enrolled patients were divided into the hypoalbuminemia group and normal albumin level group. The mean T_c>0.05 values in the normal albumin level and hypoalbuminemia groups were 36.89 and 24.93 h, respectively (P < 0.001). The risk of myelosuppression was positively correlated with T_c>0.05 . Due to the lower T_c>0.05 , the incidences of immediate AEs such as gastrointestinal reactions and rashes were higher in the hypoalbuminemia group than in the normal albumin level group, and the incidences of delayed AEs such as myelosuppression and neurotoxicity were lower in the hypoalbuminemia group.

WHAT IS NEW AND CONCLUSIONS

Plasma albumin level has a conclusive effect on T_c>0.05 , which can predict the potential clinical toxicity of paclitaxel. The study provides a theoretical basis for administration of paclitaxel.

Optimal exposure to docetaxel in adjuvant chemotherapy for early-stage breast cancer

WHAT IS KNOWN AND OBJECTIVE

Drug-induced neutropenia is the main reason for the dose limitation of docetaxel in patients with breast cancer. The area under the drug concentration-time curve (AUC) of docetaxel is associated with neutropenia. However, the optimal exposure to docetaxel for receiving postoperative adjuvant chemotherapy remains unclear. Therefore, we aimed to evaluate the relationship between the docetaxel AUC and neutropenia, identify potential influencing factors, and explore the best monitoring target for docetaxel when treating patients with early-stage breast cancer using a population pharmacokinetic (PopPK) model.

METHODS

Docetaxel plasma concentration, demographics, clinical data, and related laboratory data were collected. PopPK analyses were performed using a nonlinear mixed-effect modelling program. The docetaxel AUC was determined using the maximum a posteriori Bayesian (MAPB) method. The docetaxel exposure-toxicity threshold measured from the AUC for neutropenia was determined using the receiver operating characteristic (ROC) curve. The correlation between docetaxel exposure and neutropenia was analysed using multivariable logistic regression.

RESULTS

Among the 70 participants, 47 (67.1%) developed severe neutropenia. The PopPK analysis showed that the typical drug clearance (CL) rate was 37.4 L/h. Age was a significant covariate of CL rate, and aspartate aminotransferase and albumin levels were covariables of the volume of distribution. The multivariable regression analysis showed that AUC >3.0 mg.h/L (odds ratio [OR], 5.940; 95% confidence interval [CI], 1.693-20.843; P = 0.005), platinum use (OR, 0.156; 95% CI, 0.043-0.562; P = 0.005) and baseline haemoglobin level (OR, 0.938; 95% CI, 0.887-0.993; P = 0.027) were significant factors influencing the occurrence of grade 3/4 neutropenia. The AUC of first cycle may not predict the occurrence rates of grade 3/4 neutropenia in later cycles.

WHAT IS NEW AND CONCLUSION

We developed a docetaxel PopPK model for patients with early-stage breast cancer. Age and AST and ALB levels were significant covariates. AUC estimated using the MAPB method can predict the toxicity of docetaxel in patients with breast cancer. Docetaxel AUC >3.0 mg.h/L, absence of platinum use and low baseline haemoglobin level were risk factors for docetaxel-induced grade 3/4 neutropenia.

STUDY REGISTRATION

Chinese Clinical Trial Center Registry (ChiCTR2200056460).

Therapeutic drug monitoring in oncology - What’s out there: A bibliometric evaluation on the topic

Pharmacological therapy is the mainstay of treatment for cancer patients. Despite wide interpatient variability in systemic drug concentrations for numerous antineoplastics, dosing based on body size remains the predominant approach. Therapeutic drug monitoring (TDM) is used for few antineoplastics in specific scenarios. We conducted a rapid bibliometric evaluation of TDM in oncology to capture a snapshot of research in this area over time and explore topics that reflect development in the field. Reports with the composite, indexed term ‘therapeutic drug monitoring’ in the title and abstract were extracted from MEDLINE (inception to August 2021). Reports related to applications in cancer were selected for inclusion and were tagged by study design, antineoplastic drugs and concepts related to TDM. We present a timeline from 1980 to the present indicating the year of first report of antineoplastic agents and key terms. The reports in our sample primarily reflected development and validation of analytical methods with few relating to clinical outcomes to support implementation. Our work emphasises evidence gaps that may contribute to poor uptake of TDM in oncology.

Paclitaxel exposure-toxicity analysis reveals a pharmacokinetic determinant for dose-limiting neutropenia in East-Asian solid tumor patients: results from two prospective, phase II studies

PURPOSE

The time of a paclitaxel (PTX) concentration remains above 0.05 μM (Tc > 0.05) has been associated with PTX-induced adverse effects in Caucasians, while limited studies were reported in Asians. This study was aimed to explore the characteristics of Tc > 0.05 and the relationship between PTX exposure and toxicity in East-Asian patients.

METHODS

This study was based on two prospective phase II clinical trials and patients with advanced nasopharyngeal cancer (NPC) and non-small cell lung cancer (NSCLC) who were naïve to PTX were included independently. Eligible patients receive PTX (175 mg/m²) and carboplatin (AUC = 5) treatment every 3 weeks. PTX pharmacokinetic analysis was accessed. The relationship between PTX exposure and toxicities after first cycle as well as clinical efficacy was evaluated.

RESULTS

A total of 93 NPC and 40 NSCLC patients were enrolled. PTX exposure was consistent in two trials with average Tc > 0.05 duration of 38.8 h and 38.4 h, respectively. Average Tc > 0.05 in patients with grade 3/4 neutropenia was significantly higher than those without severe neutropenia in NPC patients (P = 0.003) and NSCLC patients (P = 0.007). Cut-off value of Tc > 0.05 were identified from the NPC cohort and then verified in the NSCLC cohort, dividing patients into high exposure Tc > 0.05 group (> 39 h) and low exposure group (≤ 39 h). Incidence of grade 3/4 neutropenia were significantly higher in the high exposure group in NPC cohort (43.3% vs 10.0%, P < 0.001) and NSCLC cohort (42.1% vs 9.5%, P = 0.028). No significant relationship between Tc > 0.05 and efficacy were observed.

CONCLUSION

Patients with PTX Tc > 0.05 duration above 39 h experience more severe neutropenia than those under 39 h. Prospective studies are needed to verify this threshold.

Muscle mass affects paclitaxel systemic exposure and may inform personalized paclitaxel dosing

AIMS

Patients with low muscle mass have increased risk of paclitaxel-induced peripheral neuropathy, which is dependent on systemic paclitaxel exposure. Dose optimization may be feasible through the secondary use of radiologic data for body composition. The objective of this study was to interrogate morphomic parameters as predictors of paclitaxel pharmacokinetics to identify alternative dosing strategies that may improve treatment outcomes.

METHODS

This was a secondary analysis of female patients with breast cancer scheduled to receive 80 mg/m² weekly paclitaxel infusions. Paclitaxel was measured at the end of initial infusion to estimate maximum concentration (C_max ). Computed tomography (CT) scans were used to measure 29 body composition features for inclusion in pharmacokinetic modelling. Monte Carlo simulations were performed to identify infusion durations that limit the probability of exceeding C_max  > 2885 ng/mL, which was selected based on prior work linking this to an unacceptable risk of peripheral neuropathy.

RESULTS

Thirty-nine patients were included in the analysis. The optimal model was a two-compartment pharmacokinetic model with T11 skeletal muscle area as a covariate of paclitaxel volume of distribution (Vd). Simulations suggest that extending infusion of the standard paclitaxel dose from 1 hour to 2 and 3 hours in patients who have skeletal muscle area 4907-7080 mm² and <4907 mm² , respectively, would limit risk of C_max  > 2885 ng/mL to <50%, consequently reducing neuropathy, while marginally increasing overall systemic paclitaxel exposure.

CONCLUSION

Extending paclitaxel infusion duration in ~25% of patients who have low skeletal muscle area is predicted to reduce peripheral neuropathy while maintaining systemic exposure, suggesting that personalizing paclitaxel dosing based on body composition may improve treatment outcomes.

Optimized Dosing: The Next Step in Precision Medicine in Non-Small-Cell Lung Cancer

In oncology, and especially in the treatment of non-small-cell lung cancer (NSCLC), dose optimization is often a neglected part of precision medicine. Many drugs are still being administered in "one dose fits all" regimens or based on parameters that are often only minor determinants for systemic exposure. These dosing approaches often introduce additional pharmacokinetic variability and do not add to treatment outcomes. Fortunately, pharmacological knowledge is increasing, providing valuable information regarding the potential of, for example, therapeutic drug monitoring. This article focuses on the evidence for the most promising and easily implemented optimized dosing approaches for the small-molecule inhibitors, chemotherapeutic agents, and monoclonal antibodies as treatment options currently approved for NSCLC. Despite limitations such as investigations having been conducted in oncological diseases other than NSCLC or the retrospective origin of many analyses, an alternative dosing regimen could be beneficial for treatment outcomes, prescriber convenience, or financial burden on healthcare systems. This review of the literature provides recommendations on the implementation of dose optimization and advice regarding promising strategies that deserve further research in NSCLC.

Feasibility of pharmacometabolomics to identify potential predictors of paclitaxel pharmacokinetic variability

PURPOSE

Paclitaxel is a commonly used chemotherapy drug with substantial variability in pharmacokinetics (PK) that affects treatment efficacy and toxicity. Pharmacometabolomic signatures that explain PK variability could be used to individualize dosing to improve therapeutic outcomes. The objective of this study was to identify pretreatment metabolites or metabolomic signatures that explain variability in paclitaxel PK.

METHODS

This analysis was conducted using data previously collected on a prospective observational study of 48 patients with breast cancer receiving weekly 80 mg/m² paclitaxel infusions. Paclitaxel plasma concentrations were measured during the first infusion to estimate paclitaxel time above threshold (T_c>0.05) and maximum concentration (C_max). Metabolites measured in pretreatment whole blood by nuclear magnetic resonance spectrometry were analyzed for an association with T_c>0.05 and C_max using Pearson correlation followed by stepwise linear regression.

RESULTS

Pretreatment creatinine, glucose, and lysine concentrations were positively correlated with T_c>0.05, while pretreatment betaine was negatively correlated and lactate was positively correlated with C_max (all uncorrected p < 0.05). After stepwise elimination, creatinine was associated with T_c>0.05, while betaine and lactate were associated with C_max (all p < 0.05).

CONCLUSION

This study identified pretreatment metabolites that may be associated with paclitaxel PK variability demonstrating feasibility of a pharmacometabolomics approach for understanding paclitaxel PK. However, identification of more robust pharmacometabolomic predictors will be required for broad and routine application for the clinical dosing of paclitaxel.

Evaluation of two software using Bayesian methods for monitoring exposure and dosing once-daily intravenous busulfan in paediatric patients receiving haematopoietic stem cell transplantation

AIM

To assess the ability of model-based personalised dosing tools to estimate busulfan exposure (i) in comparison to clinically used intensive sampling exposure estimation procedure, (ii) using limited sampling strategies and (iii) to predict changes in busulfan clearance during busulfan treatment.

METHODS

Data on intravenous busulfan dosing for patients with 4 consecutive days were entered into Bayesian forecasting software, InsightRX and NextDose. Prediction of busulfan cumulative exposure was compared to current clinical practice estimation, aiming for pre-defined individualised target of cumulative exposure. Estimation performance was tested given several limited sampling strategies.

RESULTS

Thirty-two paediatric patients (0.2-16.5 years) provided a total of 103 daily exposure measurements estimated using 7 samples taken per day (full sampling), with 19 patients having sampling following all doses administered. Both software tools utilising Bayesian methods provided acceptable relative bias and precision of cumulative exposure estimations under the tested sampling scenarios. Relative bias ranged from median RE of 0.1-14.6% using InsightRX and from 3.4-7.8% using NextDose. Precision ranged from median RMSE of 0.19-0.32 mg·h·L^-1 for InsightRX and 0.08-0.1 mg·h·L^-1 for NextDose. A median reduction in busulfan clearance from day 1 to day 4 was observed in the clinical data (-10.9%), when using InsightRX (-18.6%) and with NextDose (-14.7%).

CONCLUSION

Bayesian methods were shown to have relatively low bias and precisely estimate busulfan exposure using intensive sampling and several limited sampling strategies, which provides evidence for prospective studies to evaluate these tools in clinical practice. A trend to overestimation of exposure using Bayesian methods was observed compared to clinical practice. Reduction of busulfan clearance from day 1 to 4 of once daily dosing was confirmed and should be considered when adjusting doses.

Exploring pharmacogenetics of paclitaxel- and docetaxel-induced peripheral neuropathy by evaluating the direct pharmacogenetic-pharmacokinetic and pharmacokinetic-neuropathy relationships

Introduction: Peripheral neuropathy (PN) is an adverse effect of several classes of chemotherapy including the taxanes. Predictive PN biomarkers could inform individualized taxane treatment to reduce PN and enhance therapeutic outcomes. Pharmacogenetics studies of taxane-induced PN have focused on genes involved in pharmacokinetics, including enzymes and transporters. Contradictory findings from these studies prevent translation of genetic biomarkers into clinical practice. Areas covered: This review discusses the progress toward identifying pharmacogenetic predictors of PN by assessing the evidence for two independent associations; the effect of pharmacogenetics on taxane pharmacokinetics and the evidence that taxane pharmacokinetics affects PN. Assessing these direct relationships allows the reader to understand the progress toward individualized taxane treatment and future research opportunities. Expert opinion: Paclitaxel pharmacokinetics is a major determinant of PN. Additional clinical trials are needed to confirm the clinical benefit of individualized dosing to achieve target paclitaxel exposure. Genetics does not meaningfully contribute to paclitaxel pharmacokinetics and may not be useful to inform dosing. However, genetics may contribute to PN sensitivity and could be useful for estimating patients' optimal paclitaxel exposure. For docetaxel, genetics has not been demonstrated to have a meaningful effect on pharmacokinetics and there is no evidence that pharmacokinetics determines PN.

Role of TDM-based dose adjustments for taxane anticancer drugs

The classical taxanes (paclitaxel, docetaxel), the newer taxane cabazitaxel and the nanoparticle-bound nab-paclitaxel are among the most widely used anticancer drugs. Still, the optimal use and the value of pharmacological personalization of the taxanes is still controversial. We give an overview on the pharmacological properties of the taxanes, including metabolism, pharmacokinetics-pharmacodynamic relations and aspects in the clinical use of taxanes. The latter includes the ongoing debate on the most effective and safe regimen, the recommended initial dose, and pharmacological dosing individualization. The taxanes are among the most widely used anticancer drugs in patients with solid malignancies. Despite their longtime use in clinical routine, the optimal dosing strategy (weekly versus 3-weekly) or optimal average dose (cabazitaxel, nab-paclitaxel) has not been fully resolved, as it may differ according to tumour entity and line of treatment. The value of pharmacological individualization of the taxanes (TDM, TCI) has been partly explored for 3-weekly paclitaxel and docetaxel, but remains mostly unexplored for cabazitaxel and nab-paclitaxel at present.

Time-to-Event Analysis of Paclitaxel-Associated Peripheral Neuropathy in Advanced Non-Small-Cell Lung Cancer Highlighting Key Influential Treatment/Patient Factors

Paclitaxel-associated peripheral neuropathy (PN), a major dose-limiting toxicity, significantly impacts patients' quality of life/treatment outcome. Evaluation of risk factors often ignores time of PN onset, precluding the impact of time-dependent factors, e.g., drug exposure, needed to comprehensively characterize PN. We employed parametric time-to-event (TTE) analysis to describe the time course of risk of first occurrence of clinically relevant PN grades ≥2 (PN2+, n = 105, common terminology criteria v4.0) and associated patient/treatment characteristics, leveraging data from 365 patients (1454 cycles) receiving paclitaxel every 3 weeks (plus carboplatin AUC = 6 or cisplatin 80 mg/m2) for ≤6 cycles. Paclitaxel was intravenously administered (3 hours) as standard 200-mg/m2 doses (n = 182) or as pharmacokinetic-guided dosing (n = 183). A cycle-varying hazard TTE model linking surge in hazard of PN2+ to paclitaxel administration [PN2+ proportions (i.e., cases per 1000 patients), 1st day, cycle 1: 4.87 of 1000; cycle 6: 7.36 of 1000] and linear decline across cycle (last day, cycle 1: 1.64 of 1000; cycle 6: 2.48 of 1000) adequately characterized the time-varying hazard of PN2+. From joint covariate evaluation, PN2+ proportions (1st day, cycle 1) increased by 1.00 per 1000 with 5-μmol·h/l higher paclitaxel exposure per cycle (AUC between the start and end of a cycle, most relevant covariate), 0.429 per 1000 with 5-year higher age, 1.31 per 1000 (smokers vs. nonsmokers), and decreased by 0.670 per 1000 (females vs. males). Compared to 200 mg/m2 dosing every 3 weeks, model-predicted cumulative risk of PN2+ was significantly higher (42%) with 80 mg/m2 weekly dosing but reduced by 11% with 175 mg/m2 dosing every 3 weeks. The established TTE modeling framework enables quantification and comparison of patient's cumulative risks of PN2+ for different clinically relevant paclitaxel dosing schedules, sparing patients PN2+ to improve paclitaxel therapy. SIGNIFICANCE STATEMENT: Characterization of risk factors of paclitaxel-associated peripheral neuropathy (PN) typically involves time-independent comparison of PN odds in patient subpopulations, concealing the impact of time-dependent factors, e.g., changing paclitaxel exposure, required to comprehensively characterize PN. We developed a parametric time-to-event model describing the time course in risk of clinically relevant paclitaxel-associated PN, identifying the highest risk in older male smokers with higher paclitaxel area under the plasma concentration-time curve between the start and end of a cycle. The developed framework enabled quantification of patient's risk of PN for clinically relevant paclitaxel dosing schedules, facilitating future dosing decisions.

Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

Artificial Intelligence and Machine Learning Applied at the Point of Care

Introduction

The increasing availability of healthcare data and rapid development of big data analytic methods has opened new avenues for use of Artificial Intelligence (AI)- and Machine Learning (ML)-based technology in medical practice. However, applications at the point of care are still scarce.

Objective

Review and discuss case studies to understand current capabilities for applying AI/ML in the healthcare setting, and regulatory requirements in the US, Europe and China.

Methods

A targeted narrative literature review of AI/ML based digital tools was performed. Scientific publications (identified in PubMed) and grey literature (identified on the websites of regulatory agencies) were reviewed and analyzed.

Results

From the regulatory perspective, AI/ML-based solutions can be considered medical devices (i.e., Software as Medical Device, SaMD). A case series of SaMD is presented. First, tools for monitoring and remote management of chronic diseases are presented. Second, imaging applications for diagnostic support are discussed. Finally, clinical decision support tools to facilitate the choice of treatment and precision dosing are reviewed. While tested and validated algorithms for precision dosing exist, their implementation at the point of care is limited, and their regulatory and commercialization pathway is not clear. Regulatory requirements depend on the level of risk associated with the use of the device in medical practice, and can be classified into administrative (manufacturing and quality control), software-related (design, specification, hazard analysis, architecture, traceability, software risk analysis, cybersecurity, etc.), clinical evidence (including patient perspectives in some cases), non-clinical evidence (dosing validation and biocompatibility/toxicology) and other, such as e.g. benefit-to-risk determination, risk assessment and mitigation. There generally is an alignment between the US and Europe. China additionally requires that the clinical evidence is applicable to the Chinese population and recommends that a third-party central laboratory evaluates the clinical trial results.

Conclusions

The number of promising AI/ML-based technologies is increasing, but few have been implemented widely at the point of care. The need for external validation, implementation logistics, and data exchange and privacy remain the main obstacles.

Recent advances in taste transduction and signaling

In the last few years, single-cell profiling of taste cells and ganglion cells has advanced our understanding of transduction, encoding, and transmission of information from taste buds as relayed to the central nervous system. This review focuses on new knowledge from these molecular approaches and attempts to place this in the context of previous questions and findings in the field. The individual taste cells within a taste bud are molecularly specialized for detection of one of the primary taste qualities: salt, sour, sweet, umami, and bitter. Transduction and transmitter release mechanisms differ substantially for taste cells transducing sour (Type  III cells) compared with those transducing the qualities of sweet, umami, or bitter (Type II cells), although ultimately all transmission of taste relies on activation of purinergic P2X receptors on the afferent nerves. The ganglion cells providing innervation to the taste buds also appear divisible into functional and molecular subtypes, and each ganglion cell is primarily but not exclusively responsive to one taste quality.

Precision medicine technology hype or reality? The example of computer-guided dosing

Novel technologies labelled as ‘precision medicine’ are targeting all aspects of clinical care. Whilst some technological advances are undeniably exciting, many doctors at the frontline of healthcare view precision medicine as being out of reach for their patients. Computer-guided dosing is a precision medicine technology that predicts drug concentrations and drug responses based on individual patient characteristics. In this opinion piece, the example of computer-guided dosing is used to illustrate eight features of a precision medicine technology less likely to be hyperbole and more likely to improve patient care. Positive features in this regard include: (1) fitting the definition of ‘precision medicine’; (2) addressing a major clinical problem that negatively impacts patient care; (3) a track record of high-quality medical science published via peer-reviewed literature; (4) well-defined clinical cases for application; (5) quality evidence of benefits measured by various clinical, patient and health economic endpoints; (6) strong economic drivers; (7) user friendliness, including easy integration into clinical workflow, and (8) recognition of importance by patients and their endorsement for broader clinical use. Barriers raised by critics of the approach are given to balance the view. The value of computer-guided dosing will be decided ultimately by the extent to which it can improve cost-effective patient care.

Randomized study of individualized pharmacokinetically-guided dosing of paclitaxel compared with body-surface area dosing in Chinese patients with advanced non-small cell lung cancer

AIMS

This prospective, randomized study was initiated to assess the impact of pharmacokinetically (PK)-guided paclitaxel (PTX) dosing on toxicity and efficacy compared with body-surface area (BSA)-based dosing in Chinese non-small cell lung cancer patients.

METHODS

A total of 319 stage IIIB/IV non-small cell lung cancer patients receiving first-line chemotherapy were enrolled. Patients were randomized to receive 3-weekly carboplatin plus PTX at a starting dose of 175 mg/m² with subsequent PTX dosing based on either BSA or PK-guided dosing targeting time above a PTX plasma concentration of 0.05 μmol/L (PTX_Tc > 0.05 ) between 26 and 31 hours. The primary safety endpoint was grade 4 haematological toxicity. The secondary endpoints were neuropathy, objective response rate, progression-free survival and overall survival.

RESULTS

In total, 275 (86%) patients completed ≥2 cycles of chemotherapy (140 in BSA arm and 135 in PK arm). In cycle 1, with the same PTX dose, average PTX_Tc > 0.05 was 37 hours (range = 18-57 hours). Over cycles 2-4, patients in the PK arm had significantly lower average PTX doses and exposure compared with the BSA arm (128 vs 161 mg/m² , P < .0001 and 29 vs 35 hours, P < .0001). PK-guided dosing significantly reduced the cumulative incidence of grade 4 haematological toxicity (15% vs 24%, P = .004), grade 4 neutropenia (15% vs 23%, P = .009) and grade ≥ 2 neuropathy (8% vs 21%, P = .005). Objective response rate (32% vs 26%, P = .28) and overall survival (21.0 vs 24.0 months, P = .815) were similar in PK and BSA arms. Progression-free survival was slightly improved in PK arm (4.67 vs 4.17 months, P = .026).

CONCLUSION

PK-guided PTX dosing significantly reduced grade 4 haematological toxicities and grade ≥ 2 neuropathy without an adverse impact on clinical outcomes.