Analysis Approaches to Identify Pharmacogenetic Associations With Pharmacodynamics

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.

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.

An Integrated Pharmacological Counselling Approach to Guide Decision-Making in the Treatment with CDK4/6 Inhibitors for Metastatic Breast Cancer

A wide inter-individual variability in the therapeutic response to cyclin-dependent kinases 4 and 6 inhibitors (CDKis) has been reported. We herein present a case series of five patients treated with either palbociclib or ribociclib referred to our clinical pharmacological counselling, including therapeutic drug monitoring (TDM), pharmacogenetics, and drug–drug interaction analysis to support clinicians in the management of CDKis treatment for metastatic breast cancer. Patients’ plasma samples for TDM analysis were collected at steady state and analyzed by an LC-MS/MS method for minimum plasma concentration (Cmin) evaluation. Under and overexposure to the drug were defined based on the mean Cmin values observed in population pharmacokinetic studies. Polymorphisms in selected genes encoding for proteins involved in drug absorption, distribution, metabolism, and elimination were analyzed (CYP3A4, CYP3A5, ABCB1, SLCO1B1, and ABCG2). Three of the five reported cases presented a CDKi plasma level above the population mean value and were referred for toxicity. One of them presented a low function ABCB1 haplotype (ABCB1-rs1128503, rs1045642, and rs2032582), possibly causative of both increased drug oral absorption and plasmatic concentration. Two patients showed underexposure to CDKis, and one of them was referred for early progression. In one patient, a CYP3A5*1/*3 genotype was found to be potentially responsible for more efficient drug metabolism and lower drug plasma concentration. This intensified pharmacological approach in clinical practice has been shown to be potentially effective in supporting prescribing oncologists with dose and drug selection and could be ultimately useful for increasing both the safety and efficacy profiles of CDKi treatment.

Lack of association of CYP2B6 pharmacogenetics with cyclophosphamide toxicity in patients with cancer

PURPOSE

Cyclophosphamide is a commonly used cancer agent that is metabolically activated by polymorphic enzymes. This study aims to investigate the association between predicted activity of candidate pharmacogenes with severe toxicity during cyclophosphamide treatment.

METHODS

Genome-wide genetic data was collected from an institutional genetic data repository for CYP2B6, CYP3A4, CYP2C9, CYP2C19, GSTA1, GSTP1, ALDH1A1, ALDH3A1, ABCC1, ABCB1, and ERCC1. Treatment and toxicity data were retrospectively collected from the patient's medical record. The a priori selected primary hypothesis was that patients who have CYP2B6 reduced metabolizer activity (poor or intermediate (PM/IM) vs. normal (NM) metabolizer) have lower risk of severe toxicity or cyclophosphamide treatment modification due to toxicity.

RESULTS

In the primary analysis of 510 cyclophosphamide-treated patients with available genetic data, there was no difference in the odds of severe toxicity or treatment modification due to toxicity in CYP2B6 PM/IM vs. NM (odds ratio = 0.97, 95% Confidence Interval: 0.62-1.50, p = 0.88). In an exploratory, statistically uncorrected secondary analysis, carriers of the ALDH1A1 rs8187996 variant had a lower risk of the primary toxicity endpoint compared with wild-type homozygous patients (odds ratio = 0.31, 95% Confidence Interval: 0.09-0.78, p = 0.028). None of the other tested phenotypes or genotypes was associated with the primary or secondary endpoints in unadjusted analysis (all p > 0.05).

CONCLUSION

The finding that patients who carry ALDH1A1 rs8187996 may have a lower risk of cyclophosphamide toxicity than wild-type patients contradicts a prior finding for this variant and should be viewed with skepticism. We found weak evidence that any of these candidate pharmacogenetic predictors of cyclophosphamide toxicity may be useful to personalize cyclophosphamide dosing to optimize therapeutic outcomes in patients with cancer.

Editorial: Beyond Red Light, Green Light: Examining the Role of Pharmacogenomics in Evidence-Based Care in Child and Adolescent Psychiatry

The role of pharmacogenetics in guiding psychopharmacologic treatment for children and adolescents remains elusive for many clinicians. In the absence of a solid and comprehensive evidence base, sufficient training, education, and consensus guidelines, commercial promotion of pharmacogenetic testing panels has the potential to become the main source of information for providers. Commonly, these tests include multigene panels and group medications into color-coded bins. These panels include both pharmacokinetic (PK) and pharmacodynamic (PD) genes and, using combinatorial algorithms, direct clinicians to use medications "as directed" or caution that "moderate gene-drug interaction(s)" or "significant gene-drug interaction(s)" may exist. Many industry-sponsored studies in adults have concluded that that when clinicians select medications based on pharmacogenomic guidance, patients have better outcomes,¹ although some caution against this approach.² To provide evidence on the clinical impact and potential of pharmacogenetic testing panels in clinical practice in child and adolescent psychiatry, in this issue of the Journal, Vande Voort³ and colleagues report the results of a prospective trial of pharmacogenetically guided treatment versus treatment as usual in depressed adolescents. The authors randomized adolescents aged 13 to 18 years with moderate to severe major depressive disorder (N = 176) to treatment guided by combinatorial pharmacogenetic testing that was either available at the baseline visit (GENE arm, n = 84) or at the 8-week visit (treatment-as-usual arm, n = 92). Patients and raters were blinded, but the treating psychiatrist was not blinded and could prescribe any medication deemed clinically indicated for the patient. Improvement, side effects, and satisfaction were assessed throughout the study and at a 6-month follow-up visit. There was no significant difference in terms of symptom improvement, side effect burden, or satisfaction at 8 weeks or 6 months between patients in the GENE and treatment-as-usual arms, respectively. However, significantly more patients in the treatment-as-usual arm received selective serotonin reuptake inhibitors (SSRIs) compared with patients in the GENE arm (81.5% vs 66.7%). Therefore, there was no significant clinical impact when clinicians used combinatorial pharmacogenomic testing to guide treatment for depressed adolescents. If anything, this guidance influenced providers to more frequently prescribe medications that are not considered first-line for the treatment of depression in youths (serotonin-norepinephrine reuptake inhibitors [SNRIs], atypical antidepressants) and for which double-blind placebo-controlled trials have failed to demonstrate efficacy in depressed youths.^4,5.

Pediatric Therapeutic Drug Monitoring for Selective Serotonin Reuptake Inhibitors

Therapeutic drug monitoring (TDM) is uncommon in child and adolescent psychiatry, particularly for selective serotonin reuptake inhibitors (SSRIs)—the first-line pharmacologic treatments for depressive and anxiety disorders. However, TDM in children and adolescents offers the opportunity to leverage individual variability of antidepressant pharmacokinetics to shed light on non-response and partial response, understand drug-drug interactions, evaluate adherence, and characterize the impact of genetic and developmental variation in pharmacokinetic genes. This perspective aims to educate clinicians about TDM principles and examines evolving uses of TDM in SSRI-treated youths and their early applications in clinical practice, as well as barriers to TDM in pediatric patients. First, the impact of pharmacokinetic genes on SSRI pharmacokinetics in youths could be used to predict tolerability and response for some SSRIs (e.g., escitalopram). Second, plasma concentrations are significantly influenced by adherence, which may relate to decreased efficacy. Third, pharmacometric analyses reveal interactions with proton pump inhibitors, oral contraceptives, cannabinoids, and SSRIs in youths. Rapid developments in TDM and associated modeling have enhanced the understanding of variation in SSRI pharmacokinetics, although the treatment of anxiety and depressive disorders with SSRIs in youths often remains a trial-and-error process.

Individualized Drugs' Selection by Evaluation of Drug Properties, Pharmacogenomics and Clinical Parameters: Performance of a Bioinformatic Tool Compared to a Clinically Established Counselling Process

Purpose

Inefficacy and safety concerns are main medications’ problems, especially in the case of poly-therapies, when drug–drug interactions may alter the expected drug disposition. Ongoing efforts are aimed to establish drug selection processes aimed to preemptive evaluation of a plethora of factors affecting patient’s specific drug response, including pharmacogenomic markers, in order to minimize prescription of improper medications. In previous years, we established at the University Hospital Sant’Andrea of Rome, Italy, a Precision Medicine Service based on a multi-disciplinary experts’ team. The team is in charge to produce a drug therapy counselling report, including pharmacogenomic, pharmacokinetic and pharmacodynamic considerations. In this study, we aimed to evaluate the performance of this established “manual” process of therapy selection with a novel bioinformatic tool, the Drug-PIN system.

Patients and Methods

A total of 200 patients diagnosed with Major Depressive Disorders or a depressive episode in Bipolar Disorder, with at least three previous failed treatments, who underwent pharmacogenomic profiling and therapy counselling in the Sant’Andrea Hospital from 2017 to 2020. The baseline poly-therapy of these patients was re-evaluated and optimized by Drug-PIN. Results of the Drug-PIN poly-therapy evaluation/optimization were compared with the results of the original poly-therapy evaluation/optimization by therapy counselling. To compare the results between the two processes, the risk associated with each poly-therapy was classified as low, moderate, or high.

Results

The number of baseline poly-therapies classified in low-, moderate- or high-risk did not change significantly between manual system or Drug-PIN system. As the counselling process, also the Drug-PIN system produces a significant decrease in the predicted treatment-associated risk.

Conclusion

Drug-PIN substantially replicates the output of the counselling process, allowing a substantial reduction in the time needed for therapy evaluation. Availability of an effective bioinformatic tool for proper drug selection is expected to exponentially increase the actuation of targeted therapy strategies.