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Clinical Pharmacokinetics Jun 2024Pharmacogenetic profiling and therapeutic drug monitoring (TDM) have both been proposed to manage inter-individual variability (IIV) in drug exposure. However,...
BACKGROUND
Pharmacogenetic profiling and therapeutic drug monitoring (TDM) have both been proposed to manage inter-individual variability (IIV) in drug exposure. However, determining the most effective approach for estimating exposure for a particular drug remains a challenge. This study aimed to quantitatively assess the circumstances in which pharmacogenetic profiling may outperform TDM in estimating drug exposure, under three sources of variability (IIV, inter-occasion variability [IOV], and residual unexplained variability [RUV]).
METHODS
Pharmacokinetic models were selected from the literature corresponding to drugs for which pharmacogenetic profiling and TDM are both clinically considered approaches for dose individualization. The models were used to simulate relevant drug exposures (trough concentration or area under the curve [AUC]) under varying degrees of IIV, IOV, and RUV.
RESULTS
Six drug cases were selected from the literature. Model-based simulations demonstrated that the percentage of patients for whom pharmacogenetic exposure prediction is superior to TDM differs for each drug case: tacrolimus (11.0%), tamoxifen (12.7%), efavirenz (49.2%), vincristine (49.6%), risperidone (48.1%), and 5-fluorouracil (5-FU) (100%). Generally, in the presence of higher unexplained IIV in combination with lower RUV and IOV, exposure was best estimated by TDM, whereas, under lower unexplained IIV in combination with higher IOV or RUV, pharmacogenetic profiling was preferred.
CONCLUSIONS
For the drugs with relatively low RUV and IOV (e.g., tamoxifen and tacrolimus), TDM estimated true exposure the best. Conversely, for drugs with similar or lower unexplained IIV (e.g., efavirenz or 5-FU, respectively) combined with relatively high RUV, pharmacogenetic profiling provided the most accurate estimate for most patients. However, genotype prevalence and the relative influence of genotypes on the PK, as well as the ability of TDM to accurately estimate AUC with a limited number of samples, had an impact. The results could be used to support clinical decision making when considering other factors, such as the probability for severe side effects.
Topics: Humans; Drug Monitoring; Pharmacogenomic Testing; Tacrolimus; Tamoxifen; Area Under Curve; Vincristine; Models, Biological; Computer Simulation; Alkynes; Cyclopropanes; Benzoxazines
PubMed: 38842789
DOI: 10.1007/s40262-024-01382-3 -
Pharmacogenetics and Genomics Jun 2024Studies have reported overexpression of NAT1 gene for xenobiotic metabolizing arylamine N-acetyltransferase type 1 in estrogen receptor positive breast tumors, and this...
Studies have reported overexpression of NAT1 gene for xenobiotic metabolizing arylamine N-acetyltransferase type 1 in estrogen receptor positive breast tumors, and this association has been linked to patient chemoresistance and response to tamoxifen. We probed the expression of NAT1, using quantitative reverse transcription PCR to screen clinically characterized breast cancer tissue cDNA arrays. Primers detecting all NAT1 alternative transcripts were used, and the protocol and results are reported according to consensus guidelines. The clinical information about 166 tumor samples screened is provided, including tumor stage, estrogen and progesterone receptor status and HER2 expression. NAT1 was found to be significantly (P < 0.001) upregulated in hormone receptor positive vs. negative tumors. No correlation was apparent between NAT1 and tumor stage or HER2 expression. Our findings demonstrate a strong correlation between the expression of NAT1 and steroid hormone receptors in breast tumors, supporting its possible utility as a pharmacogenetic biomarker or drug target. Of the two polymorphic NAT genes, NAT1 is the one primarily expressed in breast tissue, and is subjected to regulation by two differential promoters and more than one polyadenylation signal. Hormonal factors may enhance NAT1 gene expression at the transcriptional or epigenetic level, and tamoxifen has additionally been shown to inhibit NAT1 enzymatic activity. The outcome of tamoxifen treatment is also more favorable in patients with NAT1 overexpressing tumors. The study adds to the growing body of evidence implicating NAT1 in breast cancer and its pharmacological treatment.
PubMed: 38842463
DOI: 10.1097/FPC.0000000000000540 -
Clinical Pharmacology and Therapeutics Jun 2024Africans are extremely underrepresented in global genomic research. African populations face high burdens of communicable and non-communicable diseases and experience...
Africans are extremely underrepresented in global genomic research. African populations face high burdens of communicable and non-communicable diseases and experience widespread polypharmacy. As population-specific genetic studies are crucial to understanding unique genetic profiles and optimizing treatments to reduce medication-related complications in this diverse population, the present study aims to characterize the pharmacogenomics profile of a rural Ugandan population. We analyzed low-pass whole genome sequencing data from 1998 Ugandans to investigate 18 clinically actionable pharmacogenes in this population. We utilized PyPGx to identify star alleles (haplotype patterns) and compared allele frequencies across populations using the Pharmacogenomics Knowledgebase PharmGKB. Clinical interpretations of the identified alleles were conducted following established dosing guidelines. Over 99% of participants displayed actionable phenotypes across the 18 pharmacogenes, averaging 3.5 actionable genotypes per individual. Several variant alleles known to affect drug metabolism (i.e., CYP3A5*1, CYP2B6*9, CYP3A5*6, CYP2D6*17, CYP2D6*29, and TMPT*3C)-which are generally more prevalent in African individuals-were notably enriched in the Ugandan cohort, beyond reported frequencies in other African peoples. More than half of the cohort exhibited a predicted impaired drug response associated with CFTR, IFNL3, CYP2B6, and CYP2C19, and approximately 31% predicted altered CYP2D6 metabolism. Potentially impaired CYP2C9, SLCO1B1, TPMT, and DPYD metabolic phenotypes were also enriched in Ugandans compared with other African populations. Ugandans exhibit distinct allele profiles that could impact drug efficacy and safety. Our findings have important implications for pharmacogenomics in Uganda, particularly with respect to the treatment of prevalent communicable and non-communicable diseases, and they emphasize the potential of pharmacogenomics-guided therapies to optimize healthcare outcomes and precision medicine in Uganda.
PubMed: 38837390
DOI: 10.1002/cpt.3309 -
Cancer Drug Resistance (Alhambra,... 2024Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell non-Hodgkin lymphoma (NHL). Despite the availability of clinical and molecular algorithms applied for...
Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell non-Hodgkin lymphoma (NHL). Despite the availability of clinical and molecular algorithms applied for the prediction of prognosis, in up to 30%-40% of patients, intrinsic or acquired drug resistance occurs. Constitutional genetics may help to predict R-CHOP resistance. This study aimed to validate previously identified single nucleotide polymorphisms (SNPs) in the literature as potential predictors of R-CHOP resistance in DLBCL patients, SNPs. Twenty SNPs, involved in R-CHOP pharmacokinetics/pharmacodynamics or other pathobiological processes, were investigated in 185 stage I-IV DLBCL patients included in a multi-institution pharmacogenetic study to validate their previously identified correlations with resistance to R-CHOP. Correlations between rs2010963 ( gene) and sex ( = 0.046), and rs1625895 ( gene) and stage ( = 0.003) were shown. After multivariate analyses, a concordant effect (i.e., increased risk of disease progression and death) was observed for rs1883112 ( gene) and rs1800871 ( gene). When patients were grouped according to the revised International Prognostic Index (R-IPI), both these SNPs further discriminated progression-free survival (PFS) and overall survival (OS) of the R-IPI-1-2 subgroup. Overall, patients harboring the rare allele showed shorter PFS and OS compared with wild-type patients. Two out of the 20 study SNPs were validated. Thus, these results support the role of previously identified rs1883112 and rs1800871 in predicting DLBCL resistance to R-CHOP and highlight their ability to further discriminate the prognosis of R-IPI-1-2 patients. These data point to the need to also focus on host genetics for a more comprehensive assessment of DLBCL patient outcomes in future prospective trials.
PubMed: 38835350
DOI: 10.20517/cdr.2024.10 -
Therapie May 2024The French National Health Data System (SNDS) comprises healthcare data that cover 99% of the population (over 67 million individuals) in France. The aim of this study...
AIM OF THE STUDY
The French National Health Data System (SNDS) comprises healthcare data that cover 99% of the population (over 67 million individuals) in France. The aim of this study was to present an overview of published pharmacoepidemiological studies using the SNDS in its maturation phase.
METHODS
We conducted a systematic literature review of original research articles in the Pubmed and EMBASE databases from January 2012 until August 2018.
RESULTS
A total of 316 full-text articles were included, with an annual increase over the study period. Only 16 records were excluded after screening because they did not involve the SNDS but other French healthcare databases. The study design was clearly reported in only 66% of studies of which 57% were retrospective cohorts and 22% cross-sectional studies. The reported study objectives were drug utilization (65%), safety (22%) and effectiveness (9%). Almost all ATC groups were studied but the most frequent ones concerned the nervous system in 149 studies (49%), cardiovascular system drugs in 104 studies (34%) and anti-infectives for systemic use in 50 studies (16%).
CONCLUSION
The SNDS is of growing interest for studies on drug use and safety, which could be conducted more in specific populations, including children, pregnant women and the elderly, as these populations are often not included in clinical trials.
PubMed: 38834394
DOI: 10.1016/j.therap.2024.05.003 -
Pharmacological Research Jul 2024About 80 % of brain disorders have a genetic basis. The pathogenesis of most neurodegenerative diseases is associated with a myriad of genetic defects, epigenetic... (Review)
Review
About 80 % of brain disorders have a genetic basis. The pathogenesis of most neurodegenerative diseases is associated with a myriad of genetic defects, epigenetic alterations (DNA methylation, histone/chromatin remodeling, miRNA dysregulation), and environmental factors. The emergence of new sequencing technologies and tools to study the epigenome has led to identifying predictive biomarkers for earlier diagnosis, opening up the possibility of prophylactical interventions. As a result, advances in pharmacogenetics and pharmacoepigenomics now allow for personalized treatments based on the profile of each patient and the specific genetic and epigenetic mechanisms involved. This Review highlights the complexity of neurodegenerative diseases and the variability in patient responses to pharmacotherapy, emphasizing the influence of genetic polymorphisms on the pharmacokinetics and pharmacodynamics of drugs used to treat those conditions. We specifically discuss the potential modulatory effect of several genetic polymorphisms associated with an increased risk of developing different neurodegenerative diseases. We explore genetic and genomic technologies and the potential of analyzing individual-specific drug metabolism to predict and influence drug response and associated clinical outcomes. We also provide insights into the mechanism of action of the drugs under investigation and their potential impact on disease-modifying pathways. Finally, the Review underscores the great potential of this field to enhance the effectiveness and safety of drug treatments through personalized medicine.
Topics: Humans; Precision Medicine; Neurodegenerative Diseases; Pharmacogenetics; Epigenesis, Genetic; Animals; Epigenomics
PubMed: 38834164
DOI: 10.1016/j.phrs.2024.107247 -
Therapeutic Drug Monitoring Jun 2024Therapeutic drug monitoring (TDM) is strongly recommended for olanzapine due to its high pharmacokinetic variability. This study aimed to investigate the impact of...
BACKGROUND
Therapeutic drug monitoring (TDM) is strongly recommended for olanzapine due to its high pharmacokinetic variability. This study aimed to investigate the impact of various clinical factors on olanzapine plasma concentrations in patients with psychiatric disorders.
METHODS
The study used TDM data from the PsyMetab cohort, including 547 daily dose-normalized, steady-state, olanzapine plasma concentrations (C:D ratios) from 248 patients. Both intrinsic factors (eg, sex, age, body weight) and extrinsic factors (eg, smoking status, comedications, hospitalization) were examined. Univariate and multivariable, linear, mixed-effects models were employed, with a stepwise selection procedure based on Akaike information criterion to identify the relevant covariates.
RESULTS
In the multivariable model (based on 440 observations with a complete data set), several significant findings emerged. Olanzapine C:D ratios were significantly lower in smokers (β = -0.65, P < 0.001), valproate users (β = -0.53, P = 0.002), and inpatients (β = -0.20, P = 0.025). Furthermore, the C:D ratios decreased significantly as the time since the last dose increased (β = -0.040, P < 0.001). The male sex had a significant main effect on olanzapine C:D ratios (β = -2.80, P < 0.001), with significant interactions with age (β = 0.025, P < 0.001) and body weight (β = 0.017, P = 0.011). The selected covariates explained 30.3% of the variation in C:D ratios, with smoking status accounting for 7.7% and sex contributing 6.9%. The overall variation explained by both the fixed and random parts of the model was 67.4%. The model facilitated the prediction of olanzapine C:D ratios based on sex, age, and body weight.
CONCLUSIONS
The clinical factors examined in this study, including sex, age, body weight, smoking status, and valproate comedication, remarkably influence olanzapine C:D ratios. Considering these factors, in addition to TDM and the clinical situation, could be important for dose adjustment.
PubMed: 38833576
DOI: 10.1097/FTD.0000000000001227 -
Zhongguo Ying Yong Sheng Li Xue Za Zhi... Dec 2023In the United States, cancer is one of the major causes of death. In 2010 alone, over 1.5 million fresh instances were recorded and over 0.5 billion died. After the... (Review)
Review
In the United States, cancer is one of the major causes of death. In 2010 alone, over 1.5 million fresh instances were recorded and over 0.5 billion died. After the completion of human genome sequence, significant progress in characterizing human epigenomes, proteomes and metabolomes has been made; a stronger knowledge of pharmacogenomics has been established and the capacity for individual personalization of health care has grown considerably. Personalized medicine has recently been primarily used to systematically select or optimize the prevention and therapeutic care of the patient through genetic or other data about the particular patient. Molecular profiling in healthy samples and cancer patients can allow for more personalized medications than is currently available. Patient protein, genetic and metabolic information may be used for adapting medical attention to the needs of that individual. The development of complementary diagnostics is a key attribute of this medicinal model. Molecular tests measuring the level of proteins, genes or specific mutations are used to provide a specific treatment for a particular individual by stratify the status of a disease, selecting the right drugs and tailoring dosages to the particular needs of the patient. These methods are also available for assessing risk factors for a patient for a number of conditions and for tailoring individual preventive therapies. Recent advances of personalized cancer medicine, challenges and futures perspectives are discussed.
Topics: Precision Medicine; Humans; Neoplasms; Rare Diseases; Pharmacogenetics
PubMed: 38830754
DOI: 10.62958/j.cjap.2023.008 -
Circulation Jun 2024
Topics: Humans; Cardiomyopathy, Hypertrophic; Pharmacogenetics; Aminobutyrates; Benzylamines; Uracil; Urea
PubMed: 38829931
DOI: 10.1161/CIRCULATIONAHA.123.066916 -
Expert Review of Clinical Pharmacology Jun 2024The treatment of HIV infection has been revolutionized in recent years thanks to the advent of dual antiretroviral regimens, administered orally or as long-acting... (Review)
Review
INTRODUCTION
The treatment of HIV infection has been revolutionized in recent years thanks to the advent of dual antiretroviral regimens, administered orally or as long-acting injectable formulations. Here, we provide an update on the usefulness of therapeutic drug monitoring (TDM) of antiretroviral drugs to optimize the management of people with HIV (PWH) in the current scenario.
AREAS COVERED
A MEDLINE PubMed search for articles published between January 2014 and January 2024 was completed matching the terms HIV, antiretrovirals and TDM. Moreover, additional studies were identified from the reference list of retrieved articles.
EXPERT OPINION
Available antiretroviral treatments achieve a response rate of 90%-95%, making the routine TDM of antiretroviral drugs of limited clinical value. However, there are still some important applications of TDM in selected clinical conditions, such as assessing patient compliance or suspected drug-drug interactions (DDIs). Indeed, we are increasingly having to deal with polypharmacy and DDIs in the context of an aging patient with comorbidities that may potentially alter the pharmacokinetics of antiretroviral drugs. Finally, the role of pharmacogenetics, which is closely related to TDM, in influencing both the disposition of antiretrovirals and the course of DDIs should also be considered.
PubMed: 38829318
DOI: 10.1080/17512433.2024.2363847