A precision medicine approach to personalized prescribing using genetic and nongenetic factors for clinical decision-making.

Screening potential drug-drug interactions, drug-gene interactions, contraindications, and other factors is crucial in clinical practice. However, implementing these screening concepts in real-world settings poses challenges. This work proposes an approach towards precision medicine that combines genetic and nongenetic factors to facilitate clinical decision-making. The approach focuses on raising the performance of four potential interaction screenings in the prescribing process, including drug-drug interactions, drug-gene interactions, drug-herb interactions, drug-social lifestyle interactions, and two potential considerations for patients with liver or renal impairment. The work describes the design of a curated knowledge-based model called the knowledge model for potential interaction and consideration screening, the screening logic for both the detection module and inference module, and the personalized prescribing report. Three case studies have demonstrated the proof-of-concept and effectiveness of this approach. The proposed approach aims to reduce decision-making processes for healthcare professionals, reduce medication-related harm, and enhance treatment effectiveness. Additionally, the recommendation with a semantic network is suggested to assist in risk-benefit analysis when health professionals plan therapeutic interventions with new medicines that have insufficient evidence to establish explicit recommendations. This approach offers a promising solution to implementing precision medicine in clinical practice.

Association of UGT1A1*6, UGT1A1*28, or ABCC2 c.3972C>T genetic polymorphisms with irinotecan-induced toxicity in Asian cancer patients: Meta-analysis.

Effects of UGT1A1*6 and UGT1A1*28 genetic polymorphisms on irinotecan-induced severe toxicities in Asian cancer patients are inconclusive. Also, ABCC2 c.3972C>T may affect toxicity of irinotecan. The aim was to assess the aggregated risk of neutropenia or diarrhea in Asian cancer patients taking irinotecan and inherited UGT1A1*6, UGT1A1*28, or ABCC2 c.3972C>T genetic variants. A PubMed literature search for eligible studies was conducted. Odds ratios (ORs) were measured using RevMan software where p values <0.05 were statistically significant. Patients that inherited both UGT1A1*6 and UGT1A1*28 genetic variants (heterozygous: UGT1A1*1/*6 + *1/*28 and homozygous: UGT1A1*6/*6 + *28/*28) were significantly associated with increased risk of neutropenia and diarrhea compared to patients with UGT1A1*1/*1 (neutropenia: OR 2.89; 95% CI 1.97-4.23; p < 0.00001; diarrhea: OR 2.26; 95% CI 1.71-2.99; p < 0.00001). Patients carrying homozygous variants had much stronger effects in developing toxicities (neutropenia: OR 6.23; 95% CI 3.11-12.47; p < 0.00001; diarrhea: OR 3.21; 95% CI 2.13-4.85; p < 0.00001) than those with heterozygous variants. However, patients carrying the ABCC2 c.3972C>T genetic variant were not significantly associated with neutropenia (OR 1.67; 95% CI 0.98-2.84; p = 0.06) and were significantly associated with a reduction in irinotecan-induced diarrhea (OR 0.31; 95% CI 0.11-0.81; p = 0.02). Asian cancer patients should undergo screening for both UGT1A1*6 and UGT1A1*28 genetic variants to reduce substantially irinotecan-induced severe toxicities.

Pharmacogenomics Factors Influencing the Effect of Risperidone on Prolactin Levels in Thai Pediatric Patients With Autism Spectrum Disorder.

We investigated the association between genetic variations in pharmacodynamic genes and risperidone-induced increased prolactin levels in children and adolescents with autism spectrum disorder (ASD). In a retrospective study, variants of pharmacodynamic genes were analyzed in 124 ASD patients treated with a risperidone regimen for at least 3 months. To simplify genotype interpretation, we created an algorithm to calculate the dopamine D2 receptor (DRD2) gene genetic risk score. There was no relationship between prolactin levels and single SNPs. However, the H1/H3 diplotype (A2/A2-Cin/Cin-A/G) of DRD2/ankyrin repeat and kinase domain containing 1 (ANKK1) Taq1A, DRD2 -141C indel, and DRD2 -141A>G, which had a genetic risk score of 5.5, was associated with the highest median prolactin levels (23 ng/ml). As the dose-corrected plasma levels of risperidone, 9-OH-risperidone, and the active moiety increased, prolactin levels in patients carrying the H1/H3 diplotype were significantly higher than those of the other diplotypes. DRD2 diplotypes showed significantly high prolactin levels as plasma risperidone levels increased. Lower levels of prolactin were detected in patients who responded to risperidone. This is the first system for describing DRD2 haplotypes using genetic risk scores based on their protein expression. Clinicians should consider using pharmacogenetic-based decision-making in clinical practice to prevent prolactin increase.