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Cuvelier E, Khazri H, Lecluse C, Hennart B, Amad A, Roche J, Tod M, Vaiva G, Cottencin O, Odou P, Allorge D, Décaudin B, Simon N. Therapeutic Drug Monitoring and Pharmacogenetic Testing as Guides to Psychotropic Drug Dose Adjustment: An Observational Study. Pharmaceuticals (Basel) 2023; 17:21. [PMID: 38256855 PMCID: PMC10818858 DOI: 10.3390/ph17010021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 12/13/2023] [Accepted: 12/15/2023] [Indexed: 01/24/2024] Open
Abstract
To avoid the failures in therapy with psychotropic drugs, treatments can be personalized by applying the results of therapeutic drug monitoring and pharmacogenetic testing. The objective of the present single-center observational study was to describe the changes in psychotropic drug management prompted by therapeutic drug monitoring and pharmacogenetic testing, and to compare the effective drug concentration based on metabolic status with the dose predicted using an in silico decision tool for drug-drug interactions. The study was conducted in psychiatry wards at Lille University Hospital (Lille, France) between 2016 and 2020. Patients with data for at least one therapeutic drug monitoring session or pharmacogenetic test were included. Blood tests were performed for 490 inpatients (mainly indicated by treatment monitoring or failure) and mainly concerned clozapine (21.4%) and quetiapine (13.7%). Of the 617 initial therapeutic drug monitoring tests, 245 (40%) complied with good sampling practice. Of the patients, 51% had a drug concentration within the therapeutic range. Regardless of the drug concentration, the drug management did not change in 83% of cases. Thirty patients underwent pharmacogenetic testing (twenty-seven had also undergone therapeutic drug monitoring) for treatment failure; the plasma drug concentration was outside the reference range in 93% of cases. The patient's metabolic status explained the treatment failure in 12 cases (40%), and prompted a switch to a drug metabolized by another CYP450 pathway in 5 cases (42%). Of the six tests that could be analyzed with the in silico decision tool, all of the drug concentrations after adjustment were included in the range estimated by the tool. Knowledge of a patient's drug concentration and metabolic status (for CYD2D6 and CYP2C19) can help clinicians to optimize psychotropic drug adjustment. Drug management can be optimized with good sampling practice, support from a multidisciplinary team (a physician, a geneticist, and clinical pharmacist), and decision support tools.
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Affiliation(s)
- Elodie Cuvelier
- CHU Lille, Institut de Pharmacie, F-59000 Lille, France (P.O.); (B.D.); (N.S.)
- GRITA—Groupe de Recherche Sur Les Formes Injectables Et Les Technologies Associées ULR 7365, CHU Lille, University Lille, F-59000 Lille, France
| | - Houda Khazri
- CHU Lille, Institut de Pharmacie, F-59000 Lille, France (P.O.); (B.D.); (N.S.)
- GRITA—Groupe de Recherche Sur Les Formes Injectables Et Les Technologies Associées ULR 7365, CHU Lille, University Lille, F-59000 Lille, France
| | - Cloé Lecluse
- CHU Lille, Institut de Pharmacie, F-59000 Lille, France (P.O.); (B.D.); (N.S.)
| | - Benjamin Hennart
- CHU Lille, Pôle de Biologie-Pathologie-Génétique, Unité Fonctionnelle de Toxicologie, F-59000 Lille, France; (B.H.); (D.A.)
| | - Ali Amad
- Inserm, CHU Lille, U1172—LilNcog—Lille Neuroscience & Cognition, University Lille, F-59000 Lille, France; (A.A.); (G.V.)
| | - Jean Roche
- CHU de Lille, Unité de Psychogériatrie, Pôle de Gérontologie, F-59037 Lille, France;
| | - Michel Tod
- UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, Université Lyon 1, F-69622 Lyon, France;
| | - Guillaume Vaiva
- Inserm, CHU Lille, U1172—LilNcog—Lille Neuroscience & Cognition, University Lille, F-59000 Lille, France; (A.A.); (G.V.)
| | - Olivier Cottencin
- CHU de Lille, Service d’addictologie, CNRS, UMR 9193, SCALab, équipe psyCHIC, CS 70001, Université de Lille, F-59037 Lille, France;
| | - Pascal Odou
- CHU Lille, Institut de Pharmacie, F-59000 Lille, France (P.O.); (B.D.); (N.S.)
- GRITA—Groupe de Recherche Sur Les Formes Injectables Et Les Technologies Associées ULR 7365, CHU Lille, University Lille, F-59000 Lille, France
| | - Delphine Allorge
- CHU Lille, Pôle de Biologie-Pathologie-Génétique, Unité Fonctionnelle de Toxicologie, F-59000 Lille, France; (B.H.); (D.A.)
- CHU Lille, Institut Pasteur Lille, ULR 4483—IMPECS—IMPact de l’Environnement Chimique sur la Santé Humaine, Université de Lille, F-59000 Lille, France
| | - Bertrand Décaudin
- CHU Lille, Institut de Pharmacie, F-59000 Lille, France (P.O.); (B.D.); (N.S.)
- GRITA—Groupe de Recherche Sur Les Formes Injectables Et Les Technologies Associées ULR 7365, CHU Lille, University Lille, F-59000 Lille, France
| | - Nicolas Simon
- CHU Lille, Institut de Pharmacie, F-59000 Lille, France (P.O.); (B.D.); (N.S.)
- GRITA—Groupe de Recherche Sur Les Formes Injectables Et Les Technologies Associées ULR 7365, CHU Lille, University Lille, F-59000 Lille, France
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Jang S, Ford LC, Rusyn I, Chiu WA. Cumulative Risk Meets Inter-Individual Variability: Probabilistic Concentration Addition of Complex Mixture Exposures in a Population-Based Human In Vitro Model. TOXICS 2022; 10:toxics10100549. [PMID: 36287830 PMCID: PMC9611413 DOI: 10.3390/toxics10100549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/03/2022] [Accepted: 09/16/2022] [Indexed: 05/16/2023]
Abstract
Although humans are continuously exposed to complex chemical mixtures in the environment, it has been extremely challenging to investigate the resulting cumulative risks and impacts. Recent studies proposed the use of “new approach methods,” in particular in vitro assays, for hazard and dose−response evaluation of mixtures. We previously found, using five human cell-based assays, that concentration addition (CA), the usual default approach to calculate cumulative risk, is mostly accurate to within an order of magnitude. Here, we extend these findings to further investigate how cell-based data can be used to quantify inter-individual variability in CA. Utilizing data from testing 42 Superfund priority chemicals separately and in 8 defined mixtures in a human cell-based population-wide in vitro model, we applied CA to predict effective concentrations for cytotoxicity for each individual, for “typical” (median) and “sensitive” (first percentile) members of the population, and for the median-to-sensitive individual ratio (defined as the toxicodynamic variability factor, TDVF). We quantified the accuracy of CA with the Loewe Additivity Index (LAI). We found that LAI varies more between different mixtures than between different individuals, and that predictions of the population median are generally more accurate than predictions for the “sensitive” individual or the TDVF. Moreover, LAI values were generally <1, indicating that the mixtures were more potent than predicted by CA. Together with our previous studies, we posit that new approach methods data from human cell-based in vitro assays, including multiple phenotypes in diverse cell types and studies in a population-wide model, can fill critical data gaps in cumulative risk assessment, but more sophisticated models of in vitro mixture additivity and bioavailability may be needed. In the meantime, because simple CA models may underestimate potency by an order of magnitude or more, either whole-mixture testing in vitro or, alternatively, more stringent benchmarks of cumulative risk indices (e.g., lower hazard index) may be needed to ensure public health protection.
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Affiliation(s)
- Suji Jang
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Lucie C. Ford
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Weihsueh A. Chiu
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
- Correspondence: ; Tel.: +1-(979)-845-4106
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Moreau F, Simon N, Walther J, Dambrine M, Kosmalski G, Genay S, Perez M, Lecoutre D, Belaiche S, Rousselière C, Tod M, Décaudin B, Odou P. Does DDI-Predictor Help Pharmacists to Detect Drug-Drug Interactions and Resolve Medication Issues More Effectively? Metabolites 2021; 11:metabo11030173. [PMID: 33802983 PMCID: PMC8002594 DOI: 10.3390/metabo11030173] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/12/2021] [Accepted: 03/15/2021] [Indexed: 12/01/2022] Open
Abstract
The characterization of drug-drug interactions (DDIs) may require the use of several different tools, such as the thesaurus issued by our national health agency (i.e., ANSM), the metabolic pathways table from the Geneva University Hospital (GUH), and DDI-Predictor (DDI-P). We sought to (i) compare the three tools’ respective abilities to detect DDIs in routine clinical practice and (ii) measure the pharmacist intervention rate (PIR) and physician acceptance rate (PAR) associated with the use of DDI-P. The three tools’ respective DDI detection rates (in %) were measured. The PIRs and PARs were compared by using the area under the curve ratio given by DDI-P (RAUC) and applying a chi-squared test. The DDI detection rates differed significantly: 40.0%, 76.5%, and 85.2% for ANSM (The National Agency for the Safety of Medicines and Health Products), GUH and DDI-P, respectively (p < 0.0001). The PIR differed significantly according to the DDI-P’s RAUC: 90.0%, 44.2% and 75.0% for RAUC ≤ 0.5; RAUC 0.5–2 and RAUC > 2, respectively (p < 0.001). The overall PAR was 85.1% and did not appear to depend on the RAUC category (p = 0.729). Our results showed that more pharmacist interventions were issued when details of the strength of the DDI were available. The three tools can be used in a complementary manner, with a view to refining medication adjustments.
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Affiliation(s)
- Fanny Moreau
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Nicolas Simon
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
- ULR 7365–GRITA–Groupe de Recherche sur les formes Injectables et les Technologies Associées, University of Lille, F-59000 Lille, France
- Correspondence: ; Tel.: +33-320-964-029
| | - Julia Walther
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Mathilde Dambrine
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Gaetan Kosmalski
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Stéphanie Genay
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
- ULR 7365–GRITA–Groupe de Recherche sur les formes Injectables et les Technologies Associées, University of Lille, F-59000 Lille, France
| | - Maxime Perez
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Dominique Lecoutre
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Stéphanie Belaiche
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Chloé Rousselière
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
| | - Michel Tod
- EMR: 3738, Faculté de Médecin Lyon-Sud-Charles Mérieux, Université Lyon 1, F-69921 Oullins, France;
- Pharmacie, Groupement Hospitalier Nord, Hospices Civils de Lyon, F-69005 Lyon, France
| | - Bertrand Décaudin
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
- ULR 7365–GRITA–Groupe de Recherche sur les formes Injectables et les Technologies Associées, University of Lille, F-59000 Lille, France
| | - Pascal Odou
- Institut de Pharmacie, CHU Lille, F-59000 Lille, France; (F.M.); (J.W.); (M.D.); (G.K.); (S.G.); (M.P.); (D.L.); (S.B.); (C.R.); (B.D.); (P.O.)
- ULR 7365–GRITA–Groupe de Recherche sur les formes Injectables et les Technologies Associées, University of Lille, F-59000 Lille, France
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Tod M, Bourguignon L, Bleyzac N, Goutelle S. Quantitative Prediction of Interactions Mediated by Transporters and Cytochromes: Application to Organic Anion Transporting Polypeptides, Breast Cancer Resistance Protein and Cytochrome 2C8. Clin Pharmacokinet 2019; 59:757-770. [DOI: 10.1007/s40262-019-00853-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Fanelli A, Palazzo C, Balzani E, Iuvaro A, Pelotti S, Melotti RM. An Explorative Study of CYP2D6’s Polymorphism in a Sample of Chronic Pain Patients. PAIN MEDICINE 2019; 21:1010-1017. [DOI: 10.1093/pm/pnz265] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Abstract
Background
A proper antalgic treatment is based on the use of titrated drugs to provide adequate relief and a good tolerability profile. Therapies have a variable effectiveness among subjects depending on medical and genetic conditions. CYP2D6 variations determine a different clinical response to most analgesic drugs commonly used in daily clinical practice by influencing the drugs’ pharmacokinetics. This study was a monocentric clinical trial exploring the CYP2D6 variants in 100 patients with a diagnosis of chronic pain.
Methods
DNA was extracted to evaluate the genotype and to classify patients as normal-fast (gNMs-F), normal-slow (gNMs-S), ultrarapid (gUMs), intermediate (gIMs), and poor metabolizers (gPMs) using the Activity Score (AS). Information on therapies and general side effects experienced by patients was collected. Nongenetic co-factors were evaluated to examine the discrepancy between metabolic profile predicted from genotype (gPh) and metabolic profile (phenocopying).
Results
The distribution of our data underlined the prevalence of the gNMs-F (67%), whereas gNMs-S were 24%, gIMs 6%, gPMs 3%, and no gUMs were found, resulting in 33% of patients with reduced metabolic activity. In the analyzed population sample, 86% and 56% of patients, respectively, took at least one or two drugs inhibiting in vitro activity of the CYP2D6 enzyme.
Conclusions
Over one-third of the enrolled patients showed altered CYP2D6 enzymatic metabolic activity, with a risk of phenocopying potentially due to polypharmacology.
Trial registration
ClinicalTrials.gov ID: NCT03411759.
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Affiliation(s)
- Andrea Fanelli
- Anesthesia and Pain Medicine Unit, Department of Emergency and Urgency, Policlinico S.Orsola-Malpighi Hospital, Bologna, Italy
| | - Chiara Palazzo
- Forensic Science and Legal Medicine, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | | | - Alessandra Iuvaro
- Forensic Science and Legal Medicine, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Susi Pelotti
- Forensic Science and Legal Medicine, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Rita Maria Melotti
- Anesthesia and Pain Medicine Unit, Department of Emergency and Urgency, Policlinico S.Orsola-Malpighi Hospital, Bologna, Italy
- University of Bologna, Bologna, Italy
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Identification of Cytochrome P450-Mediated Drug-Drug Interactions at Risk in Cases of Gene Polymorphisms by Using a Quantitative Prediction Model. Clin Pharmacokinet 2019; 57:1581-1591. [PMID: 29572664 DOI: 10.1007/s40262-018-0651-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND OBJECTIVE The magnitude of drug-drug interactions mediated by cytochrome P450 (CYP) may depend on the genotype of polymorphic cytochromes. The objective of this study was to identify drug-drug interactions with greater magnitude in CYP variant groups than in extensive metabolizers. METHODS The in-vivo mechanistic static model was used to predict the area under the curve ratio of drug-drug interactions. Five cytochromes (CYP3A4/5, 2D6, 2C9, 2C19, 1A2) and five groups of genotypes for each polymorphic cytochrome (CYP2D6, 2C9, 2C19) were considered. The area under the curve ratios were calculated for all combinations and all genotypes for 196 substrates and 96 inhibitors. Among the strongest interactions (area under the curve ratio greater than 5), two levels of gene sensitivity of drug-drug interactions were defined: the intermediate sensitivity, with a three- to five-fold stronger interaction in genotype groups other than in extensive metabolizers, and the high sensitivity, with a more than five-fold stronger interaction than in genotype groups other than extensive metabolizers. RESULTS A red list of 104 interactions with a sensitivity greater than 3, involving 13 substrates and 24 interactors was obtained. There were 59 and 45 cases of high and intermediate sensitivity, respectively. The genotypes associated with a high sensitivity were CYP2D6 *3-8 *3-8 (sensitivity up to 24.3) and CYP2C19 *2-3*2-3 (sensitivity up to 37.8). CONCLUSIONS A cytochrome polymorphism may lead to major drug-drug interactions in poor metabolizers, while these interactions may not be significant in extensive metabolizers. Among the 104 cases studied, the interaction could be of ca. 30-fold larger magnitude in the worst case. Genotyping of the patient and/or therapeutic drug monitoring of the substrate should be carried out when an association mentioned in the red list is prescribed. The concept of gene sensitivity of drug-drug interactions appears promising for the development of precision medicine.
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Tod M, Goutelle S, Bleyzac N, Bourguignon L. A Generic Model for Quantitative Prediction of Interactions Mediated by Efflux Transporters and Cytochromes: Application to P-Glycoprotein and Cytochrome 3A4. Clin Pharmacokinet 2018; 58:503-523. [DOI: 10.1007/s40262-018-0711-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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