Virtual twins for model-informed precision dosing of clozapine in patients with treatment-resistant schizophrenia.

Model-informed precision dosing using virtual twins (MIPD-VTs) is an emerging strategy to predict target drug concentrations in clinical practice. Using a high virtualization MIPD-VT approach (Simcyp version 21), we predicted the steady-state clozapine concentration and clozapine dosage range to achieve a target concentration of 350 to 600 ng/mL in hospitalized patients with treatment-resistant schizophrenia (N = 11). We confirmed that high virtualization MIPD-VT can reasonably predict clozapine concentrations in individual patients with a coefficient of determination (R2 ) ranging between 0.29 and 0.60. Importantly, our approach predicted the final dosage range to achieve the desired target clozapine concentrations in 73% of patients. In two thirds of patients treated with fluvoxamine augmentation, steady-state clozapine concentrations were overpredicted two to four-fold. This work supports the application of a high virtualization MIPD-VT approach to inform the titration of clozapine doses in clinical practice. However, refinement is required to improve the prediction of pharmacokinetic drug-drug interactions, particularly with fluvoxamine augmentation.

Cytochrome P450-2D6 activity in people with codeine use disorder.

Compound-analgesics containing codeine (CACC) have been a common source of codeine for people seeking opioid replacement therapy (ORT) for codeine use disorder (CUD). Our previous work demonstrated no relationship between pre-treatment CACC and ORT buprenorphine doses; we hypothesised that CYP2D6 activity would partially account for this disconnection. One hundred six participants with CUD were compared to a published population sample of 5408 Australian patients. Mean age of participants with CUD at treatment entry was 35 years, with mean 6.1 years duration of CUD. Mean codeine dose was 660 mg/day (range 40-2700 mg). Mean calculated CYP2D6 activity scores were significantly higher in the codeine group (CUD 1.65 + 0.63 vs. Gen pop 1.39 + 0.65, Wilcoxon W = 347,001, p < 0.001). Pre-treatment CACC dose weakly predicted sublingual buprenorphine doses overall; there was a stronger relationship within ultrarapid metabolisers. While normal and ultrarapid metabolisers of codeine were more likely to have a diagnosis of CUD, poor or intermediate CYP2D6 metaboliser status may protect against CUD.

Delineating gene-environment effects using virtual twins of patients treated with clozapine.

Studies that focus on individual covariates, while ignoring their interactions, may not be adequate for model-informed precision dosing (MIPD) in any given patient. Genetic variations that influence protein synthesis should be studied in conjunction with environmental covariates, such as cigarette smoking. The aim of this study was to build virtual twins (VTs) of real patients receiving clozapine with interacting covariates related to genetics and environment and to delineate the impact of interacting covariates on predicted clozapine plasma concentrations. Clozapine-treated patients with schizophrenia (N = 42) with observed clozapine plasma concentrations, demographic, environmental, and genotype data were used to construct VTs in Simcyp. The effect of increased covariate virtualization was assessed by performing simulations under three conditions: "low" (demographic), "medium" (demographic and environmental interaction), and "high" (demographic and environmental/genotype interaction) covariate virtualization. Increasing covariate virtualization with interaction improved the coefficient of variation (R2 ) from 0.07 in the low model to 0.391 and 0.368 in the medium and high models, respectively. Whereas R2 was similar between the medium and high models, the high covariate virtualization model had improved accuracy, with systematic bias of predicted clozapine plasma concentration improving from -138.48 ng/ml to -74.65 ng/ml. A high level of covariate virtualization (demographic, environmental, and genotype) may be required for MIPD using VTs.

Pharmacogenomics in psychiatry - the challenge of cytochrome P450 enzyme phenoconversion and solutions to assist precision dosing.

Pharmacogenomic (PGx) testing of cytochrome P450 (CYP) enzymes may improve the efficacy and/or safety of some medications. This is facilitated by increased availability and affordability of genotyping, the development of clinical practice PGx guidelines and regulatory support. However, the common occurrence of CYP phenoconversion, a mismatch between genotype-predicted CYP phenotype and the actual CYP phenotype, currently limits the application of PGx testing for precision dosing in psychiatry. This review proposes a stepwise approach to assist precision dosing in psychiatry via the introduction of PGx stewardship programs and innovative PGx education strategies. A future perspective on delivering precision dosing for psychiatrists is discussed that involves innovative clinical decision support systems powered by model-informed precision dosing.

Quantifying the Impact of Phenoconversion on Medications With Actionable Pharmacogenomic Guideline Recommendations in an Acute Aged Persons Mental Health Setting.

Introduction: Polypharmacy and genetic variants that strongly influence medication response (pharmacogenomics, PGx) are two well-described risk factors for adverse drug reactions. Complexities arise in interpreting PGx results in the presence of co-administered medications that can cause cytochrome P450 enzyme phenoconversion. Aim: To quantify phenoconversion in a cohort of acute aged persons mental health patients and evaluate its impact on the reporting of medications with actionable PGx guideline recommendations (APRs). Methods: Acute aged persons mental health patients (N = 137) with PGx and medication data at admission and discharge were selected to describe phenoconversion frequencies for CYP2D6, CYP2C19 and CYP2C9 enzymes. The expected impact of phenoconversion was then assessed on the reporting of medications with APRs. Results: Post-phenoconversion, the predicted frequency at admission and discharge increased for CYP2D6 intermediate metabolisers (IMs) by 11.7 and 16.1%, respectively. Similarly, for CYP2C19 IMs, the predicted frequency at admission and discharge increased by 13.1 and 11.7%, respectively. Nineteen medications with APRs were prescribed 120 times at admission, of which 50 (42%) had APRs pre-phenoconversion, increasing to 60 prescriptions (50%) post-phenoconversion. At discharge, 18 medications with APRs were prescribed 122 times, of which 48 (39%) had APRs pre-phenoconversion, increasing to 57 prescriptions (47%) post-phenoconversion. Discussion: Aged persons mental health patients are commonly prescribed medications with APRs, but interpretation of these recommendations must consider the effects of phenoconversion. Adopting a collaborative care model between prescribers and clinical pharmacists should be considered to address phenoconversion and ensure the potential benefits of PGx are maximised.

Use of antidepressants with pharmacogenetic prescribing guidelines in a 10-year depression cohort of adult primary care patients.

OBJECTIVE: To describe the usage patterns of antidepressants with published CYP2D6- and CYP2C19-based prescribing guidelines among depressed primary care patients and estimate the proportion of patients taking antidepressants not recommended for them based on their CYP2C19 and CYP2D6 genotype-predicted metabolizer status. METHODS: Medication use and pharmacogenetic testing results were collected on 128 primary care patients enrolled in a 10-year depression cohort study. At each 12-month interval, we calculated the proportion of patients that: (1) reported use of one or more of the 13 antidepressant medications (i.e. amitriptyline, citalopram, escitalopram, clomipramine, desipramine, doxepin, fluvoxamine, imipramine, nortriptyline, paroxetine, sertraline, trimipramine, venlafaxine) with published CYP2D6- and CYP2C19-based prescribing guidelines, (2) were taking an antidepressant that was not recommended for them based on their CYP2C19 and CYP2D6 genotype-predicted metabolizer phenotype, and (3) switched medications from the previous 12-month interval. RESULTS: The annual proportion of individuals taking an antidepressant with a CYP2D6- and CYP2C19-based prescribing guidelines ranged from 45 to 84%. The proportion of participants that used an antidepressant that was not recommended for them, based on available CYP2D6 and CYP2C19 metabolizer phenotype, ranged from 18 to 29% and these individuals tended to switch medications more frequently (10%) compared to their counterparts taking medication aligned with their metabolizer phenotype (6%). CONCLUSION: One-quarter of primary care patients used an antidepressant that was not recommended for them based on CYP2D6- and CYP2C19-based prescribing guidelines and switching medications tended to be more common in this group. Studies to determine the impact of CYP2D6 and CYP2C19 genotyping on reducing gene-antidepressant mismatches are warranted.

Impact of CYP1A2, CYP2C19, and CYP2D6 genotype- and phenoconversion-predicted enzyme activity on clozapine exposure and symptom severity.

Clozapine is an atypical antipsychotic metabolized by CYP1A2, CYP2D6, and CYP2C19 enzymes. Among 66 adult schizophrenia patients treated with clozapine-based combination therapies, we explored the impact of genotype-predicted CYP1A2, CYP2D6, and CYP2C19 activity on dose-adjusted clozapine concentrations and symptom severity, with and without correction for inhibitors and inducers of these enzymes. Uncorrected activity scores were not associated with dose-adjusted clozapine concentrations or symptom severity. CYP1A2 and CYP2D6 activity scores corrected for known inducers (i.e., smoking) and inhibitors (e.g., concomitant medications) were associated with dose-adjusted clozapine levels and in the case of CYP1A2, symptom severity. However, smoking status and certain inhibitors of clozapine metabolism (i.e., esomeprazole) explained significantly more variance in dose-adjusted clozapine levels relative to corrected activity scores. These findings highlight the clinical importance of nongenetic factors (smoking, concomitant medications) and suggest that the added utility of CYP1A2, CYP2D6, and CYP2C19 activity scores to guide clozapine dosing is currently limited.

An analysis of allele, genotype and phenotype frequencies, actionable pharmacogenomic (PGx) variants and phenoconversion in 5408 Australian patients genotyped for CYP2D6, CYP2C19, CYP2C9 and VKORC1 genes.

Common polymorphisms in the genes encoding CYP2D6, CYP2C19, CYP2C9 and VKORC1 enzymes have an important role in predicting the occurrence of adverse effects and the efficacy of substrate medications. Drug-induced changes to the enzyme's phenotype, a process called phenoconversion, comprise another important factor contributing to interindividual variability in drug response. To date, there is lack of data on the frequency of these common polymorphisms and phenoconversion in the pan-ethnic Australian population. The aim of this study was to (1) describe allele, genotype and phenotype frequencies for CYP2D6, CYP2C19, CYP2C9 and VKORC1 enzymes in the pan-ethnic Australian population and (2) evaluate the frequency of actionable pharmacogenomic (PGx) variants and phenoconversion. Frequencies were calculated using the records of 5408 Australian patients (obtained from myDNA's propriety database), who were consecutively tested with the DNAdose PGx test which included the CYP2D6, CYP2C19, CYP2C9 and VKORC1 genes. In 2509 patients with listed medications at the time of testing, phenoconversion frequencies were calculated for CYP2D6, CYP2C19 and CYP2C9 enzymes. Allele, genotype and phenotype frequencies in our Australian patients correlated with a Caucasian population. Approximately 96% of patients had at least one actionable PGx variant. A five-fold increase in the frequency of poor metabolisers (PMs) for CYP2D6 and CYP2C19 was predicted by phenoconversion. Our study results indicate a high frequency of actionable PGx variants in our Australian population. With the addition of drug-induced phenoconversion, our results provide further support for the utilisation of PGx testing in clinical practice as another tool assisting prescribers in the application of personalised medicine.

Polysubstance-induced relapse of schizoaffective disorder refractory to high-dose antipsychotic medications: a case report.

BACKGROUND: The high prevalence of comorbid illicit drug use in persons with chronic psychotic illness represents a strong determinant of psychotic relapse and rehospitalization. Epidemiological studies indicate changing patterns of illicit drug use in Australia, which are concerning because of increased use of crystal methamphetamine, also known as "ice." An important complication of habitual use of crystal methamphetamine is the development of a dose-dependent acute psychotic reaction. We report a case of an acute psychotic relapse in response to polydrug use most notable for multiple recent binges of crystal methamphetamine. Unlike previously described case reports, our patient's acute psychosis was refractory to ultra-high doses of multiple antipsychotic medications. This presented safety challenges due to the risk of serious side effects with high-dose antipsychotic medications. CASE PRESENTATION: A 30-year-old white man with a past history of schizoaffective disorder was brought to our emergency department by the police in a state of extreme agitation, combativeness, and paranoia after use of cannabis and crystal methamphetamine. Despite existing compliance with zuclopenthixol decanoate depot medication, he required multiple emergency injections of zuclopenthixol acetate, and regular high-dose droperidol, chlorpromazine, and lorazepam. However, he remained severely agitated and psychotic with continuous threats of harm to others. A test of antipsychotic drug metabolism by cytochrome P450 enzymes did not reveal a pharmacogenetic cause for the poor therapeutic efficacy of antipsychotic medications. His psychosis did not appear to be modified by psychoactive medications but was instead self-limited to the presence of endogenous methamphetamine within his system. He fully recovered 96 to 120 hours post-presentation and was discharged home with out-patient clinic follow-up. CONCLUSIONS: The current case highlights the challenging nature of a severe psychotic relapse precipitated by illicit substances that is resistant to medical management. High doses of multiple antipsychotic medications may be required to manage dangerous behaviors associated with these acute psychotic relapses. These patients require close monitoring for adverse effects with adjustment of dosing to ensure the optimal balance of risk versus benefit while the patient is acutely psychotic. The results are of relevance for the management of psychiatric emergencies in emergency departments and acute mental health settings.