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trifluoperazine + trihexyphenidyl (Fluhex forte / Fluhex / Fluhexette)

✓ Approved

A. N. Pharmacia Laboratories · CHRM1 · Small Molecule

What is trifluoperazine + trihexyphenidyl?

trifluoperazine + trihexyphenidyl is a small molecule developed by A. N. Pharmacia Laboratories. It is approved for therapeutic indications via oral (po).

Drug Profile

Brand NamesFluhex forte, Fluhex, Fluhexette
CompanyA. N. Pharmacia Laboratories
Drug ClassSmall Molecule
Molecular TargetCHRM1
RouteOral (PO)
StatusApproved
Sources: ClinicalTrials.gov, A. N. Pharmacia Laboratories

Mechanism of Action

Molecular Targets

trifluoperazine + trihexyphenidyl acts on 1 molecular target:

CHRM1cholinergic receptor muscarinic 1 (M1, HM1)
Want deeper analysis?Noah AI can explain complex mechanisms and compare to similar drugs.

Therapeutic Indications

trifluoperazine + trihexyphenidyl is developed for 1 unique indication across 1 therapeutic area.

Therapeutic AreaConditionPhase
Psychiatric disordersSubstance-induced psychotic disorder✓ Approved

Related Research Articles

PubMedCurrent drug targets2026-09-30

Identification of Potential Therapeutic Target Genes for Bipolar Disorder through Systematic Druggable Genome-wide Mendelian Randomization.

Jin Yan-Ting YT, Zhang Tian-Yu TY, Xiang Chang-Cheng CC, Ma Cai-Yi CY et al.

Bipolar Disorder (BD) is a severe psychiatric condition with high heritability and clinical heterogeneity. Despite numerous genetic variants linked to BD through Genome- Wide Association Studies (GWAS), the molecular mechanisms and effective therapeutic targets remain unclear. This study aims to identify potential therapeutic targets for BD using a systematic approach. In this study, we performed a systematic druggable genome-wide Mendelian Randomization (MR) analysis to identify potential therapeutic target genes for BD. We integrated large-scale GWAS data, expression Quantitative Trait Loci (eQTL) datasets, and druggable gene resources to construct a set of 6,888 potential druggable genes. MR methods were applied to infer causal relationships between these genes and BD. Additionally, Protein-Protein Interaction (PPI) network analysis, Gene Ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the biological functions and pathways involved. Drug enrichment analysis was performed to assess the association between identified genes and approved psychiatric drugs, while Bayesian colocalization analysis was used to provide evidence for causal genetic signals underlying potential druggable targets. Our MR analysis revealed 34 genes with significant causal associations with BD. These genes were found to be predominantly involved in immune regulation, neuro-metabolic processes, and oxidative stress-related pathways. Drug enrichment analysis identified a close association between these genes and several approved psychiatric drugs, including trifluoperazine, clozapine, and alprazolam. Further, Bayesian colocalization analysis provided strong evidence for GSTM1 and CD52 as potential druggable targets for BD, suggesting that their gene expression shares causal genetic signals with disease susceptibility. Our findings support previous studies linking immune dysregulation to BD, with the identified genes enriched in immune-metabolic and oxidative stress pathways. A key limitation is the reliance on GWAS data primarily from European cohorts, which may limit the generalizability to other populations. This study prioritizes candidate druggable genes for BD through integrative analysis of GWAS, eQTL, MR, drug enrichment, and colocalization evidence. Our findings provide insights into BD-related molecular mechanisms and suggest potential avenues for target prioritization and drug repurposing research.

PMID 42813637
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PubMedIndian journal of psychiatry2026-09-11

Adverse effect MonoPoly: Antipsychotic monopharmacy vs antipsychotic polypharmacy in the treatment of schizophrenia.

Singh Shaurya S, Shenoy Sonia S, Praharaj Samir Kumar SK

Although antipsychotic polypharmacy (APP) is not recommended for the treatment of schizophrenia, it remains a common clinical practice. While APP is generally presumed to be associated with a higher burden of adverse effects, the current evidence remains inconclusive. This study compared the adverse effects experienced by patients with schizophrenia (excluding those receiving clozapine) treated with antipsychotic monopharmacy (APM) or APP using both subjective and objective assessments. This cross-sectional study included 114 patients with schizophrenia (56 receiving APM and 58 receiving APP). Spontaneously reported adverse effects, including their number and type, were recorded. Objective adverse effects were assessed using the Liverpool University Neuroleptic Side Effect Rating Scale (LUNSERS), Simpson-Angus Scale (SAS), Barnes Akathisia Rating Scale (BARS), and Abnormal Involuntary Movement Scale (AIMS). No significant differences were observed between the APM and APP groups on the overall subjective or objective measures of adverse effects. However, headache (P = 0.04), difficulty concentrating (P = 0.01), constipation (P = 0.01), restlessness (P = 0.01), and insomnia (P = 0.006) were reported significantly more frequently in the APP group. Compared with the APM group, patients receiving APP had a significantly longer duration of illness (P = 0.004; d = 0.55), lower treatment adherence (P = 0.02; d = 0.25), a higher total chlorpromazine-equivalent dose (P < 0.001; d = 1.21), and a higher rate of trihexyphenidyl use (P = 0.01; φ = 0.23). Overall adverse effects were comparable between the APM and APP groups. However, APP was associated with higher antipsychotic and trihexyphenidyl use; more insomnia, restlessness, constipation, and difficulty concentrating; and poorer treatment adherence.

PMID 42725345
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PubMedFrontiers in medicine2026-09-10

Infectious, inflammatory, and clinical outcomes among patients prescribed trifluoperazine or amoxapine: a retrospective cohort study using real-world data.

Malik Omar O, Rodriguez-Fernandez Jorge J, Yakubu Aliu Opeyemi AO, Farrag Wedad W et al.

The rise of antimicrobial resistance and limited development of new antibiotics have increased interest in drug repurposing. Preclinical evidence suggests that certain psychotropic drugs, including trifluoperazine (TFP) and amoxapine (AXPN), possess antimicrobial or immunomodulatory properties. However, their effects on infection risk in clinical populations are largely unknown. This study evaluated whether TFP or AXPN use is associated with altered risks of infectious illnesses, systemic inflammation, and mortality compared to patients not taking antidepressants. This retrospective cohort study utilized TriNetX, a federated network of de-identified electronic health records from over 75 million patients. Patients prescribed TFP, AXPN, fluoxetine, or no antidepressants/antipsychotics (general control) were assigned to mutually exclusive cohorts. Age- and sex-matched comparisons were conducted for four groups. Assessed outcomes included bacterial and viral infections (e.g., Clostridioides difficile), severe acute respiratory syndrome coronavirus 2, an etiological agent of COVID-19, as well as for pneumonia and sepsis, inflammatory markers (C-Reactive Protein, Erythrocyte Sedimentation Rate, ferritin, and procalcitonin), Intensive Care Unit admission, and mortality. Risk ratios (RR), odds ratios (OR), 95% confidence intervals, and Kaplan-Meier survival analyses were performed for significant findings. Overall, 2,177 TFP and 834 AXPN patients met the inclusion criteria. TFP was associated with significantly lower rates of ENT/dental infections across all three age groups compared with general controls (RR 0.316-0.405, all p ≤ 0.002). It was also consistently associated with increased leukocytosis across all age strata. Reduced COVID-19 incidence was observed primarily in older adults (70-90 years) versus general controls. AXPN showed fewer associations overall, with a significant reduction in C. difficile infection (RR 0.458, p = 0.025) and lower leukocytosis (RR 0.685, p = 0.012) in the 70-90 age group compared with fluoxetine. Most other outcomes, including pneumonia, sepsis, and other inflammatory markers, did not differ significantly when compared to general control or fluoxetine groups. These exploratory findings identify potential signals linking TFP and AXPN to infection susceptibility. Given the study design, these observations are hypothesis-generating and require confirmation in future prospective studies.

PMID 42718509
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PubMedBiochimica et biophysica acta. Biomembranes2026-07-24

Molecular dynamics perspectives on annexin-mediated plasma membrane repair: From recruitment to membrane mechanics.

Hakami Zanjani Ali Asghar AA

This mini-review examines how molecular dynamics simulations reshape the view of annexin-mediated plasma membrane repair from simple recruitment to coupled protein-membrane states. Molecular dynamics simulations show that annexin-induced curvature is shaped by oligomerization, cholesterol, and anionic lipid chemistry, while engineering normally non-trimerizing annexin A3 into a trimer-forming state demonstrates that curvature generation alone does not ensure repair competence. Membrane-active perturbants such as trifluoperazine further suppress repair by altering bilayer thickness, lipid packing, phosphatidylserine mobility, and annexin binding. These findings shift the question from whether annexins arrive to how protein-membrane states generate repair-relevant remodeling.

PMID 42492800
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PubMedAntimicrobial agents and chemotherapy2026-07-23

Trifluoperazine exhibits broad-spectrum antiviral activity against arboviruses.

Mishra Laxmi L, Kalia Manjula M

The recurrent outbreaks and geographical expansion of mosquito-borne arboviruses pose a significant challenge to public health worldwide. The disease outcome for arboviral infections ranges from acute febrile illness to severe conditions such as encephalitis, hemorrhagic shock, and mortality. Current treatment options for these viruses are limited to supportive care, necessitating an urgent need for a safe and effective broad-spectrum antiviral. In this study, we have identified trifluoperazine (TFP), an FDA-approved antipsychotic, as a potent broad-spectrum antiviral against Japanese encephalitis virus (JEV), Dengue virus (DENV), and Chikungunya virus (CHIKV) infections. The antiviral effect of TFP was also seen in the animal models of JEV and CHIKV with significantly reduced disease severity. Mechanistically, TFP treatment increased the phosphorylation of eIF2a and induced an adaptive ER stress response in diverse cell types. Alleviation of TFP-induced ER stress by chemical chaperone 4PBA abolished the antiviral activity of the drug and rescued virus replication in cells and CHIKV mice model. The robust in vitro and in vivo efficacy of the drug against arboviruses highlights the potential for repurposing TFP as a broad-spectrum antiviral candidate and underscores the importance of ER stress as a therapeutic target.

PMID 42489647
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PubMedCureus2026-07-17

Multi-ancestry Transcriptome-Wide Association Study (TWAS)-Informed Prioritization of Antipsychotic Metabolic Risk: Evaluation of GLP1R as a Shared Mechanistic Link.

Cheung Ngo N

Antipsychotic-associated metabolic toxicity remains one of the most persistent clinical problems in psychopharmacology. Clozapine and olanzapine are especially effective for psychosis but carry high liability for weight gain, dyslipidemia, insulin resistance, and type 2 diabetes. Current monitoring recommendations recognize this risk, yet they remain largely uniform across patients and do not incorporate ancestry-specific genetic risk or mechanistic drug-gene information. We performed a transcriptome-wide association study-informed drug-gene prioritization analysis to examine whether approved antipsychotic target genes overlap with genes whose genetically predicted expression is associated with type 2 diabetes. The analysis used ancestry-specific type 2 diabetes transcriptome-wide association study (TWAS) results derived from a multi-ancestry genome-wide association study (GWAS) and approved antipsychotic drug-gene interactions from the Drug-Gene Interaction Database (DGIdb). For each drug, target genes were matched to TWAS genes across six metabolic tissues, and a weighted risk score was calculated as the sum of the absolute TWAS z-score multiplied by the drug-gene interaction score for significant targets. Follow-up analyses decomposed signals into targets with positive and negative TWAS directions, operationally interpreted as aggravating and compensatory, while also examining curated metabolic axis genes including GLP1R, GIPR, PPARG, and SLC2A4. The analysis identified recurrent exploratory target-overlap signals for clozapine and olanzapine. Clozapine showed the most consistent cross-ancestry aggravating profile, with recurrent target overlap involving GLP1R and immune-related genes. Olanzapine showed strong mechanistic-axis overlap involving GLP1R, GIPR, and PPARG, although its simple TWAS directionality was often classified as compensatory. Trifluoperazine emerged as a notable candidate, with significant target enrichment in the European ancestry analysis and top ranking in the Hispanic analysis. Fluspirilene also met the combined enrichment false discovery rate threshold in the European ancestry analysis, although its clinical metabolic interpretation was less direct. Haloperidol decanoate showed a high burden driven partly by SLC2A4, but its directionality was frequently mixed or compensatory. These findings nominate the incretin axis as a plausible translational bridge between antipsychotic metabolic liability and existing interventions such as GLP-1 receptor agonists. They also identify a key methodological gap. Future models must incorporate the pharmacologic mode of action to distinguish receptor blockade from activation. Except for the enrichment-positive European ancestry findings for trifluoperazine and fluspirilene, the results are exploratory prioritization signals and do not establish drug-specific metabolic effects, causal mechanisms, or ancestry-specific treatment effects. Overall, this TWAS-informed analysis provides a hypothesis-generating framework for ancestry-aware metabolic monitoring and targeted validation studies.

PMID 42465707
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