Background/Objectives: Levofloxacin (LVX) is a fluoroquinolone approved for the treatment of bacterial pneumonia, sinusitis, and prostatitis. Emerging in vitro and preclinical evidence suggests that efflux transporters are involved in LVX’s target tissue site distribution. Methods: The objective of this research was to characterize tissue exposure using a physiologically based pharmacokinetic (PBPK) model to be able to make more educated choices for optimal doses using target site pharmacokinetics data. Results: The final PBPK model in humans was applied to simulate free target site concentrations of LVX in lung and prostate, linking to minimum inhibitory concentrations (MIC) to assess appropriateness of currently approved dosing regimens for infections in both tissues. The clinical PBPK model was able to reproduce total plasma as well as free lung and prostate exposure of LVX in humans. Efflux transporters participate in LVX distribution to prostatic but not pulmonary tissue. Our results show a good penetration of LVX in both tissues with unbound partition coefficient (Kp,uu) equal to 0.79 and 0.72 for lung and prostate, respectively. Since LVX penetration in lung and prostate is similar, different sensitivities of the pathogens to LVX will dictate the effectiveness of the approved therapeutic regimen in the treatment of bacterial pneumonia, sinusitis, and prostatitis. Conclusions: Our research provides relevant insight into LVX’s target site exposure in lung and prostate. When integrated with pathogen-specific susceptibility data, these findings can be applied to refine current dosing regimens and help optimize the pharmacological treatment outcomes.

Limited data exist on predictive models incorporating patient-reported and claims-based measures to identify older adults at risk for opioid use disorder (OUD) or opioid overdose (OD). To develop a predictive model and identify predictors of time to first OUD or OD for older adults. Prognostic study using data from Health and Retirement Study (HRS) participants with linked Medicare claims between January 1, 2006, and December 31, 2021. Older (≥ 65 years) HRS-Medicare participants with chronic pain and prescribed opioids within 1 year before their first biennial HRS survey. Forty potential predictors derived from Medicare claims data and HRS surveys. Incident diagnosis of OUD or OD was ascertained from Medicare claims data. Four survival models—traditional Cox, Cox with backward variable selection, LASSO–penalized Cox, and survival random forest—were used to account for time-fixed and time-varying predictors to predict time to first OUD or OD. Of 4190 older adults, 181 experienced incident OUD or OD during a mean (SD) follow-up of 6.1 (4.0) years. All 4 survival models performed equally, with mean C statistics from 0.753 (0.043) to 0.849 (0.018) and from 0.723 (0.054) to 0.790 (0.042) in training and testing sets, respectively, in predicting time to first OUD or OD during follow-up. Across all models, the top leading predictors of OUD or OD for older adults were duration of opioid use, uncontrolled pain, and use of other central nervous system medications. In this prognostic study, traditional Cox and machine learning predictive models developed using patient-reported and claims-based measures performed equally well in predicting time to first OUD or OD and identified predictors for older adults. These models may be useful to monitor and identify older adults at risk for OUD or OD for early intervention.

Background: Use of anticonvulsants that induce cytochrome P450 3A4 (CYP3A4) concomitantly with CYP3A4-metabolised opioids is postulated to affect clinical adverse outcomes. Yet such an association has not been empirically examined in populations, including older adults.Methods: This cohort study investigated the associations of concomitant use of CYP3A4-inducing anticonvulsants and CYP3A4-metabolised opioids (vs CYP3A4-neutral opioids) with clinical outcomes and pain-related medical encounters among older nursing home (NH) residents using target trial emulation. Data were collected from a 100% US NH sample linked to the Minimum Data Set (MDS) and Medicare claims from 2010 to 2021. Participants included long-term NH residents 65 years or older who received CYP3A4-inducing anticonvulsants with a diagnosis of chronic pain for opioid use. The key exposure was initiating CYP3A4-metabolised vs CYP3A4-neutral opioids that overlapped with use of CYP3A4-inducing anticonvulsants for at least 1 day. Outcomes include clinical worsening pain, physical function, and depression from baseline to quarterly MDS assessments and counts of pain-related hospitalisations and emergency department (ED) visits.Findings: Of 20259 NH residents, use of CYP3A4-inducing anticonvulsants concomitantly with CYP3A4-metabolised (vs CYP3A4-neutral) opioids was associated with a higher adjusted rate ratio of worsening pain (1·10 [95% CI, 1·03–1·19]) and higher adjusted incidence rate ratios of pain-related hospitalisation (1·22 [95% CI, 1·03–1·46]) and pain-related ED visit (1·37 [95% CI, 1·08–1·74]), with no difference in physical function or depression. Findings were corroborated by a negative-control exposure analysis in which co-use of CYP3A4-neutral anticonvulsants with CYP3A4-metabolised (vs CYP3A4- neutral) opioids was not associated with clinical or pain-related outcomes, suggesting that unmeasured confounding was minimal in affecting the observed associations in the main analysis.Interpretation : Clinicians should be mindful of worsening pain and risk of pain-related medical encounters in older NH patients who receive CYP3A4-inducing anticonvulsants concomitantly with CYP3A4-metabolised opioids.Funding: Agency for Healthcare Research and Quality

Background:Dihydropyridine calcium channel blockers (DHP-CCB) are widely prescribed antihypertensives whose adverse effects may trigger unnecessary prescribing of additional medications, termed prescribing cascades (PC). We aimed to identify potential DHP-CCB-induced PCs using high-throughput sequence symmetry analysis (HTSSA). Methods:Using Medicare claims data (2011-2020), we identified new users aged ≥66 years with continuous enrollment ≥360 days before and ≥180 days after DHP-CCB initiation. We screened for initiation of 446 "marker" drug classes within ±90 days of DHP-CCB initiation. Sequence ratios compared marker drug initiation after versus before DHP-CCB initiation. Adjusted sequence ratios (aSR), accounting for prescribing trends over time, were calculated with 95% CIs >1 considered statistically significant. Clinical experts classified statistically significant signals as potential PCs through consensus. Results:Among 388,862 DHP-CCB initiators (mean age 76.6 ± 7.5 years; 62.5% women, 92.3% with hypertension), 82 of 446 marker drug classes had significantly elevated aSRs, of which 24 were classified as potential PCs. Strongest signals ranked by highest aSR included other systemic hemostatics (aSR 2.99; 95% CI, 1.10-8.16), other nasal preparations (aSR 1.99; 95% CI, 1.47-2.70), and drugs used in erectile dysfunction (aSR 1.85; 95% CI, 1.27-2.70). Other clinically relevant signals, ranked by number needed to harm (lowest to highest), included sulfonamides (NNTH 104; 95% CI, 98-111), electrolyte solutions (NNTH 216; 95% CI, 196-241), and osmotically acting laxatives (NNTH 710; 95% CI, 540-1056). Conclusion:Potential PCs identified in this Medicare cohort reflected known and underrecognized adverse effects of DHP-CCBs. Further studies are needed to evaluate the clinical consequences of these PCs.

Pregnant women sometimes need antiemetic combination therapy to control severe nausea and vomiting during pregnancy. Because promethazine, ondansetron, and metoclopramide have QT-prolonging effects, combination use may potentiate arrhythmic effects in mothers and cause circulatory conditions in infants, with promethazine combinations expected to exert stronger effects than metoclopramide combinations. We implemented tree-based scan statistics to screen for signals of adverse circulatory-related conditions in newborn infants following maternal exposure to promethazine-ondansetron combination compared to metoclopramide-ondansetron combination. We used Merative® Marketscan® Commercial Claims 2005–19 and Medicaid Analytic eXtract data 2005–15 to identify pregnant women aged 12–55 years with a live birth. To define combination use, pregnant women had to fill a prescription for a second antiemetic during the active days’ supply of the first antiemetic and then refill the first antiemetic during the active days’ supply of the second antiemetic. Our outcomes included circulatory diseases, individually and clustered within a hierarchical tree structure. We adjusted for potential confounders using propensity score quartile stratification and used Poisson tree-based scan statistics to screen for signals (p < 0.05). A total of 6865 and 4186 live birth deliveries with first-trimester exposure to promethazine-ondansetron combination or metoclopramide-ondansetron combination, respectively, met our inclusion criteria. After multiplicity adjustment for over 300 outcome clusters, we found three significant signals: unspecified hypotension (relative risk = 3.71, p < 0.001), chest pain (relative risk = 2.01, p < 0.001), and essential hypertension (relative risk = 1.76, p = 0.002) among infants with maternal promethazine-ondansetron combination exposure. Unspecified hypotension likely reflects neonatal conditions, whereas unspecified chest pain and essential hypertension may represent maternal conditions based on the claims origin. By scanning more than 300 infant circulatory-related outcomes, we identified unspecified hypotension as a potential safety signal among newborns whose mothers were exposed to promethazine-ondansetron combination rather than metoclopramide-ondansetron combination during the first trimester. This finding warrants further investigation and illustrates the utility of tree-based scan statistics as a hypothesis-generating tool for pregnancy medication safety research.

IntroductionGabapentin (GBP) is commonly used for chronic neuropathic pain, yet its therapeutic response varies widely across individuals. As a substrate of the organic cation transporter 2 (OCT2), encoded by the SLC22A2 gene, GBP’s penetration into the central nervous system (CNS) may be influenced by genetic variability. This study aimed to characterize the impact of SLC22A2 c.808G>T polymorphism on GBP pharmacokinetics (PK) and pharmacodynamics (PD) and inform genotype-guided dosing strategies.MethodsData from two clinical studies (n = 94) were pooled, including single and multiple oral dose regimens of GBP. Population PK/PD modeling was performed using nonlinear mixed-effects modeling.ResultsA two-compartment PK model with first-order absorption and linear elimination best described GBP disposition, with estimated apparent clearance (CL/F) significantly influenced by renal function (eGFR). Pain scores revealed delayed pain relief relative to peak plasma levels, requiring an effect compartment to link PK to an Imax model. The SLC22A2 c.808G>T (OCT2) variant was associated with a 10-fold reduction in the influx rate constant (ke1) to the effect site, suggesting impaired CNS drug delivery. Simulations demonstrated that GT carriers experienced markedly reduced pain relief, even at the maximum approved doses, compared to GG homozygotes. Renal impairment increased systemic exposure but did not alter CNS penetration.ConclusionThese findings highlight the importance of the OCT2 genotype in modulating GBP’s analgesic efficacy. Incorporating transporter pharmacogenetics into PK/PD models may enhance individualized therapy for neuropathic pain, particularly in identifying poor responders who may benefit from alternative dosing or adjunct treatments.

BackgroundMethadone and buprenorphine, effective treatments for opioid use disorder (OUD), also provide analgesia for managing pain, which is commonly experienced by patients with OUD. Limited population-based evidence exists comparing pain-related and treatment outcomes for methadone versus buprenorphine among patients with OUD and comorbid pain. The study aims to examine pain-related and treatment outcomes among Medicare patients with comorbid pain and OUD who initiated methadone or buprenorphine.Methods and findingsWe conducted a retrospective cohort study with target trial emulation using the 100% Medicare data from 2020 to 2023. Participants included patients with comorbid chronic pain and OUD who initiated methadone or buprenorphine. The key dependent variables were pain-related outcomes that included hospitalization and emergency department (ED) visit due to pain, and treatment outcomes that included opioid overdose and all-cause mortality. Outcomes were assessed 1 year following treatment initiation. Intention-to-treat and per-protocol analyses were conducted to estimate incidence rate ratios (IRRs) for pain-related outcomes and opioid overdose and hazard ratios (HRs) for all-cause mortality. For each outcome, we also calculated the adjusted risk difference (aRD) between the methadone and buprenorphine groups. We identified 49,727 eligible Medicare patients (mean [SD] age, 59.0 [11.6] years; 24,538 [49.3%] female and 25,189 [50.7%] male). Of the identified patients, 16,174 (32.5%) initiated methadone solely administered at opioid treatment programs, and 33,553 (67.5%) initiated buprenorphine primarily prescribed at office-based clinics. Compared with buprenorphine, initiation of methadone was associated with lower adjusted incidence rates of pain-related hospitalization (IRR, 0.64 (95% CI [0.58, 0.70]; P < .001); aRD, -7.2 (95% CI [-8.8 to -5.7]) per 1,000 person-years) and ED visit (IRR, 0.87 (95% CI [0.82, 0.92]; P < .001); aRD, -10.2 (95% CI [-14.4, -5.9]) per 1,000 person-years) in per-protocol analyses, with no difference in opioid overdose (IRR, 1.02 (95% CI [0.93,1.10]; P = .72); aRD, 0.33 (95% CI [-1.5, 2.1]) per 1,000 person-years) and all-cause mortality (HR, 1.06 (95% CI, [0.81-1.39]; P = .66); aRD, 1.1 (95% CI [-1.3, 1.0]) per 1,000 person-years) rates. Similar results were observed in intention-to-treat analyses. Main study limitations included unmeasured confounders and limited generalizability.ConclusionsThis population-based cohort study of Medicare patients with comorbid chronic pain and OUD found that methadone administered at opioid treatment programs is associated with reduced hospitalizations and ED visits for pain-related visits while offering treatment outcomes similar to buprenorphine primarily prescribed at office-based clinics. The favorable pain-related outcomes in patients with methadone should be interpreted with caution, as the finding may reflect differences in the underlying patient population, treatment dosing practices, pharmacological properties, and treatment practice settings, which cannot be measured in Medicare data and merit further investigations.

Anaphylaxis is a rapid, potentially fatal allergic reaction with a global prevalence of 0.04%-1.8%. Early intramuscular epinephrine administration is recommended. However, fear, pain, cost, or social barriers often delay treatment, leading to poor outcomes. To address these challenges, an intranasal (IN) epinephrine formulation was developed. Pharmacokinetic (PK) data for IN epinephrine are absent in children <4 years (7.5-15 kg) and limited in children ≥4 years. To inform pediatric dosing, we developed a population PK model to support weight-based dosing (≥30 kg, 15-<30 kg, and 7.5-<15 kg) in children. Pooled single-dose IN epinephrine data from six studies (five adults, one pediatric), with 255 subjects and 3564 observations, were analyzed using nonlinear mixed-effects modeling (NONMEM v7.5). Data handling included baseline imputation, exclusion of endogenous concentrations (>4 h), and BLQ management via the M4 method. One- and two-compartment models with allometric scaling by body weight were evaluated. Model performance was assessed using diagnostic plots, objective function value, and prediction-corrected visual predictive checks (pcVPC). Pediatric exposure simulations used CDC-based virtual populations to guide weight-based dosing. A two-compartment model with first-order absorption best described the data, with acceptable relative standard error <30% and no evidence of model misspecification. pcVPC demonstrated good agreement across adult and pediatric subgroups. Simulations indicated that the pediatric doses of 2 mg (≥30 kg) and 1 mg (15-<30 kg) achieved exposure comparable to the adult 2 mg reference, supporting the dosing strategy. Model-informed simulations support weight-based IN epinephrine dosing in young children, addressing a critical gap in anaphylaxis management.

Understanding exposure-response relationships is critical for the selection of an optimal drug dose that balances efficacy and safety. For simvastatin (SV), plasma concentrations may not accurately reflect target site exposure, because its pharmacologic effect is linked to intrahepatic unbound concentrations of its active form, simvastatin hydroxy acid (SVA). SVA is taken up into hepatocytes via the OATP1B1 transporter (encoded by SLCO1B1), where it is metabolized by CYP3A4. Physiological conditions such as obesity and post-Roux-en-Y gastric bypass (RYGB) surgery can alter drug disposition and enzyme activity, impacting hepatic drug exposure. This study aimed to evaluate gene-drug interaction and disease-drug interactions affecting SVA pharmacokinetics and optimize SV dosing by linking intrahepatic unbound SVA concentration to LDL-cholesterol (LDL-C) reduction using a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling approach. Simulations across doses, genotypes, and populations revealed that SLCO1B1 c.521T>C variation significantly affects plasma SVA exposure, but not hepatic SVA exposure. Obese individuals exhibited higher plasma and hepatic SVA exposure than non-obese individuals. A 20 mg dose achieved a 30-49% LDL-C reduction in obese subjects, regardless of SLCO1B1 genotype, whereas non-obese subjects may require 40 mg to achieve similar efficacy. In conclusion, systemic drug concentration or genotyping alone are insufficient to predict statin response. Instead, information on genetic and physiological variability needs to be integrated into a PBPK/PD framework to select optimal doses across diverse populations.

BACKGROUND:Mycobacterium tuberculosis resistance to standard-of-care agents is increasing. It is imperative to identify new combinations that increase the rate and depth of bacterial kill, shorten therapy and also suppress resistance. There has been little prior effort to identify combination regimens that employ new or repurposed drugs in a rational way. METHODS AND FINDINGS:Our group developed a pathway to combine agents to achieve this end. This pathway starts with standard baseline evaluations (e.g., MIC), leverages information from in vitro assessments (hollow fiber infection model), then analyzes 2-agent combinations in a 96 well quantitative culture checkerboard format (Greco URSA model with simulation). Finally, development of a high dimensional mathematical model allowed evaluation of 2- and 3-drug regimens in multiple metabolic states to draw inferences regarding combination therapies. We prospectively evaluated these regimens in animal models. We showed that a prospectively chosen regimen of pretomanid, moxifloxacin plus bedaquiline performed as predicted. In the BALB/c murine model, this regimen produced sterilization in a cohort that was held for 12 weeks after therapy cessation, as it did in the C3HeB/FeJ ("Kramnik") murine model. Finally, this and other regimens were evaluated in a cynomolgus macaque model. The decrement of the 18F-deoxyglucose signal in Positron emission tomography (PET)- computed tomography (CT) evaluations was best with this regimen. Other endpoints such as necropsy score and colony counts in lung and lymph nodes also demonstrated that this regimen behaved as predicted from our pathway/algorithm. CONCLUSIONS:We conclude that this provides a way forward for the future to identify the most promising regimens to shorten therapy for tuberculosis and suppress emergence of resistance.

Opioids have been the primary method used to manage pain for hundreds of years, however the increasing prescription rate of these drugs in the modern world has led to a public health crisis of overdose related deaths. Naloxone is the current standard treatment for opioid overdose rescue, but it has not been fully investigated for potential off-target toxicity effects. The current methods for pharmaceutical development do not correlate well with pre-clinical animal studies compared to clinical results, creating a need for improved methods for therapeutic evaluation. Microphysiological systems (MPS) are a rapidly growing field, and the FDA has accepted this area of research to address this concern, offering a promising alternative to traditional animal models. This study establishes a novel multi-organ MPS model of acute opioid overdose and rescue to investigate the efficacy and off-target toxicity of naloxone in combination with opioids. By integrating primary human and human induced pluripotent stem cell (hiPSC)-derived cells, including preBötzinger complex neurons, liver, cardiac, and skeletal muscle components, this study establishes a novel functional multi-organ MPS model of acute opioid overdose and rescue to investigate the efficacy and off-target toxicity of naloxone in combination with opioids, with clinically relevant functional readouts of organ function. The system was able to successfully exhibit opioid overdose using methadone, as well as rescue using naloxone evidenced by the neuronal component activity. In addition to efficacy, the multi-organ platform was able to characterize potential off-target toxicity effects of naloxone, specifically in the cardiac component.

It is unclear to what extent unrelieved pain, the most common motive for prescription opioid misuse, is associated with risks of opioid use disorder (OUD) and opioid overdose (OD) among older adults with prescribed opioids. This retrospective cohort study was conducted among Health and Retirement Study (HRS) participants with linked Medicare claims data between 2006 and 2021. Participants aged 65 years or older with chronic pain who had received at least 1 opioid prescription entered the cohort in an HRS-assessed pain assessment (index) between 2008 and 2020. We included 2 time-varying measures of HRS-assessed pain exposure: uncontrolled pain, defined as having moderate or severe pain, and high-impact pain, defined as having moderate to severe pain that impacted daily activities. Primary outcomes of incident OUD or OD diagnosis were analyzed using separate Cox regression models with marginal structural modeling. Of 3104 eligible participants identified, 1359 (43.8%) had uncontrolled pain and 1044 (33.6%) experienced high-impact pain in the index wave. In the marginal structural modeling-adjusted Cox regression model, patients with uncontrolled (vs controlled) pain had higher risks of OUD (adjusted hazard ratio [AHR] 9.70; 95% confidence interval [CI], 4.56-20.63) and OD (AHR 2.46; 95% CI 1.30-4.66). The AHR for OUD was 6.74 (95% CI 3.76-12.08) and for OD was 1.96 (95% CI 1.07-3.60) times higher for patients with vs without high-impact pain. Our findings underscore the importance of regular assessment and modification of pain management for older patients whose pain remains unrelieved after opioid treatment, to lower the risk of OUD and OD.

According to the FDA Guidance for Industry on Clinical Drug Interaction (DDI) Studies with Combined Oral Contraceptives (COCs), sponsors are expected to conduct dedicated clinical DDI studies if in vitro findings suggest weak or moderate CYP3A induction, while concomitant use of COCs with strong inducers should be avoided. The guidance further suggests that a negative DDI result for drospirenone (DRSP) may be extrapolated to other progestins that are less sensitive to CYP3A modulation, such as levonorgestrel (LNG). This approach assumes that DDI‐mediated changes in exposure directly translate into clinical efficacy across progestins. To evaluate the validity of this assumption, we established a quantitative link between dose, exposure, and response (Pearl Index [PI] and ovulation rate [OR]) via an integrated model‐based meta‐analysis, physiologically based pharmacokinetic, and pharmacokinetic/pharmacodynamic (PK/PD) modeling and simulation approach using data from 51 clinical studies in 36,040 women receiving LNG or DRSP. COCs containing LNG and DRSP were selected because they represent clinically relevant progestins at the lower and the upper end of the fraction metabolized via CYP3A4. The results of our analysis show a moderate correlation (Pearson's r = 0.52, 95% CI 0.46‐0.58, P < 0.001) between PI and OR, which enables the use of OR as an ethically measurable endpoint, even at subtherapeutic doses/exposures, to predict efficacy outcomes. They further show that DDI‐induced changes in exposure do not directly translate into clinical response. Therefore, DDIs with COCs should be interpreted in a PK/PD rather than a PK‐only context. The quantitative framework developed in this study can serve as the scientific basis to do so.

INTRODUCTION:Whether prescription opioid exposure, duration, and dose are associated with cognitive function remains inconclusive. METHODS:A longitudinal cohort among 3097 older adults with chronic pain and without dementia was conducted using Health and Retirement Study (HRS) linked to Medicare data from 2006 to 2020. Prescription opioid exposure, cumulative use for ≥ 90 days, and high-dose use (≥ 90 morphine milligram equivalents [MME] daily) were assessed biennially. Memory score and dementia probability were derived from HRS cognitive measures and analyzed using linear mixed-effects models. RESULTS:Adjusted memory decline and dementia probability were not statistically different between patients with (vs. without) opioid exposure and between patients with cumulative use for ≥ 90 days (vs. < 90 days) but were higher between participants with high-dose opioid use (vs. low-dose) at the end of the follow-up. DISCUSSION:Prescription opioid exposure and duration were not associated, but high-dose opioid use was associated with greater memory decline and dementia probability. HIGHLIGHTS:Opioid use versus no use was not related to memory decline and dementia probability. Long-term opioid use was not related to memory decline and dementia probability. High-dose opioid use was related to greater memory decline and dementia probability.

Chronic hepatitis B virus (HBV) infection remains a significant global health challenge. While the dynamic interplay between viral replication and host immune responses determines infection outcomes, the mechanisms driving the resolution of acute infection versus the emergence of chronicity remain incompletely understood. To address this challenge, we developed a detailed quantitative systems pharmacology (QSP) model of acute HBV infection capturing several key host immune and viral mechanisms absent in previous models. The model was parameterized using publicly available data and calibrated against clinical time-course datasets from multiple acute HBV case studies. Perturbation and local sensitivity analyses identified key drivers of biomarker dynamics, particularly hepatitis B virus DNA (HBV DNA), hepatitis B surface antigen (HBsAg), and alanine aminotransferase (ALT). These dynamics were most sensitive to parameters governing viral replication (e.g., HBV entry via the sodium taurocholate cotransporting polypeptide [NTCP] receptor, covalently closed circular DNA [cccDNA] formation, and hepatocyte turnover) and adaptive immune responses (e.g., CD8+ T cell activity, dendritic cell-mediated priming, and regulatory T cell [Treg]-driven immunosuppression). These influential parameters were used to generate a virtual population that reproduced the observed heterogeneity in biomarker trajectories. Notably, the magnitude and timing of biomarker peaks captured most of the variability, reflecting interindividual differences in individual immune responses and viral dynamics. While the current model nicely captures processes associated with acute HBV infections, it will be extended to different stages of chronic HBV with the objective of informing the rational design of novel therapies and supporting the development of curative HBV strategies.

BACKGROUND AND OBJECTIVES:Concomitant use of tramadol and antidepressants with potent inhibition of the cytochrome P450 2D6 (CYP2D6) enzyme is postulated to increase risk of seizures in older adults; yet, such an association has not been empirically tested in populations. We aimed to examine the association of concomitant tramadol and CYP2D6-inhibiting vs CYP2D6-neutral antidepressant use and the risk of seizures among older nursing home (NH) residents. METHODS:This population-based cohort study was conducted using a 100% Medicare NH sample from January 2010 to December 2021. We included long-term residents aged 65 years or older who initiated antidepressants on existing tramadol use (tramadol-antidepressant users) or initiated tramadol on existing antidepressant use (antidepressant-tramadol users). Patients were followed up until the end of 1 year, NH discharge, death, or study end. The key exposure was concomitant use of tramadol with CYP2D6-inhibiting vs CYP2D6-neutral antidepressants. The key outcome was incident rates of medical encounters with a diagnosis of seizure and analyzed using negative binomial or Poisson regression models adjusted for baseline covariates (e.g., pain status and depressive, physical, and cognitive function) through the inverse probability of treatment weighting. RESULTS:We identified 11,162 concomitant tramadol-antidepressant users (mean [SD] age, 86.2 [8.5] years; 9,077 [81.3%] female) and 58,994 concomitant antidepressant-tramadol users (mean [SD] age, 85.3 [8.4] years; 47,053 [79.8%] female). The incidence rate of seizures was 16.10 and 20.17 per 100 patient-years, respectively, for the tramadol-antidepressant and antidepressant-tramadol group. In both subgroups, co-use of tramadol with CYP2D6-inhibiting (vs with CYP2D6-neutral) antidepressants was associated with higher adjusted incidence rate ratios of seizures (1.09 [95% CI 1.02-1.18] and 1.06 [95% CI 1.03-1.10]). Findings were corroborated by a negative control exposure analysis in which co-use of hydrocodone with CYPD2D6-inhibiting (vs CYP2D6-neutral) antidepressants was not associated with risk of seizures. DISCUSSION:Concomitant use of tramadol with CYP2D6-inhibiting vs CYP2D6-neutral antidepressants was associated with increased risk of seizures. Findings are only generalizable to long-term NH populations and are subject to residual confounding. Clinicians should be mindful of seizure risk in older patients who use tramadol concomitantly with antidepressants, particularly CYP2D6-inhibiting antidepressants. CLASSIFICATION OF EVIDENCE:This study provides Class II evidence that the combination of tramadol and CYP2D6-inhibiting antidepressants is associated with a higher risk of seizures compared with the combination of tramadol and CYP2D6-neutral antidepressants.

Background The safety of pharmacokinetic opioid-antidepressant interactions may be affected by the sequence in which the drug is initiated. Previous literature showed that initiation of cytochrome P450 (CYP) 2D6-inhibiting versus CYP2D6-neutral antidepressants concomitantly with existing CYP2D6-metabolized opioids (i.e., antidepressant-triggered interaction) was associated with heightened risks of adverse outcomes (e.g., worsening pain). However, little is known about whether and to what extent the risks exist when CYP2D6-metabolized opioids are initiated on existing antidepressants (i.e., opioid-triggered interaction), a more common pattern of concomitant use of these two drugs. The study aims to examine the association of initiation of CYP2D6-metabolized opioids with risks of adverse outcomes among older nursing home residents who already received antidepressants. Methods and findings We conducted a retrospective cohort study using a 100% Medicare nursing home sample linked to Medicare claims and Minimum Data Set (MDS) assessments from January 1, 2010, to December 31, 2021. Participants included long-term care residents 65 years of age or older who initiated CYP2D6-metabolized opioids while already receiving antidepressants for at least 30 days. The key exposure was the use of CYP2D6-inhibiting (versus CYP2D6-neutral) antidepressants concomitantly with CYP2D6-metabolized opioids, with day 1 of antidepressant-opioid concomitant use designated as cohort entry. Patients were followed from cohort entry until the end of 1 year, nursing home discharge, death, or study end (12/31/2021). Seven adverse outcomes included worsening pain, physical function, and depression, and counts of pain-related hospitalizations and emergency department (ED) visits, opioid use disorder (OUD), and opioid overdose (OD). We identified 127,200 older nursing home long-term residents who initiated CYP2D6-metabolized opioids while already receiving antidepressants (mean [SD] age, 84.4 [8.7] years). After covariate adjustment via inverse probability of treatment weighting, use of CYP2D6-inhibiting (versus CYP2D6-neutral) antidepressants concomitantly with CYP2D6-metabolized opioids was associated with a higher risk of worsening pain (relative risk:1.04 [95% CI, 1.02, 1.06]; P < 0.001; risk difference (RD): 1.1% [95% CI, 0.6%, 1.6%]) and a higher incidence rate of pain-related hospitalizations (incidence rate ratio [IRR]:1.13 [95% CI, 1.04, 1.22]; P = 0.003; RD: 1.21 [95% CI, 0.39, 1.89] per 1,000 patient-years) and pain-related ED visits (IRR = 1.17 [95% CI, 1.07, 1.29]; P = 0.003; RD: 0.85 [95% CI, 0.29, 1.41] per 1,000 patient-years), with no difference in physical function, depression, OUD, and OD. Main study limitations included unmeasured confounding and limited generalizability. Conclusion This cohort study of older nursing home residents showed that initiation of CYP2D6-metabolized opioids on existing CYP2D6-inhibiting (versus CYP2D6-neutral) antidepressants was associated with increased risk of worsening pain, pain-related hospitalizations, and pain-related ED visits, although the relative and absolute risks are small to moderate. Clinicians should be aware of potential worsening pain and hospital and ED visits due to pain among patients who used CYP2D6-metabolizing opioids concomitantly with antidepressants, particularly those with CYP2D6-inhibiting antidepressants.

Objectives: The Hepatitis B virus (HBV), identified as a hepatotropic, double-stranded DNA virus, gives rise to both acute and chronic diseases. HBV infection not only jeopardizes health outcomes but also results in a substantial socioeconomic burden. Therefore, the goal of our project is to establish and verify a quantitative systems pharmacology (QSP) model for HBV to characterize and predict the dynamic interplay between the virus and the patient’s immune response as well as changes therein over time. Once developed and verified, this model will be expanded to hepatitis delta virus (HDV) coinfections.Methods: A systematic literature search on HBV, focusing on its pathogenesis, clinical aspects, surrogate endpoints, and available disease progression models was conducted. A database of biomarkers like HBV DNA, hepatitis B surface antigen, hepatitis B e antigen, and alanine aminotransferase, and existing models was established to develop a disease modeling framework for acute and chronic HBV infections. A QSP model for acute HBV infection was then constructed using MATLAB to capture the dynamic interplay between the virus life cycle and the host immune response. Parametrization of our model was determined based on literature, experimental data, and the CYTOCON database. Simulations were conducted to explore various scenarios of acute HBV infection. We will incorporate clinically relevant endpoints such as the previously mentioned biomarkers and immune components like cytokines and immune cell concentrations (natural killer, CD8+ T cells) from publicly available data to appropriately assess disease progression.Results: We examined a total of 71 publications and found 24 containing relevant information on quantifying HBV infections over time. These publications included information on key processes relevant to acute and chronic HBV infections, viral dynamics, respective biomarkers, and parameters related to the host immune system (both innate and adaptive responses). Based on this information, we developed a QSP-based disease modeling framework for acute HBV QSP, which includes 44 species and 110 parameters distributed across three compartments (liver, plasma, and lymph).Conclusions: We laid the foundation for a QSP-based disease modeling framework for characterizing and predicting the dynamic interplay between HBV and its human host. The model will be expanded to a QSP-based disease-drug-trial model going forward by including different drugs with different mechanisms of action under different treatment conditions to select optimal treatment regimens. Once established and verified for HB, this platform will be expanded to HDV.Citations: [1] 1. Asín-Prieto E, Parra-Guillen ZP, Gómez Mantilla JD, et al. A quantitative systems pharmacology model for acute viral hepatitis B. Computational and Structural Biotechnology Journal. 2021;19:4997-5007. doi:10.1016/j.csbj.2021.08.052

Initiation of Glucagon-Like Peptide-1 receptor agonists (GLP-1RA) in patients with type 2 diabetes (T2D) treated with levothyroxine may decrease the required levothyroxine dose due to weight loss or enhance levothyroxine absorption through delayed gastric emptying. These changes may cause thyroid hormone over-replacement and increased risk of atrial fibrillation/flutter (AF/Aflutter) and stroke. Our study aims to investigate the impact of GLP-1RA initiation on risks of AF/Aflutter and stroke in patients with T2D treated with levothyroxine, compared to sodium-glucose cotransporter 2 (SGLT2) inhibitors. Leveraging the target trial emulation framework, we conducted a retrospective study using observational data to emulate a new user, active comparator trial examining the effects of initiating GLP-1RA (exposure group) versus SGLT2 inhibitors (control group), with random treatment assignment emulated by propensity score matching with 1:1 ratio. We used a 15