Clinical Pharmacology & Therapeutics

BackgroundCarbamazepine (CBZ) and valproic acid (VPA) are long-standing treatments for epilepsy in children. Interestingly, they display unique drug disposition characteristics and maturation of drug metabolizing enzymes further complicates personalized dosing. Physiologically-based pharmacokinetic (PBPK) modeling includes these mechanisms and is hence a promising tool to optimize dosing. Our aim is to better support pediatric drug dosing of CBZ and VPA. MethodsAll CBZ and VPA dosing simulations were conducted with Simcyp, using available CBZ and VPA compound models linked with adult and pediatric population models. Current Dutch national dosing strategies were simulated to evaluate their appropriateness to achieve therapeutic levels. Where doses could be optimized, alternative dosing strategies were proposed based on simulations. ResultsTherapeutic levels of CBZ and VPA will be reached after 1 or 2 weeks of treatment with the current dosing strategies. Simulations suggest a CBZ starting dose of 7 mg/kg/day for neonates rather than 10 mg/kg/day. In contrast, children aged 12 to 18 years may receive a higher starting dose (e.g., 400 mg/day instead of 200 mg/day), to reach therapeutic levels more quickly. For VPA, when higher doses are needed (i.e., [≥]30 mg/kg/day), measuring unbound VPA concentrations are advised to guide dosing. ConclusionWe demonstrate that PBPK modeling is a valuable tool to confirm and further optimize dosing recommendations in children. The use of PBPK modeling offers a practical, cost-effective, and swift method to provide valuable comprehensive evidence for guiding clinical practice and potentially informing pediatric drug labeling, thus eliminating the necessity for clinical studies.

Background Plasma gelsolin (pGSN) is a non-immunosuppressive anti-inflammatory immunomodulator with demonstrated efficacy in animal models of acute lung injury. Its potential role in moderate-to-severe acute respiratory distress syndrome (ARDS) is currently under investigation. Methods We conducted a phase 1, randomized, double-blind, placebo-controlled study to evaluate the safety, tolerability, and pharmacokinetics of recombinant human pGSN (rhu-pGSN) following intravenous (IV) administration to healthy volunteers. Thirty-two participants were assigned to 4 sequentially ascending dose cohorts (6, 12, 18, 24 mg/kg of body weight) to receive five IV infusions of rhu-pGSN or saline placebo. Each cohort includes 8 subjects randomized 3:1 with rhu-pGSN or placebo. Doses were administered at 0 hours, 12 hours, 36 hours, 60 hours, and 84 hours. The primary outcome is the incidence and severity of clinical and laboratory AEs regardless of causality. Secondary outcomes include the pharmacokinetics of IV rhu-pGSN and the presence of anti-rhu-pGSN antibodies at Day 28. Results Overall, 10 subjects (41.7%) who received rhu-pGSN reported a total of 13 adverse events (AEs), and 1 subject (12.5%) who received placebo reported an AE. All AEs were mild or moderate. AEs in system organ classes that were reported by 2 or more subjects in either arm were skin and subcutaneous tissue disorders (12.5% rhu-pGSN; 0% placebo), gastrointestinal disorders (8.3% rhu-pGSN; 0% placebo), and nervous system disorders (12.5% rhu-pGSN; 12.5% placebo). No AEs by preferred term were reported by more than 1 subject in either arm. Three subjects (12.5%) experienced an AE assessed as related to study drug. No serious AEs occurred, and no AEs led to study discontinuation, dose interruption/reduction, or death. There were no apparent between-treatment differences in laboratory abnormalities, vital signs, or electrocardiogram findings. Conclusions Overall, in this study, IV rhu-pGSN (up to 24 mg/kg daily) appeared safe and well tolerated compared to placebo. The median half-life of rhu-pGSN exceeded 14 h across all dosing regimens, supporting once daily IV dosing in healthy subjects. Trial registration This study was registered with ClinicalTrials.gov on 2023-03-29 under the registration identifier NCT05789745.

Background. Polypharmacy is an important source of phenoconversion caused by drug interactions potentially modulated by genetic variability. Aims. To develop a linear phenoconversion model for TDM data and provide quantitative estimates of drug-drug-gene interactions (DDGIs) in the pharmacogenetic phenotype groups of CYP2C19. Methods. Escitalopram TDM data in a large real-world sample (n=2,852) was analysed for phenoconversion of CYP2C19 activity. Co-medication was identified by reprocessing high-resolution mass-spectra (Orbitrap). We developed a statistical model to identify inhibition from co-medication in the CYP2C19 and in alternative elimination pathways. We extended the model to estimate the inhibition ensuing from individual co-medications, using a single model for all data to account for multiple co-medications and confounders simultaneously. A Bayesian approach allowed us to stabilize the fit and provide well-calibrated credibility intervals. Results. Reprocessing of TDM analyses identified 17 co-medications, which were shown to phenoconvert CYP2C19 activity proportionally to the activity in non-medicated phenotypes. Phenoconversion decreased the original CYP2C19 activity by about one third for a co-medication that corresponded to a 100% substrate of CYP2C19. The extent of CYP2C19 phenoconversion correlated strongly with the fractional contribution of CYP2C19 to the metabolism of the specific co-medication reported in the pharmacogenetic literature (R2=0.55) so long as the mechanism was competitive inhibition. Conclusion. We provide the statistical methodology to estimate phenoconversion from co-medication in TDM data and combine TDM and pharmacogenetic datasets in future studies aiming at establishing quantitative models of DDGIs.

NMD670 is a first-in-class inhibitor of skeletal muscle-specific chloride channel ClC-1, developed to improve muscle weakness and fatigue in neuromuscular diseases. Preclinical studies show that ClC-1 inhibition enhances muscle excitability, improving muscle contractility and strength. We describe the first-in-human administration of ClC-1 inhibitor NMD670. In this randomized, double-blind, placebo-controlled study we evaluated safety, pharmacokinetics, and pharmacodynamics of single and multiple doses of NMD670 in healthy male and female subjects. Single-ascending doses were administered in a (partial) cross-over design; multiple-ascending doses were administered in a parallel design. Differences in pharmacokinetics between males/females and fed/fasted state were evaluated. Pharmacodynamic effects were evaluated using muscle velocity recovery cycles (MVRC), and analyzed using mixed effects modelling, with baseline as covariate. NMD670 was considered safe and well-tolerated. Symptoms of myotonia were observed at the highest dose levels. Moreover, NMD670 significantly increased the following MVRC parameters after a single dose of 1200mg compared to placebo: early supernormality (estimated difference (ED) 2.04; 95% confidence interval (CI) (0.379, 3.70); p=0.0242); early supernormality after 5 conditioning stimuli (ED 2.51; 95%CI (0.599, 4.41); p=0.0177; supernormality at 20 ms (ED 2.78; 95%CI (1.377, 4.181); p=0.0021. Importantly, the results of this study indicate pharmacological target engagement of NMD670 as ClC-1 inhibitor, at dose levels that were considered safe in healthy subjects. Firstly, because myotonia was an expected exaggerated on-target pharmacological effect. Secondly, because the effects on MVRC indicate increased muscle cell excitability. This study in healthy subjects indicates proof-of-mechanism and provides a solid base for translation to patients with neuromuscular diseases.

Many patients with painful diabetic neuropathy (PDN) do not achieve meaningful pain relief with standard of care. MEDI7352 is a unique bispecific fusion protein targeting two key mediators of pain, TNF and NGF (at relatively low levels of suppression). We report a randomized, double-blind, placebo-controlled, Phase-2a study (NCT03755934/EudraCT-2018-002523-42) assessing efficacy and safety of MEDI7352 in patients aged [≥]18 years with inadequately controlled PDN. Patients remained on background standard-of-care treatment and were randomized to placebo (n=54) or MEDI7352 intravenously (5g/kg [n=6], 150g/kg [n=16], 450g/kg [n=36]). Primary endpoint was change in pain scores from baseline to Week 12 vs placebo on a numeric rating scale (NRS). Key secondary outcomes included change in pain scores from baseline at visits prior to Week 12 and responder rates. Of 112 patients randomized, 107 received [≥]1 dose study medication; mean age (standard deviation [SD]) in the modified-intent-to-treat population was 60.5 (9.34) years; 62.6% males, 37.4% females. With MEDI7352 450g/kg, change from baseline in pain scores at Week 12 vs placebo was: -1.39 [95% CI: -2.19 to -0.58], p=0.0009; at Week 12, mean (SD) pain scores decreased vs baseline by -2.70 (2.08); 66.7% of patients experienced decreased pain by [≥]30% (p=0.0311 vs. placebo); 42.4% experienced decrease [≥]50% (p=0.0029). MEDI7352 safety was similar to placebo; no adjudicated Rapidly Progressing Osteoarthritis (RPOA) type-1 or RPOA type-2 events were observed in any group. MEDI7352 achieved statistically significant and clinically meaningful pain reduction in patients with PDN vs placebo and provides an opportunity to change the paradigm for challenging-to-treat pain.

Sotrovimab is a recombinant human monoclonal antibody that has been shown to prevent progression to hospitalization or death from severe disease in non-hospitalized high-risk patients with mild-to-moderate COVID-19 following either intravenous (IV) or intramuscular (IM) administration. Population pharmacokinetic (popPK) and exposure-response (ER) analyses were performed to characterize sotrovimab PK and the relationship between exposure and response (probability of progression), as well as covariates that may contribute to between-participant variability in sotrovimab PK and efficacy following IV or IM administration. Sotrovimab PK was described by a two-compartment model with linear elimination; IM absorption was characterized by a sigmoid absorption model. PopPK covariate analysis led to the addition of the effect of body weight on systemic clearance and peripheral volume of distribution, sex on IM bioavailability and first-order absorption rate (KA), and body mass index on KA. However, the magnitude of covariate effect was not pronounced and was therefore not expected to be clinically relevant based on available data to date. For ER analysis, sotrovimab exposure measures were predicted using the final popPK model. An ER model was developed using the exposure measure of sotrovimab concentration at 168 hours that described the relationship between exposure and probability of progression within the ER dataset for COMET-TAIL. The number of risk factors ([≤]1 vs >1) was incorporated as an additive shift on the model-estimated placebo response but had no impact on overall drug response. Limitations in the ER model may prevent generalization of these results to describe the sotrovimab exposure-progression relationship across SARS-COV-2 variants.

Blocking of IL-23 has shown a profound effect on patient outcomes in psoriasis. The current IL-23 binding monoclonal antibodies show differences in dosing regimens, pharmacokinetics, affinity for the target, and efficacy outcomes in the clinic. The goal of the current work is to use a mechanistic pharmacokinetics/pharmacodynamics mathematical model to estimate projected free IL-23 neutralization for the different therapeutic molecules and connect it to clinical efficacy outcomes. The meta-analysis indicates a sigmoid-like relationship and suggests that the best current anti-IL23 antibodies are close to saturating the efficacy that can be achieved by this pathway in psoriasis.

Kinase inhibitors are a successful category of therapeutics used in treating diseases such as cancer, autoimmunity, and neurodegeneration. Despite their efficacy, these drugs often present clinically relevant adverse events that can limit their therapeutic utility or lead to their failure in clinical trials. The adverse event profile of a kinase inhibitor can be explained by its off- and on-target binding profile. Unfortunately, there are limited resources to couple inhibition of a specific kinase to clinical adverse events. Discerning which adverse events can be attributed to a specific kinase, and which are more generally caused by the kinase inhibitor drug class, is crucial for designing next-generation drugs that avoid toxicity and enhance clinical viability. By integrating adverse event incident data from the FDA Adverse Events Reporting Database with machine learning-predicted molecular binding profiles, we developed a statistical method that associates specific adverse events with potent inhibition of certain kinases. We also identify general adverse events inherent to the kinase inhibitor class. We validate our model through an extensive literature review of known kinase-adverse event pairs, comparison with the OnSIDES drug label side effect dataset, and prospective prediction of adverse events of recently approved kinase inhibitors. We show that our method can recapitulate well-established kinase-toxicity associations and identify previously unreported kinases associated with adverse events.

Adverse drug events (ADEs) are the fourth leading cause of death in the US and cost billions of dollars annually in increased healthcare costs. However, few machine-readable databases of ADEs exist, limiting the opportunity to study drug safety on a broader, systematic scale. Recent advances in Natural Language Processing methods, such as BERT models, present an opportunity to accurately extract relevant information from unstructured biomedical text. As such, we fine-tuned a PubMedBERT model to extract ADE terms from descriptive text in FDA Structured Product Labels for prescription drugs. With this model, we achieve an F1 score of 0.90, AUROC of 0.92, and AUPR of 0.95 at extracting ADEs from the labels "Adverse Reactions". We further utilize this method to extract serious ADEs from labels "Boxed Warnings", and ADEs specifically noted for pediatric patients. Here, we present OnSIDES (ON-label SIDE effectS resource), a compiled, computable database of drug-ADE pairs generated with this method. OnSIDES contains more than 3.6 million drug-ADE pairs for 3,233 unique drug ingredient combinations extracted from 47,211 labels. Additionally, we expand this method to extract ADEs from drug labels of other major nations/regions - Japan, the UK, and the EU - to build a complementary OnSIDES-INTL database. To present potential applications, we used OnSIDES to predict novel drug targets and indications, analyze enrichment of ADEs across drug classes, and predict novel ADEs from chemical compound structures. We conclude that OnSIDES can be utilized as a comprehensive resource to study and enhance drug safety. One Sentence SummaryOnSIDES is a large, comprehensive database of adverse drug events extracted from drug labels using natural language processing methods.

BackgroundPre-treatment DPYD screening is mandated in the UK and EU to reduce the risk of severe and potentially fatal fluoropyrimidine-related toxicity. Four DPYD gene variants which are more prominently found in Europeans are tested. MethodsOur systematic review in patients of non-European ancestry followed PRISMA guidelines to identify relevant articles up to April 2023. Published in silico functional predictions and in vitro functional data were also extracted. We also undertook in silico prediction for all DPYD variants identified. ResultsIn 32 studies, published between 1998 and 2022, 53 DPYD variants were evaluated in patients from 12 countries encompassing 5 ethnic groups: African American, East Asian, Latin American, Middle Eastern, and South Asian. One of the 4 common European DPYD variants, c.1905+1G>A, is also present in South Asian, East Asian and Middle Eastern patients with severe fluoropyrimidine-related toxicity. There seems to be relatively strong evidence for the c.557A>G variant, which is found in individuals of African ancestry, but is not currently included in the UK genotyping panel. ConclusionExtending UK pre-treatment DPYD screening to include variants that are present in some non-European ancestry groups will improve patient safety and reduce race and health inequalities in ethnically diverse societies.

Limited information exists regarding the impact of pharmacotherapy in pregnancy due to ethical concerns of unintended foetal harm. We investigate genetically proxied intrauterine antihypertensive exposure on offspring outcomes, including gestational age and birthweight, using two-sample multivariable Mendelian randomization. Higher levels of maternal protein targets for calcium channel blockers increased gestational age by 3.99 days (95%CI: 0.02, 7.96) per 10mmHg decrease in SBP. Genetically proxied maternal protein targets for beta-adrenoceptor blocking drugs, vasodilator antihypertensive drugs on the KNCJ11 gene, potassium-sparing diuretics and aldosterone antagonists demonstrated little evidence of increased risk to offspring. Both parental genetic protein targets for vasodilator antihypertensive drugs demonstrated similar effects on birthweight, suggesting detrimental offspring effects due to genetic perturbation of these pathways is unlikely. Little evidence for increased risk of adverse offspring outcomes due to maternal antihypertensive drug target perturbation was found. Triangulation of these findings with existing evidence may guide physicians and mothers during pregnancy.

BackgroundDrug suitability is determined by safety, efficacy, and pathological appropriateness. The pharmacogenomics of drug suitability can be assessed by analyzing drug response and drug choice in large population cohorts. MethodsWe investigated drug response and drug choice for dyslipidemia and hypertension using genetic, phenotypic, and prescribing data from the UK Biobank and the All of Us Research Program. Drug response was reassessed with rigorous biomarker scaling, while genome-wide association studies (GWAS) and polygenic scores were used to examine genetic factors influencing drug choice. ResultsConventional analyses showed that variants influencing baseline LDL cholesterol (LDL-C) were inversely associated with absolute LDL-C change but concordant with relative change following statin therapy; these signals disappeared after applying a variance-stabilizing Box-Cox transformation, indicating a methodological artifact in biomarker scaling. GWAS for drug choice identified several significant loci and unique genetic correlation patterns with cardiometabolic traits. Polygenic scores for drug choice yielded statistically significant predictive performance, which was enhanced by incorporating demographic factors, though prediction strength in clinical settings remains modest. ConclusionVariance-stabilizing transformation corrects spurious pharmacogenetic associations introduced by biomarker scaling. Genetic variation informs drug choice for dyslipidemia and hypertension, but current polygenic scores provide only modest benefits in clinical application.

ObjectiveTo establish an optimized sotalol dosing strategy for fetal tachycardia by using a pregnancy computational model for dose simulations. MethodsA physiologically-based computational model, including pregnancy-related changes and placental transfer values, was established and verified. Simulations of the current dosing advises and prospective dosing scenarios were performed. To avoid maternal dose-related toxicity (QT-prolongation) we aimed for maternal concentrations <2.5 mg/L. Based on neonatal concentration-effect data, we aimed for a fetal Ctrough concentrations of 0.4 - 1.0 mg/L. ResultsThe pregnancy physiologically-based pharmacokinetic model accurately predicted maternal and fetal exposures. Predictions indicate that almost 16% of maternal plasma concentrations exceed the toxic level of 2.5 mg/L at the maximum oral daily dose of 480 milligram, while 90% of fetuses have a Ctrough concentration within the therapeutic window. When lowering the maximum daily dose to 400 mg, 0.1% of maternal plasma concentrations exceed 2.5 mg/L, while 87% of the fetal plasma concentrations remain in the therapeutic window. Additionally dosing 480 mg in three times daily reduces the risk of high maternal plasma exposure to 0.3%, while maintaining effective fetal Ctrough concentrations in 95% of fetuses. ConclusionPregnancy computational modeling can be used to adequately predict maternal and fetal sotalol exposures. Our simulations suggest that daily doses should not exceed 400 milligram and that dividing the oral daily dose over three doses improves the balance between high maternal plasma exposure and effective fetal concentrations. FundingThis publication is based on research funded by the Bill & Melinda Gates Foundation (INV-023795).

ObjectiveIn spite of evidence and recommendations reflecting the importance of pharmacogenomic testing, most prescriptions are still given without testing. We demonstrate the real world implications of the use of testing and evaluate adverse events and outcomes in individuals who did not receive pharmacogenomic testing for clopidogrel. MethodsWe analyzed ~100K individuals with paired EHR and exome sequencing data from population health studies administered at multiple medical centers using the Helix Exome+(R) assay. We inferred clopidogrel dosage by processing the prescription with an LLM. We identified all instances of individuals with at least one prescription that is not in concordance with their CYP2C19 genotype. Lastly, we identify instances of thrombosis using a comprehensive codeset based on ICD9, ICD10, and SNOMED terms. ResultsWe identified 16,140 prescriptions of clopidogrel given to 3,853 participants. We found that 29% of these individuals have a mismatch between the recommended clopidogrel dosage guideline based on their CYP2C19 genotype and their actual prescribed daily dosage. 25% of poor metabolizers experienced thrombosis, with 40% occurring within 2 months of treatment. Poor and intermediate metabolizers receiving clopidogrel are much more likely to experience thrombosis and myocardial infarction (binomial p-value = 0.001). ConclusionsWe estimate a 38% excess of adverse events occur in poor and intermediate metabolizers relative to normal and rapid metabolizers. The lack of testing may be responsible for 1 thrombosis event per every ~30 people prescribed clopidogrel.

Glucagon/glucagon-like peptide-1 (GLP-1) receptor co-agonists may provide greater weight loss than agonists targeting the GLP-1 receptor alone. We report results from three phase 1 trials investigating the glucagon/GLP-1 receptor co-agonist NNC9204-1177 (NN1177) for once-weekly subcutaneous use in adults with overweight or obesity. Our focus was a 12-week multiple ascending dose (MAD), placebo-controlled, double-blind trial in which adults (N=99) received NN1177 (dose-escalated to treatment doses of 200, 600, 1,300, 1,900, 2,800, 4,200, and 6,000 g) or placebo. Two other trials also contribute to the findings in this report: a first human dose (FHD) / single ascending dose (SAD), placebo-controlled, double-blind trial in which adults (N=49) received NN1177 (treatment doses of 10, 40, 120, 350, 700 and 1,100 g) or placebo, and a drug-drug interaction (DDI), open-label, single-sequence trial in which adults (N=45) received a 4,200 g dose of NN1177. Pharmacokinetic, safety and tolerability, and pharmacodynamic endpoints were assessed. For the MAD and FHD/SAD trials, baseline characteristics were generally balanced across groups. The half-life of NN1177 was estimated at between 77.3 and 111 hours. NN1177 appeared tolerable across trials; however, a number of safety concerns were observed, including an increase in heart rate (range 5-22 beats per minute) and decrease in reticulocyte count, which were both dose dependent, and increased markers of inflammation (fibrinogen and C-reactive protein), hepatic disturbances (increased aspartate aminotransferase and alanine aminotransferase), impaired glucose tolerance (dose groups 2,800-6,000 ug) and reduced blood levels of some amino acids. Clinically relevant weight loss was achieved (up to 12.6% at week 12; 4,200 ug in the MAD trial), but this was not accompanied by cardiometabolic improvements. In conclusion, although treatment with NN1177 was associated with dose-dependent and clinically relevant weight loss, unacceptable safety concerns precluded further clinical development.

Topiramate (TPM) is approved for seizures and migraine prophylaxis and is used off-label for several neuropsychiatric conditions. The available dosage forms, including tablets and sprinkle capsules, are unsuitable for patients who may be unable to take medicine orally. The resulting potential treatment interruptions could have untoward consequences and underscores the importance of developing a parenteral formulation. In this study, we developed a population pharmacokinetic model of a novel, intravenous TPM formulation using data from a study in patients with epilepsy or migraine receiving a single intravenous dose of stable-labeled TPM. In total, 246 TPM concentrations from 20 adult patients were included for model development. A three-compartment pharmacokinetic model with linear elimination fit the concentration-time data best. Simulations for various loading and maintenance regimens for patients with and without enzyme-inducing comedications were performed. The final estimates(95% confidence interval (CI)) for CL (L/h), V1 (L), and the peripheral volumes, V2 and V3 for a 70 kg person were 1.31(1.01 - 1.53), 9.84 (8.49 - 11.0), 39.1 (36.5 - 41.8)L, and 9.01 (6.41 - 44.3) respectively. The use of enzyme-inducing co-medication was the only significant covariate, associated with a 63% increase in clearance .Goodness-of-fit plots and visual predictive checks indicate satisfactory model performance and prediction. The simulation results indicate that adjusting doses for patients receiving IV TPM can mitigate the changes in plasma TPM concentrations resulting from enzyme induction. This population pharmacokinetic model for intravenous topiramate can inform dosing decisions for patients with epilepsy when used as either initiation or bridging therapy.

IntroductionThe efficacy and safety of elexacaftor/tezacaftor/ivacaftor (ETI) have been established in prospective clinical trials. Liver function test elevations were observed in a greater proportion of patients receiving ETI compared with placebo; however, the relatively small number of patients and short duration of study preclude detection of rare but clinically significant associations with drug-induced liver injury (DILI). To address this gap, we assessed the real-world risk of DILI associated with ETI through data mining of the FDA Adverse Event Reporting System (FAERS). MethodsDisproportionality analyses were conducted on FAERS data from the fourth quarter of 2019 through the third quarter of 2022. Comparative patient demographics, onset time and outcomes for ETI-DILI were also obtained. Results452 reports of DILI associated with ETI were found, representing 2.1% of all adverse event reports for ETI. All disproportionality measures were significant for ETI-DILI at p < 0.05; the reporting odds ratio (ROR) was comparable to that of drugs classified by FDA as "Most-DILI concern". The most notable demographic finding was a male majority for ETI-DILI compared to a female majority for non ETI-DILI. Median ETI-DILI onset time was 50.5 days, and hospitalization was the second most common complication. ConclusionUsing FAERS data, ETI was found to be disproportionality associated with DILI. Future research is needed to investigate the hepatotoxic mechanisms and assess potential mitigation strategies for ETI-induced hepatotoxicity. Article HighlightsO_LIUsing the FDA Adverse Event Reporting System database, ETI and DILI were found to be significantly associated (p < 0.05) for all disproportionality measures (PRR, ROR, IC, EGBM, Yates chi-squared). C_LIO_LIThe ROR for ETI-DILI is greater than that of many "Most-DILI concern" drugs in the FDA DILIRank dataset but is not within the top 20 drugs associated with DILI. C_LIO_LIPatient reports for ETI-DILI were predominately male, in contrast to patient reports for other drugs and DILI. C_LIO_LI"Hospitalization" was the second most common patient outcome for ETI-DILI after "other serious outcomes". C_LIO_LIMost patients had onset times within 3 months of initiation, several patients had an onset time greater than 1 year. C_LIO_LIOnset times indicate that liver function test monitoring should be initiated earlier than 3 months and potentially extend beyond 1 year in some patients. C_LI

Blinatumomab is a bispecific T-cell engager (BiTE) that binds to CD3 on T cells and CD19 on B cells. It has been approved for use in B-cell acute lymphoblastic leukemia (B-ALL) with a regimen that requires continuous infusion (cIV) for four weeks per treatment cycle. It is currently in clinical trials for Non-Hodgkin lymphoma (NHL) with cIV administration. Recently, there have been studies investigating dose-response after subcutaneous (SC) dosing in B-ALL and in NHL to determine whether this more convenient method of delivery would have a similar efficacy/safety profile as continuous infusion. We constructed mechanistic PKPD models of blinatumomab activity in B-ALL and NHL patients, investigating the amount of CD3:blinatumomab:CD19 trimers the drug forms at different dosing administrations and regimens. The modeling and analysis demonstrate that the explored SC doses in B-ALL and NHL achieve similar trimer numbers as the cIV doses in those indications. We further simulated various subcutaneous dosing regimens, and identified conditions where trimer formation dynamics are similar between constant infusion and subcutaneous dosing. Based on the model results, subcutaneous dosing is a viable and convenient strategy for blinatumomab and is projected to result in similar trimer numbers as constant infusion.

Mocravimod (KRP203) is a selective sphingosine 1-phosphate (S1P) receptor modulator currently in development for patients with haematological malignancies undergoing allogenic haematopoietic cell transplantation (HCT). This first-in-human, randomised, double-blind, placebo-controlled, single ascending oral dose study evaluated the safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) of mocravimod in 136 healthy adult participants (EudraCT No. 2006-006814-13). Participants received single doses ranging from 0.01 to 40 mg or placebo, with a cohort dedicated to studying food-effect at 3 mg. Mocravimod demonstrated slow absorption (mean Tmax 6-11 hrs), extensive distribution, and a long terminal half-life (91-132 hrs). Exposure increased dose-proportionally for doses [&ge;]2 mg. The most common adverse events were headache, dizziness, and fatigue, all graded as mild or moderate; no serious adverse events or deaths occurred. Mocravimod-phosphate induced robust, dose-dependent reductions in lymphocyte counts, with significant decreases at doses [&ge;]2 mg and recovery to baseline observed in all but the highest dose groups. Cardiac effects included transient bradycardia and benign second-degree atrioventricular (AV) block at higher doses, without clinically significant arrhythmias. Food intake had minimal impact on PK. No clinically meaningful changes in pulmonary function or laboratory safety signals were detected. These results indicate that single oral doses of mocravimod up to 40 mg are safe and well tolerated in healthy adults, with predictable PK and expected PD effects. The findings support further clinical development of mocravimod as a targeted immunomodulator in settings such as allogeneic HCT for haematological malignancies.

Pharmacogenetics studies how genetic variation leads to variability in drug response. Guidelines for selecting the right drug and right dose to patients based on their genetics are clinically effective, but are still widely unused. For some drugs, the normal clinical decision making process may lead to the optimal dose of a drug that minimizes side effects and maximizes effectiveness. Without measurements of genotype, physicians and patients may observe and adjust dosage in a manner that reflects the underlying genetics. The emergence of genetic data linked to longitudinal clinical data in large biobanks offers an opportunity to confirm known pharmacogenetic interactions as well as discover novel associations by investigating outcomes from normal clinical practice. Here we use the UK Biobank to search for pharmacogenetic interactions among 200 drugs and 9 genes among 200,000 participants. We identify associations between pharmacogene phenotypes and drug maintenance dose as well as side effect incidence. We find support for several known drug-gene associations as well as novel pharmacogenetic interactions.