Drug Metabolism and Disposition最新文献

{"title":"Clearance prediction with three novel plated human hepatocyte models compared to conventional suspension assays: Assessment with 50 compounds and multiple donors.","authors":"David A Kukla, Julia A Schulz Pauly, Paul R Lesniak, Elizabeth Sande, Yue-Ting Wang, John Cory Kalvass, David M Stresser","doi":"10.1016/j.dmd.2024.100032","DOIUrl":"10.1016/j.dmd.2024.100032","url":null,"abstract":"<p><p>Incubation of drugs with suspension hepatocytes (SH) to determine intrinsic clearance is common in drug discovery. However, the limited duration of SH assays hampers clearance assessment of metabolically stable compounds. In turn, this has driven the development of alternative in vitro approaches to generate intrinsic clearance estimates. Culturing primary hepatocytes with supportive cells as co/tricultures has been shown to maintain morphology, viability, and drug-metabolizing enzyme function for weeks, permitting extended incubations. Another assay from our laboratory is the preloaded hepatocyte assay (preload assay), which involves preloading plated monoculture hepatocytes with compounds and measuring the loss from cells in drug-free media. This approach increases analytical sensitivity compared to assays that measure bulk compound loss in the cells plus medium. We conducted a systematic evaluation of the ability of coculture, triculture, and preload assay models to predict human in vivo clearance for 50 predominantly low-clearance compounds with a range of physicochemical properties, including equal numbers of compounds following or violating Lipinski's rule of 5, across 3 hepatocyte donors. The results were compared with SH. Co/tricultures exhibited lower inter-donor differences compared to the preload and SH assays, likely due to the blunting of environmental cues after 5 days in culture prior to compound introduction. All 3 plated models significantly reduced the number of compounds with insufficient turnover to calculate CL_int,u compared to SH (SH: 40%; preload: 18%; cocultures: 8%; tricultures: 4%), exhibited strong interexperimental reproducibility and robust predictions of blood clearance (preload: 26/41; cocultures: 31/46; tricultures: 30/48 within 3-fold of observed). SIGNIFICANCE STATEMENT: Preloading plated hepatocytes with compounds and measuring the loss in drug-free media, or culturing hepatocytes with supportive cells as co/tricultures, facilitate quantitation of metabolically stable compounds in substrate depletion assays compared to suspension hepatocytes (SH). All 4 models exhibit robust estimates of CL_int,u and CL_b, but plated models allowed assessment of several compounds found to be too stable to evaluate in SH.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 2","pages":"100032"},"PeriodicalIF":4.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143536814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physiologically based pharmacokinetic modeling of small molecules: How much progress have we made?","authors":"Nina Isoherranen","doi":"10.1124/dmd.123.000960","DOIUrl":"10.1124/dmd.123.000960","url":null,"abstract":"<p><p>Physiologically based pharmacokinetic (PBPK) models of small molecules have become mainstream in drug development and in academic research. The use of PBPK models is continuously expanding, with the majority of work now focusing on predictions of drug-drug interactions, drug-disease interactions, and changes in drug disposition across lifespan. Recently, publications that use PBPK modeling to predict drug disposition during pregnancy and in organ impairment have increased reflecting the advances in incorporating diverse physiologic changes into the models. Because of the expanding computational power and diversity of modeling platforms available, the complexity of PBPK models has also increased. Academic efforts have provided clear advances in better capturing human physiology in PBPK models and incorporating more complex mathematical concepts into PBPK models. Examples of such advances include the segregated gut model with a series of gut compartments allowing modeling of physiologic blood flow distribution within an organ and zonation of metabolic enzymes and series compartment liver models allowing simulations of hepatic clearance for high extraction drugs. Despite these advances in academic research, the progress in assessing model quality and defining model acceptance criteria based on the intended use of the models has not kept pace. This Minireview suggests that awareness of the need for predefined criteria for model acceptance has increased, but many manuscripts still lack description of scientific justification and/or rationale for chosen acceptance criteria. As artificial intelligence and machine learning approaches become more broadly accepted, these tools offer promise for development of comprehensive assessment for existing observed data and analysis of model performance. SIGNIFICANCE STATEMENT: Physiologically based pharmacokinetic (PBPK) modeling has become a mainstream application in academic literature and is broadly used for predictions, analysis, and evaluation of pharmacokinetic data. Significant progress has been made in developing advanced PBPK models that better capture human physiology, but oftentimes sufficient justification for the chosen model acceptance criterion and model structure is still missing. This Minireview provides a summary of the current landscape of PBPK applications used and highlights the need for advancing PBPK modeling science and training in academia.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100013"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pharmacokinetics and absorption, distribution, metabolism and excretion profiling of tanimilast following an intravenous ¹⁴C-microtracer coadministered with an inhaled dose in healthy male individuals.","authors":"Michele Bassi, Veronica Puviani, Debora Santoro, Sonia Biondaro, Aida Emirova, Mirco Govoni","doi":"10.1124/dmd.124.001895","DOIUrl":"10.1124/dmd.124.001895","url":null,"abstract":"<p><p>Tanimilast is an inhaled phosphodiesterase-4 inhibitor currently in phase III clinical development for treating chronic obstructive pulmonary disease and asthma. This trial aimed to characterize the pharmacokinetics, mass balance, and metabolite profiling of tanimilast. Eight healthy male volunteers received a single dose of nonradiolabeled tanimilast via powder inhaler (Chiesi NEXThaler [3200 μg]), followed by a concomitant intravenous infusion of a microtracer ([¹⁴C]-tanimilast: 18.5 μg and 500 nCi). Plasma, whole blood, urine, and feces samples were collected up to 240 hours after dose to quantify nonradiolabeled tanimilast, [¹⁴C]-tanimilast, and total-[¹⁴C]. The inhaled absolute bioavailability of tanimilast was found to be approximately 50%. Following intravenous administration of [¹⁴C]-tanimilast, plasma clearance was 22 L/h, the steady-state volume of distribution was 201 L, and the half-life was shorter compared to inhaled administration (14 vs 39 hours, respectively), suggesting that plasma elimination is limited by the absorption rate from the lungs. Seventy-nine percent (71% in feces; 8% in urine) of the intravenous dose was recovered in excreta as total-[¹⁴C]. [¹⁴C]-tanimilast was the major radioactive compound in plasma, whereas no recovery was observed in urine and only 0.3% was recovered in feces, indicating predominant elimination through metabolic route. Importantly, as far as no metabolites accounting for more than 10% of the circulating drug-related exposure in plasma or the administered dose in excreta were detected, no further qualification is required according to regulatory guidelines. This study design successfully characterized the absorption, distribution, and elimination of tanimilast, providing key pharmacokinetic parameters to support its clinical development and regulatory application. SIGNIFICANCE STATEMENT: This trial investigates pharmacokinetic and absorption, distribution, metabolism and excretion profile of tanimilast, an inhaled phosphodiesterase-4 inhibitor for chronic obstructive pulmonary disease and asthma. Eight male volunteers received a dose of nonradiolabeled tanimilast via Chiesi NEXThaler and a microtracer intravenous dose. Results show pivotal pharmacokinetic results for the characterization of tanimilast, excretion route and quantification of significant metabolites, facilitating streamlined clinical development and regulatory approval.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100009"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efflux transporters in drug disposition during pregnancy.","authors":"Xin Chen, Chunying Gao, Lyrialle W Han, Sibylle Heidelberger, Michael Z Liao, Naveen K Neradugomma, Zhanglin Ni, Diana L Shuster, Honggang Wang, Yi Zhang, Lin Zhou","doi":"10.1124/dmd.123.001385","DOIUrl":"10.1124/dmd.123.001385","url":null,"abstract":"<p><p>Evidence-based dose selection of drugs in pregnant women has been lacking because of challenges in studying maternal-fetal pharmacokinetics. Hence, many drugs are administered off-label during pregnancy based on data obtained from nonpregnant women. During pregnancy, drug transporters play an important role in drug disposition along with known gestational age-dependent changes in physiology and drug-metabolizing enzymes. In this review, as Dr Qingcheng Mao's former and current laboratory members, we summarize the collective contributions of Dr Mao, who lost his life to cancer, focusing on the role of drug transporters in drug disposition during pregnancy. Dr Mao and his team initiated their research by characterizing the structure of breast cancer resistance protein (ATP-binding cassette G2). Subsequently, they have made significant contributions to the understanding of the role of breast cancer resistance protein and other transporters, particularly P-glycoprotein (ATP-binding cassette B1), in the exposure of pregnant women and their fetuses to various drugs, including nitrofurantoin, glyburide, buprenorphine, bupropion, tetrahydrocannabinol, and their metabolites. This review also highlights the gestation- and pregnancy-dependent transporter expression at the blood-brain and blood-placenta barriers in mice. SIGNIFICANCE STATEMENT: Dr Qingcheng Mao and his team have made significant contributions to the investigation of the role of efflux transporters, especially P-glycoprotein and breast cancer resistance protein, in maternal-fetal exposure to many xenobiotics: nitrofurantoin, glyburide, buprenorphine, bupropion, tetrahydrocannabinol, and their metabolites. Studies of individual compounds and the expression of transporters during gestation and pregnancy have improved the understanding of maternal-fetal pharmacokinetics.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100022"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterotropic allosteric modulation of CYP3A4 in vitro by progesterone: Evidence for improvement in prediction of time-dependent inhibition for macrolides.","authors":"Luc R A Rougée, Pooja V Hegde, Kaitlin Shin, Trent L Abraham, Alec Bell, Stephen D Hall","doi":"10.1124/dmd.124.001820","DOIUrl":"10.1124/dmd.124.001820","url":null,"abstract":"<p><p>Predictions of drug-drug interactions resulting from time-dependent inhibition (TDI) of CYP3A4 have consistently overestimated or mispredicted (ie, false positives) the interaction that is observed in vivo. Recent findings demonstrated that the presence of the allosteric modulator progesterone (PGS) in the in vitro assay could alter the in vitro kinetics of CYP3A4 TDI with inhibitors that interact with the heme moiety, such as metabolic-intermediate complex forming inhibitors. The impact of the presence of 100 μM PGS on the TDI of molecules in the class of macrolides typically associated with metabolic-intermediate complex formation was investigated. The presence of PGS resulted in varied responses across the inhibitors tested. The TDI signal was eliminated for 5 inhibitors, and unaltered in the case of 1, fidaxomicin. The remaining molecules erythromycin, clarithromycin, and troleandomycin were observed to have a decrease in both potency and maximum inactivation rate ranging from 1.7- to 6.7-fold. These changes in TDI kinetics led to a >90% decrease in inactivation efficiency. To determine in vitro conditions that could reproduce in vivo inhibition, varied concentrations of PGS were incubated with clarithromycin and erythromycin. The resulting in vitro TDI kinetics were incorporated into dynamic physiologically based pharmacokinetic models to predict clinically observed interactions. The results suggested that a concentration of ∼45 μM PGS would result in TDI kinetic values that could reproduce in vivo observations and could potentially improve predictions for CYP3A4 TDI. SIGNIFICANCE STATEMENT: The impact of the allosteric heterotropic modulator progesterone on the CYP3A4 time-dependent inhibition kinetics was quantified for a set of metabolic-intermediate complex forming mechanism-based inhibitors. We identify the in vitro conditions that optimally predict time-dependent inhibition for in vivo drug-drug interactions through dynamic physiologically based pharmacokinetic modeling. The optimized assay conditions improve in vitro to in vivo translation and prediction of time-dependent inhibition.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100006"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of genetic polymorphisms and drug-drug interactions mediated by carboxylesterase 1 on remimazolam deactivation.","authors":"Zhuo Wang, Zachary McCalla, Li Lin, Dominic Tornichio, Yaw Agyemang, John A Bastulli, Xiaochun Susan Zhang, Hao-Jie Zhu, Xinwen Wang","doi":"10.1124/dmd.124.001916","DOIUrl":"10.1124/dmd.124.001916","url":null,"abstract":"<p><p>Remimazolam (Byfavo, Acacia Pharma), a recent Food and Drug Administration-approved ester-linked benzodiazepine, offers advantages in sedation, such as rapid onset and predictable duration, making it suitable for broad anesthesia applications. Its favorable pharmacological profile is primarily attributed to rapid hydrolysis, the primary metabolism pathway for its deactivation. Thus, understanding remimazolam hydrolysis determinants is essential for optimizing its clinical use. This study aimed to identify the enzyme(s) and tissue(s) responsible for remimazolam hydrolysis and to evaluate the influence of genetic polymorphisms and drug-drug interactions on its hydrolysis in the human liver. An initial incubation study with remimazolam and PBS, human serum, and the S9 fractions of human liver and intestine demonstrated that remimazolam was exclusively hydrolyzed by human liver S9 fractions. Subsequent incubation studies utilizing a carboxylesterase inhibitor (bis(4-nitrophenyl) phosphate), recombinant human carboxylesterase 1 (CES1) and carboxylesterase 2 confirmed that remimazolam is specifically hydrolyzed by CES1 in human liver. Furthermore, in vitro studies with wild-type CES1 and CES1 variants transfected cells revealed that certain genetic polymorphisms significantly impair remimazolam deactivation. Notably, the impact of CES1 G143E was verified using individual human liver samples. Moreover, our evaluation of the drug-drug interactions between remimazolam and several other substrates/inhibitors of CES1-including simvastatin, enalapril, clopidogrel, and sacubitril-found that clopidogrel significantly inhibited remimazolam hydrolysis at clinically relevant concentrations, with CES1 genetic variants potentially influencing the interactions. In summary, CES1 genetic variants and its interacting drugs are crucial factors contributing to interindividual variability in remimazolam hepatic hydrolysis, holding the potential to serve as biomarkers for optimizing remimazolam use. SIGNIFICANCE STATEMENT: This investigation demonstrates that remimazolam is deactivated by carboxylesterase 1 (CES1) in the human liver, with CES1 genetic variants and drug-drug interactions significantly influencing its metabolism. These findings emphasize the need to consider CES1 genetic variability and potential drug-drug interactions in remimazolam use, especially in personalized pharmacotherapy to achieve optimal anesthetic outcomes.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100023"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncovering the impact of COVID-19-mediated bidirectional dysregulation of cytochrome P450 3A4 on systemic and pulmonary drug concentrations using physiologically based pharmacokinetic modeling.","authors":"Chukwunonso K Nwabufo","doi":"10.1124/dmd.124.001893","DOIUrl":"10.1124/dmd.124.001893","url":null,"abstract":"<p><p>Several clinical studies have shown that COVID-19 increases the systemic concentration of drugs in hospitalized patients with COVID-19. However, it is unclear how COVID-19-mediated bidirectional dysregulation of hepatic and pulmonary cytochrome P450 (CYP) 3A4 affects drug concentrations, especially in the lung tissue, which is most affected by the disease. Herein, physiologically based pharmacokinetic modeling was used to demonstrate the differences in systemic and pulmonary concentrations of 4 respiratory infectious disease drugs when CYP3A4 is concurrently downregulated in the liver and upregulated in the lung based on existing clinical data on COVID-19-CYP3A4 interactions at varying severity levels including outpatients, non-intensive care unit (ICU), and ICU patients. The study showed that hepatic metabolism is the primary determinant of both systemic and pulmonary drug concentrations despite the concurrent bidirectional dysregulation of liver and lung CYP3A4. ICU patients had the most systemic and pulmonary drug exposure, with a percentage increase in the area under the concentration-time curve in the plasma compartment of approximately 44%, 56%, 114%, and 196% for clarithromycin, nirmatrelvir, dexamethasone, and itraconazole, respectively, relative to the healthy group. Within the ICU cohort, clarithromycin exhibited its highest exposure in lung tissue mass with a fold change of 1189, whereas nirmatrelvir and dexamethasone showed their highest exposure in the plasma compartment, with fold changes of about 126 and 5, respectively, compared with the maximum therapeutic concentrations for their target pathogens. Itraconazole was significantly underexposed in the lung fluid compartment, potentially explaining its limited efficacy for the treatment of COVID-19. These findings underscore the importance of optimizing dosing regimens in at risk ICU patients to enhance both efficacy and safety profiles. SIGNIFICANCE STATEMENT: This study investigated whether COVID-19-mediated concurrent hepatic downregulation and pulmonary upregulation of cytochrome P450 (CYP) 3A4 leads to differences in the systemic and pulmonary concentrations of 4 respiratory medicines. The study demonstrated that intercompartmental differences in drug concentrations were driven by only hepatic CYP3A4 expression. This work suggests that ICU patients with significant COVID-19-CYP3A4 interactions may be at risk of clinically relevant COVID-19-drug interactions, highlighting the need for optimizing dosing regimens in this patient group to improve safety and efficacy.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100008"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world application of physiologically based pharmacokinetic models in drug discovery.","authors":"Laura G A Santos, Swati Jaiswal, Kuan-Fu Chen, Hannah M Jones, Ian E Templeton","doi":"10.1124/dmd.122.001036","DOIUrl":"https://doi.org/10.1124/dmd.122.001036","url":null,"abstract":"<p><p>The utility of physiologically based pharmacokinetic (PBPK) models in support of drug development has been well documented. During the discovery stage, PBPK modeling has increasingly been applied for early risk assessment, prediction of human dose, toxicokinetic dose projection, and early formulation assessment. Previous review articles have proposed model-building and application strategies for PBPK-based first-in-human predictions with comprehensive descriptions of the individual components of PBPK models. This includes the generation of decision trees based on literature reviews to guide the application of PBPK models in the discovery setting. The goal of this minireview is to provide additional guidance on the real-world application of PBPK models in support of the discovery stage of drug development, to assist in decision making. We have illustrated our recommended approach through description of case examples where PBPK models have been successfully applied to aid in human pharmacokinetic projection, candidate selection, and prediction of drug interaction liability for parent and metabolite. Through these case studies, we have highlighted fundamental issues, including preverification in preclinical species, the application of empirical scalars in the prediction of in vivo clearance from in vitro systems, in silico prediction of permeability, and the exploration of aqueous and biorelevant solubility data to predict dissolution. In addition, current knowledge gaps have been highlighted and future directions proposed. SIGNIFICANCE STATEMENT: Through description of 3 case studies, this minireview highlights the fundamental principles of physiologically based pharmacokinetic application during drug discovery. These include preverification of the model in preclinical species, application of empirical scalars where necessary in the prediction of clearance, in silico prediction of permeability, and the exploration of aqueous and biorelevant solubility data to predict dissolution. In addition, current knowledge gaps have been highlighted and future directions proposed.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100015"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The absorption, distribution, metabolism and elimination characteristics of small interfering RNA therapeutics and the opportunity to predict disposition in pregnant women.","authors":"Ogochukwu Amaeze, Nina Isoherranen, Sara Shum","doi":"10.1124/dmd.123.001383","DOIUrl":"10.1124/dmd.123.001383","url":null,"abstract":"<p><p>Small interfering RNA (siRNA) therapeutics represent an emerging class of pharmacotherapy with the potential to address previously hard-to-treat diseases. Currently approved siRNA therapeutics include lipid nanoparticle-encapsulated siRNA and tri-N-acetylated galactosamine-conjugated siRNA. These siRNA therapeutics exhibit distinct pharmacokinetic characteristics and unique absorption, distribution, metabolism, and elimination (ADME) properties. As a new drug modality, limited clinical data are available for siRNA therapeutics in specific populations, including pediatrics, geriatrics, individuals with renal or hepatic impairment, and pregnant women, making dosing challenging. In this Minireview, a mechanistic overview of the ADME properties of the 5 currently approved siRNA therapeutics is presented. A concise overview of the clinical data available for therapeutic siRNAs in special populations, focusing on the potential impact of physiologic changes during pregnancy on siRNA disposition, is provided. The utility of physiologically based pharmacokinetic (PBPK) modeling as a tool to elucidate the characteristics and disposition of siRNA therapeutics in pregnant women is explored. Additionally, opportunities to integrate known physiologic alterations induced by pregnancy into PBPK models that incorporate siRNA ADME mechanisms to predict the effects of pregnancy on siRNA disposition are discussed. Clinical data regarding the use of therapeutic siRNA in special populations remain limited. Data for precise parameterization of maternal-fetal siRNA PBPK models are lacking presently and underscore the need for further research in this area. Addressing this gap in knowledge will not only enhance our understanding of siRNA pharmacokinetics during pregnancy but also advance the possible development of siRNA therapeutics to treat pregnancy-related conditions. SIGNIFICANCE STATEMENT: This Minireview proposes a framework on how small interfering RNA (siRNA) disposition can be predicted in pregnancy based on mechanistic absorption, distribution, metabolism, and elimination (ADME) information using physiologically-based pharmacokinetic (PBPK) modeling. The mechanistic ADME information and available clinical data in special populations of currently Food and Drug Administration-approved siRNA therapeutics are summarized. Additionally, how physiological changes during pregnancy may affect siRNA disposition is reviewed, and the opportunities to use PBPK modeling to predict siRNA disposition in pregnant women is explored.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100018"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utility of physiologically based pharmacokinetic modeling in predicting and characterizing clinical drug interactions.","authors":"Robert S Foti","doi":"10.1124/dmd.123.001384","DOIUrl":"10.1124/dmd.123.001384","url":null,"abstract":"<p><p>Physiologically based pharmacokinetic (PBPK) modeling is a mechanistic dynamic modeling approach that can be used to predict or retrospectively describe changes in drug exposure due to drug-drug interactions (DDIs). With advancements in commercially available PBPK software, PBPK DDI modeling has become a mainstream approach from early drug discovery through to late-stage drug development and is often used to support regulatory packages for new drug applications. This Minireview will briefly describe the approaches to predicting DDI using PBPK and static modeling approaches, the basic model structures and features inherent to PBPK DDI models, and key examples where PBPK DDI models have been used to describe complex DDI mechanisms. Future directions aimed at using PBPK models to characterize transporter-mediated DDI, predict DDI in special populations, and assess the DDI potential of protein therapeutics will be discussed. A summary of the 209 PBPK DDI examples published to date in 2023 will be provided. Overall, current data and trends suggest a continued role for PBPK models in the characterization and prediction of DDI for therapeutic molecules. SIGNIFICANCE STATEMENT: Physiologically based pharmacokinetic (PBPK) models have been a key tool in the characterization of various pharmacokinetic phenomena, including drug-drug interactions. This Minireview will highlight recent advancements and publications around physiologically based pharmacokinetic drug-drug interaction modeling, an important area of drug discovery and development research in light of the increasing prevalence of polypharmacology in clinical settings.</p>","PeriodicalId":11309,"journal":{"name":"Drug Metabolism and Disposition","volume":"53 1","pages":"100021"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}