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In silico techniques, such as physiologically based pharmacokinetic modeling (PBKP), are recently gaining importance. Computational methods in drug discovery and development and the generic drugs industry enhance research effectiveness by saving time and money and avoiding ethical issues. One key advantage is the ability to conduct toxicology studies without risking harm to living beings. This study aimed to repurpose the multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) PBPK model for simulation permeation through porcine ear skin under in vitro conditions. The work was divided into four steps: (1) the development of a pig ear skin model based on a previously collected dataset; (2) testing the model's ability to discriminate permeation between pig ear, human abdomen, and human back skin; (3) development of a caffeine permeation model; and (4) testing the caffeine model's performance against in vitro generated data sourced from the scientific literature. Data from 31 manuscripts were used for the development of the pig skin model. Based on these data, values specific to pig skin were found for 22 parameters of the MPML MechDermA model. The model was able to discriminate permeation between pig and human skin. A caffeine model was developed and used to simulate seven experiments identified in the literature. The model's performance was assessed by comparing simulated to observed results. Based on a visual check, all simulations were considered acceptable, whereas three out of seven experiments met the twofold difference criterion. The variability of the experimental data was considered the biggest challenge for reliable model assessment.
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In vitro-in vivo extrapolation is a commonly applied technique for liver clearance prediction. Various in vitro models are available such as hepatocytes, human liver microsomes, or recombinant cytochromes P450. According to the free drug theory, only the unbound fraction (fu) of a chemical can undergo metabolic changes. Therefore, to ensure the reliability of predictions, both specific and nonspecific binding in the model should be accounted. However, the fraction unbound in the experiment is often not reported. The study aimed to provide a detailed repository of the literature data on the compound's fu value in various in vitro systems used for drug metabolism evaluation and corresponding human plasma binding levels. Data on the free fraction in plasma and different in vitro models were supplemented with the following information: the experimental method used for the assessment of the degree of drug binding, protein or cell concentration in the incubation, and other experimental conditions, if different from the standard ones, species, reference to the source publication, and the author's name and date of publication. In total, we collected 129 literature studies on 1425 different compounds. The provided data set can be used as a reference for scientists involved in pharmacokinetic/physiologically based pharmacokinetic modelling as well as researchers interested in Quantitative Structure-Activity Relationship models for the prediction of fraction unbound based on compound structure. Database URL: https://data.mendeley.com/datasets/3bs5526htd/1.
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Hepatócitos , Humanos , Hepatócitos/metabolismo , Taxa de Depuração Metabólica , Animais , Modelos Biológicos , Preparações Farmacêuticas/metabolismo , Ligação Proteica , Microssomos Hepáticos/metabolismoRESUMO
To understand and describe neurotoxicity mechanistically, we must first understand the processes and responses that occur within neuronal cell systems after the administration of a chemical. The dataset we present is a collection of experimental results from the literature that comprises various neurotoxic endpoints in human-derived in vitro models, allowing for easy data analysis. Currently available and free databases such as the EPA's ToxCast, which focuses on forecasting toxic health risks, are created by collecting reports on cytotoxicity testing and creating mathematical fits that could help predict the effects of a given chemical on various types of cells. We, in contrast, provide a smaller, raw, and heterogeneous dataset created solely of results on human-derived cell models that not only summarises the cytotoxic effects of certain substances but also creates a possibility for analysing the significance of the experimental set-up for the prediction of outcome.
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Amantadine, despite being on the market for 55 years, has several unknown aspects of its pharmacokinetics especially related to the influence of covariates such as age, disease, or interactions linked to amantadine's renal elimination. As amantadine is used in Parkinson's disease and is considered a potential candidate in COVID treatment and other diseases, there is an unmet need for thorough understanding of its pharmacokinetic in special populations, such as the elderly. We aimed to mechanistically describe amantadine pharmacokinetics in healthy subjects and shed some light on the differences in drug behavior between healthy volunteers (18-65 years) and an elderly/geriatric population (65-98 years) using PBPK modeling and simulation. The middle-out PBPK model includes mechanistic description of drug renal elimination, specifically an organic cation transporter (OCT)2-mediated electrogenic bidirectional transport (basolateral) and multidrug and toxic compound extrusion (MATE)1-mediated efflux (apical). The model performance was verified against plasma and urine data reported after single and multiple dose administration in healthy volunteers and elderly patients from 18 independent studies. The ratios of predicted vs. observed maximal plasma concentration and area under the concentration-time curve values were within 1.25-fold. The model illustrates that renal transporter activity is expected to decrease in healthy elderly compared to healthy volunteers, which is in line with literature proteomic data for OCT2. The model was applied to assess the potential of reaching toxicity-related plasma concentrations in different age groups of geriatric subjects.
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Amantadina , Modelos Biológicos , Humanos , Idoso , Amantadina/farmacocinética , Amantadina/administração & dosagem , Adulto , Pessoa de Meia-Idade , Idoso de 80 Anos ou mais , Masculino , Adulto Jovem , Adolescente , Feminino , Transportador 2 de Cátion Orgânico/metabolismo , Eliminação Renal , Proteínas de Transporte de Cátions Orgânicos/metabolismo , Tratamento Farmacológico da COVID-19 , Fatores Etários , Voluntários Saudáveis , Simulação por ComputadorRESUMO
Variability of the gastrointestinal tract is rarely reflected in in vitro test protocols but often turns out to be crucial for the oral dosage form performance. In this study, we present a generation method of dissolution profiles accounting for the variability of fasted gastric conditions. The workflow featured 20 biopredictive tests within the physiological variability. The experimental array was constructed with the use of the design of experiments, based on three parameters: gastric pH and timings of the intragastric stress event and gastric emptying. Then, the resulting dissolution profiles served as a training data set for the dissolution process modeling with the machine learning algorithms. This allowed us to generate individual dissolution profiles under a customizable gastric pH and motility patterns. For the first time ever, we used the method to successfully elucidate dissolution properties of two dosage forms: pellet-filled capsules and bare pellets of the marketed dabigatran etexilate product Pradaxa. We showed that the dissolution of capsules was triggered by mechanical stresses and thus was characterized by higher variability and a longer dissolution onset than observed for pellets. Hence, we proved the applicability of the method for the in vitro and in silico characterization of immediate-release dosage forms and, potentially, for the improvement of in vitro-in vivo extrapolation.
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Cápsulas , Dabigatrana , Jejum , Esvaziamento Gástrico , Dabigatrana/química , Dabigatrana/administração & dosagem , Dabigatrana/farmacologia , Cápsulas/química , Esvaziamento Gástrico/fisiologia , Esvaziamento Gástrico/efeitos dos fármacos , Humanos , Concentração de Íons de Hidrogênio , Solubilidade , Liberação Controlada de Fármacos , Administração Oral , Simulação por Computador , Estômago/fisiologia , Estômago/efeitos dos fármacosRESUMO
AIMS: The current work describes the development of mechanistic vaginal absorption and metabolism model within Simcyp Simulator to predict systemic concentrations following vaginal application of ring and gel formulations. METHODS: Vaginal and cervix physiology parameters were incorporated in the model development. The study highlights the model assumptions including simulation results comparing systemic concentrations of 5 different compounds, namely, dapivirine, tenofovir, lidocaine, ethinylestradiol and etonogestrel, administered as vaginal ring or gel. Due to lack of data, the vaginal absorption parameters were calculated based on assumptions or optimized. The model uses release rate/in vitro release profiles with formulation characteristics to predict drug mass transfer across vaginal tissue into the systemic circulation. RESULTS: For lidocaine and tenofovir vaginal gel, the predicted to observed AUC0-t and Cmax ratios were well within 2-fold error limits. The average fold error (AFE) and absolute AFE indicating bias and precision of predictions range from 0.62 to 1.61. For dapivirine, the pharmacokinetic parameters are under and overpredicted in some studies due to lack of formulation composition details and relevance of release rate used in ring model. The predicted to observed AUC0-t and Cmax ratios were well within 2-fold error limits for etonogestrel and ethinylestradiol vaginal ring (AFEs and absolute AFEs from 0.84 to 1.83). CONCLUSION: The current study provides first of its kind physiologically based pharmacokinetic framework integrating physiology, population and formulation data to carry out in silico mechanistic vaginal absorption studies, with the potential for virtual bioequivalence assessment in the future.
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Simulação por Computador , Dispositivos Anticoncepcionais Femininos , Modelos Biológicos , Tenofovir , Vagina , Absorção Vaginal , Cremes, Espumas e Géis Vaginais , Feminino , Humanos , Cremes, Espumas e Géis Vaginais/administração & dosagem , Cremes, Espumas e Géis Vaginais/farmacocinética , Tenofovir/farmacocinética , Tenofovir/administração & dosagem , Vagina/metabolismo , Vagina/efeitos dos fármacos , Administração Intravaginal , Etinilestradiol/farmacocinética , Etinilestradiol/administração & dosagem , Desogestrel/administração & dosagem , Desogestrel/farmacocinética , Pirimidinas/farmacocinética , Pirimidinas/administração & dosagem , Adulto , Área Sob a Curva , Fármacos Anti-HIV/farmacocinética , Fármacos Anti-HIV/administração & dosagemRESUMO
As the field of personalized dosing develops, the pharmaceutical manufacturing industry needs to offer flexibility in terms of tailoring the drug release and strength to the individual patient's needs. One of the promising tools which have such capacity is 3D printing technology. However, manufacturing small batches of drugs for each patient might lead to huge test burden, including the need to conduct bioequivalence trials of formulations to support the change of equipment or strength. In this paper we demonstrate how to use 3D printing in conjunction with virtual bioequivalence trials based on physiologically based pharmacokinetic (PBPK) modeling. For this purpose, we developed 3D printed ropinirole formulations and tested their bioequivalence with the reference product Polpix. The Simcyp simulator and previously developed ropinirole PBPK model were used for the clinical trial simulations. The Weibull-fitted dissolution profiles of test and reference formulations were used as inputs for the model. The virtual bioequivalence trials were run using parallel design. The study power of 80% was reached using 125 individuals. The study demonstrated how to use PBPK modeling in conjunction with 3D printing to test the virtual bioequivalence of newly developed formulations. This virtual experiment demonstrated the bioequivalence of one of the newly developed formulations with a reference product available on a market.
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The number of modeling and simulation applications, including physiologically based pharmacokinetic (PBPK) models, physiologically based biopharmaceutics modeling (PBBM), and empirical models, has been constantly increasing along with the regulatory acceptance of these methodologies. While aiming at minimizing unnecessary human testing, these methodologies are used today to support the development and approval of novel drug products and generics. Modeling approaches are leveraged today for assessing drug-drug interaction, informing dose adjustments in renally or hepatically impaired patients, perform dose selection in pediatrics and pregnant women and diseased populations, and conduct biopharmaceutics-related assessments such as establish clinically relevant specifications for drug products and achieve quality assurance throughout the product life cycle. In the generics space, PBPK analyses are utilized toward virtual bioequivalence assessments within the scope of alternative bioequivalence approaches, product-specific guidance development, and food effect assessments among others. Case studies highlighting the evolving and expanding role of modeling and simulation approaches within the biopharmaceutics space were presented at the symposium titled "Model Informed Drug Development (MIDD): Role in Dose Selection, Vulnerable Populations, and Biowaivers - Chemical Entities" and Prologue "PBPK/PBBM to inform the Bioequivalence Safe Space, Food Effects, and pH-mediated DDIs" at the American Association of Pharmaceutical Scientists (AAPS) PharmSci 360 Annual Meeting in Boston, MA, on October 16-19, 2022, and are summarized here.
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Desenvolvimento de Medicamentos , Modelos Biológicos , Gravidez , Humanos , Feminino , Criança , Solubilidade , Administração Oral , Desenvolvimento de Medicamentos/métodos , Equivalência Terapêutica , Biofarmácia/métodosRESUMO
Gastric mechanical stress often impacts drug dissolution from solid oral dosage forms, but in vitro experiments cannot recreate the substantial variability of gastric motility in a reasonable time. This study, for the first time, combines a novel dissolution apparatus with the design of experiments (DoE) and machine learning (ML) to overcome this obstacle. The workflow involves the testing of soft gelatin capsules in a set of fasted-state biorelevant dissolution experiments created with DoE. The dissolution results are used by an ML algorithm to build the classification model of the capsule's opening in response to intragastric stress (IS) within the physiological space of timing and magnitude. Next, a random forest algorithm is used to model the further drug dissolution. The predictive power of the two ML models is verified with independent dissolution tests, and they outperform a polynomial-based DoE model. Moreover, the developed tool reasonably simulates over 50 dissolution profiles under varying IS conditions. Hence, we prove that our method can be utilized for the simulation of dissolution profiles related to the multiplicity of individual gastric motility patterns. In perspective, the developed workflow can improve virtual bioequivalence trials and the patient-centric development of immediate-release oral dosage forms.
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Precision medicine requires selecting the appropriate dosage regimen for a patient using the right drug, at the right time. Model-Informed Precision Dosing (MIPD) is a concept suggesting utilization of model-based prediction methods for optimizing the treatment benefit-harm balance, based on individual characteristics of the patient, disease, treatment method, and other factors. Here, we discuss a theoretical workflow comprising several elements, beginning from the physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, through 3D printed tablets with the model proposed dose, information range and flow, and the patient themselves. We also describe each of these elements, and the connection between them, highlighting challenges and potential obstacles.
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Modelos Biológicos , Impressão Tridimensional , Humanos , SolubilidadeRESUMO
We present a physiologically based pharmacokinetic (PBPK) model simulating systemic drug concentrations following administration to the human rectum. Rectum physiology is parameterized based on literature data. The model utilizes in vitro release (IVRT) profiles from which drug mass transfer through the rectal fluid and tissue and into the systemic circulation are predicted. Due to a lack of data, rectal fluid and tissue absorption parameters are predicted either from colon absorption, with modifications relevant to rectal physiology, or optimized. The PBPK model is evaluated by simulating 29 clinical studies for 10 drugs. For 8 drugs (diazepam, diclofenac, indomethacin, naproxen, paracetamol, pentobarbital, phenobarbital and theophylline) the bias (average fold error, AFE) and precision (absolute average fold error, AAFE) of Cmax, AUC0-t and AUC0-inf simulations range from 0.87 to 2.22, indicating good agreement with observed values. For prochlorperazine and promethazine, the AFEs and AAFEs of Cmax predictions are 1.30 and 2.52, respectively. TheAUC0-t and AUC0-inf are overpredicted for both compounds(AFEs and AAFEs from 2.66 to 4.90). This results from a lack of reliable elimination data for prochlorperazine and the relevance of the IVRT profiles used in the promethazine model. The model paves the way for more mechanistic rectal drug absorption studies and virtual bioequivalence methods for rectal drug products.
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Absorção Retal , Humanos , Preparações Farmacêuticas , Proclorperazina , Prometazina , Equivalência Terapêutica , Modelos Biológicos , Simulação por ComputadorRESUMO
The paper presents the collection of physicochemical parameters of bisphenol A (BPA) and its sulfate (BPAS) and glucuronide (BPAG) conjugates, accompanied by data characterizing their absorption, distribution, metabolism and excretion (ADME) behavior following oral administration of BPA. The data were collected from open literature sources and publicly available databases. Additionally, data calculated by using the MarvinSketch 18.30.0 software or predicted by relevant QSAR models built in Simcyp® Simulator were also used. All data were analysed and are fit for purpose if necessary to ensure a reliable prediction of pharmacokinetics of BPA and its conjugates. The data selection process and reasoning for fitting is provided to allow critical assessment and to ensure data transparency. Finally, the sensitivity analysis was performed to assess the influence of the selected parameters on the PBPK model predictions.
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The aim of the current study was to develop an in silico model to predict the sensitizing potential of cosmetic ingredients based on their physicochemical characteristics and to compare the predictions with historical animal data and results from "omics"-based in vitro studies. An in silico model was developed with the use of WEKA machine learning software fed with physicochemical and structural descriptors of haptens and trained with data from published epidemiological studies compiled into estimated odds ratio (eOR) and estimated attributable risk (eAR) indices. The outcome classification was compared to the results of animal studies and in vitro tests. Of all the models tested, the best results were obtained for the Naive Bayes classifier trained with 24 physicochemical descriptors and eAR, which yielded an accuracy of 86%, sensitivity of 80%, and specificity of 90%. This model was subsequently used to predict the sensitizing potential of 15 emerging and less-studied haptens, of which 7 were classified as sensitizers: cyclamen aldehyde, N,N-dimethylacrylamide, dimethylthiocarbamyl benzothiazole sulphide, geraniol hydroperoxide, isobornyl acrylate, neral, and prenyl caffeate. The best-performing model (NaiveBayes eAR, 24 parameters), along with an alternative model based on eOR (Random Comittee eOR, 17 parameters), are available for further tests by interested readers. In conclusion, the proposed infotechnomics approach allows for a prediction of the sensitizing potential of cosmetic ingredients (and possibly also other haptens) with accuracy comparable to historical animal tests and in vitro tests used nowadays. In silico models consume little resources, are free of ethical concerns, and can provide results for multiple chemicals almost instantly; therefore, the proposed approach seems useful in the safety assessment of cosmetics.
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Inteligência Artificial , Cosméticos , Animais , Teorema de Bayes , Simulação por Computador , Cosméticos/efeitos adversos , Cosméticos/química , Técnicas In Vitro , Haptenos , Qualidade de Produtos para o ConsumidorRESUMO
The development of in vitro/in vivo translational methods and a clinical trial framework for synergistically acting drug combinations are needed to identify optimal therapeutic conditions with the most effective therapeutic strategies. We performed physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) modelling and virtual clinical trial simulations for siremadlin, trametinib, and their combination in a virtual representation of melanoma patients. In this study, we built PBPK/PD models based on data from in vitro absorption, distribution, metabolism, and excretion (ADME), and in vivo animals' pharmacokinetic-pharmacodynamic (PK/PD) and clinical data determined from the literature or estimated by the Simcyp simulator (version V21). The developed PBPK/PD models account for interactions between siremadlin and trametinib at the PK and PD levels. Interaction at the PK level was predicted at the absorption level based on findings from animal studies, whereas PD interaction was based on the in vitro cytotoxicity results. This approach, combined with virtual clinical trials, allowed for the estimation of PK/PD profiles, as well as melanoma patient characteristics in which this therapy may be noninferior to the dabrafenib and trametinib drug combination. PBPK/PD modelling, combined with virtual clinical trial simulation, can be a powerful tool that allows for proper estimation of the clinical effect of the above-mentioned anticancer drug combination based on the results of in vitro studies. This approach based on in vitro/in vivo extrapolation may help in the design of potential clinical trials using siremadlin and trametinib and provide a rationale for their use in patients with melanoma.
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Melanoma , Animais , Simulação por Computador , Melanoma/tratamento farmacológico , Quinases de Proteína Quinase Ativadas por Mitógeno , Modelos BiológicosRESUMO
Bisphenol A (BPA) is one of the best studied industrial chemicals in terms of exposure, toxicity, and toxicokinetics. This renders it an ideal candidate to exploit the recent advancements in physiologically based pharmacokinetic (PBPK) modelling to support risk assessment of BPA specifically, and of other consumer-relevant hazardous chemicals in general. Using the exposure from thermal paper as a case scenario, this study employed the multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) model available in the Simcyp® Simulator to simulate the dermal toxicokinetics of BPA at local and systemic levels. Sensitivity analysis helped to identify physicochemical and physiological factors influencing the systemic exposure to BPA. The iterative modelling process was as follows: (i) development of compound files for BPA and its conjugates, (ii) setting-up of a PBPK model for intravenous administration, (iii) extension for oral administration, and (iv) extension for exposure via skin (i.e., hand) contact. A toxicokinetic study involving hand contact to BPA-containing paper was used for model refinement. Cumulative urinary excretion of total BPA had to be employed for dose reconstruction. PBPK model performance was verified using the observed serum BPA concentrations. The predicted distribution across the skin compartments revealed a depot of BPA in the stratum corneum (SC). These findings shed light on the role of the SC to act as temporary reservoir for lipophilic chemicals prior to systemic absorption, which inter alia is relevant for the interpretation of human biomonitoring data and for establishing the relationship between external and internal measures of exposure.
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Absorção Cutânea , Pele , Humanos , Cinética , Pele/metabolismo , Compostos Benzidrílicos/toxicidade , Compostos Benzidrílicos/farmacocinéticaRESUMO
The development of a generic drug product involves demonstrating that there is no significant difference in the rate and extent to which the active ingredient becomes available at the site of action, relative to the reference listed drug product. This remains challenging for many locally acting topical dermatological products because measuring the concentration of the active ingredient at the site of action in the skin may not be straightforward, and, in most instances, there are no established relationships between skin and plasma pharmacokinetic profiles. In recent years, the Office of Generic Drugs of the US Food and Drug Administration (FDA) established scientific research programs with the goal of enhancing patient access to high quality, affordable topical dermatological generics. A key strategy of these research programs was to leverage modeling and simulation methodologies that accelerate the development of these generics by facilitating alternative bioequivalence approaches for dermatological drug products. This report summarizes relevant insights and discussions from a 2021 FDA public workshop titled "Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches," which illustrated how mechanistic modeling and simulation approaches can be utilized (and have been used) to inform generic drug product development and regulatory decisions during the assessment of generic drug applications submitted to the FDA.
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Medicamentos Genéricos , Relatório de Pesquisa , Humanos , Preparações Farmacêuticas , Pele , Equivalência TerapêuticaRESUMO
Translation of the synergy between the Siremadlin (MDM2 inhibitor) and Trametinib (MEK inhibitor) combination observed in vitro into in vivo synergistic efficacy in melanoma requires estimation of the interaction between these molecules at the pharmacokinetic (PK) and pharmacodynamic (PD) levels. The cytotoxicity of the Siremadlin and Trametinib combination was evaluated in vitro in melanoma A375 cells with MTS and RealTime-Glo assays. Analysis of the drug combination matrix was performed using Synergy and Synergyfinder packages. Calculated drug interaction metrics showed high synergy between Siremadlin and Trametinib: 23.12%, or a 7.48% increase of combined drug efficacy (concentration-independent parameter ß from Synergy package analysis and concentration-dependent δ parameter from Synergyfinder analysis, respectively). In order to select the optimal PD interaction parameter which may translate observed in vitro synergy metrics into the in vivo setting, further PK/PD studies on cancer xenograft animal models coupled with PBPK/PD modelling are needed.
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Antineoplásicos , Melanoma , Animais , Humanos , Inibidores de Proteínas Quinases/uso terapêutico , Inibidores de Proteínas Quinases/farmacocinética , Melanoma/tratamento farmacológico , Antineoplásicos/farmacologia , Quinases de Proteína Quinase Ativadas por Mitógeno , Proteínas Proto-Oncogênicas c-mdm2RESUMO
The use of animal as opposed to human skin for in vitro permeation testing (IVPT) is an alternative, which can reduce logistical and economic issues. However, this surrogate also has ethical considerations and may not provide an accurate estimation of dermal absorption in humans due to physiological differences. The current project aimed to provide a detailed repository for the anatomical and physiological parameters of porcine skin, with the aim of parametrizing the Multi-phase Multi-layer Mechanistic Dermal Absorption (MPML MechDermA) Model in the Simcyp Simulator. The MPML MechDermA Model is a physiologically based pharmacokinetic (PBPK) model that accounts for the physiology and geometry of skin in a mechanistic mathematical modelling framework. The database provided herein contains information on 14 parameters related to porcine skin anatomy and physiology, namely, skin surface pH, number of stratum corneum (SC) layers, SC thickness, corneocyte thickness, corneocyte dimensions (length and width), volume fraction of water in corneocyte (where SC is divided into four parts with different water contents), intercellular lipid thickness, viable epidermis thickness, dermis thickness, hair follicle and hair shaft diameter, hair follicle depth and hair follicle density. The collected parameters can be used to parameterize PBPK models, which could be further utilized to bridge the gap between animal and human studies with interspecies extrapolation or to predict dermatokinetic properties typically assessed in IVPT experiments. Database URL: https://data.mendeley.com/datasets/mwz9xv4cpd/1.
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Epiderme , Pele , Animais , Humanos , Lipídeos , Suínos , ÁguaRESUMO
The development of in vitro/in vivo translational methods for synergistically acting drug combinations is needed to identify the most effective therapeutic strategies. We performed PBPK/PD modelling for siremadlin, trametinib, and their combination at various dose levels and dosing schedules in an A375 xenografted mouse model (melanoma cells). In this study, we built models based on in vitro ADME and in vivo PK/PD data determined from the literature or estimated by the Simcyp Animal simulator (V21). The developed PBPK/PD models allowed us to account for the interactions between siremadlin and trametinib at PK and PD levels. The interaction at the PK level was described by an interplay between absorption and tumour disposition levels, whereas the PD interaction was based on the in vitro results. This approach allowed us to reasonably estimate the most synergistic and efficacious dosing schedules and dose levels for combinations of siremadlin and trametinib in mice. PBPK/PD modelling is a powerful tool that allows researchers to properly estimate the in vivo efficacy of the anticancer drug combination based on the results of in vitro studies. Such an approach based on in vitro and in vivo extrapolation may help researchers determine the most efficacious dosing strategies and will allow for the extrapolation of animal PBPK/PD models into clinical settings.
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Melanoma , Quinases de Proteína Quinase Ativadas por Mitógeno , Proteínas Proto-Oncogênicas c-mdm2 , Animais , Melanoma/tratamento farmacológico , Camundongos , Quinases de Proteína Quinase Ativadas por Mitógeno/antagonistas & inibidores , Modelos Biológicos , Proteínas Proto-Oncogênicas c-mdm2/antagonistas & inibidoresRESUMO
WHAT IS KNOWN AND OBJECTIVE: Fenspiride, a drug that had been used for decades for the treatment of respiratory diseases, was recently withdrawn from the market due to the potential risk of QT prolongation and proarrhythmia. This is the first such withdrawal for many years and hence poses a question whether such risk could have been predicted and to what degree non-drug-specific parameters play a role in the reported QT prolongation and cases of TdP. The study aim was to test various 'what-if' scenarios to assess the influence of age, gender, heart rate, and plasma potassium concentration on QT interval prolongation due to various doses of fenspiride with the use of mechanistic mathematical modelling. METHODS: Concentration-time profiles were simulated with the use of a PBPK model developed based on published physico-chemical data, data from in vitro ADME experiments, and in vivo PK study results. Pharmacodynamic effect, that is, drug-triggered pseudoECG signal modification was simulated using a biophysically detailed model of human cardiac myocytes. Analysis of the qNet metric was also performed to classify proarrhythmic risk related to fenspiride. RESULTS: In the simulation study, arrhythmia was not observed even in the 'what-if' scenarios with extreme exposure, age, heart rate, and plasma potassium concentration. The qNet metric value positioned fenspiride in the intermediate risk class. WHAT IS NEW AND CONCLUSION: It can be hypothesized that the clinically observed arrhythmia cases were not directly caused by fenspiride alone but a combination of multiple factors, including comedications.