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  Subjects -> PHARMACY AND PHARMACOLOGY (Total: 575 journals)
Showing 1 - 200 of 253 Journals sorted by number of followers
Nature Reviews Drug Discovery     Full-text available via subscription   (Followers: 332)
International Journal of Drug Policy     Hybrid Journal   (Followers: 254)
Journal of Clinical Oncology     Hybrid Journal   (Followers: 242)
Journal of Medicinal Chemistry     Hybrid Journal   (Followers: 157)
Journal of Pharmaceutical Sciences     Hybrid Journal   (Followers: 155)
Drugs     Full-text available via subscription   (Followers: 146)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 98)
Pharmaceutical Research     Hybrid Journal   (Followers: 94)
European Journal of Pharmaceutical Sciences     Hybrid Journal   (Followers: 86)
Drug Safety     Full-text available via subscription   (Followers: 83)
Annals of Pharmacotherapy     Hybrid Journal   (Followers: 56)
Biomaterials     Hybrid Journal   (Followers: 54)
Clinical Pharmacology & Therapeutics     Hybrid Journal   (Followers: 44)
Regulatory Toxicology and Pharmacology     Hybrid Journal   (Followers: 42)
Journal of Controlled Release     Hybrid Journal   (Followers: 38)
Annual Review of Pharmacology and Toxicology     Full-text available via subscription   (Followers: 38)
International Journal of Pharmaceutics     Hybrid Journal   (Followers: 37)
Clinical Therapeutics     Hybrid Journal   (Followers: 34)
European Journal of Pharmaceutics and Biopharmaceutics     Hybrid Journal   (Followers: 34)
Pharmacoepidemiology and Drug Safety     Hybrid Journal   (Followers: 33)
British Journal of Clinical Pharmacology     Hybrid Journal   (Followers: 32)
Journal of Pharmacy and Pharmacology     Full-text available via subscription   (Followers: 31)
Drug Development and Industrial Pharmacy     Hybrid Journal   (Followers: 29)
PharmacoEconomics     Full-text available via subscription   (Followers: 27)
Clinical Pharmacokinetics     Full-text available via subscription   (Followers: 27)
AAPS Journal     Hybrid Journal   (Followers: 26)
Critical Reviews in Toxicology     Hybrid Journal   (Followers: 25)
Journal of Clinical Psychopharmacology     Hybrid Journal   (Followers: 24)
International Journal of Pharmacy Practice     Full-text available via subscription   (Followers: 24)
Toxicology and Applied Pharmacology     Hybrid Journal   (Followers: 24)
Chemical Research in Toxicology     Hybrid Journal   (Followers: 22)
Journal of Pharmacokinetics and Pharmacodynamics     Hybrid Journal   (Followers: 22)
Journal of Pain & Palliative Care Pharmacotherapy     Hybrid Journal   (Followers: 21)
Trends in Pharmacological Sciences     Full-text available via subscription   (Followers: 20)
Journal of Applied Toxicology     Hybrid Journal   (Followers: 19)
Journal of Clinical Pharmacology     Hybrid Journal   (Followers: 19)
Pharmaceutical Development and Technology     Hybrid Journal   (Followers: 19)
American Journal of Cardiovascular Drugs     Hybrid Journal   (Followers: 19)
Clinical Trials     Hybrid Journal   (Followers: 18)
Toxicology     Hybrid Journal   (Followers: 18)
Journal of Pharmaceutical and Biomedical Analysis     Hybrid Journal   (Followers: 18)
Clinical Toxicology     Hybrid Journal   (Followers: 18)
International Journal of Toxicology     Hybrid Journal   (Followers: 17)
Critical Reviews in Clinical Laboratory Sciences     Hybrid Journal   (Followers: 16)
Journal of Clinical Pharmacy and Therapeutics     Hybrid Journal   (Followers: 16)
Journal of Natural Products     Hybrid Journal   (Followers: 16)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 15)
Toxicology Letters     Hybrid Journal   (Followers: 15)
Journal of Pharmacy Practice     Hybrid Journal   (Followers: 15)
Psychopharmacology     Hybrid Journal   (Followers: 15)
Basic & Clinical Pharmacology & Toxicology     Hybrid Journal   (Followers: 14)
Cardiovascular Drugs and Therapy     Hybrid Journal   (Followers: 14)
European Journal of Clinical Pharmacology     Hybrid Journal   (Followers: 14)
Current Medicinal Chemistry     Hybrid Journal   (Followers: 13)
American Journal of Therapeutics     Hybrid Journal   (Followers: 13)
Drug and Chemical Toxicology     Hybrid Journal   (Followers: 13)
Journal of the American Pharmacists Association     Full-text available via subscription   (Followers: 13)
Clinical Research and Regulatory Affairs     Hybrid Journal   (Followers: 12)
Seminars in Hematology     Hybrid Journal   (Followers: 12)
Drug Discovery Today: Technologies     Full-text available via subscription   (Followers: 12)
Current Pharmaceutical Design     Hybrid Journal   (Followers: 12)
Journal of Oncology Pharmacy Practice     Hybrid Journal   (Followers: 12)
Journal of Psychopharmacology     Hybrid Journal   (Followers: 11)
Biopharmaceutics and Drug Disposition     Hybrid Journal   (Followers: 11)
Toxicology in Vitro     Hybrid Journal   (Followers: 11)
Drug Development Research     Hybrid Journal   (Followers: 11)
Drug Metabolism and Disposition     Hybrid Journal   (Followers: 11)
Seminars in Oncology Nursing     Full-text available via subscription   (Followers: 10)
Biochemical Pharmacology     Hybrid Journal   (Followers: 10)
Journal of Separation Science     Hybrid Journal   (Followers: 10)
CNS Drugs     Full-text available via subscription   (Followers: 10)
Current Pharmaceutical Biotechnology     Hybrid Journal   (Followers: 10)
Journal of Medical Marketing     Hybrid Journal   (Followers: 10)
Drugs & Aging     Full-text available via subscription   (Followers: 10)
European Neuropsychopharmacology     Hybrid Journal   (Followers: 9)
Food Additives & Contaminants Part A     Hybrid Journal   (Followers: 9)
Journal of Pharmacology and Experimental Therapeutics     Hybrid Journal   (Followers: 9)
Environmental Toxicology and Pharmacology     Hybrid Journal   (Followers: 9)
Medicinal Chemistry     Hybrid Journal   (Followers: 9)
Biometrical Journal     Hybrid Journal   (Followers: 9)
Drugs & Therapy Perspectives     Full-text available via subscription   (Followers: 9)
Prescriber     Hybrid Journal   (Followers: 9)
ChemMedChem     Hybrid Journal   (Followers: 9)
Current Opinion in Pharmacology     Hybrid Journal   (Followers: 9)
European Journal of Pharmacology     Hybrid Journal   (Followers: 8)
Inhalation Toxicology     Hybrid Journal   (Followers: 8)
Antiviral Research     Hybrid Journal   (Followers: 8)
Drug Metabolism Reviews     Hybrid Journal   (Followers: 8)
Progress in Neuro-Psychopharmacology and Biological Psychiatry     Hybrid Journal   (Followers: 8)
Human & Experimental Toxicology     Hybrid Journal   (Followers: 8)
Drug Delivery     Open Access   (Followers: 8)
BioDrugs     Full-text available via subscription   (Followers: 8)
Frontiers in Drug Design & Discovery     Hybrid Journal   (Followers: 8)
Expert Review of Pharmacoeconomics & Outcomes Research     Full-text available via subscription   (Followers: 8)
Experimental and Clinical Psychopharmacology     Full-text available via subscription   (Followers: 7)
Toxicology Mechanisms and Methods     Hybrid Journal   (Followers: 7)
Journal of Pharmacological and Toxicological Methods     Hybrid Journal   (Followers: 7)
Clinical and Experimental Pharmacology and Physiology     Hybrid Journal   (Followers: 7)
Scandinavian Journal of Clinical and Laboratory Investigation     Hybrid Journal   (Followers: 7)
Epilepsy Research     Hybrid Journal   (Followers: 7)
Clinical Drug Investigation     Full-text available via subscription   (Followers: 7)
Journal of Veterinary Pharmacology and Therapeutics     Hybrid Journal   (Followers: 6)
Toxicology and Industrial Health     Hybrid Journal   (Followers: 6)
Skin Pharmacology and Physiology     Full-text available via subscription   (Followers: 6)
Journal of Cardiovascular Pharmacology     Hybrid Journal   (Followers: 6)
AAPS PharmSciTech     Hybrid Journal   (Followers: 6)
Current Drug Discovery Technologies     Hybrid Journal   (Followers: 6)
Current Drug Delivery     Hybrid Journal   (Followers: 6)
Current Therapeutic Research     Open Access   (Followers: 6)
Expert Review of Cardiovascular Therapy     Full-text available via subscription   (Followers: 6)
Neuropharmacology     Hybrid Journal   (Followers: 5)
Current Drug Metabolism     Hybrid Journal   (Followers: 5)
Fitoterapia     Hybrid Journal   (Followers: 5)
Expert Review of Molecular Diagnostics     Full-text available via subscription   (Followers: 5)
Expert Review of Anti-infective Therapy     Full-text available via subscription   (Followers: 5)
Anti-Infective Agents     Hybrid Journal   (Followers: 5)
Toxicon     Hybrid Journal   (Followers: 5)
Medicinal Research Reviews     Hybrid Journal   (Followers: 5)
Investigational New Drugs     Hybrid Journal   (Followers: 5)
Anti-Inflammatory & Anti-Allergy Agents in Medicinal Chemistry     Hybrid Journal   (Followers: 5)
Current Cancer Therapy Reviews     Hybrid Journal   (Followers: 5)
Reviews of Physiology, Biochemistry and Pharmacology     Hybrid Journal   (Followers: 4)
Planta Medica     Hybrid Journal   (Followers: 4)
Current Vascular Pharmacology     Hybrid Journal   (Followers: 4)
Pharmaceutical Medicine     Full-text available via subscription   (Followers: 4)
Journal of Child and Adolescent Psychopharmacology     Hybrid Journal   (Followers: 4)
CNS Drug Reviews     Open Access   (Followers: 4)
Inpharma Weekly     Full-text available via subscription   (Followers: 4)
Journal of Labelled Compounds and Radiopharmaceuticals     Hybrid Journal   (Followers: 4)
Immunopharmacology and Immunotoxicology     Hybrid Journal   (Followers: 4)
International Journal of Pharmaceutical and Healthcare Marketing     Hybrid Journal   (Followers: 4)
Inflammation Research     Hybrid Journal   (Followers: 4)
Cancer Chemotherapy and Pharmacology     Hybrid Journal   (Followers: 4)
International Journal of Neuropsychopharmacology     Open Access   (Followers: 3)
Pharmacology & Therapeutics     Hybrid Journal   (Followers: 3)
Physiology International     Full-text available via subscription   (Followers: 3)
Cardiovascular Therapeutics     Open Access   (Followers: 3)
ASSAY and Drug Development Technologies     Hybrid Journal   (Followers: 3)
Pharmacopsychiatry     Hybrid Journal   (Followers: 3)
Chemotherapy     Full-text available via subscription   (Followers: 3)
Therapeutic Drug Monitoring     Hybrid Journal   (Followers: 3)
Current Drug Therapy     Hybrid Journal   (Followers: 3)
Research in Social and Administrative Pharmacy     Hybrid Journal   (Followers: 3)
PharmacoEconomics & Outcomes News     Full-text available via subscription   (Followers: 3)
Journal of Aerosol Medicine and Pulmonary Drug Delivery     Hybrid Journal   (Followers: 3)
Journal of Ethnopharmacology     Hybrid Journal   (Followers: 3)
Drug Resistance Updates     Hybrid Journal   (Followers: 3)
Journal of Pain Management & Medicine     Open Access   (Followers: 3)
Journal of Infection and Chemotherapy     Hybrid Journal   (Followers: 3)
Journal of Cardiovascular Pharmacology and Therapeutics     Hybrid Journal   (Followers: 3)
Current Pharmacogenomics and Personalized Medicine     Hybrid Journal   (Followers: 3)
Acta Pharmacologica Sinica     Hybrid Journal   (Followers: 3)
Microbial Drug Resistance     Hybrid Journal   (Followers: 3)
Frontiers in Medicinal Chemistry     Hybrid Journal   (Followers: 3)
Human Psychopharmacology Clinical and Experimental     Hybrid Journal   (Followers: 3)
BMC Pharmacology     Open Access   (Followers: 2)
The Brown University Psychopharmacology Update     Hybrid Journal   (Followers: 2)
International Clinical Psychopharmacology     Hybrid Journal   (Followers: 2)
Canadian Journal of Physiology and Pharmacology     Hybrid Journal   (Followers: 2)
Journal of Drug Targeting     Hybrid Journal   (Followers: 2)
Inflammopharmacology     Hybrid Journal   (Followers: 2)
Journal of Inflammation     Open Access   (Followers: 2)
Fundamental & Clinical Pharmacology     Hybrid Journal   (Followers: 2)
Behavioural Pharmacology     Hybrid Journal   (Followers: 2)
Vascular Pharmacology     Hybrid Journal   (Followers: 2)
Pulmonary Pharmacology & Therapeutics     Hybrid Journal   (Followers: 2)
Biomedicine & Pharmacotherapy     Full-text available via subscription   (Followers: 2)
Clinical Neuropharmacology     Hybrid Journal   (Followers: 2)
Drugs in R & D     Full-text available via subscription   (Followers: 2)
International Immunopharmacology     Hybrid Journal   (Followers: 2)
Pharmacology Biochemistry and Behavior     Hybrid Journal   (Followers: 2)
Letters in Drug Design & Discovery     Hybrid Journal   (Followers: 2)
Archiv der Pharmazie     Hybrid Journal   (Followers: 2)
Pharmacological Reviews     Hybrid Journal   (Followers: 2)
Molecular Pharmacology     Hybrid Journal   (Followers: 2)
Journal of Microencapsulation: Microcapsules, Liposomes, Nanoparticles, Microcells, Microspheres     Hybrid Journal   (Followers: 2)
Toxicological & Environmental Chemistry     Hybrid Journal   (Followers: 2)
Particulate Science and Technology: An International Journal     Hybrid Journal   (Followers: 1)
Pharmacological Research     Hybrid Journal   (Followers: 1)
Current Enzyme Inhibition     Hybrid Journal   (Followers: 1)
Journal of Neuroimmune Pharmacology     Hybrid Journal   (Followers: 1)
Current Pharmaceutical Analysis     Hybrid Journal   (Followers: 1)
Current Neuropharmacology     Hybrid Journal   (Followers: 1)
Pharmacogenetics and Genomics     Hybrid Journal   (Followers: 1)
Journal of Texture Studies     Hybrid Journal   (Followers: 1)
Pharmaceutical Biology     Open Access  
Journal of Liposome Research     Hybrid Journal  
Toxin Reviews     Hybrid Journal  
Kaohsiung Journal of Medical Sciences     Open Access  
Redox Report     Open Access  
Pharmacology     Full-text available via subscription  
Pharmaceutical Chemistry Journal     Hybrid Journal  
NeuroMolecular Medicine     Hybrid Journal  
Journal of Ocular Pharmacology and Therapeutics     Hybrid Journal  
Harm Reduction Journal     Open Access  
Current Nanoscience     Hybrid Journal  
Infectious Disorders - Drug Targets     Hybrid Journal  
Current Bioactive Compounds     Hybrid Journal  
Cancer Biotherapy & Radiopharmaceuticals     Hybrid Journal  
Autonomic & Autacoid Pharmacology     Hybrid Journal  

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Similar Journals
Journal Cover
Journal of Pharmacokinetics and Pharmacodynamics
Journal Prestige (SJR): 0.784
Citation Impact (citeScore): 2
Number of Followers: 22  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-8744 - ISSN (Online) 1567-567X
Published by Springer-Verlag Homepage  [2467 journals]
  • Pharmacometric modeling of drug adverse effects: an application of mixture
           

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      Abstract: Abstract Clozapine has superior efficacy to other antipsychotics yet is underutilized due to its adverse effects, such as neutropenia, weight gain, and tachycardia. The current investigation aimed to introduce a pharmacometric approach to simultaneously model drug adverse effects, with examples from schizophrenia spectrum patients receiving clozapine. The adverse drug effects were represented as a function of time by incorporating a mixture model to describe individual susceptibility to the adverse effects. Applications of the proposed method were presented by analyzing retrospective data from patients’ medical records in Psychiatric Clinic, Penang General Hospital. Tachycardia, weight gain, and absolute neutrophils count (ANC) decrease were best described by an offset, a piecewise linear, and a transient surge function, respectively. 42.9% of the patients had all the adverse effects, including weight gain (0.01 kg/m2 increase every week over a baseline of 24.7 kg/m2 until stabilizing at 279 weeks), ANC decrease (20% decrease from 4540 cells/µL week 12-20.8), and tachycardia (14% constant increase over a baseline of 87.9 bpm for a clozapine maintenance dose of 450 mg daily). 32.5% of the patients had only tachycardia, while the remaining 24.6% had none of the adverse effects. A new pharmacometric approach was proposed to describe adverse drug effects with examples of clozapine-induced weight gain, ANC drop, and tachycardia. The current approach described the longitudinal time changes of continuous data while assessing patient susceptibility. Furthermore, the model revealed the possible co-existence of ANC drop and weight gain; thus, neutrophil monitoring might predict future changes in body weight.
      PubDate: 2022-11-15
       
  • Pharmacometric model of agalsidase–migalastat interaction in human: a
           novel mechanistic model of drug-drug interaction between a therapeutic
           protein and a small molecule

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      Abstract: Abstract Recently, a new mechanism of drug–drug interaction (DDI) was reported between agalsidase, a therapeutic protein, and migalastat, a small molecule, both of which are treatment options of Fabry disease. Migalastat is a pharmacological chaperone that stabilizes the native form of both endogenous and exogenous agalsidase. In Fabry patients co-administrated with agalsidase and migalastat, the increase in active agalsidase exposure is considered a pharmacokinetic effect of agalsidase infusion but a pharmacodynamic effect of migalastat administration, which makes this new DDI mechanism even more interesting. To quantitatively characterize the interaction between agalsidase and migalastat in human, a pharmacometric DDI model was developed using literature reported concentration–time data. The final model includes three components: a 1-compartment linear model component for migalastat; a 2-compartment linear model component for agalsidase; and a DDI component where the agalsidase-migalastat complex is formed via second order association constant kon, dissociated with first order dissociation constant koff, and distributed/eliminated with same rates as agalsidase alone, albeit the complex (i.e., bound agalsidase) has higher enzyme activity compared to free agalsidase. The final model adequately captured several key features of the unique interaction between agalsidase and migalastat, and successfully characterized the kinetics of migalastat as well as the kinetics and activities of agalsidase when both drugs were used alone or in combination following different doses. Most parameters were reasonably estimated with good precision. Because the model includes mechanistic basis of therapeutic protein and small molecule pharmacological chaperone interaction, it can potentially serve as a foundational work for DDIs with similar mechanism.
      PubDate: 2022-11-14
       
  • The Finite Absorption Time (FAT) concept en route to PBPK modeling and
           pharmacometrics

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      Abstract: Abstract The concept of Finite Absorption Time (FAT) for oral drug administration is set to affect pharmacokinetic analyses, Physiologically-based Pharmacokinetics simulations, and Pharmacometrics.
      PubDate: 2022-11-11
       
  • Individualized optimization of colistin loading doses

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      Abstract: Abstract Colistin remains one of the few available options for the treatment of infections caused by resistant bacteria. Pharmacokinetic (PK) studies have been successful in estimating the appropriate colistin methanesulfonate (CMS) dose to achieve a target colistin concentration. Currently, there is a consensus that the dose of CMS should vary according to the patient renal function since CMS is mainly eliminated by renal route. For this same reason, the loading dose should vary according to the patient's renal capacity; however, this is not the current clinical practice. In this study we develop a framework to determine two key parameters for the loading dose regimen: (1) the optimal dose according to the characteristics (renal function and weight) of the patient; (2) the waiting time before the maintenance dose. Based on a previous PK model, our framework allows a fast parameter sweep so as to select optimal loading dose and waiting time minimizing the deviation between the plasma concentration and a target value. The results showed that patients presenting low creatinine clearance (CrCL) should receive a lower CMS loading dose with longer interval to start maintenance treatment to avoid nephrotoxic colistin concentrations. In cases of high CrCL, the dose should be higher and the interval to the next dose shorter to avoid subtherapeutic concentrations. Optimization of the loading dose should considerably improve colistin therapy, as the target concentration is reached more quickly, without reaching toxic values.
      PubDate: 2022-11-02
       
  • Accelerating robust plausible virtual patient cohort generation by
           substituting ODE simulations with parameter space mapping

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      Abstract: Abstract The generation of plausible virtual patients (VPs) is an important step in most quantitative systems pharmacology (QSP) workflows, which requires time-intensive solving of ordinary differential equations (ODEs). However, non-physiological profiles of outputs of interest (OoI) are frequently produced, and additional acceptance/rejection steps are needed for comparing and removing VPs with predicted values outside a pre-defined range. Here, a new approach is developed to accelerate the acceptance/rejection steps by leveraging patterns of parameter associations with OoI. In most models, some parameters are monotonic with respect to OoI, such that an increase in a parameter value always induces an increase or decrease in the OoI. This monotonic property can be used to replace some ODE-solving steps with appropriate monotonic parameter value comparisons to extrapolate the rejection or interpolate the acceptance of some VPs (after simulation) to others. Two algorithms were built that directly extract plausible VPs from a pre-defined initial cohort. These algorithms were first tested using a simple tumor growth inhibition model. Analyzing 200,000 VPs took 50 s with a reference method and 3 to 41 s (depending on the initial set-up) with the first algorithm. The method was then applied to an apoptosis QSP model, in which the clinical phenotypes (i.e., treatment sensitive or resistant) of 200,000 VPs were fully characterized for four different drug regimens in 12 min as compared to over 80 min with the reference approach. Extraction of each phenotype can also be performed individually in 34 s to 8 min, demonstrating the time benefit and flexibility of this approach.
      PubDate: 2022-10-31
       
  • Modeling of the effect of cerebrospinal fluid flow modulation on locally
           delivered drugs in the brain

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      Abstract: Abstract Cerebrospinal fluid (CSF) plays a vital role in maintaining brain homeostasis and recent research has focused on elucidating the role that convective flow of CSF plays in brain health. This paper describes a computational compartmental model of how CSF dynamics affect drug pharmacokinetics in the rat brain. Our model implements a local, sustained release approach for drug delivery to the brain. Simulation outputs highlight the potential for modulating CSF flow to improve overall drug pharmacokinetics in the central nervous system and suggest that concomitant CSF modulation and optimized drug release rates from implantable depots can be used to engineer the duration of action of chemotherapeutics. As an example, the tissue exposure of temozolomide, the standard of care treatment for glioblastoma, was modeled in conjunction with two CSF-modulating drugs: acetazolamide and verapamil. Simulations indicate that temozolomide exposure in the interstitial fluid is increased by 25% when using local sustained release delivery systems and concomitant acetazolamide delivery to reduce CSF production. This computational model can be used to produce insight on how to appropriately modulate CSF production and engineer drug release to tailor drug exposure in the brain while limiting off-target effects. As new research continues to elucidate the dynamic roles of CSF, this model can be further improved and leveraged to provide information on how CSF modulation may play a beneficial role in treating a wide variety of neurological disease.
      PubDate: 2022-10-25
       
  • Physiologically-based pharmacokinetic model for pulmonary disposition of
           protein therapeutics in humans

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      Abstract: Abstract Lung related disorders like COPD and Asthma, as well as various infectious diseases, form a major therapeutic area which would benefit from a predictive and adaptable mathematical model for describing pulmonary disposition of biological modalities. In this study we fill that gap by extending the cross-species two-pore physiologically-based pharmacokinetic (PBPK) platform with more detailed respiratory tract that includes the airways and alveolar space with epithelial lining fluid. We parameterize the paracellular and FcRn-facilitated exchange pathways between the epithelial lining fluid and lung interstitial space by building a mechanistic model for the exchange between the two. The optimized two-pore PBPK model described pulmonary exposure of several systemically dosed mAbs for which data is available and is also in agreement with the observed levels of endogenous IgG and albumin. The proposed framework can be used to assess pharmacokinetics of new lung-targeting biologic therapies and guide their dosing to achieve desired exposure at the pulmonary site-of-action.
      PubDate: 2022-10-20
       
  • A system pharmacology Boolean network model for the TLR4-mediated
           inflammatory response in early sepsis

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      Abstract: Abstract Sepsis is a life-threatening condition driven by the dysregulation of the host immune response to an infection. The complex and interacting mechanisms underlying sepsis remain not fully understood. By integrating prior knowledge from literature using mathematical modelling techniques, we aimed to obtain a deeper mechanistic insight into sepsis pathogenesis and to evaluate promising novel therapeutic targets, with a focus on Toll-like receptor 4 (TLR4)-mediated pathways. A Boolean network of regulatory relationships was developed for key immune components associated with sepsis pathogenesis after TLR4 activation. Perturbation analyses were conducted to identify therapeutic targets associated with organ dysfunction or antibacterial activity. The developed model consisted of 42 nodes and 183 interactions. Perturbation analyses suggest that over-expression of tumour necrosis factor alpha (TNF-α) or inhibition of soluble receptor sTNF-R, tissue factor, and inflammatory cytokines (IFN-γ, IL-12) may lead to a reduced activation of organ dysfunction related endpoints. Over-expression of complement factor C3b and C5b led to an increase in the bacterial clearance related endpoint. We identified that combinatory blockade of IFN-γ and IL-10 may reduce the risk of organ dysfunction. Finally, we found that combining antibiotic treatment with IL-1β targeted therapy may have the potential to decrease thrombosis. In summary, we demonstrate how existing biological knowledge can be effectively integrated using Boolean network analysis for hypothesis generation of potential treatment strategies and characterization of biomarker responses associated with the early inflammatory response in sepsis.
      PubDate: 2022-10-19
       
  • A quantitative systems pharmacology model for simulating OFF-Time in
           

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      Abstract: Abstract The clinical impact of therapeutic interventions in Parkinson’s disease is often measured as a reduction in OFF-time when the beneficial effects of the standard-of-care L-DOPA formulations wanes off. We investigated the pharmacodynamic interactions of augmentation therapy to standard-of-care using a quantitative systems pharmacology (QSP) model of the basal ganglia motor circuit, essentially a computer model of neuronal firing in the different subregions with anatomically informed connectivity, cell-specific expression of 17 different G-protein coupled receptors and corresponding coupling to voltage-gated ion channel effector proteins based on experimentally observed intracellular signaling. The calculated beta/gamma (b/g) power spectrum of the local field potentials in the subthalamic nucleus was previously calibrated on the clinically relevant Unified Parkinson’s Disease Rating Scale (UPDRS). When combining this QSP model with PK modeling of different formulations of L-DOPA, we calculated the b/g fluctuations over a 16 h awake period and used a weighted distance from a specific threshold to determine the cumulative liability of OFF-Time. Prediction of OFF-time with clinical observations of different L-DOPA formulations showed a significant correlation. Simulations show that augmentation with the adenosine A2A antagonist preladenant reduces OFF-time with 6 min for carbidopa/levodopa 950 mg 5-times daily to 37 min for 100 mg L-DOPA – 3 or 5 times daily. Exploring delays between preladenant and L-DOPA intake did not improve the outcome. Hypothetical A2A antagonists with an ideal PK and pharmacology profile can achieve OFF-Time reductions ranging from 9.5 min with DuoDopa to 55 min with low dose L-DOPA formulations. Combination of the QSP model with PK modeling can predict the anticipated OFF-Time reduction of novel A2A antagonists with standard of care. With the large number of GPCR in the model, this combination can support both the design of clinical trials with new therapeutic agents and the optimization of combination therapy in clinical practice.
      PubDate: 2022-10-09
       
  • Impact of model misspecification on model-based tests in PK studies with
           parallel design: real case and simulation studies

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      Abstract: Abstract This article evaluates the performance of pharmacokinetic (PK) equivalence testing between two formulations of a drug through the Two-One Sided Tests (TOST) by a model-based approach (MB-TOST), as an alternative to the classical non-compartmental approach (NCA-TOST), for a sparse design with a few time points per subject. We focused on the impact of model misspecification and the relevance of model selection for the reference data. We first analysed PK data from phase I studies of gantenerumab, a monoclonal antibody for the treatment of Alzheimer’s disease. Using the original rich sample data, we compared MB-TOST to NCA-TOST for validation. Then, the analysis was repeated on a sparse subset of the original data with MB-TOST. This analysis inspired a simulation study with rich and sparse designs. With rich designs, we compared NCA-TOST and MB-TOST in terms of type I error and study power. With both designs, we explored the impact of misspecifying the model on the performance of MB-TOST and adding a model selection step. Using the observed data, the results of both approaches were in general concordance. MB-TOST results were robust with sparse designs when the underlying PK structural model was correctly specified. Using the simulated data with a rich design, the type I error of NCA-TOST was close to the nominal level. When using the simulated model, the type I error of MB-TOST was controlled on rich and sparse designs, but using a misspecified model led to inflated type I errors. Adding a model selection step on the reference data reduced the inflation. MB-TOST appears as a robust alternative to NCA-TOST, provided that the PK model is correctly specified and the test drug has the same PK structural model as the reference drug.
      PubDate: 2022-09-16
      DOI: 10.1007/s10928-022-09821-z
       
  • PBPK model for antibody disposition in mouse brain: validation using
           large-pore microdialysis data

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      Abstract: Abstract The objective of this manuscript was to validate a physiologically-based pharmacokinetic (PBPK) model developed to characterize brain pharmacokinetics (PK) of monoclonal antibodies (mAbs) using novel large-pore microdialysis data generated in mice. To support this objective, brain, CSF, and ISF PK of a human anti-tetanus toxin (TeTx) antibody was measured in mice following intraperitoneal (IP) administration. This antibody has no binding in mice. In addition, our recently published mouse brain PK data generated following intravenous (IV) and IP administration of trastuzumab in mice, and other published PK data for brain disposition of antibody in mice, were used to evaluate the PBPK model. All the model parameters were obtained from literature or kept the same as in our previously published manuscript. The revised PBPK model was able to characterize the PK of antibodies in mice brain, CSF, and ISF reasonably well (i.e., within a three-fold error). However, a priori selected parameters led to underprediction of ISF PK during the initial phase of the profile. A local sensitivity analysis suggested that minor changes in several brain-related parameters can help overcome this discrepancy, where an increase in the convective flow of antibodies across BBB was found to be the most parsimonious way to capture all the PK profiles well. However, the presence of this pathway needs further validation. As such, here we have presented an improved PBPK model to characterize and predict the PK of mAbs in different regions of the mouse brain following systemic administration. This model can serve as a quantitative tool to facilitate the discovery, preclinical evaluation, and preclinical-to-clinical translation of novel antibodies targeted against CNS disorders.
      PubDate: 2022-09-10
      DOI: 10.1007/s10928-022-09823-x
       
  • Pharmacodynamic model of slow reversible binding and its applications in
           pharmacokinetic/pharmacodynamic modeling: review and tutorial

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      Abstract: Therapeutic responses of most drugs are initiated by the rate and degree of binding to their receptors or targets. The law of mass action describes the rate of drug-receptor complex association (kon) and dissociation (koff) where the ratio koff/kon is the equilibrium dissociation constant (Kd). Drugs with slow reversible binding (SRB) often demonstrate delayed onset and prolonged pharmacodynamic effects. This report reviews evidence for drugs with SRB features, describes previous pharmacokinetic/pharmacodynamic (PK/PD) modeling efforts of several such drugs, provides a tutorial on the mathematics and properties of SRB models, demonstrates applications of SRB models to additional compounds, and compares PK/PD fittings of SRB with other mechanistic models. We identified and summarized 52 drugs with in vitro-confirmed SRB from a PubMed literature search. Simulations with a SRB model and observed PK/PD profiles showed delayed and prolonged responses and that increasing doses/kon or decreasing koff led to greater expected maximum effects and a longer duration of effects. Recession slopes for return of responses to baseline after single doses were nearly linear with an inflection point that approaches a limiting value at larger doses. The SRB model newly captured literature data for the antihypertensive effects of candesartan and antiallergic effects of noberastine. Their PD profiles could also be fitted with indirect response and biophase models with minimal differences. The applicability of SRB models is probably commonplace, but underappreciated, owing to the need for in vitro confirmation of binding kinetics and the similarity of PK/PD profiles to models with other mechanistic determinants. Graphical abstract
      PubDate: 2022-08-30
      DOI: 10.1007/s10928-022-09822-y
       
  • Towards a comprehensive assessment of QSP models: what would it take'

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      Abstract: Abstract Quantitative Systems Pharmacology (QSP) has emerged as a powerful ensemble of approaches aiming at developing integrated mathematical and computational models elucidating the complex interactions between pharmacology, physiology, and disease. As the field grows and matures its applications expand beyond the boundaries of research and development and slowly enter the decision making and regulatory arenas. However, widespread acceptance and eventual adoption of a new modeling approach requires assessment criteria and quantifiable metrics that establish credibility and increase confidence in model predictions. QSP aims to provide an integrated understanding of pathology in the context of therapeutic interventions. Because of its ambitious nature and the fact that QSP emerged in an uncoordinated manner as a result of activities distributed across organizations and academic institutions, high entropy characterizes the tools, methods, and computational methodologies and approaches used. The eventual acceptance of QSP model predictions as supporting material for an application to a regulatory agency will require that two key aspects are considered: (1) increase confidence in the QSP framework, which drives standardization and assessment; and (2) careful articulation of the expectations. Both rely heavily on our ability to rigorously and consistently assess QSP models. In this manuscript, we wish to discuss the meaning and purpose of such an assessment in the context of QSP model development and elaborate on the differentiating features of QSP that render such an endeavor challenging. We argue that QSP establishes a conceptual, integrative framework rather than a specific and well-defined computational methodology. QSP elicits the use of a wide variety of modeling and computational methodologies optimized with respect to specific applications and available data modalities, which exceed the data structures employed by chemometrics and PK/PD models. While the range of options fosters creativity and promises to substantially advance our ability to design pharmaceutical interventions rationally and optimally, our expectations of QSP models need to be clearly articulated and agreed on, with assessment emphasizing the scope of QSP studies rather than the methods used. Nevertheless, QSP should not be considered an independent approach, rather one of many in the broader continuum of computational models.
      PubDate: 2022-08-13
      DOI: 10.1007/s10928-022-09820-0
       
  • Current practices for QSP model assessment: an IQ consortium survey

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      Abstract: Abstract Quantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions.
      PubDate: 2022-08-11
      DOI: 10.1007/s10928-022-09811-1
       
  • Analysis of cellular kinetic models suggest that physiologically based
           model parameters may be inherently, practically unidentifiable

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      Abstract: Abstract Physiologically-based pharmacokinetic and cellular kinetic models are used extensively to predict concentration profiles of drugs or adoptively transferred cells in patients and laboratory animals. Models are fit to data by the numerical optimisation of appropriate parameter values. When quantities such as the area under the curve are all that is desired, only a close qualitative fit to data is required. When the biological interpretation of the model that produced the fit is important, an assessment of uncertainties is often also warranted. Often, a goal of fitting PBPK models to data is to estimate parameter values, which can then be used to assess characteristics of the fit system or applied to inform new modelling efforts and extrapolation, to inform a prediction under new conditions. However, the parameters that yield a particular model output may not necessarily be unique, in which case the parameters are said to be unidentifiable. We show that the parameters in three published physiologically-based pharmacokinetic models are practically (deterministically) unidentifiable and that it is challenging to assess the associated parameter uncertainty with simple curve fitting techniques. This result could affect many physiologically-based pharmacokinetic models, and we advocate more widespread use of thorough techniques and analyses to address these issues, such as established Markov Chain Monte Carlo and Bayesian methodologies. Greater handling and reporting of uncertainty and identifiability of fit parameters would directly and positively impact interpretation and translation for physiologically-based model applications, enhancing their capacity to inform new model development efforts and extrapolation in support of future clinical decision-making.
      PubDate: 2022-08-06
      DOI: 10.1007/s10928-022-09819-7
       
  • Variability and uncertainty: interpretation and usage of pharmacometric
           simulations and intervals

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      Abstract: Abstract Variability and estimation uncertainty are important sources of variation in pharmacometric simulations. Different combinations of uncertainty and the variability components lead to a variety types of simulation intervals, and many realized and unrealized confusions exist among pharmacometricians on their interpretation and usage. This commentary aims to clarify some of the important underlying concepts and provide a convenient guideline on pharmacometric simulation conduct and interpretation.
      PubDate: 2022-08-04
      DOI: 10.1007/s10928-022-09817-9
       
  • Development of minimal physiologically-based
           pharmacokinetic-pharmacodynamic models for characterizing cellular
           kinetics of CAR T cells following local deliveries in mice

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      Abstract: Abstract Chimeric antigen receptor (CAR) T cell therapies have revolutionized the treatment of hematologic malignancies and have potentials for solid tumor treatment. To overcome limited CAR T cell infiltration to solid tumors, local delivery of CAR T cells is a practical strategy that has shown promising therapeutic outcome and safety profile in the clinic. It is of great interest to understand the impact of dosing routes on CAR T cell distribution, subsequent proliferation and tumor killing in a quantitative manner to identify key factors that contribute to CAR T efficacy and safety. In this study, we established mouse minimal physiologically-based pharmacokinetic (mPBPK) models combined with pharmacodynamic (PD) components to delineate CAR T cell distribution, proliferation, tumor growth, and tumor cell killing in the cases of pleural and liver tumors. The pleural tumor model reasonably captured published CAR T cellular kinetic and tumor growth profiles in mice. The mPBPK-PD simulation of a liver tumor mouse model showed a substantial increase in initial tumor infiltration and earlier CAR T cell proliferation with local hepatic artery delivery compared to portal vein and intravenous (i.v.) injections whereas portal vein injection showed little difference from i.v. administration, suggesting the importance of having the injection site close to tumor for maximal effect of non-systemic administration. Blood flow rate in the liver tumor was found to be a sensitive parameter for cellular kinetics and efficacy, indicating a potential role of tumor vascularization in the efficacy of CAR T cell therapies.
      PubDate: 2022-07-22
      DOI: 10.1007/s10928-022-09818-8
       
  • Application of different approaches to generate virtual patient
           populations for the quantitative systems pharmacology model of
           erythropoiesis

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      Abstract: Abstract In a standard situation, a quantitative systems pharmacology model describes a “reference patient,” and the model parameters are fixed values allowing only the mean values to be described. However, the results of clinical trials include a description of variability in patients’ responses to a drug, which is typically expressed in terms of conventional statistical parameters, such as standard deviations (SDs) from mean values. Therefore, in this study, we propose and compare four different approaches: (1) Monte Carlo Markov Chain (MCMC); (2) model fitting to Monte Carlo sample; (3) population of clones; (4) stochastically bounded selection to generate virtual patient populations based on experimentally measured mean data and SDs. We applied these approaches to generate virtual patient populations in the QSP model of erythropoiesis. According to the results of our research, stochastically bounded selection showed slightly better results than the other three methods as it allowed the description of any number of patients from clinical trials and could be applied in the case of complex models with a large number of variable parameters.
      PubDate: 2022-07-07
      DOI: 10.1007/s10928-022-09814-y
       
  • Global sensitivity analysis in physiologically-based
           pharmacokinetic/pharmacodynamic models of inhaled and opioids anesthetics
           and its application to generate virtual populations

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      Abstract: Abstract The integration between physiologically-based pharmacokinetics (PBPK) models and pharmacodynamics (PD) models makes it possible to describe the absorption, distribution, metabolism and excretion processes of drugs, together with the concentration–response relationship, being a fundamental framework with wide applications in pharmacology. Nevertheless, the enormous complexity of PBPK models and the large number of parameters that define them leads to the need to study and understand how the uncertainty of the parameters affects the variability of the models output. To study this issue, this paper proposes a global sensitivity analysis (GSA) to identify the parameters that have the greatest influence on the response of the model. It has been selected as study cases the PBPK models of an inhaled anesthetic and an analgesic, along with two PD interaction models that describe two relevant clinical effects, hypnosis and analgesia during general anesthesia. The subset of the most relevant parameters found adequately with the GSA method has been optimized for the generation of a virtual population that represents the theoretical output variability of various model responses. The generated virtual population has the potential to be used for the design, development and evaluation of physiological closed-loop control systems.
      PubDate: 2022-05-26
      DOI: 10.1007/s10928-022-09810-2
       
  • Knowledge dissemination and central indexing of resources in
           pharmacometrics: an ISOP education working group initiative

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      Abstract: Abstract Pharmacometrics is a constantly evolving field that plays a major role in decision making in drug development and clinical monitoring. Scientists in Pharmacometrics, especially in their early phases of career, are often faced with the challenge of identifying adequate resources for self-training and education. Hence, the ISoP Education Committee through its working group dedicated to Central Indexing and knowledge Dissemination has built a database of worldwide educational programs and most common references in Pharmacometrics.
      PubDate: 2022-04-26
      DOI: 10.1007/s10928-022-09809-9
       
 
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