scholarly journals Integrating physiologically based kinetic (PBK) and Monte Carlo modelling to predict inter-individual and inter-ethnic variation in bioactivation and liver toxicity of lasiocarpine

2019 ◽  
Vol 93 (10) ◽  
pp. 2943-2960 ◽  
Author(s):  
Jia Ning ◽  
Ivonne M. C. M. Rietjens ◽  
Marije Strikwold
Keyword(s):  
Monte Carlo ◽  
Liver Toxicity ◽  
Population Distribution ◽  
Geometric Mean ◽  
Caucasian Population ◽  
Individual Variations ◽  
Physiologically Based ◽  
Adjustment Factors ◽  
Human Kinetic

Abstract The aim of the present study was to predict the effect of inter-individual and inter-ethnic human kinetic variation on the sensitivity towards acute liver toxicity of lasiocarpine in the Chinese and the Caucasian population, and to derive chemical specific adjustment factors (CSAFs) by integrating variation in the in vitro kinetic constants Vmax and Km, physiologically based kinetic (PBK) modelling and Monte Carlo simulation. CSAFs were derived covering the 90th and 99th percentile of the population distribution of pyrrole glutathione adduct (7-GS-DHP) formation, reflecting bioactivation. The results revealed that in the Chinese population, as compared to the Caucasian population, the predicted 7-GS-DHP formation at the geometric mean, the 90th and the 99th percentile were 2.1-, 3.3- and 4.3-fold lower respectively. The CSAFs obtained using the 99th percentile values were 8.3, 17.0 and 19.5 in the Chinese, the Caucasian population and the two populations combined, respectively, while the CSAFs were generally 3.0-fold lower at the 90th percentile. These results indicate that when considering the formation of 7-GS-DHP the Caucasian population may be more sensitive towards acute liver toxicity of lasiocarpine, and further point out that the default safety factor of 3.16 for inter-individual human kinetic differences may not be sufficiently protective. Altogether, the results obtained demonstrate that integrating PBK modelling with Monte Carlo simulations using human in vitro data is a powerful strategy to quantify inter-individual variations in kinetics, and can be used to refine the human risk assessment of pyrrolizidine alkaloids.

scholarly journals Development of Physiologically Based Pharmacokinetic Model for Orally Administered Fexuprazan in Humans

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 813
Author(s):  
Yoo-Seong Jeong ◽  
Min-Soo Kim ◽  
Nora Lee ◽  
Areum Lee ◽  
Yoon-Jee Chae ◽  
...  
Keyword(s):  
Gastric Acid ◽  
Pbpk Model ◽  
Pbpk Modeling ◽  
Drug Candidate ◽  
Metabolite Formation ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Fexuprazan is a new drug candidate in the potassium-competitive acid blocker (P-CAB) family. As proton pump inhibitors (PPIs), P-CABs inhibit gastric acid secretion and can be used to treat gastric acid-related disorders such as gastroesophageal reflux disease (GERD). Physiologically based pharmacokinetic (PBPK) models predict drug interactions as pharmacokinetic profiles in biological matrices can be mechanistically simulated. Here, we propose an optimized and validated PBPK model for fexuprazan by integrating in vitro, in vivo, and in silico data. The extent of fexuprazan tissue distribution in humans was predicted using tissue-to-plasma partition coefficients in rats and the allometric relationships of fexuprazan distribution volumes (VSS) among preclinical species. Urinary fexuprazan excretion was minimal (0.29–2.02%), and this drug was eliminated primarily by the liver and metabolite formation. The fraction absorbed (Fa) of 0.761, estimated from the PBPK modeling, was consistent with the physicochemical properties of fexuprazan, including its in vitro solubility and permeability. The predicted oral bioavailability of fexuprazan (38.4–38.6%) was within the range of the preclinical datasets. The Cmax, AUClast, and time-concentration profiles predicted by the PBPK model established by the learning set were accurately predicted for the validation sets.

scholarly journals The Emerging Terbinafine-Resistant Trichophyton Epidemic: What Is the Role of Antifungal Susceptibility Testing?

Dermatology ◽  
2021 ◽  
pp. 1-20
Author(s):  
Julia J. Shen ◽  
Maiken C. Arendrup ◽  
Shyam Verma ◽  
Ditte Marie L. Saunte
Keyword(s):  
Gene Mutation ◽  
Susceptibility Testing ◽  
Geometric Mean ◽  
Antifungal Susceptibility ◽  
Antifungal Susceptibility Testing ◽  
Squalene Epoxidase ◽  
Exclusion Criteria ◽  
Huge Variation

<b><i>Background:</i></b> Dermatophytosis is commonly encountered in the dermatological clinics. The main aetiological agents in dermatophytosis of skin and nails in humans are <i>Trichophyton</i> (<i>T</i>.) <i>rubrum</i>, <i>T. mentagrophytes</i> and <i>T. interdigitale</i> (former <i>T. mentagrophytes-</i>complex). Terbinafine therapy is usually effective in eradicating infections due to these species by inhibiting their squalene epoxidase (SQLE) enzyme, but increasing numbers of clinically resistant cases and mutations in the SQLE gene have been documented recently. Resistance to antimycotics is phenotypically determined by antifungal susceptibility testing (AFST). However, AFST is not routinely performed for dermatophytes and no breakpoints classifying isolates as susceptible or resistant are available, making it difficult to interpret the clinical impact of a minimal inhibitory concentration (MIC). <b><i>Summary:</i></b> PubMed was systematically searched for terbinafine susceptibility testing of dermatophytes on October 20, 2020, by two individual researchers. The inclusion criteria were <i>in vitro</i> terbinafine susceptibility testing of <i>Trichophyton (T.) rubrum</i>, <i>T. mentagrophytes</i> and <i>T. interdigitale</i> with the broth microdilution technique. The exclusion criteria were non-English written papers. Outcomes were reported as MIC range, geometric mean, modal MIC and MIC<sub>50</sub> and MIC<sub>90</sub> in which 50 or 90% of isolates were inhibited, respectively. The reported MICs ranged from &#x3c;0.001 to &#x3e;64 mg/L. The huge variation in MIC is partly explained by the heterogeneity of the <i>Trichophyton</i> isolates, where some originated from routine specimens (wild types) whereas others came from non-responding patients with a known SQLE gene mutation. Another reason for the great variation in MIC is the use of different AFST methods where MIC values are not directly comparable. High MICs were reported particularly in isolates with SQLE gene mutation. The following SQLE alterations were reported: F397L, L393F, L393S, H440Y, F393I, F393V, F415I, F415S, F415V, S443P, A448T, L335F/A448T, S395P/A448T, L393S/A448T, Q408L/A448T, F397L/A448T, I121M/V237I and H440Y/F484Y in terbinafine-resistant isolates.

scholarly journals 1315. No Dose Adjustment of Metformin with Fostemsavir Coadministration Based on Mechanistic Static and Physiologically Based Pharmacokinetic Models

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S669-S669
Author(s):  
Dung N Nguyen ◽  
Xiusheng Miao ◽  
Mindy Magee ◽  
Guoying Tai ◽  
Peter D Gorycki ◽  
...  
Keyword(s):  
Dose Adjustment ◽  
Pbpk Model ◽  
Systemic Exposure ◽  
Multidrug Resistant ◽  
Pbpk Modeling ◽  
Repeat Dose ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Abstract Background Fostemsavir (FTR) is an oral prodrug of the first-in-class attachment inhibitor temsavir (TMR) which is being evaluated in patients with multidrug resistant HIV-1 infection. In vitro studies indicated that TMR and its 2 major metabolites are inhibitors of organic cation transporters (OCT)1, OCT2, and multidrug and toxin extrusion transporters (MATEs). To assess the clinical relevance, of OCT and MATE inhibition, mechanistic static DDI prediction with calculated Imax,u/IC50 ratios was below the cut-off limits for a DDI flag based on FDA guidelines and above the cut-off limits for MATEs based on EMA guidelines. Methods Metformin is a commonly used probe substrate for OCT1, OCT2 and MATEs. To predict the potential for a drug interaction between TMR and metformin, a physiologically based pharmacokinetic (PBPK) model for TMR was developed based on its physicochemical properties, in vitro and in vivo data. The model was verified and validated through comparison with clinical data. The TMR PBPK model accurately described AUC and Cmax within 30% of the observed data for single and repeat dose studies with or without food. The SimCYP models for metformin and ritonavir were qualified using literature data before applications of DDI prediction for TMR Results TMR was simulated at steady state concentrations after repeated oral doses of FTR 600 mg twice daily which allowed assessment of the potential OCT1, OCT2, and MATEs inhibition by TMR and metabolites. No significant increase in metformin systemic exposure (AUC or Cmax) was predicted with FTR co-administration. In addition, a sensitivity analysis was conducted for either hepatic OCT1 Ki, or renal OCT2 and MATEs Ki values. The model output indicated that, a 10-fold more potent Ki value for TMR would be required to have a ~15% increase in metformin exposure Conclusion Based on mechanistic static models and PBPK modeling and simulation, the OCT1/2 and MATEs inhibition potential of TMR and its metabolites on metformin pharmacokinetics is not clinically significant. No dose adjustment of metformin is necessary when co-administered with FTR Disclosures Xiusheng Miao, PhD, GlaxoSmithKline (Employee) Mindy Magee, Doctor of Pharmacy, GlaxoSmithKline (Employee, Shareholder) Peter D. Gorycki, BEChe, MSc, PhD, GSK (Employee, Shareholder) Katy P. Moore, PharmD, RPh, ViiV Healthcare (Employee)

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