Virtual thorough QT (TQT) trial-extrapolation of "In Vitro" cardiac safety data to "In Vivo" situation using multi-scale physiologically based ventricular cell-wall model exemplified with tolterodine and fesoterodine

QT interval prolongation typically assessed with dedicated clinical trials called thorough QT/QTc (TQT) studies is used as surrogate to identify the proarrhythmic risk of drugs albeit with criticism in terms of cost-effectiveness in establishing the actual risk of torsade de pointes (TdP). Quantitative systems toxicology and safety (QSTS) models have potential to quantitatively translate the in vitro cardiac safety data to clinical level including simulation of TQT trials. Virtual TQT simulations have been exemplified with use of two related drugs tolterodine and fesoterodine. The impact of bio-relevant concentration in plasma versus estimated heart tissue exposure on predictions was also assessed. Tolterodine and its therapeutically equipotent metabolite formed via CYP2D6 pathway, 5-HMT, inhibit multiple cardiac ion currents (IKr, INa, ICaL). The QSTS model was able to accurately simulate the QT prolongation at therapeutic and supra-therapeutic dose levels of tolterodine well within 95% confidence interval limits of observed data. The model was able to predict the QT prolongation difference between CYP2D6 extensive and poor metaboliser subject groups at both dose levels thus confirming the ability of the model to account for electrophysiologically active metabolite. The QSTS model was able to simulate the negligible QT prolongation observed with fesoterodine establishing that the 5-HMT does not prolong QT interval even though it is a blocker of hERG channel. With examples of TOL and FESO, we demonstrated the utility of the QSTS approaches to simulate virtual TQT trials, which in turn could complement and reduce the clinical studies or help optimise clinical trial designs

Real patient and its virtual twin : application of quantitative systems toxicology modelling in the cardiac safety assessment of citalopram

Abstract. A quantitative systems toxicology (QST) model for citalopram was established to simulate, in silico, a ‘virtual twin’ of a real patient to predict the occurrence of cardiotoxic events previously reported in patients under various clinical conditions. The QST model considers the effects of citalopram and its most notable electrophysiologically active primary (desmethylcitalopram) and secondary (didesmethylcitalopram) metabolites, on cardiac electrophysiology. The in vitro cardiac ion channel current inhibition data was coupled with the biophysically detailed model of human cardiac electrophysiology to investigate the impact of (i) the inhibition of multiple ion currents (IKr, IKs, ICaL); (ii) the inclusion of metabolites in the QST model; and (iii) unbound or total plasma as the operating drug concentration, in predicting clinically observed QT prolongation. The inclusion of multiple ion channel current inhibition and metabolites in the simulation with unbound plasma citalopram concentration provided the lowest prediction error. The predictive performance of the model was verified with three additional therapeutic and supra-therapeutic drug exposure clinical cases. The results indicate that considering only the hERG ion channel inhibition of only the parent drug is potentially misleading, and the inclusion of active metabolite data and the influence of other ion channel currents should be considered to improve the prediction of potential cardiac toxicity. Mechanistic modelling can help bridge the gaps existing in the quantitative translation from preclinical cardiac safety assessment to clinical toxicology. Moreover, this study shows that the QST models, in combination with appropriate drug and systems parameters, can pave the way towards personalised safety assessment

Quantitative approach for cardiac risk assessment and interpretation in tuberculosis drug development

Cardiotoxicity is among the top drug safety concerns, and is of specific interest in tuberculosis, where this is a known or potential adverse event of current and emerging treatment regimens. As there is a need for a tool, beyond the QT interval, to quantify cardiotoxicity early in drug development, an empirical decision tree based classifier was developed to predict the risk of Torsades de pointes (TdP). The cardiac risk algorithm was developed using pseudo-electrocardiogram (ECG) outputs derived from cardiac myocyte electromechanical model simulations of increasing concentrations of 96 reference compounds which represented a range of clinical TdP risk. The algorithm correctly classified 89% of reference compounds with moderate sensitivity and high specificity (71 and 96%, respectively) as well as 10 out of 12 external validation compounds and the anti-TB drugs moxifloxacin and bedaquiline. The cardiac risk algorithm is suitable to help inform early drug development decisions in TB and will evolve with the addition of emerging data

Virtual bioequivalence for achlorhydric subjects: The use of PBPK modelling to assess the formulation-dependent effect of achlorhydria

Majority of bioequivalence studies are conducted in healthy volunteers. It has been argued that bioequivalence may not necessarily hold true in relevant patient populations due to a variety of reasons which affect one formulation more than the other for instance in achlorhydric patients where elevated gastric pH may lead to differential effects on formulations which are pH-sensitive with respect to release or dissolution. We therefore examined achlorhydria-related disparity in bioequivalence of levothyroxine and nifedipine formulations using virtual bioequivalence within a physiologically-based pharmacokinetic (PBPK) modelling framework. The in vitro dissolution profiles at neutral pH were incorporated into PBPK models to mimic the achlorhydria with in vitro–in vivo relationship established using bio-relevant pH media. The PBPK models successfully reproduced the outcome of the bioequivalence studies in healthy volunteers under the normal conditions as well as under proton pump inhibitor-induced achlorhydria. The geometric mean test/reference ratios for Cmax and AUC between levothyroxine tablet and capsule in patients receiving proton pump inhibitor were 1.21 (90%CI, 1.13–1.29) and 1.09 (90%CI, 1.02–1.17), respectively. Extension of the virtual bioequivalence study to Japanese elderly, who show high incidence of achlorhydria, indicated bio-inequivalence which Cmax and AUC ratios between nifedipine control-released reference and test formulations were 3.08 (90%CI, 2.81–3.38) and 1.57 (90%CI, 1.43–1.74), respectively. Virtual bioequivalence studies through the PBPK models can highlight the need for conduct of specific studies in elderly Japanese populations where there are discrepancies in pH-sensitivity of dissolution between the test and reference formulations

Swiadomośc ekologiczna a wybory konsumentow.

Celem badań jest przedstawienie istoty wyborów konsumenckich w zakresie produktów ekologicznych, a także określenie poziomu świadomości ekologicznej i jej wpływu na decyzje zakupowe konsumentów, na przykładzie studentów Uniwersytetu Jagiellońskiego. Istniejąca literatura sugeruje, że istnieje korelacja pomiędzy polityką rządu i popytem na produkty ekologiczne jednak w Polsce istnieje luka badawcza w tym zakresie. Obecne badanie zmierza do wypełnienia tej luki. Grupą docelową badania byli studenci Uniwersytetu Jagiellońskiego, a próba zbadana wyniosła 381 studentów. Odpowiedzi zostały zebrane przy użyciu kwestionariusza, który badał zmienne adaptowane do obecnego badania na podstawie przeglądu literatury. Dane zanalizowano za pomocą oprogramowania SmartPLS, z wykorzystaniem metody równań strukturalnych. Wyniki badań wskazują, że troska o środowisko, świadomość ekologiczna, wygląd produktu, cena, marka oraz wizerunek marki są kluczowymi czynnikami wpływającymi na wybory konsumentów. Ponadto, wyniki potwierdzają, rolę polityki rządu, jak ważnego moderatora w tej relacji. Rezultaty badań są również przydatne dla praktyków, wskazując czynniki istotne w marketingu produktów i usług.The aim of this thesis is to present the essence of consumer choices in the area of green products, and to identify the level of green awareness as well as its impact on purchasing decisions by student consumers, based on the example of the Jagiellonian University students. Previous literature suggests that there is a significant relationship between government policy and the purchase of green products, but there is a research gap in this area in Poland. In order to fill this gap, the present study empirically explores the influence of green awareness factors on consumer choices, and it explains the moderating role of government policies. The target population comprises the students of the Jagiellonian University, with a final sample of 381 students, based the convenience sampling method. The responses were collected through a self-administered questionnaire regarding variables, which were obtained and modified based on the prior research studies.The obtained data was analyzed through SmartPLS and with the use of structural equation modeling. The findings reveal that environmental concern, awareness of green product features, price, and brand image are the key factors influencing consumer choices. The results also empirically support that the role that government policies play as moderator of the relationship between two types of awareness and student's intention to buy. The results are useful for practitioners to guide them about the factors which company should consider marketing its products or services

Age and gender dependent heart rate circadian model development and performance verification on the proarrhythmic drug case study

BACKGROUND: There are two main reasons for drug withdrawals at the various levels of the development path – hepatic and cardiac toxicity. The latter one is mainly connected with the proarrhythmic potency and according to the present practice is supposed to be recognized at the pre-clinical (in vitro and animal in vivo) or clinical level (human in vivo studies). There are, although, some limitations to all the above mentioned methods which have led to novel in vitro – in vivo extrapolation methods being introduced. With the use of in silico implemented mathematical and statistical modelling it is possible to translate the in vitro findings into the human in vivo situation at the population level. Human physiology is influenced by many parameters and one of them which needs to be properly accounted for is a heart rate which follows the circadian rhythm. We described such phenomenon statistically which enabled the improved assessment of the drug proarrhythmic potency. METHODS: A publicly available data set describing the circadian changes of the heart rate of 18 healthy subjects, 5 males (average age 36, range 26–45) and 13 females (average age 34, range 20–50) was used for the heart rate model development. External validation was done with the use of a clinical research database containing heart rate measurements derived from 67 healthy subjects, 34 males and 33 females (average age 33, range 17–72). The developed heart rate model was then incorporated into the ToxComp platform to simulate the impact of circadian variation in the heart rate on QTc interval. The usability of the combined models was assessed with moxifloxacin (MOXI) as a model drug. RESULTS: The developed heart rate model fitted well, both to the training data set (RMSE = 128 ms and MAPE = 12.3%) and the validation data set (RMSE = 165 ms and MAPE = 17.1%). Simulations performed at the population level proved that the combination of the IVIVE platform and the population variability description allows for the precise prediction of the circadian variation of drugs proarrhythmic effect. CONCLUSIONS: It can be concluded that a flexible and practically useful model describing the heart rate circadian variation has been developed and its performance was verified