An integrative pharmacokinetic-cardiovascular physiology modelling approach based on in vivo dog studies including five reference compounds.

Cardiovascular (CV) effects represent a major safety issue during drug development. Typically, this risk is mitigated by preclinical in vivo CV studies, based on which measured CV readouts are analyzed independently. Here, we apply a regression approach to simultaneously integrate CV readouts, i.e., heart rate (HR), mean arterial pressure (MAP) and QT from five dog telemetry studies. These CV studies comprise data on verapamil, captopril, dofetilide, pimobendan, and formoterol, and are combined with the respective dog pharmacokinetic (PK) profiles. A published PK/CV model structure for rats is extended by a semi-mechanistic parameterization of the interaction between HR and QT specific to dogs. This semi-mechanistic modelling approach allows differentiation between compound-independent system-specific parameters (e.g., HR baseline) and compound-specific parameters (e.g., EC50). Compared to previous results in rodents, estimated parameters for dogs indicate stronger dependency of stroke volume on HR, slower HR response, faster QT response and steeper concentration-response relationships. In addition, we illustrate how to practically apply the PK/CV model to derive concentration-response relationships for CV readouts. This approach allows a more detailed quantitative evaluation based on the maximum effect on CV effects (Emax), the EC50, and the steepness of this relation (Hill coefficient) especially for HR-independent effects on QT interval duration (QTc) while taking the systemic feedback into account. This approach also allows to derive plasma concentrations associated with relevant CV effects ("threshold concentration"; CTHRESH). The presented modelling analysis highlights the potential of an integrative evaluation of CV data and provides a framework for obtaining quantitative insights from safety pharmacology evaluations.

An Integrative Approach for Improved Assessment of Cardiovascular Safety Data.

Cardiovascular adverse effects in drug development are a major source of compound attrition. Characterization of blood pressure (BP), heart rate (HR), stroke volume (SV), and QT-interval prolongation are therefore necessary in early discovery. It is, however, common practice to analyze these effects independently of each other. High-resolution time courses are collected via telemetric techniques, but only low-resolution data are analyzed and reported. This ignores codependencies among responses (HR, BP, SV, and QT-interval) and separation of system (turnover properties) and drug-specific properties (potencies, efficacies). An analysis of drug exposure-time and high-resolution response-time data of HR and mean arterial blood pressure was performed after acute oral dosing of ivabradine, sildenafil, dofetilide, and pimobendan in Han-Wistar rats. All data were modeled jointly, including different compounds and exposure and response time courses, using a nonlinear mixed-effects approach. Estimated fractional turnover rates [h-1, relative standard error (%RSE) within parentheses] were 9.45 (15), 30.7 (7.8), 3.8 (13), and 0.115 (1.7) for QT, HR, total peripheral resistance, and SV, respectively. Potencies (nM, %RSE within parentheses) were IC 50 = 475 (11), IC 50 = 4.01 (5.4), EC 50 = 50.6 (93), and IC 50 = 47.8 (16), and efficacies (%RSE within parentheses) were I max = 0.944 (1.7), Imax = 1.00 (1.3), E max = 0.195 (9.9), and Imax = 0.745 (4.6) for ivabradine, sildenafil, dofetilide, and pimobendan. Hill parameters were estimated with good precision and below unity, indicating a shallow concentration-response relationship. An equilibrium concentration-biomarker response relationship was predicted and displayed graphically. This analysis demonstrates the utility of a model-based approach integrating data from different studies and compounds for refined preclinical safety margin assessment. SIGNIFICANCE STATEMENT: A model-based approach was proposed utilizing biomarker data on heart rate, blood pressure, and QT-interval. A pharmacodynamic model was developed to improve assessment of high-resolution telemetric cardiovascular safety data driven by different drugs (ivabradine, sildenafil, dofetilide, and pimobondan), wherein system- (turnover rates) and drug-specific parameters (e.g., potencies and efficacies) were sought. The model-predicted equilibrium concentration-biomarker response relationships and was used for safety assessment (predictions of 20% effective concentration, for example) of heart rate, blood pressure, and QT-interval.

Opposing effects of in vitro differentiated macrophages sub-type on epithelial wound healing.

Inappropriate repair responses to pulmonary epithelial injury have been linked to perturbation of epithelial barrier function and airway remodelling in a number of respiratory diseases, including chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. We developed an in vitro mechanical scratch injury model in air-liquid interface differentiated primary human small airway epithelial cells that recapitulates many of the characteristics observed during epithelial wound injury in both human tissue and small animal models. Wound closure was initially associated with de-differentiation of the differentiated apical cells and rapid migration into the wound site, followed by proliferation of apical cells behind the wound edge, together with increases in FAK expression, fibronectin and reduction in PAI-1 which collectively facilitate cell motility and extracellular matrix deposition. Macrophages are intimately involved in wound repair so we sought to investigate the role of macrophage sub-types on this process in a novel primary human co-culture model. M1 macrophages promoted FAK expression and both M1 and M2 macrophages promoted epithelial de-differentiation. Interestingly, M2a macrophages inhibited both proliferation and fibronectin expression, possibly via the retinoic acid pathway, whereas M2b and M2c macrophages prevented fibronectin deposition, possibly via MMP expression. Collectively these data highlight the complex nature of epithelial wound closure, the differential impact of macrophage sub-types on this process, and the heterogenic and non-delineated function of these macrophages.