Physiologically based pharmacokinetics modeling and transporter proteomics to predict systemic and local liver and muscle disposition of statins.

Statins are used to reduce liver cholesterol levels but also carry a dose-related risk of skeletal muscle toxicity. Concentrations of statins in plasma are often used to assess efficacy and safety, but because statins are substrates of membrane transporters that are present in diverse tissues, local differences in intracellular tissue concentrations cannot be ruled out. Thus, plasma concentration may not be an adequate indicator of efficacy and toxicity. To bridge this gap, we used physiologically based pharmacokinetic (PBPK) modeling to predict intracellular concentrations of statins. Quantitative data on transporter clearance were scaled from in vitro to in vivo conditions by integrating targeted proteomics and transporter kinetics data. The developed PBPK models, informed by proteomics, suggested that organic anion-transporting polypeptide 2B1 (OATP2B1) and multidrug resistance-associated protein 1 (MRP1) play a pivotal role in the distribution of statins in muscle. Using these PBPK models, we were able to predict the impact of alterations in transporter function due to genotype or drug-drug interactions on statin systemic concentrations and exposure in liver and muscle. These results underscore the potential of proteomics-guided PBPK modeling to scale transporter clearance from in vitro data to real-world implications. It is important to evaluate the role of drug transporters when predicting tissue exposure associated with on- and off-target effects.

Discovery of Clinical Candidate AZD5462, a Selective Oral Allosteric RXFP1 Agonist for Treatment of Heart Failure.

Optimization of the highly potent and selective, yet metabolically unstable and poorly soluble hRXFP1 agonist AZ7976 led to the identification of the clinical candidate, AZD5462. Assessment of RXFP1-dependent cell signaling demonstrated that AZD5462 activates a highly similar panel of downstream pathways as relaxin H2 but does not modulate relaxin H2-mediated cAMP second messenger responsiveness. The therapeutic potential of AZD5462 was assessed in a translatable cynomolgus monkey heart failure model. Following 8 weeks of treatment with AZD5462, robust improvements in functional cardiac parameters including LVEF were observed at weeks 9, 13, and 17 without changes in heart rate or mean arterial blood pressure. AZD5462 was well tolerated in both rat and cynomolgus monkey and has successfully completed phase I studies in healthy volunteers. In summary, AZD5462 is a small molecule pharmacological mimetic of relaxin H2 signaling at RXFP1 and holds promise as a potential therapeutic approach to treat heart failure patients.

Understanding Statin-Roxadustat Drug-Drug-Disease Interaction Using Physiologically-Based Pharmacokinetic Modeling.

A different drug-drug interaction (DDI) scenario may exist in patients with chronic kidney disease (CKD) compared with healthy volunteers (HVs), depending on the interplay between drug-drug and disease (drug-drug-disease interaction (DDDI)). Physiologically-based pharmacokinetic (PBPK) modeling, in lieu of a clinical trial, is a promising tool for evaluating these complex DDDIs in patients. However, the prediction confidence of PBPK modeling in the severe CKD population is still low when nonrenal pathways are involved. More mechanistic virtual disease population and robust validation cases are needed. To this end, we aimed to: (i) understand the implications of severe CKD on statins (atorvastatin, simvastatin, and rosuvastatin) pharmacokinetics (PK) and DDI; and (ii) predict untested clinical scenarios of statin-roxadustat DDI risks in patients to guide suitable dose regimens. A novel virtual severe CKD population was developed incorporating the disease effect on both renal and nonrenal pathways. Drug and disease PBPK models underwent a four-way validation. The verified PBPK models successfully predicted the altered PKs in patients for substrates and inhibitors and recovered the observed statin-rifampicin DDIs in patients and the statin-roxadustat DDIs in HVs within 1.25- and 2-fold error. Further sensitivity analysis revealed that the severe CKD effect on statins PK is mainly mediated by hepatic BCRP for rosuvastatin and OATP1B1/3 for atorvastatin. The magnitude of statin-roxadustat DDI in patients with severe CKD was predicted to be similar to that in HVs. PBPK-guided suitable dose regimens were identified to minimize the risk of side effects or therapeutic failure of statins when co-administered with roxadustat.

Does the choice of applied physiologically-based pharmacokinetics platform matter? A case study on simvastatin disposition and drug-drug interaction.

Physiologically-based pharmacokinetic (PBPK) models have an important role in drug discovery/development and decision making in regulatory submissions. This is facilitated by predefined PBPK platforms with user-friendly graphical interface, such as Simcyp and PK-Sim. However, evaluations of platform differences and the potential implications for disposition-related applications are still lacking. The aim of this study was to assess how PBPK model development, input parameters, and model output are affected by the selection of PBPK platform. This is exemplified via the establishment of simvastatin PBPK models (workflow, final models, and output) in PK-Sim and Simcyp as representatives of established whole-body PBPK platforms. The major finding was that the choice of PBPK platform influenced the model development strategy and the final model input parameters, however, the predictive performance of the simvastatin models was still comparable between the platforms. The main differences between the structure and implementation of Simcyp and PK-Sim were found in the absorption and distribution models. Both platforms predicted equally well the observed simvastatin (lactone and acid) pharmacokinetics (20-80 mg), BCRP and OATP1B1 drug-gene interactions (DGIs), and drug-drug interactions (DDIs) when co-administered with CYP3A4 and OATP1B1 inhibitors/inducers. This study illustrates that in-depth knowledge of established PBPK platforms is needed to enable an assessment of the consequences of PBPK platform selection. Specifically, this work provides insights on software differences and potential implications when bridging PBPK knowledge between Simcyp and PK-Sim users. Finally, it provides a simvastatin model implemented in both platforms for risk assessment of metabolism- and transporter-mediated DGIs and DDIs.

Proteomics-Informed Prediction of Rosuvastatin Plasma Profiles in Patients With a Wide Range of Body Weight.

Rosuvastatin is a frequently used probe to study transporter-mediated hepatic uptake. Pharmacokinetic models have therefore been developed to predict transporter impact on rosuvastatin disposition in vivo. However, the interindividual differences in transporter concentrations were not considered in these models, and the predicted transporter impact was compared with historical in vivo data. In this study, we investigated the influence of interindividual transporter concentrations on the hepatic uptake clearance of rosuvastatin in 54 patients covering a wide range of body weight. The 54 patients were given an oral dose of rosuvastatin the day before undergoing gastric bypass or cholecystectomy, and pharmacokinetic (PK) parameters were established from each patient's individual time-concentration profiles. Liver biopsies were sampled from each patient and their individual hepatic transporter concentrations were quantified. We combined the transporter concentrations with in vitro uptake kinetics determined in HEK293-transfected cells, and developed a semimechanistic model with a bottom-up approach to predict the plasma concentration profiles of the single dose of rosuvastatin in each patient. The predicted PK parameters were evaluated against the measured in vivo plasma PKs from the same 54 patients. The developed model predicted the rosuvastatin PKs within two-fold error for rosuvastatin area under the plasma concentration versus time curve (AUC; 78% of the patients; average fold error (AFE): 0.96), peak plasma concentration (Cmax ; 76%; AFE: 1.05), and terminal half-life (t1/2 ; 98%; AFE: 0.89), and captured differences in the rosuvastatin PKs in patients with the OATP1B1 521T

Novel Chemical Series of 5-Lipoxygenase-Activating Protein Inhibitors for Treatment of Coronary Artery Disease.

5-Lipoxygenase (5-LO)-activating protein (FLAP) inhibitors have proven to attenuate 5-LO pathway activity and leukotriene production in human clinical trials. However, previous clinical candidates have been discontinued and the link between FLAP inhibition and outcome in inflammatory diseases remains to be established. We here describe a novel series of FLAP inhibitors identified from a screen of 10k compounds and the medicinal chemistry strategies undertaken to progress this series. Compound 4i showed good overall properties and a pIC50 hWBfree of 8.1 and an lipophilic ligand efficiency of 5.2. Target engagement for 4i was established in dogs using ex vivo measurement of leukotriene B4 (LTB4) levels in blood with good correlation to in vitro potency. A predicted human dose of 280 mg b.i.d. suggests a wide margin to any identified in vitro off-target effects and sufficient exposure to achieve an 80% reduction of LTB4 levels in humans. Compound 4i is progressed to preclinical in vivo safety studies.

Physiologically Based Pharmacokinetic Model of Itraconazole and Two of Its Metabolites to Improve the Predictions and the Mechanistic Understanding of CYP3A4 Drug-Drug Interactions.

Physiologically based pharmacokinetic (PBPK) modeling for itraconazole using a bottom-up approach is challenging, not only due to complex saturable pharmacokinetics (PK) and the presence of three metabolites exhibiting CYP3A4 inhibition, but also because of discrepancies in reported in vitro data. The overall objective of this study is to provide a comprehensive mechanistic PBPK model for itraconazole in order to increase the confidence in its drug-drug interaction (DDI) predictions. To achieve this, key in vitro and in vivo data for itraconazole and its major metabolites were generated. These data were crucial to developing a novel bottom-up PBPK model in Simcyp (Simcyp Ltd., Certara, Sheffield, United Kingdom) for itraconazole and two of its major metabolites: hydroxy-itraconazole (OH-ITZ) and keto-itraconazole (keto-ITZ). Performance of the model was validated using prespecified acceptance criteria against different dosing regimens, formulations for 29 PK, and DDI studies with midazolam and other CYP3A4 substrates. The main outcome is an accurate PBPK model that simultaneously predicts the PK profiles of itraconazole, OH-ITZ, and keto-ITZ. In addition, itraconazole DDIs with midazolam and other CYP3A4 substrates were successfully predicted within a 2-fold error. Prediction precision and bias of DDI expressed as geometric mean fold error were for the area under the concentration-time curve and peak concentration, 1.06 and 0.96, respectively. To conclude, in this paper a comprehensive data set for itraconazole and its metabolites is provided that enables bottom-up mechanism-based PBPK modeling. The presented model is applicable for studying the contribution from the metabolites and allows improved assessments of itraconazole DDI.

Intrinsic Clearance Assay Incubational Binding: A Method Comparison.

The fraction of unbound drug (fuinc) in in vitro intrinsic clearance (CLint) incubation is an important parameter in the pursuit of accurate clearance predictions and is often predicted using algorithms based on drug lipophilicity measures. However, analysis of an AstraZeneca database suggests that simple lipophilicity alone is a relatively poor predictor of fuinc measured using equilibrium dialysis. He fuinc value can also be measured directly in CLint assays using multiple concentrations of hepatocytes or microsomal protein. Since this approach informs of the unbound drug concentration in the assay used to predict in vivo clearance, it should be considered the gold standard method. As a starting point for building better predictive algorithms we aimed to determine if equilibrium dialysis really is an appropriate assay for assessing fuinc Employing a large number of compounds with a wide range of lipophilicities, experiments were performed to measure fuinc using rat hepatocytes (RH) and human liver microsomes (HLM) in both assay formats. A high percentage (94% and 93% for HLM and RH, respectively) of the fuinc values were within 2-fold when the compound distribution coefficient describing the ratio of compound concentration in octanol and pH 7.4 buffer when the test system is at equilibrium (lipophilicity measure) (logD7.4) values were less than 3.5. However, with logD7.4 values greater than these, the agreement was considerably worse. Additional experimental data generated indicated that this discrepancy was likely due to failings in the direct method when drug binding is high. Thus, we conclude that unbound CLint can be indeed calculated indirectly by incorporating equilibrium dialysis data with measured CLint but that simple lipophilicity descriptors alone may be inadequate for predicting fuinc.

The role of ghrelin signalling for sexual behaviour in male mice.

Ghrelin, a gut-brain signal, is well known to regulate energy homeostasis, food intake and appetite foremost via hypothalamic ghrelin receptors (GHS-R1A). In addition, ghrelin activates the reward systems in the brain, namely the mesolimbic dopamine system, and regulates thereby the rewarding properties of addictive drugs as well as of palatable foods. Given that the mesolimbic dopamine system mandates the reinforcing properties of addictive drugs and natural rewards, such as sexual behaviour, we hypothesize that ghrelin plays an important role for male sexual behaviour, a subject for the present studies. Herein we show that ghrelin treatment increases, whereas pharmacological suppression (using the GHSR-1A antagonist JMV2959) or genetic deletion of the GHS-R1A in male mice decreases the sexual motivation for as well as sexual behaviour with female mice in oestrus. Pre-treatment with L-dopa (a dopamine precursor) prior to treatment with JMV2959 significantly increased the preference for female mouse compared with vehicle treatment. On the contrary, treatment with 5-hydroxythyptohan (a precursor for serotonin) prior to treatment with JMV2959 decreased the sexual motivation compared to vehicle. In separate experiments, we show that ghrelin and GHS-R1A antagonism do not affect the time spent over female bedding as measured in the androgen-dependent bedding test. Collectively, these data show that the hunger hormone ghrelin and its receptor are required for normal sexual behaviour in male mice and that the effects of the ghrelin signalling system on sexual behaviour involve dopamine neurotransmission.

Ghrelin and GHS-R1A signaling within the ventral and laterodorsal tegmental area regulate sexual behavior in sexually naïve male mice.

In addition to food intake and energy balance regulation, ghrelin mediate the rewarding and motivational properties of palatable food as well as addictive drugs. The ability of ghrelin to regulate reinforcement involves the cholinergic-dopaminergic reward link, which encompasses a cholinergic projection from the laterodorsal tegmental area (LDTg) to the ventral tegmental area (VTA) together with mesolimbic dopaminergic projections from the VTA to the nucleus accumbens (NAc). Recently, systemic ghrelin was shown to regulate sexual behavior and motivation in male mice via dopamine neurotransmission. The present study therefore elucidates the role of ghrelin and ghrelin receptor (GHS-R1A) antagonist treatment within NAc, VTA or LDTg for sexual behavior in sexually naïve male mice. Local administration of the GHSR-1A antagonist, JMV2959, into the VTA or LDTg was found to reduce the preference for female mice, the number of mounts and the duration of mounting as well as to prolong the latency to mount. This was further substantiated by the findings that ghrelin administration into the VTA or LDTg increased the number of mounts and the duration of mounting and decreased the latency to mount. Moreover, ghrelin administered into the LDTg increased the preference for female mice. Accumbal administration of ghrelin increased whereas GHS-R1A antagonist decreased the intake of palatable food, but did not alter sexual behavior. In males exposed to sexual interaction, systemic administration of ghrelin increases whereas JMV2959 decreases the turnover of dopamine in the VTA. These data suggest that ghrelin signaling within the tegmental areas is required for sexual behavior in sexually naïve male mice.