Multiparametric magnetic resonance imaging to characterize cabotegravir long-acting formulation depot kinetics in healthy adult volunteers.

AIM: Cabotegravir long-acting (LA) intramuscular (IM) injection is being investigated for HIV preexposure prophylaxis due to its potent antiretroviral activity and infrequent dosing requirement. A subset of healthy adult volunteers participating in a Phase I study assessing cabotegravir tissue pharmacokinetics underwent serial magnetic resonance imaging (MRI) to assess drug depot localization and kinetics following a single cabotegravir LA IM targeted injection. METHODS: Eight participants (four men, four women) were administered cabotegravir LA 600 mg under ultrasonographic-guided injection targeting the gluteal muscles. MRI was performed to determine injection-site location in gluteal muscle (IM), subcutaneous (SC) adipose tissue and combined IM/SC compartments, and to quantify drug depot characteristics, including volume and surface area, on Days 1 (≤2 hours postinjection), 3 and 8. Linear regression analysis examined correlations between MRI-derived parameters and plasma cabotegravir exposure metrics, including maximum observed concentration (Cmax ) and partial area under the concentration-time curve (AUC) through Weeks 4 and 8. RESULTS: Cabotegravir LA depot locations varied by participant and were identified in the IM compartment (n = 2), combined IM/SC compartments (n = 4), SC compartment (n = 1) and retroperitoneal cavity (n = 1). Although several MRI parameter and exposure metric correlations were determined, total depot surface area on Day 1 strongly correlated with plasma cabotegravir concentration at Days 3 and 8, Cmax and partial AUC through Weeks 4 and 8. CONCLUSION: MRI clearly delineated cabotegravir LA injection-site location and depot kinetics in healthy adults. Although injection-site variability was observed, drug depot surface area correlated with both plasma Cmax and partial AUC independently of anatomical distribution.

Current practices for QSP model assessment: an IQ consortium survey.

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.

In Vitro and in Silico Tools To Assess Extent of Cellular Uptake and Lysosomal Sequestration of Respiratory Drugs in Human Alveolar Macrophages.

Accumulation of respiratory drugs in human alveolar macrophages (AMs) has not been extensively studied in vitro and in silico despite its potential impact on therapeutic efficacy and/or occurrence of phospholipidosis. The current study aims to characterize the accumulation and subcellular distribution of drugs with respiratory indication in human AMs and to develop an in silico mechanistic AM model to predict lysosomal accumulation of investigated drugs. The data set included 9 drugs previously investigated in rat AM cell line NR8383. Cell-to-unbound medium concentration ratio (Kp,cell) of all drugs (5 µM) was determined to assess the magnitude of intracellular accumulation. The extent of lysosomal sequestration in freshly isolated human AMs from multiple donors (n = 5) was investigated for clarithromycin and imipramine (positive control) using an indirect in vitro method (±20 mM ammonium chloride, NH4Cl). The AM cell parameters and drug physicochemical data were collated to develop an in silico mechanistic AM model. Three in silico models differing in their description of drug membrane partitioning were evaluated; model (1) relied on octanol-water partitioning of drugs, model (2) used in vitro data to account for this process, and model (3) predicted membrane partitioning by incorporating AM phospholipid fractions. In vitro Kp,cell ranged >200-fold for respiratory drugs, with the highest accumulation seen for clarithromycin. A good agreement in Kp,cell was observed between human AMs and NR8383 (2.45-fold bias), highlighting NR8383 as a potentially useful in vitro surrogate tool to characterize drug accumulation in AMs. The mean Kp,cell of clarithromycin (81, CV = 51%) and imipramine (963, CV = 54%) were reduced in the presence of NH4Cl by up to 67% and 81%, respectively, suggesting substantial contribution of lysosomal sequestration and intracellular binding in the accumulation of these drugs in human AMs. The in vitro data showed variability in drug accumulation between individual human AM donors due to possible differences in lysosomal abundance, volume, and phospholipid content, which may have important clinical implications. Consideration of drug-acidic phospholipid interactions significantly improved the performance of the in silico models; use of in vitro Kp,cell obtained in the presence of NH4Cl as a surrogate for membrane partitioning (model (2)) captured the variability in clarithromycin and imipramine Kp,cell observed in vitro and showed the best ability to predict correctly positive and negative lysosomotropic properties. The developed mechanistic AM model represents a useful in silico tool to predict lysosomal and cellular drug concentrations based on drug physicochemical data and system specific properties, with potential application to other cell types.

Quantitative systems toxicology modeling in pharmaceutical research and development: An industry-wide survey and selected case study examples.

Quantitative systems toxicology (QST) models are increasingly being applied for predicting and understanding toxicity liabilities in pharmaceutical research and development. A European Federation of Pharmaceutical Industries and Associations (EFPIA)-wide survey was completed by 15 companies. The results provide insights into the current use of QST models across the industry. 73% of responding companies with more than 10,000 employees utilize QST models. The most applied QST models are for liver, cardiac electrophysiology, and bone marrow/hematology. Responders indicated particular interest in QST models for the central nervous system (CNS), kidney, lung, and skin. QST models are used to support decisions in both preclinical and clinical stages of pharmaceutical development. The survey suggests high demand for QST models and resource limitations were indicated as a common obstacle to broader use and impact. Increased investment in QST resources and training may accelerate application and impact. Case studies of QST model use in decision-making within EFPIA companies are also discussed. This article aims to (i) share industry experience and learnings from applying QST models to inform decision-making in drug discovery and development programs, and (ii) share approaches taken during QST model development and validation and compare these with recommendations for modeling best practices and frameworks proposed in the literature. Discussion of QST-specific applications in relation to these modeling frameworks is relevant in the context of the recently proposed International Council for Harmonization (ICH) M15 guideline on general principles for Model-Informed Drug Development (MIDD).

Mathematical Modeling of Complement Pathway Dynamics for Target Validation and Selection of Drug Modalities for Complement Therapies.

Motivation: The complement pathway plays a critical role in innate immune defense against infections. Dysregulation between activation and regulation of the complement pathway is widely known to contribute to several diseases. Nevertheless, very few drugs that target complement proteins have made it to the final regulatory approval because of factors such as high concentrations and dosing requirements for complement proteins and serious side effects from complement inhibition. Methods: A quantitative systems pharmacology (QSP) model of the complement pathway has been developed to evaluate potential drug targets to inhibit complement activation in autoimmune diseases. The model describes complement activation via the alternative and terminal pathways as well as the dynamics of several regulatory proteins. The QSP model has been used to evaluate the effect of inhibiting complement targets on reducing pathway activation caused by deficiency in factor H and CD59. The model also informed the feasibility of developing small-molecule or large-molecule antibody drugs by predicting the drug dosing and affinity requirements for potential complement targets. Results: Inhibition of several complement proteins was predicted to lead to a significant reduction in complement activation and cell lysis. The complement proteins that are present in very high concentrations or have high turnover rates (C3, factor B, factor D, and C6) were predicted to be challenging to engage with feasible doses of large-molecule antibody compounds (≤20 mg/kg). Alternatively, complement fragments that have a short half-life (C3b, C3bB, and C3bBb) were predicted to be challenging or infeasible to engage with small-molecule compounds because of high drug affinity requirements (>1 nM) for the inhibition of downstream processes. The drug affinity requirements for disease severity reduction were predicted to differ more than one to two orders of magnitude than affinities needed for the conventional 90% target engagement (TE) for several proteins. Thus, the QSP model analyses indicate the importance for accounting for TE requirements for achieving reduction in disease severity endpoints during the lead optimization stage.

FDA-Industry Scientific Exchange on assessing quantitative systems pharmacology models in clinical drug development: a meeting report, summary of challenges/gaps, and future perspective.

The pharmaceutical industry is actively applying quantitative systems pharmacology (QSP) to make internal decisions and guide drug development. To facilitate the eventual development of a common framework for assessing the credibility of QSP models for clinical drug development, scientists from US Food and Drug Administration and the pharmaceutical industry organized a full-day virtual Scientific Exchange on July 1, 2020. An assessment form was used to ensure consistency in the evaluation process. Among the cases presented, QSP was applied to various therapeutic areas. Applications mostly focused on phase 2 dose selection. Model transparency, including details on expert knowledge and data used for model development, was identified as a major factor for robust model assessment. The case studies demonstrated some commonalities in the workflow of QSP model development, calibration, and validation but differ in the size, scope, and complexity of QSP models, in the acceptance criteria for model calibration and validation, and in the algorithms/approaches used for creating virtual patient populations. Though efforts are being made to build the credibility of QSP models and the confidence is increasing in applying QSP for internal decisions at the clinical stages of drug development, there are still many challenges facing QSP application to late stage drug development. The QSP community needs a strategic plan that includes the ability and flexibility to Adapt, to establish Common expectations for model Credibility needed to inform drug Labeling and patient care, and to AIM to achieve the goal (ACCLAIM).

Multimodal imaging approach to examine biodistribution kinetics of Cabotegravir (GSK1265744) long acting parenteral formulation in rat.

Long-Acting Parenterals (LAPs) have been used in the clinic to provide sustained therapeutic drug levels at a target site, and thereby reducing the frequency of dosing required. In an effort to understand the factors associated with long-acting cabotegravir (GSK1265744 LAP) pharmacokinetic variability, the current study was designed to investigate the temporal relationship between intramuscular (IM) or subcutaneous (SC) drug depot morphology and distribution kinetics with plasma pharmacokinetics. Therefore, a multi-modal molecular imaging (MRI & MALDI IMS) approach was employed to examine the temporal GSK1265744 LAP biodistribution in rat following either IM or SC administration. Serial MRI was performed immediately post drug administration, and then at day 1 (24h post), 2, 3, 4, 7, and 14. In a separate cohort of rats, an MRI contrast agent, Feraheme® (USPIO), was administered 2days post IM drug injection in order to investigate the potential involvement of macrophages trafficking to the GSK1265744 LAP and Vehicle depot sites. The GSK1265744 LAP depot volume increased rapidly by day 2 in the IM injected rats (~3-7 fold) compared with a ~1 fold increase in the SC injected rats. In addition, the USPIO contrast agent labeled macrophages were shown to be present in the depot region of the GSK1265744 LAP injected gastrocnemius while the Vehicle injected gastrocnemius appeared to show reduced uptake. Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) of muscle and abdominal tissue sections identified the drug content primarily within the depot. Co-registration of the GSK1265744 ion images with immunohistochemical images established that the drug was taken up by macrophages associated with the depot. Linear regression analysis demonstrated that the drug depot characteristics including volume, surface area, and perimeter assessed by MRI at day 2 correlated with early time point plasma drug concentrations. In summary, a multimodal molecular imaging approach was used to identify the drug depot location and volumetric/physiologic changes in both IM and SC locations following GSK1265744 LAP administration. The IM depot volume increased rapidly to a maximum volume at 2days post-GSK1265744 LAP administration, while the Vehicle depot did not suggesting that the active drug substance and/or related particle was a key driver for drug depot evolution. The depot expansion was associated with an increase in macrophage infiltration and edema in and around the depot region and was correlated to plasma drug concentration at early time points (0-4days). Consequently, molecular imaging approaches may be used in patients to help understand the biodistribution of GSK1265744 LAP and its associated pharmacokinetics.