This work provides a perspective on the qualification and verification of physiologically based pharmacokinetic (PBPK) platforms/models intended for regulatory submission based on the collective experience of the Simcyp Consortium members. Examples of regulatory submission of PBPK analyses across various intended applications are presented and discussed. European Medicines Agency (EMA) and US Food and Drug Administration (FDA) recent draft guidelines regarding PBPK analyses and reporting are encouraging, and to advance the use and acceptability of PBPK analyses, more clarity and flexibility are warranted.
Despite the success of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines, there remains a need for more prevention and treatment options for individuals remaining at risk of coronavirus disease 2019 (COVID-19). Monoclonal antibodies (mAbs) against the viral spike protein have potential to both prevent and treat COVID-19, and reduce the risk of severe disease and death. Here, we describe AZD7442, a combination of two mAbs, AZD8895 (tixagevimab) and AZD1061 (cilgavimab), that simultaneously bind to distinct, nonoverlapping epitopes on the spike protein receptor binding domain to neutralize SARS-CoV-2. Initially isolated from individuals with prior SARS-CoV-2 infection, the two mAbs were designed to extend their half-lives and reduce effector functions. The AZD7442 mAbs individually prevent the spike protein from binding to angiotensin-converting enzyme 2 receptor, blocking virus cell entry, and neutralize all tested SARS-CoV-2 variants of concern. In a nonhuman primate model of SARS-CoV-2 infection, prophylactic AZD7442 administration prevented infection, whereas therapeutic administration accelerated virus clearance from lung. In an ongoing phase 1 study in healthy participants (NCT04507256), a 300 mg intramuscular injection of AZD7442 provided SARS-CoV-2 serum geometric mean neutralizing titers greater than 10-fold above those of convalescent serum for at least 3 months, which remained 3-fold above those of convalescent serum at 9 months post-AZD7442 administration. Approximately 1 to 2% of serum AZD7442 was detected in nasal mucosa, a site of SARS-CoV-2 infection. Extrapolation of the time course of serum AZD7442 concentration suggests AZD7442 may provide up to 12 months of protection and benefit individuals at high-risk of COVID-19.
Reactive oxygen species are recognized as important mediators of biological responses. Hyperglycemia promotes the intracellular generation of superoxide anion and hydrogen peroxide. In several cell lines, oxidant stress has been linked to the activation of death programs. Here, we report for the first time that high ambient glucose concentration induces apoptosis in murine and human mesangial cells by an oxidant-dependent mechanism. The signaling cascade activated by glucose-induced oxidant stress included the heterodimeric redox-sensitive transcription factor NF-kappaB, which exhibited an upregulation in p65/c-Rel binding activity and suppressed binding activity of the p50 dimer. Recruitment of NF-kappaB and mesangial cell apoptosis were both inhibited by antioxidants, implicating oxidant-induced activation of NF-kappaB in the transmission of the death signal. The genetic program for glucose-induced mesangial cell apoptosis was characterized by an upregulation of the Bax/Bcl-2 ratio. In addition, phosphorylation of the proapoptotic protein Bad was attenuated in mesangial cells maintained at high-glucose concentration, favoring progression of the apoptotic process. These perturbations in the expression and phosphorylation of the Bcl-2 family were coupled with the release of cytochrome c from mitochondria and caspase activation. Our findings indicate that in mesangial cells exposed to high ambient glucose concentration, oxidant stress is a proximate event in the activation of the death program, which culminates in mitochondrial dysfunction and caspase-3 activation, as the terminal event.
Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling. ) † Venkatesh Pilla Reddy and Kunal S. Taskar equally contributed to this article and are joint first authors.
REVIEW(1)) CL H,int = (PS inf ,act + PS inf,pas ) * (CL int,met + CL int,sec ) PS ef f,act + PS ef f,pas + CL int,met + CL int,sec (3) CL H,int = PS inf * REVIEW
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