Objectives: A physiologically based pharmacokinetic (PBPK) model of the lung was integrated with a quantitative systems pharmacology (QSP) model of asthma to predict fractional exhaled nitric oxide (FeNO) response to inhaled JAK inhibitors in patients with mild to moderate asthma. Methods: A PBPK model for inhaled JAK inhibitors was developed describing regional particle deposition within the lung, followed by dissolution in the bronchial lining fluid, and drug permeation into the bronchial tissue, which is the site of action. The PBPK model was integrated with an asthma QSP model, which included FeNO response.[1] JAK inhibition was then implemented as a reduction in cell-specific cytokine signals mediated by JAK isoforms: IL-4/IL-13 for JAK1, and IL-5/TSLP for JAK2. Additionally, a reference virtual patient (VP) and virtual population (Vpop) were developed to represent mild to moderate asthma patients appropriate to inhaled JAK inhibitor clinical trials. Results: The lung PBPK model captures the observed plasma pharmacokinetic profiles for inhaled JAK inhibitors.[2,3] Relevant clinical data for key cytokines and cells at baseline is well represented by the mild to moderate asthma reference VP within the QSP model. Additionally, the mild to moderate asthma Vpop captures clinical variability for FeNO and eosinophil levels, both at baseline and in response to lebrikizumab therapy.[4] Finally, utilizing the integrated PBPK/QSP model, the new Vpop appropriately describes clinical data for FeNO response to the inhaled JAK inhibitors GDC-0214 and GDC-4379.[3,5] Conclusions: The PBPK/QSP model developed for inhaled JAK inhibitors captures relevant clinical data both at baseline and in response to therapy for patients with mild to moderate asthma. The model can thus be utilized to predict FeNO response to novel inhaled JAK inhibitors in this patient population. Applications of the model include informing candidate selection in a preclinical setting, as well as supporting dose selection for proof of concept clinical trials.Citations: [1] Gadkar, K., et al. (2022). Integrated systems modeling of severe asthma: Exploration of IL‐33/ST2 antagonism. CPT: Pharmacomet Syst Pharmacol, 11(9), 1268–1277. [2] Zhu, R., et al. (2022). Phase I and scintigraphy studies to evaluate safety, tolerability, pharmacokinetics, and lung deposition of inhaled GDC‐0214 in healthy volunteers. Clin Transl Sci, 15(5), 1225–1237.[3] Chen, H., et al. (2022). Effects of inhaled JAK inhibitor GDC-4379 on exhaled nitric oxide and peripheral biomarkers of inflammation. Pulm Pharmacol Ther, 75, 102133.[4] Noonan, M., et al. (2013). Dose-ranging study of lebrikizumab in asthmatic patients not receiving inhaled steroids. J Allergy Clin Immunol, 132(3), 567-574.e12.[5] Braithwaite, I. E., et al. (2021). Inhaled JAK inhibitor GDC-0214 reduces exhaled nitric oxide in patients with mild asthma: A randomized, controlled, proof-of-activity trial. J Allergy Clin Immunol, 148(3), 783–789.

BACKGROUND AND OBJECTIVES:Despite significant progress in biomedical research, the rate of success in oncology drug development remains inferior to that of other therapeutic fields. Mechanistic models provide comprehensive understanding of the therapeutic effects of drugs, which is crucial for designing effective clinical trials. This study was performed to acquire a better understanding of PI3K-AKT-TOR pathway modulation and preclinical to clinical translational bridging for a specific compound, apitolisib (PI3K/mTOR inhibitor), by developing integrated mechanistic models. METHODS:Integrated pharmacokinetic (PK)-pharmacodynamic (PD)-efficacy models were developed for xenografts bearing human renal cell adenocarcinoma and for patients with solid tumors (phase 1 studies) to characterize relationships between exposure of apitolisib, modulation of the phosphorylated Akt (pAkt) biomarker triggered by inhibition of the PI3K-AKT-mTOR pathway, and tumor response. RESULTS:Both clinical and preclinical integrated models show a steep sigmoid curve linking pAkt inhibition to tumor growth inhibition and quantified that a minimum of 35-45% pAkt modulation is required for tumor shrinkage in patients, based on platelet-rich plasma surrogate matrix and in xenografts based on tumor tissue matrix. Based on this relationship between targeted pAkt modulation and tumor shrinkage rate, it appeared that a constant pAkt inhibition of 61% and 65%, respectively, would be necessary to achieve tumor stasis in xenografts and patients. CONCLUSIONS:These results help when it comes to evaluating the translatability of the preclinical analysis to the clinical target, and provide information that will enhance the value of future preclinical translational dose-finding and dose-optimization studies to accelerate clinical drug development. TRIAL REGISTRY:ClinicalTrials.gov NCT00854152 and NCT00854126.

Cancer remains a significant global health challenge, and despite remarkable advancements in therapeutic strategies, poor tolerability of drugs (causing dose reduction/interruptions) and/or the emergence of drug resistance are major obstacles to successful treatment outcomes. Metastatic renal cell carcinoma (mRCC) accounts for 2% of global cancer diagnoses and deaths. Despite the initial success of targeted therapies in mRCC, challenges remain to overcome drug resistance that limits the long-term efficacy of these treatments. Our analysis aim was to develop a semi-mechanistic longitudinal exposure-tumor growth inhibition model for patients with mRCC to characterize and compare everolimus (mTORC1) and apitolisib's (dual PI3K/mTORC1/2) ability to inhibit tumor growth, and quantitate each drug's efficacy decay caused by emergence of tumor resistance over time. Model-estimated on-treatment tumor growth rate constant was 1.7-fold higher for apitolisib compared to everolimus. Estimated half-life for loss of treatment effect over time for everolimus was 16.1 weeks compared to 7.72 weeks for apitolisib, suggesting a faster rate of tumor re-growth for apitolisib patients likely due to the emergence of resistance. Goodness-of-fit plots including visual predictive check indicated a good model fit and the model was able to capture individual tumor size-time profiles. Based on our knowledge, this is the first clinical report to quantitatively assess everolimus (mTORC1) and apitolisib (PI3K/mTORC1/2) efficacy decay in patients with mRCC. These results highlight the difference in overall efficacy of 2 drugs due to the quantified efficacy decay caused by emergence of resistance, and emphasize the importance of model-informed drug development for targeted cancer therapy.

Among cases of breast cancer, estrogen receptor-positive (ER +), PIK3CA-mutant, HER2- advanced breast cancer stands as a particularly complex clinical indication where approximately 40

Discontinuation of the Codman 3000 pump in 2018 left no Food and Drug Administration (FDA)-approved hepatic artery infusion (HAI) device for unresectable colorectal liver metastases (uCLM) and intrahepatic cholangiocarcinoma (uIHC). Historically, HAI has been performed at academic medical centers in large metropolitan areas, which are often inaccessible to rural patients. Consequently, feasibility of dissemination of HAI to rural populations is unknown. Under an FDA investigational device exemption, we opened the only HAI program in Kentucky and enrolled patients with uCLM and uIHC in a phase I clinical trial. The trial examined the safety of the hybrid Codman catheter/Medtronic SynchroMed II pump (hCMP) combination, defined as successful completion of one cycle of HAI chemotherapy. Rural feasibility was assessed by number of missed pump fills appointments. A total of 21 patients (n = 17 uCLM, n = 4 uIHC) underwent hCMP implantation before accrual was stopped early owing to FDA approval of the Intera 3000 pump. 20/21 (95

The voltage-gated sodium (Na V ) channel Na V 1.7 has been identified as a potential novel analgesic target due to its involvement in human pain syndromes. However, clinically available Na V channel-blocking drugs are not selective among the nine Na V channel subtypes, Na V 1.1–Na V 1.9. Moreover, the two currently known classes of Na V 1.7 subtype-selective inhibitors (aryl- and acylsulfonamides) have undesirable characteristics that may limit their development. To this point understanding of the structure–activity relationships of the acylsulfonamide class of Na V 1.7 inhibitors, exemplified by the clinical development candidate GDC-0310 , has been based solely on a single co-crystal structure of an arylsulfonamide inhibitor bound to voltage-sensing domain 4 (VSD4). To advance inhibitor design targeting the Na V 1.7 channel, we pursued high-resolution ligand-bound Na V 1.7-VSD4 structures using cryogenic electron microscopy (cryo-EM). Here, we report that GDC-0310 engages the Na V 1.7-VSD4 through an unexpected binding mode orthogonal to the arylsulfonamide inhibitor class binding pose, which identifies a previously unknown ligand binding site in Na V channels. This finding enabled the design of a novel hybrid inhibitor series that bridges the aryl- and acylsulfonamide binding pockets and allows for the generation of molecules with substantially differentiated structures and properties. Overall, our study highlights the power of cryo-EM methods to pursue challenging drug targets using iterative and high-resolution structure-guided inhibitor design. This work also underscores an important role of the membrane bilayer in the optimization of selective Na V channel modulators targeting VSD4.

Inhibition of NF-κB inducing kinase (NIK) has been pursued as a promising therapeutic target for autoimmune disorders due to its highly regulated role in key steps of the NF-κB signaling pathway. Previously reported NIK inhibitors from our group were shown to be potent, selective, and efficacious, but had higher human dose projections than desirable for immunology indications. Herein we report the clearance-driven optimization of a NIK inhibitor guided by metabolite identification studies and structure-based drug design. This led to the identification of an azabicyclo[3.1.0]hexanone motif that attenuated in vitro and in vivo clearance while maintaining NIK potency and increasing selectivity over other kinases, resulting in a greater than ten-fold reduction in predicted human dose.

Determination of drug binding kinetics in plasma is important yet extremely challenging. Accordingly, we introduce "dynamic free fraction" as a new binding parameter describing drug-protein binding kinetics. We demonstrate theoretically and experimentally that the dynamic free fraction can be determined by coupling the drug binding assay with a reporter enzyme in combination with high-resolution mass spectrometry measuring the relative initial steady-state rates of enzymatic reactions in the absence and presence of matrix proteins. This novel and simple methodology circumvents a long-standing challenge inherent in existing methods for determining binding kinetics constants, such as kon and koff, and enables assessment of the impact of protein binding kinetics on pharmaceutical properties of drugs. As demonstrated with nine model drugs, the predicted liver extraction ratio, a measure of efficiency of drug removal by the liver, correlates significantly better to the observed extraction ratio when using the dynamic free fraction (fD) in place of the unbound fraction (fu) of the drug in plasma. Similarly, the in vivo hepatic clearance of these drugs, a measure of liver drug elimination, is highly comparable to the clearance values calculated with the dynamic free fraction (fD), which is markedly better than those calculated with the unbound fraction (fu). In contrast to the prevailing view, these results indicate that protein binding kinetics is an important pharmacokinetic property of a drug. As plasma protein binding is one of the most important drug properties, this new methodology may represent a breakthrough and could have a real impact on the field.

Vision impairment resulting from chronic eye diseases, such as macular degeneration and glaucoma, severely impacts patients' quality of life and poses an immense global financial burden. Current standard of care for such diseases includes daily eye drops or frequent intravitreal (ITV) injections, which are burdensome treatment modalities resulting in low patient compliance. There remains a growing need for easily administered long-acting delivery technologies for prolonging exposure of ocular therapeutics with each administration. Here, this work deploys a supramolecular polymer-nanoparticle (PNP) hydrogel for ITV delivery of the glaucoma drug bimatoprost. PNP hydrogels are shear-thinning and self-healing, key properties for injectability, and enable slow release of molecular cargo in vitreous humor (VH) mimics. An in vivo study in New Zealand white rabbits demonstrated intravitreally injected PNP hydrogels form depots that degrade slowly over time, maintaining detectable levels of bimatoprost in the VH up to 8 weeks following injection. Ophthalmic examinations and histopathology identified a mild foreign body response (FBR) to the hydrogel, characterized by rare clusters of foamy macrophages and giant cells associated with minimal, patchy fibroplasia. This work shows that PNP hydrogels exhibit numerous desirable traits for sustained drug delivery and further work will be necessary to optimize tolerability in the eye.

Highlights Abstract Background: Totally implanted venous access devices, or ports, are safe and durable, allowing for long-term venous access. Port insertion in the upper extremity is associated with high rates of technical success and few complications. This retrospective review evaluates complication rates of power injectable ports in the upper arm preformed at a tertiary academic institution. Methods: A single center retrospective review of all patients undergoing arm port implantation between October 1, 2017, and January 30, 2019, were included. A minimum of 11 months of data was reviewed for each subject. A total of 165 subjects were initially enrolled. Results: The most frequent indication for port insertion was malignancy (n = 157). Port insertion technical success rate was 99.4%. There was no significant difference in port-related complications by gender, malignancy, clinical indication for placement, or arm used for implantation. Rates of infection (5.5%), mechanical malfunction (6.7%), device removal (10%) and arterial injury (0%) were similar to previously reported values. The rate of port-related venous thrombosis was 8.6%, exceeding previously reported values. Conclusion: Venous thrombosis was increased using this arm port. The polyurethane catheter material may play a role in this. Further work is warranted to investigate venous thrombosis for this device that incorporates information about insertion vein size and insertion vein characteristics.

The improvement in the ability of the pharmaceutical industry to predict human pharmacokinetic behavior are attributable to major technological shifts from 1990 to the present day. The opportunity for the application of AI/ML based approaches in the pharmaceutical industry is driven by the abundance of data sets that exist within individual pharmaceutical and biotech companies and the availability, within these environments, of abundant computing power. This chapter seeks to describe opportunities for artificial intelligence to contribute to the assessment and evaluation of the dug metabolism and pharmacokinetic (DMPK) properties of novel compounds across the drug discovery and development continuum. Many initiatives are already underway with respect to the application of AI/ML in predicting pharmacokinetic profiles so the question is not whether AI will influence pharmacokinetic prediction but rather how to best utilize and incorporate this and how to evaluate the value added from these applications. Since our understanding of the underlying biology of the in vitro and in vivo systems with respect to ADME, one of the key challenges to AI-based methods will be the ability to adapt to data sets that change in quality over time.

Predicting human pharmacokinetics (PK) during the drug discovery phase is valuable to assess doses required to reach therapeutic exposures. For orally administered compounds, however, this can be especially difficult, since the absorption process is complex. Vismodegib is a compound with unique nonlinear oral PK characteristics in humans. Oral physiologically based pharmacokinetic (PBPK) models were built using preclinical in vitro and in vivo data and successfully predicted the oral PK profiles in rats, dogs, and monkeys. Simulated drug exposures (area under the concentration-time curve from time 0 to infinity and Cmax) following oral administration were within twofold of observed values for dogs and monkeys, and close to twofold for rats, providing validation to the model structure. Adaptation of this oral PBPK model to humans, using human physiologic parameters coupled with predicted human PK, resulted in underpredictions of vismodegib exposure following both single and multiple doses. When observed human PK was used to drive the oral PBPK model, oral PK profiles in humans were well predicted, with fold errors in predicted versus observed drug exposures being close to 1. Importantly, the oral PBPK model captured the unique nonlinear, nondose-dependent PK of vismodegib at a steady state. The mechanism responsible for nonlinearity was consistent with oral absorption being influenced by nonsink permeation conditions. We introduce a new parameter, the permeation gradient factor, to characterize the effect of nonsink conditions on permeation. Using vismodegib as an example, we demonstrate the value of using oral PBPK models in drug discovery to predict the oral PK of compounds with nonlinear absorption characteristics in human. SIGNIFICANCE STATEMENT: A physiologically based pharmacokinetic (PBPK) model was built to demonstrate the value of these models early in the drug discovery stage for the prediction of human pharmacokinetics for compounds with unusual oral pharmacokinetics. In this study, our PBPK model could successfully capture the unique steady-state oral pharmacokinetics of our model compound, vismodegib. The mechanism for nonlinearity can be attributed to nonsink permeation conditions in vivo. We introduce the permeation gradient factor as a parameter to assess this effect.

Background: Janus Kinases (JAKs) mediate activity of many asthma-relevant cytokines. GDC-0214, an inhaled small molecule JAK1 inhibitor, has reduced FeNO ~40% in patients with mild asthma. Aim: To assess whether GDC-4379, a structurally related JAK inhibitor, also reduces FeNO. Methods: This double-blind, randomized, placebo-controlled, Phase 1 study assessed activity of GDC-4379 in patients with mild asthma. Patients were adults (18–65y) with a diagnosis of asthma for ≥6 months, FeNO >40 ppb, using as-needed relief medication only. Three sequential, 14-day, ascending-dose cohorts (Table) were randomized 2:1 (GDC-4379:placebo). The primary activity outcome was percent change from baseline (CFB) in FeNO to Day 14. We assessed pharmacokinetics, safety, and tolerability. Results: Of 36 enrolled patients (mean age, 25y), 56% were female. Baseline mean FeNO was 92 ppb. GDC-4379 treatment led to dose-dependent reductions in FeNO; at 40 mg BID, mean FeNO decreased 58% (-52 ppb) vs. pooled placebo (Table). Higher plasma drug concentrations corresponded with greater FeNO reductions. No dose-limiting adverse events (AEs), serious AEs, or treatment discontinuations occurred. Most common AEs were headache and oropharyngeal pain (sore throat), without imbalances in AEs or laboratory findings between groups. Conclusions: In patients with mild asthma, 14-day treatment with GDC-4379 reduced FeNO. Treatment was well tolerated, without evidence of systemic toxicity.

Drug reabsorption following biliary excretion is well-known as enterohepatic recirculation (EHR). Renal tubular reabsorption (RTR) following renal excretion is also common but not easily assessed. Intestinal excretion (IE) and enteroenteric recirculation (EER) have not been recognized as common disposition mechanisms for metabolically stable and permeable drugs. IE and intestinal reabsorption (IR:EHR/EER), as well as RTR, are governed by dug concentration gradients, passive diffusion, active transport, and metabolism, and together they markedly impact disposition and pharmacokinetics (PK) of small molecule drugs. Disruption of IE, IR, or RTR through applications of active charcoal (AC), transporter knockout (KO), and transporter inhibitors can lead to changes in PK parameters. The impacts of intestinal and renal reabsorption on PK are under-appreciated. Although IE and EER/RTR can be an intrinsic drug property, there is no apparent strategy to optimize compounds based on this property. This review seeks to improve understanding and applications of IE, IR, and RTR mechanisms.

Drug Metabolism Reviews has an impressive track record of providing scientific reviews in the area of xenobiotic biotransformation over 47 years. It has consistently proved to be resourceful to many scientists from pharmaceutical industry, academia, regulatory agencies working in diverse areas including enzymology, pharmacology, pharmacokinetics, and toxicology. Over the last 5 years Drug metabolism Reviews has annually published an industry commentary aimed to highlight novel insights and approaches that have made significant impacts on the field of biotransformation (led by Cyrus Khojasteh). We hope to continue this tradition by providing an overview of advances made in the field of drug transporters during 2020. The field of drug transporters is rapidly evolving as they play an essential role in drug absorption, distribution, clearance, and elimination. In this review, we have selected outstanding drug transporter articles that have significantly contributed to moving forward the field of transporter science with respect to translation and improved understanding of diverse aspects including uptake clearance, clinical biomarkers, induction, proteomics, emerging transporters, and tissue targeting. The theme of this review consists of a synopsis that summarizes each article followed by our commentary. The objective of this work is not to provide a comprehensive review but rather to exemplify novel insights and state-of-the-art highlights of recent research that have advanced our understanding of drug transporters in drug disposition. We are hopeful that this effort will prove useful to the scientific community and as such request feedback, and further extend an invitation to anyone interested in contributing to future reviews.

Historically, failure rates in drug development are high; increased sophistication and investment throughout the process has shifted the reasons for attrition, but the overall success rates have remained stubbornly and consistently low. Only 8% of new entities entering clinical testing gain regulatory approval, indicating that significant obstacles still exist for efficient therapeutic development. The continued high failure rate can be partially attributed to the inability to link drug exposure with the magnitude of observed safety and efficacy-related pharmacodynamic (PD) responses; frequently, this is a result of nonclinical models exhibiting poor prediction of human outcomes across a wide range of disease conditions, resulting in faulty evaluation of drug toxicology and efficacy. However, the increasing quality and standardization of experimental methods in preclinical stages of testing has created valuable data sets within companies that can be leveraged to further improve the efficiency and accuracy of preclinical prediction for both pharmacokinetics (PK) and PD. Models of Quantitative structure-activity relationships (QSAR), physiologically based pharmacokinetics (PBPK), and PK/PD relationships have also improved efficiency. Founded on a core understanding of biochemistry and physiological interactions of xenobiotics, these in silico methods have the potential to increase the probability of compound success in clinical trials. Integration of traditional computational methods with machine-learning approaches and existing internal pharma databases stands to make a fundamental impact on the speed and accuracy of predictions during the process of drug development and approval.

Fenebrutinib is a CYP3A substrate and time‐dependent inhibitor, as well as a BCRP and OATP1B transporter inhibitor in vitro. Physiologically‐based pharmacokinetic (PBPK) modeling strategies with the ultimate goal of understanding complex drug‐drug interactions (DDIs) and proposing doses for untested scenarios were developed. The consistency in the results of two independent approaches, PBPK simulation and endogenous biomarker measurement, supported that the observed transporter DDI is primarily due to fenebrutinib inhibition of intestinal BCRP, rather than hepatic OATP1B. A mechanistic‐absorption model accounting for the effects of excipient complexation with fenebrutinib was used to rationalize the unexpected observation of itraconazole‐fenebrutinib DDI (maximum plasma concentration (Cmax) decreased, and area under the curve (AUC) increased). The totality of the evidence from sensitivity analysis and clinical and nonclinical data suggested that fenebrutinib is likely a sensitive CYP3A substrate. This advanced PBPK application allowed the use of model‐informed approach to facilitate the development of concomitant medication recommendations for fenebrutinib without requiring additional clinical DDI studies.

Model-informed drug development (MIDD) has become an important approach to improving clinical trial efficiency, optimizing drug dosing, and proposing drug labeling in the absence of dedicated clinical trials. For the first time, we developed a physiologically based pharmacokinetic (PBPK) model-based approach to assess CYP3A-mediated drug-drug interaction (DDI) risk for polatuzumab vedotin (Polivy), an anti-CD79b-vc-monomethyl auristatin E (MMAE) antibody-drug conjugate (ADC). The model was developed and verified using data from the existing clinical DDI study for brentuximab vedotin, a similar vc-MMAE ADC. Analogous to the brentuximab vedotin clinical study, polatuzumab vedotin at the proposed labeled dose was predicted to have a limited drug interaction potential with strong CYP3A inhibitor and inducer. Polatuzumab vedotin was also predicted to neither inhibit nor induce CYP3A. The present work demonstrated a high-impact application using a PBPK MIDD approach to predict the CYP3A-mediated DDI to enable drug labeling in the absence of any dedicated clinical DDI study. The key considerations for the PBPK report included in the Biologics License Application/Marketing Authorization Application submission, as well as the strategy and responses to address some of the critical and challenging questions from the health authorities following the submission are also discussed. Our experience and associated perspective using a PBPK approach to ultimately enable a drug interaction label claim for polatuzumab vedotin in lieu of a dedicated clinical DDI study, as well as the interactions with the regulatory agencies, further provides confidence in applying MIDD to accelerate the registration and approval of new drug therapies.