Human Pharmacokinetic Parameters Research Articles

Pharmacokinetics and pharmacodynamics of bacteriophage therapy: a review with a focus on multidrug-resistant Gram-negative bacterial infections.

SUMMARYDespite the early recognition of their therapeutic potential and the current escalation of multidrug-resistant (MDR) pathogens, the adoption of bacteriophages into mainstream clinical practice is hindered by unfamiliarity with their basic pharmacokinetic (PK) and pharmacodynamic (PD) properties, among others. Given the self-replicative nature of bacteriophages in the presence of host bacteria, the adsorption rate, and the clearance by the host's immunity, their PK/PD characteristics cannot be estimated by conventional approaches, and thus, the introduction of new considerations is required. Furthermore, the multitude of different bacteriophage types, preparations, and treatment schedules impedes drawing general conclusions on their in vivo PK/PD features. Additionally, the drawback of acquired bacteriophage resistance of MDR pathogens with clinical and environmental implications should be taken into consideration. Here, we provide an overview of the current state of the field of PK and PD of bacteriophage therapy with a focus on its application against MDR Gram-negative infections, highlighting the potential knowledge gaps and the challenges in translation from the bench to the bedside. After reviewing the in vitro PKs and PDs of bacteriophages against the four major MDR Gram-negative pathogens, Klebsiella pneumoniae, Acinetobacter baumannii complex, Pseudomonas aeruginosa, and Escherichia coli, specific data on in vivo PKs (tissue distribution, route of administration, and basic PK parameters in animals and humans) and PDs (survival and reduction of bacterial burden in relation to the route of administration, timing of therapy, dosing regimens, and resistance) are summarized. Currently available data merit close scrutiny, and optimization of bacteriophage therapy in the context of a better understanding of the underlying PK/PD principles is urgent to improve its therapeutic effect and to minimize the occurrence of bacteriophage resistance.

A systematic review of allometric scaling exponents for IgG mAbs

Increasing complexity of mAbs in development creates challenges in predicting human pharmacokinetic (PK) parameters from preclinical data. The aim of this analysis was to identify optimal allometric scaling exponents. Data were extracted from literature to create a central database (currently the largest available published database) of two-compartment model parameters for mAbs (n = 59) in cynomolgus monkey (CM) and human. Global allometric exponents were calculated and drug-dependent factors were investigated as potential variables in determining the optimal scaling factor. The global exponents for scaling CM mAb PK data were 0.74 (CL), 0.80 (CL with Fc-modified mAbs excluded), 0.44 (CL with Fc-modified mAbs only), 0.71 (Q), 1.12 (V1), and 0.99 (V2). These values are in line with previously published literature values.

Predicting Human Subcutaneous Bioavailability of Therapeutic Monoclonal Antibodies from Systemic Clearance and Volume of Distribution.

Subcutaneous delivery of monoclonal antibody therapeutics is often preferred to intravenous delivery due to better patient compliance and overall lower cost to the healthcare system. However, the systemic absorption of biologics dosed subcutaneously is often incomplete. The aim of this work was to describe a human bioavailability prediction method for monoclonal antibodies delivered subcutaneously that utilizes intravenous pharmacokinetic parameters as input. A two-compartment pharmacokinetic model featuring a parallel-competitive absorption pathway and a presystemic metabolism pathway was employed. A training data set comprised 19 monoclonal antibodies (geometric mean bioavailability of 68%), with previously reported human pharmacokinetic parameters, while a validation set included data compiled from 5 commercial drug products (geometric mean bioavailability of 69%). A single fitted absorption rate constant, paired with compound-specific estimates of presystemic metabolism rate proportional to compound-specific systemic clearance parameters, resulted in calculations of human subcutaneous bioavailability closely mimicking clinical data in the training data set with a root-mean-square error of 5.5%. Application of the same approach to the validation data set resulted in predictions characterized by 12.6% root-mean-square error. Factors that may have impacted the prediction accuracy include a limited number of validation data set compounds and an uncertainty in the absorption rate, which were subsequently discussed. The predictive method described herein provides an initial estimate of the subcutaneous bioavailability based exclusively on pharmacokinetic parameters available from intravenous dosing.

Estimating human pharmacokinetic parameters forelectronic nicotine delivery system products from chemical analyses of their aerosols.

The ability of Electronic Nicotine Delivery Systems (ENDS) to deliver nicotine is central to their function to substitute for cigarettes, allowing people who smoke to switch away from smoking, thus reducing their exposure to harmful chemicals in cigarette smoke. The nicotine concentration in ENDS e-liquid has proved to be a poor predictor of nicotine uptake in users. Using meta-analytic methods to analyze 12 pharmacokinetic studies of nicotine-salt closed-system ENDS, this paper examines whether the mass of nicotine/puff of aerosol can predict Cmax in pharmacokinetic studies. Cmax values were available for 38 products, in 58 use conditions (including both controlled [3s] and ad libitum puffing), comprising 1769 participant observations. Nicotine/puff data reflected chemical analyses of aerosol obtained under nonintense (3s) or intense (6s) machine puffing. Meta-regression analyses (weighted by reliability of Cmax estimate) assessed the relationship of nicotine/puff to Cmax. In some models, empirical data were used to impute the variation in Cmax or the nicotine/puff value under intense puffing. In simple linear models, Cmax was significantly associated with nicotine/puff under all combinations of intense/nonintense and controlled/ad-libitum conditions, with R2 values of 0.71-0.77. More complex models based on quadratic effects or log[nicotine/puff] did not generally improve upon more parsimonious linear models. Application of the model illustrates the divergence between nicotine concentration in e-liquids and expected Cmax when other ENDS parameters vary. The meta-analytic model may have utility in settings where clinical pharmacokinetic data are not available, including product development.

Pharmacodynamic evaluation of ceftriaxone single-dose therapy (0.125-1 g) to eradicate ceftriaxone-susceptible and ceftriaxone-resistant Neisseria gonorrhoeae strains in a hollow fibre infection model for gonorrhoea.

Antimicrobial resistance in Neisseria gonorrhoeae is threatening the gonorrhoea treatment, and optimizations of the current ceftriaxone-treatment regimens are crucial. We evaluated the pharmacodynamics of ceftriaxone single-dose therapy (0.125-1 g) against ceftriaxone-susceptible and ceftriaxone-resistant gonococcal strains, based on EUCAST ceftriaxone-resistance breakpoint (MIC > 0.125 mg/L), in our hollow fibre infection model (HFIM) for gonorrhoea. Gonococcal strains examined were WHO F (ceftriaxone-susceptible, MIC < 0.002 mg/L), R (ceftriaxone-resistant, MIC = 0.5 mg/L), Z (ceftriaxone-resistant, MIC = 0.5 mg/L) and X (ceftriaxone-resistant, MIC = 2 mg/L). Dose-range HFIM 7 day experiments simulating ceftriaxone 0.125-1 g single-dose intramuscular regimens were conducted. Ceftriaxone 0.125-1 g single-dose treatments rapidly eradicated WHO F (wild-type ceftriaxone MIC). Ceftriaxone 0.5 and 1 g treatments, based on ceftriaxone human plasma pharmacokinetic parameters, eradicated most ceftriaxone-resistant gonococcal strains (WHO R and Z), but ceftriaxone 0.5 g failed to eradicate WHO X (high-level ceftriaxone resistance). When simulating oropharyngeal gonorrhoea, ceftriaxone 0.5 g failed to eradicate all the ceftriaxone-resistant strains, while ceftriaxone 1 g eradicated WHO R and Z (low-level ceftriaxone resistance) but failed to eradicate WHO X (high-level ceftriaxone resistance). No ceftriaxone-resistant mutants were selected using any ceftriaxone treatments. Ceftriaxone 1 g single-dose intramuscularly cure most of the anogenital and oropharyngeal gonorrhoea cases caused by the currently internationally spreading ceftriaxone-resistant gonococcal strains, which should be further confirmed clinically. A ceftriaxone 1 g dose (±azithromycin 2 g) should be recommended for first-line empiric gonorrhoea treatment. This will buy countries some time until novel antimicrobials are licensed. Using ceftriaxone 1 g gonorrhoea treatment, the EUCAST ceftriaxone-resistance breakpoint is too low.

Preclinical Pharmacokinetics and Translational Pharmacokinetic/Pharmacodynamic Modeling of M8891, a Potent and Reversible Inhibitor of Methionine Aminopeptidase 2

IntroductionM8891 is a selective and reversible inhibitor of methionine aminopeptidase 2 (MetAP2). We describe translational research to define the target pharmacokinetics (PK) of M8891 and associated pharmacodynamic (PD) levels, which were used to support efficacious dose selection in humans.MethodsIn vitro and in vivo PK characteristics were investigated in animal species, and data integrated using in vitro–in vivo correlation and allometric methods to predict the clearance, volume of distribution, and absorption parameters of M8891 in humans. In parallel, inhibition of MetAP2 activity by M8891 was studied in renal cancer xenografts in mice by measuring accumulation of Met-EF1α, a substrate of MetAP2. The corresponding PD effect was described by a turnover and effect compartment model. This model was used to simulate PD at the M8891 dose showing in vivo efficacy, i.e. significant tumor growth inhibition. Simulations of M8891 PK and associated PD in humans were conducted by integrating predicted human PK parameters into the preclinical PK/PD model.ResultsThe target minimum PD level associated with efficacy was determined to be 125 µg Met-EF1α per mg protein. Integrating predicted human PK parameters into the preclinical PK/PD model defined a minimal M8891 concentration at steady-state (Ctrough) of 1500 ng/mL (3.9 µM) in humans as being required to produce the corresponding minimum target Met-EF1a level (125 µg per mg protein).ConclusionThe defined target PK and PD levels supported the design of the clinical Phase Ia dose escalation study of M8891 (NCT03138538) and selection of the recommended Phase II dose.

Combined translational pharmacometrics approach to support the design and conduct of the first-in-human study of DWP16001.

The objective of this study was to characterize the pharmacokinetics (PK)/pharmacodynamics (PD) of DWP16001, a novel sodium-glucose cotransporter 2 inhibitor, and predict efficacious doses for the first-in-human study using various translational approaches. A mechanistic PK/PD model was developed for DWP16001 using nonlinear mixed-effect modelling to describe animal PK/PD properties. Using allometry and in silico physiologically based equations, human PK parameters were predicted. Human PD parameters were scaled by applying interspecies difference and in vitro drug-specific factors. Human parameters were refined using early clinical data. Model-predicted PK and PD outcomes were compared to observations before and after parameter refinement. The PK/PD model of DWP16001 was developed using a 2-compartment model with first-order absorption and indirect response. Efficacious doses of 0.3 and 2 mg of DWP16001 were predicted using human half-maximal inhibitory concentration values translated from Zucker Diabetic Fatty rats and normal rats, respectively. After parameter refinement, doses of 0.2 and 1 mg were predicted to be efficacious for each disease model, which improved the prediction results to within a 1.2-fold difference between the model prediction and observation. This study predicted efficacious human doses of DWP16001 using population PK/PD modelling and a combined translational pharmacometrics approach. Early clinical data allowed the methods used to translate in vitro and in vivo findings to clinical PK/PD values for DWP16001 to be optimized. This study has shown that a refinement step can be readily applied to improve model prediction and further support the study design and conduct of a first-in-human study.

Prediction of Human Pharmacokinetics of Phosphorodiamidate Morpholino Oligonucleotides in Duchenne Muscular Dystrophy Patients Using Viltolarsen.

Several modified antisense oligonucleotides (ASOs) have recently been approved for clinical use. Some are phosphorodiamidate morpholino oligomers (PMOs), which, unlike other nucleic acids, are not negatively charged. Thus, PMOs differ from other ASOs in their pharmacokinetic (PK) properties. Drugs with a PMO backbone have been administered to Duchenne muscular dystrophy pediatric patients; however, appropriate methodologies are not currently available to predict their human PK from nonclinical data. In this study, we used viltolarsen as a representative PMO to investigate the applicability of the allometric scaling approach to human PK prediction. We first summarized the nonclinical and clinical PK data for viltolarsen as showing high total clearance, low serum protein binding, metabolic resistance, and urinary excretion as the unchanged drug in both animals and humans. We then investigate the PK of viltolarsen in mice, rats, cynomolgus monkeys, and dogs and used the results, with body weight, to extrapolate to humans by several methods. The estimate of human total clearance obtained from cynomolgus monkeys was the best, and body weight may be the key factor in accurately predicting human total clearance. In contrast, all of the well-known prediction methods for the volume of distribution at steady state gave underestimates. However, the human PK profiles predicted from the PK parameters in cynomolgus monkeys fit the observed human plasma concentrations well. These results are expected to contribute to the further development of PMOs. SIGNIFICANCE STATEMENT: We investigated how to predict the human PK of phosphorodiamidate morpholino oligomers from nonclinical data. The estimates of human PK parameters and profiles determined from cynomolgus monkeys by an allometric scaling approach were the most suitable, and the cynomolgus monkey body weight may be the key factor in accurately predicting human total clearance.

Application of in Silico Technologies for Drug Target Discovery and Pharmacokinetic Analysis.

Drug discovery is researched and developed through many processes, but its overall success rate is extremely low, requiring a very long period of development and considerable costs. Clearly, there is a need to reduce research and development costs by improving the probability of success and increasing process efficiency. One promising approach to this challenge is so-called "in silico drug discovery," which is drug discovery utilizing information and communications technologies (ICT) such as artificial intelligence (AI) and molecular simulation. In recent years, ICT-based science and technology, such as bioinformatics, systems biology, cheminformatics, and molecular simulation, which have been developed mainly in the life science and chemistry fields, have changed the face of drug development. AI-based methods have been developed in the drug discovery process, mainly in relation to drug target discovery and pharmacokinetic analysis. In drug target discovery, an in silico method has been developed that uses a probabilistic framework that eliminates the problems of conventional experimental approaches and provides a key to understanding the pathways and mechanisms from compounds to phenotypes. In the field of pharmacokinetic analysis, we have seen the development of a method using nonclinical data to predict human pharmacokinetic parameters, which are important for predicting drug efficacy and toxicity in clinical trials. In this article, we provide an overview of these methods.

ADME, Pharmacokinetic Scaling, Pharmacodynamic and Prediction of Human Dose and Regimen of Novel Antiviral Drugs.

The search for new drugs is an extremely time-consuming and expensive endeavour. Much of that time and money go into generating predictive human pharmacokinetic profiles from preclinical efficacy and safety animal data. These pharmacokinetic profiles are used to prioritize or minimize the attrition at later stages of the drug discovery process. In the area of antiviral drug research, these pharmacokinetic profiles are equally important for the optimization, estimation of half-life, determination of effective dose, and dosing regimen, in humans. In this article we have highlighted three important aspects of these profiles. First, the impact of plasma protein binding on two primary pharmacokinetic parameters-volume of distribution and clearance. Second, interdependence of primary parameters on unbound fraction of the drug. Third, the ability to extrapolate human pharmacokinetic parameters and concentration time profiles from animal profiles.

Relationship between Body Composition and Serum Immunoglobulin Concentrations after Administration of Intravenous Immune Globulin-Preclinical and Clinical Evidence.

The purpose of this study was to investigate the effect of obesity on immunoglobulin G (IgG) pharmacokinetics in a rat model of obesity, and to collect clinical evidence for an association between the body composition and intravenous immune globulin (IVIG) pharmacokinetic parameters in humans. In a preclinical study, pharmacokinetics of human IgG was evaluated after intravenous (IV) and subcutaneous (SC) delivery to obese and lean rats (n = 6 in each group). Serial serum samples were analyzed using an ELISA. The animal body composition was assessed using computer tomography. Patients with primary immunodeficiency currently managed with IVIG, and at a steady state, were enrolled in the clinical study (n = 8). Serum immune globulin (Ig) concentrations were measured at baseline and immediately after the administration of two consecutive treatments, with an additional measurement at two weeks after the first administration. In addition to the patient demographic and clinical characteristics, body composition was measured using bioelectrical impedance analysis. The pharmacokinetics of human IgG was significantly different between the obese and lean rats after both the IV and SC administration of 0.5 g/kg. Furthermore, a significant difference in endogenous rat IgG was observed between the two strains. In the human study, total serum IgG and subtype (IgG1, IgG2, IgG3, IgG4) half-life negatively correlated with the body mass index and fat mass. The mean change in the total serum IgG concentration was significantly correlated to body mass index and fat mass. The results of the studies corroborated one another. In the animal study, most pharmacokinetic parameters of human IgG following IV and SC administration were significantly affected by obesity and changes in the body composition. In the clinical study, the mean serum IgG change after the IVIG administration strongly correlated to the BMI and body fat mass. Future studies are needed to establish the outcomes achieved with more frequent dosing in obese individuals with primary immunodeficiency.

Pharmacokinetics of Long-Acting Aqueous Nano-/Microsuspensions After Intramuscular Administration in Different Animal Species and Humans-a Review.

Formulating aqueous suspensions is an attractive strategy to incorporate poorly water-soluble drugs, where the drug release can be tailored to maintain desired release profiles of several weeks to months after parenteral (i.e., intramuscular or subcutaneous) administration. A sustained drug release can be desirable to combat chronic diseases by overcoming pill fatigue of a daily oral intake, hence, improving patient compliance. Although the marketed aqueous suspensions for intramuscular injection efficiently relieve the daily pill burden in chronic diseases, the exact drug release mechanisms remain to be fully unraveled. The in vivo drug release and subsequent absorption to the systemic circulation are influenced by a plethora of variables, resulting in a complex in vivo behavior of aqueous suspensions after intramuscular administration. A better understanding of the factors influencing the in vivo performance of aqueous suspensions could advance their drug development. An overview of the potential influential variables on the drug release after intramuscular injection of aqueous suspensions is provided with, where possible, available pharmacokinetic parameters in humans or other species derived from literature, patents, and clinical trials. These variables can be categorized into drug substance and formulation properties, administration site properties, and the host response towards drug particles. Based on the findings, the most critical factors are particle size, dose level, stabilizing excipient, drug lipophilicity, gender, body mass index, and host response.

EXTH-102. PLASMA AND CEREBROSPINAL FLUID (CSF) PHARMACOKINETICS (PK) OF MIRDAMETINIB IN A NON-HUMAN PRIMATE (NHP) MODEL

Abstract Mirdametinib is a MEK inhibitor with reported CSF penetration in pre-clinical models. Murine studies reported ERK phosphorylation inhibition in brain tissue at 1.15 nM (0.73 ng/mL) and tumor cell lines at 0.33–0.59 nM (0.16-0.28 ng/mL). A phase II clinical trial evaluating mirdametinib for neurofibromatosis type 1-related plexiform neurofibromas reported a 42% partial response rate and a mean plasma exposure (AUC0-12h) of 443 h*ng/mL. This study determined the plasma and CSF pharmacokinetic (PK) profile of mirdametinib in a non-human primate (NHP) model where CSF penetration serves as a proxy for CNS penetration. METHODS Four NHP received mirdametinib PO q.d, 0.50 mg/kg, in serial studies as a single dose (Single-Dose), three doses (Multiple-Dose), or IV, 0.20 mg/kg, followed by paired plasma and CSF sample collections through 96 hours. Mirdametinib was quantified by LC-MS/MS. PK parameters were calculated via noncompartmental methods. Plasma protein binding was determined by rapid equilibrium dialysis. RESULTS Mean □ standard deviation values reported. Three subjects were evaluable for both plasma (total and unbound) and CSF drug concentrations. Plasma – AUClast: Single-Dose 500.3 □ 253.4 and IV 552.3 □ 43 h*ng/mL; AUCtau: Multiple-Dose 456.3 □ 120.6 h*ng/mL. CSF Cmax (ng/mL): Single-Dose 0.43 □ 0.18, IV 2.0 □ 1.8, Multiple-Dose 0.56 □ 0.18. CSF Penetration (%): Single-Dose 1.3 □ 0.45, IV-1.6 □ 0.95 (AUCcsf-last:AUCplasma-last); Multiple-Dose 1.3 □ 0.56 (AUCcsf-tau:AUCplasma-tau). CSF/unbound plasma ratios ranged from 2.5-3.0 Plasma free fraction (%): 0.52 □ 0.1. CONCLUSION Notable mirdametinib CSF penetration was demonstrated in this NHP model. A higher CSF to unbound plasma ratio suggests that the efflux of mirdametinib from the CSF was delayed. The NHP CSF Cmax approached the ERK phosphorylation inhibition concentrations previously reported. The ability of this NHP model to predict human PK parameters was demonstrated via the comparable NHP to patient plasma exposure reported in the Phase II clinical trial.

MODELING AND SIMULATION PREDICTS ROBUST HAE ATTACK SUPPRESSION WITH EVERY 3 MONTH DOSING OF STAR-0215

<h3>Introduction</h3> Inhibition of plasma kallikrein is a validated mechanism for prevention of hereditary angioedema (HAE) attacks. STAR-0215 is a long-acting monoclonal antibody inhibitor of plasma kallikrein. We sought to generate a mechanistic quantitative systems pharmacology (QSP) model to explore the potential for reduction of HAE attacks with different dosing regimens of STAR-0215. <h3>Methods</h3> A simplified QSP model was established based on published reaction parameters for the plasma kallikrein-kininogen pathway in the vascular space and adjacent to the endothelial surface. The pharmacokinetic (PK) parameters of STAR-0215 were derived from cynomolgus monkey PK studies and scaled to estimate human PK parameters. Variability in PK parameters was simulated using a standard deviation of 50% and a Poisson distribution was applied to randomly determine the timing of trigger events with an average attack frequency of 3 per month. <h3>Results</h3> A long circulating half-life of STAR-0215 in humans (108 days) was predicted from empirically obtained PK parameters in cynomolgus monkeys. The QSP model predicted long-term robust HAE attack suppression following a single subcutaneous administration of STAR-0215 at dose levels of ≥300 mg. The QSP model simulations also showed subcutaneously administered STAR-0215 could provide a potential prolonged HAE attack suppression with a once every 3 months maintenance dose regimen. <h3>Conclusions</h3> STAR-0215 is a novel, potent and selective long-acting monoclonal antibody plasma kallikrein inhibitor for the potential treatment of HAE. Results from the QSP model support STAR-0215 dosing once every 3 months or longer for robust suppression of HAE attacks.

Translational PK/PD Modeling of Tumor Growth Inhibition and Target Inhibition to Support Dose Range Selection of the LMP7 Inhibitor M3258 in Relapsed/Refractory Multiple Myeloma.

M3258 is an orally bioavailable, potent, selective, reversible inhibitor of the large multifunctional peptidase 7 (LMP7, β5i, PSMB8) proteolytic subunit of the immunoproteasome, a component of the cellular protein degradation machinery, highly expressed in malignant hematopoietic cells including multiple myeloma. Here we describe the fit-for-purpose pharmacokinetic (PK)/pharmacodynamic (PD)/efficacy modeling of M3258 based on preclinical data from several species. The inhibition of LMP7 activity (PD) and tumor growth (efficacy) were tested in human multiple myeloma xenografts in mice. PK and efficacy data were correlated yielding a free M3258 concentration of 45 nM for half-maximal tumor growth inhibition (KC50). As M3258 only weakly inhibits LMP7 in mouse cells, both in vitro and in vivo bridging studies were performed in rats, monkeys, and dogs for translational modeling. These data indicated that the PD response in human xenograft models was closely reflected in dog PBMCs. A PK/PD model was established, predicting a free IC50 value of 9 nM for M3258 in dogs in vivo, in close agreement with in vitro measurements. In parallel, the human PK parameters of M3258 were predicted by various approaches including in vitro extrapolation and allometric scaling. Using PK/PD/efficacy simulations, the efficacious dose range and corresponding PD response in human were predicted. Taken together, these efforts supported the design of a phase Ia study of M3258 in multiple myeloma patients (NCT04075721). At the lowest tested dose level, the predicted exposure matched well with the observed exposure while the duration of LMP7 inhibition was underpredicted by the model. SIGNIFICANCE STATEMENT: M3258 is a novel inhibitor of the immunoproteasome subunit LMP7. The human PK and human efficacious dose range of M3258 were predicted using in vitro-in vivo extrapolation and allometric scaling methods together with a fit-for-purpose PK/PD and efficacy model based on data from several species. A comparison with data from the Phase Ia clinical study showed that the human PK was accurately predicted, while the extent and duration of PD response were more pronounced than estimated.

How effective are ionization state-based QSPKR models at predicting pharmacokinetic parameters in humans?

Optimizing the pharmacokinetics (PK) of a drug candidate to support oral dosing is a key challenge in drug development. PK parameters are usually estimated from the concentration-time profile following intravenous administration; however, traditional methods are time-consuming and expensive. In recent years, quantitative structure-pharmacokinetic relationship (QSPKR), an in silico tool that aims to develop a mathematical relationship between the structure of a molecule and its PK properties, has emerged as a useful alternative to experimental testing. Due to the complex nature of the various processes involved in dictating the fate of a drug, the development of adequate QSPKR models that can be used in real-world pre-screening situations has proved challenging. Given the crucial role played by a molecule's ionization state in determining its PK properties, this work aims to build predictive QSPKR models for PK parameters in humans using an ionization state-based strategy. We divide a high-quality dataset into clusters based on ionization state at physiological pH and build global and ion subset-based 'local' models for three major PK parameters: plasma clearance (CL), steady-state volume of distribution (VDss), and half-life (t1/2). We use a robust methodology developed in our lab entitled 'EigenValue ANalySis' that accounts for the stereospecificity in drug disposition and use the support vector machine algorithm for model building. Our findings suggest that categorizing compounds in accordance with ionization state does not result in improved QSPKR models. The narrow ranges in the endpoints along with redundancies in the data adversely affect the ion subset-based QSPKR models. We suggest alternative approaches such as elimination route-based models that account for drug-transporter interactions for CL and chemotype-specific QSPKR for VDss.

Pharmacokinetic evaluation of radiolabeled intraocular anti-CLEC14a antibody in preclinical animal species and application in humans.

Anti-angiogenic antibodies are widely used in the treatment of neovascular macular degeneration. Human antibody targeting C-type lectin domain family 14 member A (CLEC14a) is potential therapeutic agents owing to its antiangiogenic activity. In the present study, we aimed to predict the human intraocular pharmacokinetic (PK) properties of an anti-CLEC14a antibody. I-125 labeled aflibercept and anti-CLEC14a antibody were intravitreally injected into mice, rats, and rabbits. Single photon emission computed tomography/computed tomography imaging was performed, and the intraocular radioactivity concentration (%ID/ml) was obtained. The PK parameters in those three animal species were obtained by compartmental analysis. The PK parameters in humans were estimated by allometric scaling of the animal PK parameters with consideration of the hydrodynamic radius of the antibody. The mean half-life values of intraocular I-125-labeled aflibercept in mice, rats, and rabbits were 1.13 days, 1.25 days, and 4.91 days, respectively, by analysis with a one-compartment model. The predicted human half-life of intraocular aflibercept was 5.75 days based on vitreal volume by allometric scaling. The half-life values of intraocular I-125-labeled anti-CLEC14a in mice, rats and rabbits were 1.05 days, 1.84 days, and 6.37 days, respectively, by analysis with a one-compartment model. The predicted human half-life of intraocular anti-CLEC14a was 10.29 days based on vitreal volume. According to the hydrodynamic volume of the anti-CLEC14a, the predicted human half-life of intraocular anti-CLEC14a was 9.81 days. The PK characteristics of the intraocular anti-CLEC14a antibody were evaluated noninvasively in animals using I-125 labeling, and the intraocular PK characteristics in humans were predicted using these animal data. This methodology can be applied for the development of new antiangiogenic antibodies to treat macular degeneration.

Can We Predict Clinical Pharmacokinetics of Highly Lipophilic Compounds by Integration of Machine Learning or In Vitro Data into Physiologically Based Models? A Feasibility Study Based on 12 Development Compounds.

While high lipophilicity tends to improve potency, its effects on pharmacokinetics (PK) are complex and often unfavorable. To predict clinical PK in early drug discovery, we built human physiologically based PK (PBPK) models integrating either (i) machine learning (ML)-predicted properties or (ii) discovery stage in vitro data. Our test set was composed of 12 challenging development compounds with high lipophilicity (mean calculated log P 4.2), low plasma-free fraction (50% of compounds with fu,p < 1%), and low aqueous solubility. Predictions focused on key human PK parameters, including plasma clearance (CL), volume of distribution at steady state (Vss), and oral bioavailability (%F). For predictions of CL, the ML inputs showed acceptable accuracy and slight underprediction bias [an average absolute fold error (AAFE) of 3.55; an average fold error (AFE) of 0.95]. Surprisingly, use of measured data only slightly improved accuracy but introduced an overprediction bias (AAFE = 3.35; AFE = 2.63). Predictions of Vss were more successful, with both ML (AAFE = 2.21; AFE = 0.90) and in vitro (AAFE = 2.24; AFE = 1.72) inputs showing good accuracy and moderate bias. The %F was poorly predicted using ML inputs [average absolute prediction error (AAPE) of 45%], and use of measured data for solubility and permeability improved this to 34%. Sensitivity analysis showed that predictions of CL limited the overall accuracy of human PK predictions, partly due to high nonspecific binding of lipophilic compounds, leading to uncertainty of unbound clearance. For accurate predictions of %F, solubility was the key factor. Despite current limitations, this work encourages further development of ML models and integration of their results within PBPK models to enable human PK prediction at the drug design stage, even before compounds are synthesized. Further evaluation of this approach with more diverse chemical types is warranted.

Predicting Total Drug Clearance and Volumes of Distribution Using the Machine Learning-Mediated Multimodal Method through the Imputation of Various Nonclinical Data

Pharmacokinetic research plays an important role in the development of new drugs. Accurate predictions of human pharmacokinetic parameters are essential for the success of clinical trials. Clearance (CL) and volume of distribution (Vd) are important factors for evaluating pharmacokinetic properties, and many previous studies have attempted to use computational methods to extrapolate these values from nonclinical laboratory animal models to human subjects. However, it is difficult to obtain sufficient, comprehensive experimental data from these animal models, and many studies are missing critical values. This means that studies using nonclinical data as explanatory variables can only apply a small number of compounds to their model training. In this study, we perform missing-value imputation and feature selection on nonclinical data to increase the number of training compounds and nonclinical datasets available for these kinds of studies. We could obtain novel models for total body clearance (CLtot) and steady-state Vd (Vdss) (CLtot: geometric mean fold error [GMFE], 1.92; percentage within 2-fold error, 66.5%; Vdss: GMFE, 1.64; percentage within 2-fold error, 71.1%). These accuracies were comparable to the conventional animal scale-up models. Then, this method differs from animal scale-up methods because it does not require animal experiments, which continue to become more strictly regulated as time passes.

Abstract 5457: QLH11811, a selective 4th-generation EGFR inhibitor for osimertinib-resistant EGFR-mutant NSCLC

Abstract Background: The 3rd-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI), like osimertinib, provide marked clinical benefit for EGFR-mutant non-small cell lung cancer (NSCLC) patients with extended overall survival vs former EGFR TKIs (e.g., gefitinib). Approximate 10%-24% of NSCLC patients acquired C797S mutation when treated with osimertinib. Unfortunately, limited treatments are available for patients after osimertinib resistance. QLH11811 is a new generation EGFR TKI designed to target the EGFR with ex19del/L858R/T790M/C797S mutations. Here, we disclosed its preclinical data to support its clinical development in EGFR-mutant NSCLC. Methods: The inhibitory activity of QLH11811 on mutated and wild-type EGFR was tested in engineered cell lines and patient-derived organoid (PDO). The in vivo antitumor activity of QLH11811 was evaluated in the patient-derived xenograft (PDX) model with cis EGFR ex19del/T790M/C797S triple mutations, and the H1975 (cis EGFR L858R/T790M/C797S and cis EGFR ex19del/T790M/C797S), PC-9 (EGFR ex19del), and Ba/F3 (EGFR ex19del/C797S) cell line-derived xenograft (CDX) models. The pharmacokinetic (PK) profile was investigated in animals, and the human PK profile was projected using allometric scaling method. Results: QLH11811 displayed potent anti-proliferation activity against Ba/F3 (EGFR ex19del/T790M/C797S, L858R/T790M/C797S, ex19del/C797S, or L858R/C797S), PC-9 (EGFR ex19del/T790M/C797S), H1975 (EGFR L858R/T790M/C797S, L858R/T790M), H3255 (L858R) and HCC827 (ex19del) with IC50 of 2.6, 3.1, 2.4, 4.1, 51, 50, 27, 21, and 11 nM, respectively. QLH11811 also showed excellent selectivity when compared the above values with its IC50 against Ba/F3 (EGFR wild-type, 61 nM) and A431 (EGFR wild-type, 440nM). QLH11811 demonstrated excellent inhibitory activities against seven osimertinib-resistant PDO models. Daily oral QLH11811 significantly inhibited tumor growth at all doses tested (P &amp;lt;0.001) in the PDX model, the H1975, PC-9, and Ba/F3 CDX models. QLH11811 had good PK profile in mice, rats, dogs, and monkeys, with the absolute bioavailability at 71%, 29%, 80% and 42%. The human PK parameters were obtained by allometric scaling method, and the efficacious dose in human was projected to 103 mg, daily. Conclusion: The in vitro and in vivo preclinical data demonstrated QLH11811 is a highly potent and selective 4th-generation EGFR TKI with activity against the osimertinib-resistant NSCLC with EGFR C797S mutation. The preclinical PK data supported the efficacious dose of QLH11811 in human would be 103 mg. Citation Format: Shansong Zheng, Wei Deng, Qingmei Zheng, Yingying Yang, Na Li, Tan Pang, Xueying Feng, Simon Taylor, Lina Ma, Yaqiong Wu, Ziwei Zhao. QLH11811, a selective 4th-generation EGFR inhibitor for osimertinib-resistant EGFR-mutant NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5457.