Target-mediated Drug Disposition Research Articles

#243 Characteristics and safety in patients with atypical haemolytic uraemic syndrome switching to ravulizumab from eculizumab: a global registry analysis

Abstract Background and Aims Atypical haemolytic uraemic syndrome (aHUS) is a progressive rare disease caused by complement dysregulation that can result in severe organ damage and death. Ravulizumab, a next-generation terminal complement inhibitor, was designed via targeted modification of eculizumab to enhance antibody recycling and attenuate target-mediated drug disposition to achieve an extended half-life. Ravulizumab was first approved for the treatment of aHUS in 2019. Real-world evidence with ravulizumab in patients with aHUS is limited. This analysis aimed to assess real-world safety outcomes in patients with aHUS who switched to ravulizumab from eculizumab using data from the Global aHUS Registry. Method The Global aHUS Registry is a multicentre study (NCT01522183) collecting retrospective and prospective data on patients with aHUS since 2012, making it the largest registry of real-world data for this patient population. Safety outcomes (including serious and non-serious adverse events [AEs], meningococcal infections and deaths) were assessed in patients with aHUS who switched to ravulizumab from eculizumab up to 3 July 2023. Results Overall, 60 patients were included in the analysis population and evaluated for baseline demographics and characteristics, and safety outcomes. Most patients were female (70%) and the median (range) age at ravulizumab initiation was 34 (2–72) years (Table 1). In total, 27 patients (45%) had pathogenic complement variants and 19 (32%) had a kidney transplantation prior to ravulizumab initiation. Among extrarenal manifestations (experienced at any time during observation), the most common were gastrointestinal (n = 29 [48%]), central nervous system (n = 19 [32%]) and cardiovascular (n = 15 [25%]). The median (range) time on treatment was 21 (2–40) months for ravulizumab and 62 (11–155) months for eculizumab. No new events of thrombotic microangiopathy, dialysis or kidney transplantation were reported during ravulizumab treatment. One patient who was on chronic dialysis under eculizumab switched to ravulizumab; the patient returned to eculizumab (per local guidelines) for a planned kidney transplantation with the intention to switch back to ravulizumab post-transplantation (data not yet available). In total, 20 AEs were reported in 13 patients, of which none were unexpected (Table 2). Three serious AEs were reported in three patients (1 event each of squamous cell carcinoma, atrial fibrillation, SARS-CoV-2 infection). Ten AEs occurred in eight patients who received a kidney transplantation before ravulizumab initiation. Treatment-related AEs occurred in two patients while on ravulizumab: one infusion reaction event in one patient was assessed to be probably related to ravulizumab by the investigator (the event resolved within 24 hours and the patient continued treatment); one patient experienced headaches and fatigue while on ravulizumab, which resolved after switching back to eculizumab. The most common AEs were infection (n = 7 events), including SARS-CoV-2 infection (n = 4), influenza (n = 1), infection without focus (n = 1) and pulmonary nodular infiltration (n = 1); all infections were resolved except for one event of SARS-CoV-2 infection that was ongoing/persistent. No meningococcal infections or deaths were reported during ravulizumab treatment. Conclusion This analysis from the Global aHUS Registry reports the largest real-world safety dataset from patients with aHUS treated with ravulizumab. No unexpected AEs, meningococcal infections or deaths were reported during ravulizumab treatment. These data provide evidence for the long-term safety of ravulizumab in patients with aHUS who switched from eculizumab and reinforce the positive benefit–risk profile of ravulizumab.

A Minimal PBPK/PD Model with Expansion-Enhanced Target-Mediated Drug Disposition to Support a First-in-Human Clinical Study Design for a FLT3L-Fc Molecule.

FLT3L-Fc is a half-life extended, effectorless Fc-fusion of the native human FLT3-ligand. In cynomolgus monkeys, treatment with FLT3L-Fc leads to a complex pharmacokinetic/pharmacodynamic (PK/PD) relationship, with observed nonlinear PK and expansion of different immune cell types across different dose levels. A minimal physiologically based PK/PD model with expansion-enhanced target-mediated drug disposition (TMDD) was developed to integrate the molecule's mechanism of action, as well as the complex preclinical and clinical PK/PD data, to support the preclinical-to-clinical translation of FLT3L-Fc. In addition to the preclinical PK data of FLT3L-Fc in cynomolgus monkeys, clinical PK and PD data from other FLT3-agonist molecules (GS-3583 and CDX-301) were used to inform the model and project the expansion profiles of conventional DC1s (cDC1s) and total DCs in peripheral blood. This work constitutes an essential part of our model-informed drug development (MIDD) strategy for clinical development of FLT3L-Fc by projecting PK/PD in healthy volunteers, determining the first-in-human (FIH) dose, and informing the efficacious dose in clinical settings. Model-generated results were incorporated in regulatory filings to support the rationale for the FIH dose selection.

Elucidating nonlinear pharmacokinetics of telmisartan: Integration of target-mediated drug disposition and OATP1B3-mediated hepatic uptake in a physiologically based model.

Telmisartan, a selective inhibitor of angiotensin II receptor type 1 (AT1), demonstrates nonlinear pharmacokinetics (PK) when orally administered in ascending doses to healthy volunteers, but the underlying mechanisms remain unclear. This study presents a physiologically based pharmacokinetic model integrated with target-mediated drug disposition (TMDD-PBPK model) to explore the mechanism of its nonlinear PK. We employed the Cluster-Gauss Newton method for top-down analysis, estimating the invivo Km,OATP1B3 (Michaelis-Menten constant for telmisartan hepatic uptake via Organic Anion Transporting Polypeptide 1B3) to be 2.0-5.7 nM. This range is significantly lower than the reported invitro value of 810 nM, obtained in 0.3% human serum albumin (HSA) conditions. Further validation was achieved through invitro assessment in plated human hepatocytes with 4.5% HSA, showing a Km of 4.5 nM. These results underscore the importance of albumin-mediated uptake effect for the hepatic uptake of telmisartan. Our TMDD-PBPK model, developed through a "middle-out" approach, underwent sensitivity analysis to identify key factors in the nonlinear PK of telmisartan. We found that the nonlinearity in the area under the concentration-time curve (AUC) and/or maximum concentration (Cmax) of telmisartan is sensitive to Km,OATP1B3 across all dosages. Additionally, the dissociation constant (Kd) for telmisartan binding to the AT1 receptor, along with its receptor abundance, notably influences PK at lower doses (below 20 mg). In conclusion, the nonlinear PK of telmisartan appears primarily driven by hepatic uptake saturation across all dose ranges and by AT1-receptor binding saturation, notably at lower doses.

Note on importance of correct stoichiometric assumptions for modeling of monoclonal antibodies.

Pharmacokinetic modeling of monoclonal antibodies (mAbs) with non-linear binding is based on equations of the target-mediated drug disposition (Mager and Jusko, J Pharmacokinet Pharmacodyn 28:507-532, 2001). These equations demonstrated their utility in countless examples and drug development programs. The model assumes that the mAb drug and the target have only one binding site each while, in reality, most antibodies have two binding sites. Thus, the currently used model does not correspond to the biological process that it aims to describe. The correct mechanistic model should take into account both binding sites. We investigated, using simulations, whether this discrepancy is important and when it is advisable to use a model with correct stoichiometric 2-to-1 ratio. We show that for soluble targets when elimination rate of the drug-target complex is comparable with the elimination rate of the drug or lower, and when measurements of both total drug and total target concentrations are available, the model with 1-to-1 (monovalent) binding cannot describe data simulated from the model with 2-to-1 (bivalent) binding. In these cases, models with correct stoichiometric assumptions may be necessary for an adequate description of the observed data. Also, a model with allosteric binding that encompasses both 2-to-1 and 1-to-1 binding models as particular cases was proposed and applied. It was shown to be identifiable given the detailed concentration data of total drug and total target.

Validity conditions of approximations for a target-mediated drug disposition model: A novel first-order approximation and its comparison to other approximations.

Target-mediated drug disposition (TMDD) is a phenomenon characterized by a drug's high-affinity binding to a target molecule, which significantly influences its pharmacokinetic profile within an organism. The comprehensive TMDD model delineates this interaction, yet it may become overly complex and computationally demanding in the absence of specific concentration data for the target or its complexes. Consequently, simplified TMDD models employing quasi-steady state approximations (QSSAs) have been introduced; however, the precise conditions under which these models yield accurate results require further elucidation. Here, we establish the validity of three simplified TMDD models: the Michaelis-Menten model reduced with the standard QSSA (mTMDD), the QSS model reduced with the total QSSA (qTMDD), and a first-order approximation of the total QSSA (pTMDD). Specifically, we find that mTMDD is applicable only when initial drug concentrations substantially exceed total target concentrations, while qTMDD can be used for all drug concentrations. Notably, pTMDD offers a simpler and faster alternative to qTMDD, with broader applicability than mTMDD. These findings are confirmed with antibody-drug conjugate real-world data. Our findings provide a framework for selecting appropriate simplified TMDD models while ensuring accuracy, potentially enhancing drug development and facilitating safer, more personalized treatments.

Characterizing the Nonlinear Pharmacokinetics and Pharmacodynamics of BI 187004, an 11β-Hydroxysteroid Dehydrogenase Type 1 Inhibitor, in Humans by a Target-Mediated Drug Disposition Model.

BI 187004, a selective small-molecule inhibitor of 11β-hydroxysteroid dehydrogenase-1 (11β-HSD1), displayed complex nonlinear pharmacokinetics (PK) in humans. Following nine single oral doses, BI 187004 exhibited nonlinear PK at low doses and linear PK at higher doses. Notably, substantial hepatic 11β-HSD1 inhibition (50%) was detected in a very low-dose group, achieving a consistent 70% hepatic enzyme inhibition in subsequent ascending doses without any dose-dependent effects. The unusual PK and PD profiles of BI 187004 suggest the presence of pharmacological target-mediated drug disposition (TMDD), arising from the saturable binding of BI 187004 compound to its high-affinity and low-capacity target 11β-HSD1. The non-intuitive dose, exposure, and response relationship for BI 187004 pose a significant challenge in rational dose selection. This study aimed to construct a TMDD model to explain the complex nonlinear PK behavior and underscore the importance of recognizing TMDD in this small-molecule compound. Among the various models explored, the best model was a two-compartment TMDD model with three transit absorption components. The final model provides insights into 11β-HSD1 binding-related parameters for BI 187004, including the total amount of 11β-HSD1 in the liver (estimated to be 8000 nmol), the second order association rate constant (estimated to be 0.102 nM-1h-1), and the first-order dissociation rate constant (estimated to be 0.11h-1). Our final population PK model successfully characterized the intricate nonlinear PK of BI 187004 across a wide dose range. This modeling work serves as a valuable reference for the rational selection of the dose regimens for BI 187004's future clinical trials.

Target-mediated drug disposition model for drugs with N > 2 binding sites that bind to a target with one binding site.

The paper extended the TMDD model to drugs with more than two (N > 2) identical binding sites (N-to-one TMDD). The quasi-steady-state (N-to-one QSS), quasi-equilibrium (N-to-one QE), irreversible binding (N-to-one IB), and Michaelis-Menten (N-to-one MM) approximations of the model were derived. To illustrate properties of new equations and approximations, N = 4 case was investigated numerically. Using simulations, the N-to-one QSS approximation was compared with the full N-to-one TMDD model. As expected, and similarly to the standard TMDD for monoclonal antibodies (mAb), N-to-one QSS predictions were nearly identical to N-to-one TMDD predictions, except for times of fast changes following initiation of dosing, when equilibrium has not yet been reached. Predictions for mAbs with soluble targets (slow elimination of the complex) were simulated from the full 4-to-one TMDD model and were fitted to the 4-to-one TMDD model and to its QSS approximation. It was demonstrated that the 4-to-one QSS model provided nearly identical description of not only the observed (simulated) total drug and total target concentrations, but also unobserved concentrations of the free drug, free target, and drug-target complexes. For mAb with a membrane-bound target, the 4-to-one MM approximation adequately described the data. The 4-to-one QSS approximation converged 8 times faster than the full 4-to-one TMDD.

Reducing target binding affinity improves the therapeutic index of anti-MET antibody-drug conjugate in tumor bearing animals.

Many oncology antibody-drug conjugates (ADCs) have failed to demonstrate efficacy in clinic because of dose-limiting toxicity caused by uptake into healthy tissues. We developed an approach that harnesses ADC affinity to broaden the therapeutic index (TI) using two anti-mesenchymal-epithelial transition factor (MET) monoclonal antibodies (mAbs) with high affinity (HAV) or low affinity (LAV) conjugated to monomethyl auristatin E (MMAE). The estimated TI for LAV-ADC was at least 3 times greater than the HAV-ADC. The LAV- and HAV-ADCs showed similar levels of anti-tumor activity in the xenograft model, while the 111In-DTPA studies showed similar amounts of the ADCs in HT29 tumors. Although the LAV-ADC has ~2-fold slower blood clearance than the HAV-ADC, higher liver toxicity was observed with HAV-ADC. While the SPECT/CT 111In- and 124I- DTPA findings showed HAV-ADC has higher accumulation and rapid clearance in normal tissues, intravital microscopy (IVM) studies confirmed HAV mAb accumulates within hepatic sinusoidal endothelial cells while the LAV mAb does not. These results demonstrated that lowering the MET binding affinity provides a larger TI for MET-ADC. Decreasing the affinity of the ADC reduces the target mediated drug disposition (TMDD) to MET expressed in normal tissues while maintaining uptake/delivery to the tumor. This approach can be applied to multiple ADCs to improve the clinical outcomes.

Dosing optimization of rituximab for primary membranous nephropathy by population pharmacokinetic and pharmacodynamic study.

Primary membranous nephropathy (PMN) is the most common cause for adult nephrotic syndrome. Rituximab has demonstrated promising clinical efficacy by random controlled trials and the off-label use is widely adopted in PMN. However, the standard dosage is borrowed from B cell lymphoma treatment with far more antigens and is oversaturated for PMN treatment, accompanied with additional safety risk and unnecessary medical cost. More than 15% serious adverse events were observed under standard dosage and low dose therapies were explored recently. Dose optimization by clinical trials is extremely time- and cost-consuming and can be significantly accelerated with the aid of model-informed drug development. Here, we aim to establish the first population pharmacokinetic and pharmacodynamic (PPK/PD) model for rituximab in PMN to guide its dosage optimization. Rituximab pharmacokinetic and pharmacodynamic data from 41 PMN patients in a retrospective study under a newly proposed monthly mini-dose were used to construct quantitative dose-exposure-response relationship via mechanistic target-mediated drug disposition (TMDD) model followed by regression between the reduction of anti-PLA2R titer and time after the treatment. The final model, validated by goodness-of-fit plots, visual predictive checks and bootstrap, was used to recommend the optimized dosing regimen by simulations. The model was well validated for PK/PD prediction. The systemic clearance and half-life are 0.54L/h and 14.7 days, respectively. Simulation of a novel regimen (6 monthly doses of 100mg) indicated the comparable ability and superior duration time of CD20+ B cell depletion compared with standard dosage, while the cumulative dosage and safety risk was significantly decreased. We established the first PPK/PD model and provide evidence to support the dosage optimization based on monthly mini-dose. Our study can also efficiently accelerate dosage optimization of novel anti-CD20 antibodies in PMN and other indications.

Confounding mitigation for the exposure-response relationship of bevacizumab in colorectal cancer patients.

The exposure-response relationship of bevacizumab may be confounded by various factors, including baseline characteristics, time-dependent target engagement and recursive relationships between exposure and response, requiring effective mitigation. This study aimed to investigate the exposure-response relationships of bevacizumab in metastatic colorectal cancer (mCRC) patients while mitigating potential biases. Bevacizumab pharmacokinetics was described using target-mediated drug disposition modelling. Relationships between target kinetics, progression-free (PFS) and overall (OS) survivals were assessed using joint pharmacokinetic and parametric hazard function models. Both prognostic-driven and response-driven potential biases were mitigated. These models evaluated the impact of increased antigen target levels, clearance and intensified dosing regimen on survival. Estimated target-mediated pharmacokinetic parameters in 130 assessed patients were baseline target levels (R0 = 8.4nM), steady-state dissociation constant (KSS = 10 nM) and antibody-target complexes elimination constant (kint = 0.52 day-1). The distribution of R0 was significantly associated with increased baseline concentrations of carcinoembryonic antigen, circulating vascular endothelial growth factor and the presence of extrahepatic metastases. Unbound target levels (R) significantly influenced both progression and death hazard functions. Increasing baseline target levels and/or clearance values led to decreased bevacizumab unbound concentrations, increased R levels and shortened PFS and OS, while increasing bevacizumab dose led to decreased R and longer survival. This study is the first to demonstrate the relationship between bevacizumab concentrations, target involvement and clinical efficacy by effectively mitigating potential sources of bias. Most of the target amount may be tumoural in mCRC. Future studies should provide a more in-depth description of this relationship.

Formation and clearance of TNF-TNF inhibitor complexes during TNF inhibitor treatment.

Millions of patients with inflammatory diseases are treated with tumour necrosis factor (TNF) inhibitors (TNFi). Individual treatment response varies, in part related to variable drug clearance. The role of TNF-TNFi complexes in clearance of the different TNFi is controversial. Moreover, mechanistic insight into the structural aspects and biological significance of TNF-TNFi complexes is lacking. We hypothesized a role for Fc-mediated clearance of TNF-TNFi immune complexes. Therefore, we investigated circulating TNF-TNFi complexes upon treatment with certolizumab-lacking Fc tails-in comparison with adalimumab, golimumab, infliximab and etanercept. Drug-tolerant ELISAs were developed and used to quantify TNF during adalimumab, golimumab, etanercept, certolizumab and infliximab treatment in patients with inflammatory arthritis or ulcerative colitis for a maximum follow-up of 1 year. Effects on in vitro TNF production and Fc-mediated uptake of TNF-TNFi complexes were investigated for all five TNFi. Circulating TNF concentrations were >20-fold higher during certolizumab treatment compared with adalimumab, reaching up to 23.1 ng·ml-1 . Internalization of TNF-TNFi complexes by macrophages depended on Fc valency, with efficient uptake for the full antibody TNFi (three Fc tails), but little or no uptake for etanercept and certolizumab (one and zero Fc tail, respectively). TNF production was not affected by TNFi. Total TNF load did not affect clearance rate of total TNFi. Differences in TNFi structure profoundly affect clearance of TNF, while it is unlikely that TNF itself significantly contributes to target-mediated drug disposition of TNFi.

Abstract A138: Preclinical pharmacokinetic-pharmacodynamic modeling guides setting of the human starting dose of DS-1471a, a novel anti-CD147 antibody

Abstract Background: CD147 is a member of the immunoglobulin superfamily that is highly expressed in various cancers and is involved in growth, metastasis, and activation of inflammatory signals in cancer cells. DS-1471a is a novel humanized anti-human CD147 monoclonal antibody under development as an anticancer agent. In this study, pharmacokinetic (PK)-pharmacodynamic (PD) analysis of DS-1471a was conducted to set the dose and dosing regimen for first-in-human (FIH) study. The safety profile of DS-1471a was also assessed in cynomolgus monkeys. Methods: Preclinical pharmacological study was conducted in xenograft model mice transplanted with MIA PaCa-2 cells by intravenous (IV) administration of DS-1471a, and receptor occupancy (RO) of CD147 in tumor was measured. Monkey PK and RO in blood were measured after the IV administration of DS-1471a. The expression levels of CD147 in hepatocytes and erythrocytes in monkeys and humans were measured to estimate the species differences. Using monkey PK, RO, and CD147 expression data, a minimal physiologically based pharmacokinetic (PBPK) model was constructed. Subsequently, PK and RO profiles in humans were predicted by replacing physiological parameters and CD147 expression levels with human values. For the safety assessment, DS-1471a was intravenously administered to monkeys every 2 weeks for 1 month. Results: In xenograft model mice, DS-1471a exhibited partial and potent antitumor activity at 1 and 3 mg/kg, respectively. At those doses, RO in tumor the day after dosing was 18% (1 mg/kg) and 89% (3 mg/kg). In monkeys, non-linear PK was observed, owing to high expression of CD147 in erythrocytes, resulting in target-mediated drug disposition. Compared to the findings in monkeys, the human expression level of CD147 was lower in erythrocytes and higher in hepatocytes. PBPK modeling, incorporating species differences in CD147 expression levels, projected that RO in tumor after the IV administration of DS-1471a to humans would reach 20%, 50%, and 90% at 2 day after injection at 0.3, 1, and 3 mg/kg, respectively. In the monkey toxicity study, DS-1471a was well tolerated at up to 158.4 mg/kg (human equivalent dose of 51 mg/kg). Conclusions: Based on preclinical PK-PD analysis and safety study of DS-1471a, the starting dose in FIH study was set to 1 mg/kg as a safe and efficacious dose. Citation Format: Miki Yokoyama, Masataka Oitate, Ken Sakurai, Takuma Iguchi, Katja Damme, Kayoko Nanai, Keisuke Fukuchi. Preclinical pharmacokinetic-pharmacodynamic modeling guides setting of the human starting dose of DS-1471a, a novel anti-CD147 antibody [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A138.

Pharmacokinetic/LDL-C and exposure-response analysis of tafolecimab in Chinese hypercholesterolemia patients: Results from phase I, II, and III studies.

Tafolecimab, a novel fully human monoclonal antibody targeting PCSK9, has been assessed in Chinese healthy volunteers and patients with hypercholesterolemia. This analysis is to develop and qualify a population pharmacokinetics (PopPKs)/LDL-C model to characterize tafolecimab PK and LDL-C profiles, evaluate the impact of potential covariates on tafolecimab, estimate individual predicted exposure, and LDL-C decreasing, furthermore, explore exposure-response relationship to support clinical use. Data from six clinical trials in China were used to develop the PopPK/LDL-C model. A Michaelis-Menten approximation of the target-mediated drug disposition (TMDD) model was used to describe PK data and indirect response (IDR) model was developed to estimate the LDL-C profile. A stochastic approximation expectation maximization algorithm was applied to estimate PopPK/LDL-C parameters. The PK/LDL-C time course data for tafolecimab were well described by TMDD/IDR model. Baseline covariates resulting in statistically significant changes in PK/LDL-C parameters included: body weight and sex on absorption rate constant; body weight, sex, and unbound PCSK9 on central volume; body weight and sex on clearance; baseline LDL-C on first-order rate constants for the removal of an effect); and disease and sex on maximum effect. However, the magnitudes of changes associated with these covariates do not necessitate dose adjustment. Exposure-efficacy relationship indicated that the nadir of LDL-C reduction achieved with the steady-state trough plasma concentration (Ctrough ) of tafolecimab at 5 μg/mL, and no further LDL-C decreasing with the increasing Ctrough . There was no exposure dependency observed in exposure-safety exploration. The PopPK/LDL-C model was successfully developed, validated, and predicted tafolecimab/LDL-C concentrations and individual exposures.

Population Pharmacokinetics of Subcutaneous Epcoritamab in Relapsed or Refractory B-Cell Non-Hodgkin Lymphoma

Background: The US FDA approved epcoritamab SC, a CD3xCD20 bispecific antibody developed using the DuoBody ® platform, in May 2023 for the treatment of adults with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL), not otherwise specified, including DLBCL arising from indolent lymphoma, and high-grade B-cell lymphoma after at least 2 lines of systemic therapy. Here we report the results of a population pharmacokinetic (PK) model-based analysis using data from 2 phase 1/2 clinical trials (EPCORE™ NHL-1 [NCT03625037] and EPCORE NHL-3 [NCT04542824]) evaluating epcoritamab in patients with R/R B-cell non-Hodgkin lymphoma (B-NHL). Methods: In EPCORE NHL-1 dose expansion and EPCORE NHL-3, epcoritamab SC was administered QW during weeks 1-12 (cycles 1-3), Q2W during weeks 13-36 (cycles 4-9), and Q4W thereafter (cycles ≥10). In EPCORE NHL-1 dose escalation, dosing was QW in cycles 1 and 2, Q2W in cycles 3‒6, and Q4W in cycles ≥7. Patients received step-up priming (0.004-0.16 mg), intermediate (0.25-1.6 mg), and full (0.0128-60 mg) doses. A total of 6819 quantifiable PK observations were collected and analyzed from 327 patients (large B-cell lymphoma [LBCL], n=212; indolent B-NHL, n=97; and mantle cell lymphoma, n=18) who received epcoritamab SC. Nonlinear mixed-effects modeling was used for data analysis. Results: The PK of epcoritamab following SC administration in patients with R/R B-NHL were adequately characterized by a quasi-steady state approximation of a 2-compartment target-mediated drug disposition model with first-order absorption. Among patients with R/R LBCL who received the recommended full dose (48 mg) in EPCORE NHL-1, the estimated median time of maximum concentration (t max) was 4 days (range, 0.3-7) after the first full dose and 2.3 days (range, 0.3-3.2) at the end of weekly dosing (end of cycle 3). The geometric mean (coefficient of variation [CV] %) of the apparent total volume of distribution was 25.6 L (82%). Epcoritamab exposure increased more than proportionally over the range of full doses up to the recommended full dose (1.5-48 mg). For the 48-mg full dose of epcoritamab, the geometric mean (CV%) of terminal half-life at the end of cycle 3 was 22 days (58%), while the geometric mean (CV%) of apparent total clearance after the end of cycle 3 was 0.53 L/day (40%). Body weight was a statistically significant covariate on apparent clearance and central and peripheral volumes of distribution, and age was significant on absorption rate; however, no association was identified between body weight or age and clinical efficacy or safety. After accounting for body weight, no statistically significant effects on epcoritamab PK were observed for age, sex, race, renal or hepatic function, or other disease characteristics. The risk of immunogenicity was low; antidrug antibodies (ADAs) were detected in only 4 (2.6%) of 156 evaluable patients treated with the approved 0.16/0.8/48-mg dosing regimen. No clinically meaningful differences in epcoritamab exposure were observed between ADA-positive patients and ADA-negative patients. Conclusions: The population PK model appropriately characterized epcoritamab PK in R/R B-NHL. No dosage adjustments are recommended in subpopulations based on body weight, age, sex, race, mild to moderate renal impairment, or mild hepatic impairment.

Preliminary Results of a Phase 1, First-in-Human Study of INA03, an Anti-CD71 Antibody-Drug Conjugate in Patients with Relapsed or Refractory (R/R) Acute Leukemias

Background: Relapsed or refractory (R/R) acute leukemias (AL) represent major therapeutic challenges. Several reports have highlighted the deregulation of iron metabolism in various proliferative tumor models (and notably AL) which includes the over-expression of the transferrin receptor (TfR1/CD71). Our strategy is thus to harness CD71 overexpression to specifically target cytotoxic agents to leukemic cells. INA03 is an antibody drug conjugate (ADC) constituted of a humanized monoclonal IgG 4 against CD71 and MMAE. We herein report the preliminary safety and efficacy data of a phase 1 trial INA03 (NCT03957915) evaluating INA03 in R/R AL. Methods: INA03 is given as 30 minutes IV infusion on days 1 (Loading dose,LD) followed by maintenance injections on D15 for cycle 1 and on D1 and D15 of cycle 2 and beyond. Eligibility criteria are age >18y, ECOG<2, R/R AL after at least one line of treatment with high dose chemotherapy and/or Vidaza and Venetoclax (VEN), LVEF>50%, Creatinine Clearance >30ml/min, normal liver function. The study design is based on a continuous reassessment method and includes 2 parts: a Loading Dose (LD) Titration study (Part 1, completed), followed by a Dose Escalation Part 2. During Part 1, sequential cohorts of 2 pts were included to receive ascending LD of INA03 followed by repeated fixed doses of INA03 to deal with a potential sink effect related to the high expression of CD71 in normal erythroblasts. During Part 2, sequential cohorts of 3 pts received escalating doses of INA03 Q2 weeks in 28-day cycles. The objectives were to establish the maximal tolerated dose (MTD) for subsequent administration and both safety/tolerability and anti-leukemic activity. Results: With a cutoff date of July 05, 2023, 27 patients (pts) across 10 cohorts were included in the study. The median age was 73 (range: 39 - 83), 25 (93%) pts had AML and two (7%) had ALL. Four (14.8%) pts had a prior allogeneic stem cell transplantation and 18 (66.6%) had prior VEN exposure. Pts received escalating doses of INA03 of 0.02 mg/kg to 3 mg/kg. Two patients in the 3 mg/kg loading dose cohort presented a dose limiting toxicity (DLT), one with grade 3 toxic erythema, grade 3 hepatitis and grade 3 mucositis and one with grade 4 colonic perforation. Up to the 2.5 mg/kg dose, no grade 2-4 treatment emerging adverse events (TEAE) were observed among the 19 evaluable pts and only one related grade 1 TEAE (hyperkalemia/phosphatemia) was reported. Transient decrease of reticulocyte count and erythroblasts percentage were observed at 0.5 mg/kg and above. Blasts reductions were seen in 6/20 (30%) evaluable pts at dose > 1 mg/kg including two partial responses according to ELN 2022 classification. MMAE pharmacokinetics (PK) appears dose-proportional with a small accumulation after repeated IV, while INA03 PK exhibits target-mediated drug disposition without accumulation. Conclusions: The preliminary results of this phase 1 study indicate that INA03 is well tolerated for doses up to 2.5 mg/kg. Induction of transient erythroblastopenia indicates effective targeting of CD71 in vivo and early signs of antileukemic efficacy have been observed in patients with refractory AL. Inclusion in the trial are continuing and additional data will be presented.

Target Reserve and Turnover Parameters Determine Rightward Shift of Enalaprilat Potency From its Binding Affinity to the Angiotensin Converting Enzyme

Drug effects are often assumed to be directly proportional to the fraction of occupied targets. However, for a number of antagonists that exhibit target-mediated drug disposition (TMDD), such as angiotensin-converting enzyme (ACE) inhibitors, drug binding to the target at low concentrations may be significant enough to influence pharmacokinetics but insufficient to elicit a drug response (i.e., differences in drug-target binding affinity and potency). In this study, a pharmacokinetic/pharmacodynamic model for enalaprilat was developed in humans to provide a theoretical framework for assessing the relationship between ex vivo drug potency (IC50) and in vivo target-binding affinity (KD). The model includes competitive binding of angiotensin I and enalaprilat to ACE and accounts for the circulating target pool. Data were obtained from the literature, and model fitting and parameter estimation were conducted using maximum likelihood in ADAPT5. The model adequately characterized time-courses of enalaprilat concentrations and four biomarkers in the renin-angiotensin system and provided estimates for in vivo KD (0.646 nM) and system-specific parameters, such as total target density (32.0 nM) and fraction of circulating target (19.8%), which were in agreement with previous reports. Model simulations were used to predict the concentration-effect curve of enalaprilat, revealing a 6.3-fold increase in IC50 from KD. Additional simulations demonstrated that target reserve and degradation parameters are key factors determining the extent of shift of enalaprilat ex vivo potency from its in vivo binding affinity. This may be a common phenomenon for drugs exhibiting TMDD and has implications for translating binding affinity to potency in drug development.

Low-dimensional neural ODEs and their application in pharmacokinetics

Machine Learning (ML) is a fast-evolving field, integrated in many of today’s scientific disciplines. With the recent development of neural ordinary differential equations (NODEs), ML provides a new tool to model dynamical systems in the field of pharmacology and pharmacometrics, such as pharmacokinetics (PK) or pharmacodynamics. The novel and conceptionally different approach of NODEs compared to classical PK modeling creates challenges but also provides opportunities for its application. In this manuscript, we introduce the functionality of NODEs and develop specific low-dimensional NODE structures based on PK principles. We discuss two challenges of NODEs, overfitting and extrapolation to unseen data, and provide practical solutions to these problems. We illustrate concept and application of our proposed low-dimensional NODE approach with several PK modeling examples, including multi-compartmental, target-mediated drug disposition, and delayed absorption behavior. In all investigated scenarios, the NODEs were able to describe the data well and simulate data for new subjects within the observed dosing range. Finally, we briefly demonstrate how NODEs can be combined with mechanistic models. This research work enhances understanding of how NODEs can be applied in PK analyses and illustrates the potential for NODEs in the field of pharmacology and pharmacometrics.

Role of Statistical Physics Formalism in Pharmaceutical Science

Abstract: Statistical physics (SP) formalism in medicine involves applying concepts and methods to study biological systems and medical problems. It is an interdisciplinary field that combines physics, mathematics, and biology to analyze complex biological processes at molecular, cellular, and tissue levels. The goal of SP in medicine is to gain insights into biological systems' mechanisms and develop new strategies for diagnosing and treating diseases. SP is used in drug discovery, disease modeling, medical imaging, and the study of pharmaceutical systems in pharmacy. SP is applied to understand the anticoagulant properties of substances by modeling interactions between blood components and studying blood properties affecting coagulation. For antiviral drugs, SP models simulate interactions between antiviral molecules, virus particles, and other biological components to optimize drug efficacy. SP models are also used in studying antifungals, antibiotics, and anticancer drugs to understand drug behavior in complex systems and improve treatments. In PS, mathematical models are used for drug absorption, dosage regimens, target-mediated drug disposition, population pharmacokinetics, and physiological-based pharmacokinetic modeling and simulation (PBPK). In rheology, SP is applied to study the flow and deformation of materials like liquids and semi-solids. In understanding physicochemical principles/processes, SP helps predict and explain the behavior of systems with many particles, such as solutions, solubilization, and adsorption. For drug delivery systems, SP is used to study drug transport and distribution in the body, improving drug efficacy and safety. Metal nanocomposites are studied using SP to understand their behavior as antibacterial agents and anticoagulants. SP models predict the mechanical, electrical, and thermal properties of metal nanocomposites for various applications.

Factors contributing to the nonlinear pharmacokineticsof astegolimab: a close examination of potential causes.

Aim: This paper describes a case study of an antibody therapeutic targeting a membrane-bound receptor, also present in systemic circulation, as a soluble receptor. During phase I studies of astegolimab, nonlinear pharmacokinetics (PKs) were observed. We investigated the potential contribution of antidrug antibodies, target-mediated drug dispositionand assay format. Materials & methods: A more target-tolerant assay was developed, and a subset of phase I samples were evaluated in both free and total PK assay formats. Results & conclusion: Our results demonstrate that there were two main contributors to PK nonlinearity: soluble target interference in the free PK assay, in addition to target-mediated drug disposition. Antidrug antibody status did not significantly impact PK.

A Quantitative Systems Pharmacology Model of the Incretin Hormones GIP and GLP1, Glucagon, Glucose, Insulin, and the Small Molecule DPP-4 Inhibitor, Linagliptin

In the current study, we established a comprehensive quantitative systems pharmacology (QSP) model using linagliptin as the model drug, where drug disposition, drug intervention on dipeptidyl peptidase-4 (DPP-4), glucose-dependent insulinotropic peptide (GIP), Glucagon-like peptide-1 (GLP-1), glucagon, glucose, and insulin are integrated together with the cross talk and feedback loops incorporated among the whole glycemic control system. In the final linagliptin QSP model, the complicated disposition of linagliptin was characterized by a 2-compartment pharmacokinetic (PK) model with an enterohepatic cycling (EHC) component as well as target-mediated drug disposition (TMDD) processes occurring in both tissues and plasma, and the inhibitory effect of linagliptin on DPP-4 was determined by the linagliptin-DPP-4 complex in the central compartment based on target occupancy principle. The integrated GIP-GLP1-glucagon-glucose-insulin system contains five indirect response models as the “skeleton” structure with 12 feedback loops incorporated within the glucose control system. Our model adequately characterized the substantial nonlinear PK of linagliptin, time course of DPP-4 inhibition, as well as the kinetics of GIP, GLP-1, glucagon, and glucose simultaneously in humans. Our model provided valuable insights on linagliptin pharmacokinetics/pharmacodynamics and complicated glucose homeostasis. Since the glucose regulation modeling framework within the QSP model is “drug-independent”, our model can be easily adopted by others to evaluate the effect of other DPP-4 inhibitors on the glucose control system. In addition, our QSP model, which contains more components than other reported glucose regulation models, can potentially be used to evaluate the effect of combination antidiabetic therapy targeting different components of glucose control system.