The AAPS Journal[JOURNAL]
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200 papers
High Concordance of Total Antibody and Transduction Inhibition Assays Enables Replacement of Cell-Based Antibody Testing for Preexisting Anti-AAV Immunity in Cynomolgus Monkey.
Neff F, Antony M, Merz J … +3 more , Ros F, Wessels U, Stubenrauch KG
AAPS J · 2026 May · PMID 42091787 · Publisher ↗
Testing for preexisting anti-AAV immunity in non-human primates constitutes an essential part of screening procedures for nonclinical studies with gene therapy, which is customary performed using transduction inhibition...
Testing for preexisting anti-AAV immunity in non-human primates constitutes an essential part of screening procedures for nonclinical studies with gene therapy, which is customary performed using transduction inhibition (TI) assays. These assays cause high costs and a significant operational burden owing to their complexity and low throughput. However, broader implementation of more practical total antibody assays (TAb) is hindered by the lack of conclusive data demonstrating assays comparability in non-human primates. To determine whether TAb assays can serve as a viable alternative to TI assays for anti-AAV screening in monkeys, we conducted a comparative study for two AAV serotypes (AAV2 and AAV9), with tailored specificity control measures incorporated in both assay formats. Both the TI and TAb assays showed a high concordance in detection of preexisting anti-AAV immunity in cynomolgus monkey. The presented TAb assay offers a simple, cost- and time-saving alternative to TI assays for pre-study testing of non-human primates. The use of such TAb assays can thus result in concordant animal enrollment at lower cost and greater speed as compared to TI-based screening tests.
Evaluating the Utility and Constraints of the Competitive Counter Flow (CCF) Assay in OATP1B1 Substrate Profiling.
Mathialagan S, West MA, Yamaguchi E … +7 more , Moulton HM, Kapinos B, Paryad Zanjani S, Tess DA, Kimoto E, Varma MVS, Yee SW
AAPS J · 2026 May · PMID 42091780 · Publisher ↗
The organic anion transporting polypeptide 1B1 (OATP1B1) plays a critical role in hepatic uptake of a wide range of high- and low-permeability, anionic molecules, particularly those in Extended Clearance Classification S...
The organic anion transporting polypeptide 1B1 (OATP1B1) plays a critical role in hepatic uptake of a wide range of high- and low-permeability, anionic molecules, particularly those in Extended Clearance Classification System (ECCS) Classes 1 and 3. However, conventional uptake assays using HEK293 cells overexpressing OATP1B1 can yield false-negative results, especially for highly permeable, lipophilic anionic or zwitterionic compounds, where passive diffusion and nonspecific binding may mask transporter-mediated uptake. In this study, we applied the competitive counterflow (CCF) assay to evaluate 58 compounds across different ECCS classes. The assay measures steady-state changes in intracellular [3H]-estradiol-17β-glucuronide retention following exposure to test compounds across multiple concentrations. Several known OATP1B1 substrates, exhibited more than 50% loss of intracellular [3H]-estradiol-17β-glucuronide at one or more concentrations compared to control. Using a three-tier classification based on tracer retention across multiple concentrations, the assay demonsrated high sensitivity for detecting compounds that are OATP1B1 substrates. Notably, the CCF assay enabled identification of four xenobiotics-bumetanide, candesartan, naringin and sulfasalazine-not previously recognized as OATP1B1 substrates using OATP1B1 uptake assay. Overall, this work provides a comprehensive evaluation of the CCF assay as a complementary, early‑stage screening and triage tool for OATP1B1 substrate assessment. The findings underscore the importance of an integrative strategy that combines CCF data with orthogonal in vitro and in vivo evidence to mitigate the risk of both false‑negative and false‑positive conclusions, particularly for ECCS Class 1B compounds where traditional overexpression systems show limited sensitivity.
Foreign Comparator Drug Products, Manufacturing & Supply Chain Considerations for Otic, Ophthalmic, And Parenteral Solutions - Generic Drugs Perspective.
Nana A, Hughes J, Dandamudi S … +2 more , Gong L, Braddy AC
AAPS J · 2026 May · PMID 42091779 · Publisher ↗
In the United States (US), only the Food and Drug Administration (FDA)-approved drug products serve as comparator products in bioequivalence (BE) studies. Using foreign comparator drug products raises concerns about comp...
In the United States (US), only the Food and Drug Administration (FDA)-approved drug products serve as comparator products in bioequivalence (BE) studies. Using foreign comparator drug products raises concerns about comparability to FDA-approved Reference Listed Drugs (RLD), particularly regarding quality standards and therapeutic equivalence. There is potential for differences in BE that may result from even slight differences between the foreign comparator and the US-approved RLD. Such discrepancies can compromise safety, efficacy, and product performance, undermining market access by disrupting manufacturing and supply chain operations for generic drug products. This paper examined biowaiver considerations, product-specific guidances, labeling requirements, and manufacturing guidelines from nine regulatory agencies: FDA, ANVISA (Brazil), COFEPRIS (Mexico), EMA (European Union), Health Canada (Canada), MHLW/PMDA (Japan), SAHPRA (South Africa), Swissmedic (Switzerland), and TGA (Australia). The analysis focused on foreign comparator drug product considerations for parenteral, otic, and ophthalmic solutions, identifying regulatory similarities and differences across jurisdictions. Generally, biowaivers for in vivo BE studies are considered acceptable for these drug products across jurisdictions. However, criteria for qualitative (Q1) and quantitative (Q2) sameness between generic and RLD formulations vary among regulatory agencies. Labeling requirements also differ, though Q1 information is typically mandated for inclusion. Regarding quality-related regulations-including specifications, container and closure systems, stability, storage conditions, and CMC post-approval changes-most regulatory authorities align with international guidelines, particularly ICH quality guidance documents. This alignment suggests potential harmonization opportunities while acknowledging jurisdictional variations in specific requirements for the utilization of foreign comparator products to establish BE for generic drug products.
De-risking Biopharma Asset Acquisition: Towards a Quantitative Framework for Strategic Decision-making.
Ma X, Lu Z, Zhao Y … +1 more , Sheng J
AAPS J · 2026 May · PMID 42091774 · Publisher ↗
The impending patent cliff projected between 2028-2030 poses significant commercial and strategic challenges for innovative pharmaceutical and biotechnology companies. To sustain growth and maintain competitive positioni...
The impending patent cliff projected between 2028-2030 poses significant commercial and strategic challenges for innovative pharmaceutical and biotechnology companies. To sustain growth and maintain competitive positioning, organizations are increasingly relying on strategic mergers, acquisitions, and partnerships to replenish pipelines. However, systematic quantitative strategies and framework for asset evaluation remain limited. This review outlines how clinical pharmacology and pharmacometrics (CPP) can support asset evaluation and decision-making during the asset due diligence. First, CPP spans the entire drug development continuum, providing a quantitative framework for evaluating external assets, including pharmacological plausibility, dosing feasibility, and overall development risks. Second, Model-informed drug development (MIDD) approaches can be applied to predict human pharmacokinetics, inform dose selection, and estimate the probability of technical and regulatory success. Third, we examine the emerging role of artificial intelligence and machine learning in asset evaluation and portfolio decision-making, by discovering prognostic and predictive factors, and identifying the patient sub-group. We also introduce NewCo as an emerging drug-development and business model, where quantitative strategies may be deployed. Further, we address cognitive biases, such as confirmation bias and sunk cost fallacies that can influence acquisition outcomes. Importantly, we propose the development of a bias-aware, fit-for-purpose corporate template to integrate CPP and MIDD insights, standardize evaluation criteria, and support cross-functional decision-making during asset due diligence. Embedding quantitative and bias-mitigated CPP frameworks into due diligence workflows, can help identify high-value opportunities, de-risk development uncertainties, and accelerate delivery of innovative therapies to patients with unmet medical needs.
Raltegravir Plasma Exposure: A Machine Learning-Based Model for its Prediction Using Limited Sampling Strategy.
De Lucca Thomaz M, de Azevedo KLR, Paz TA … +6 more , Nardotto GHB, de Lima Moreira F, Duarte G, Woillard JB, Lanchote VL, Ximenez JPB
AAPS J · 2026 May · PMID 42091773 · Publisher ↗
Recent studies have applied machine learning (ML)-based limited sampling strategies (LSS) to predict drug exposure (AUC), achieving low prediction error and performance comparable to or better than multiple linear regres...
Recent studies have applied machine learning (ML)-based limited sampling strategies (LSS) to predict drug exposure (AUC), achieving low prediction error and performance comparable to or better than multiple linear regression and population pharmacokinetics LSS. This study aimed to develop and validate a machine learning-based limited sampling strategy capable of predicting raltegravir (RAL) exposure. Four machine learning algorithms (XGBoost, Random Forest, GLMNet, and SVM) were trained using pharmacokinetic profiles generated via Monte Carlo simulation from a population pharmacokinetic (POPPK) model. Data were divided into training (75%) and test (25%) sets. All possible combinations of sampling times, pairs and triplets, in steady-state, up to 12 h post-dose were evaluated. Model performance was assessed by the lowest root mean square error (RMSE) in the cross-validation, and the best performing model was evaluated in the test set and externally validated using simulated PK profiles from an independent POPPK model and patient data from a clinical study. XGBoost trained with concentrations at 0.5, 2, and 4 h showed the best predictive performance. The model achieved excellent accuracy in the test set (bias/RMSE: 0.8%/8.7%) and in the independent simulation (1.9%/14.3%). Performance decreased in real patient data (5.0%/24.1%), highlighting the need for caution when extrapolating predictions to populations whose characteristics differ from those represented in the training datasets. A machine learning model using only three sampling timepoints has been developed and validated in different datasets, enabling accurate estimation of RAL AUC₀-₁₂. This approach provides a tool for pharmacokinetic and PK/PD studies and reduces intensive sampling need in clinical settings.
Control Strategy Considerations for the Continuous Manufacturing of Low-dose Oral Solid Dosage Formulations.
Dumarey M, Ruiz Samblás C, Bautista M … +3 more , Kim SS, Doddridge GD, Shier AP
AAPS J · 2026 May · PMID 42091770 · Publisher ↗
The adoption of Continuous Manufacturing (CM) for Oral Solid Dosages (OSD) is often challenged by the limited sensitivity of traditional Process Analytical Technology (PAT), such as Near-infrared (NIR) and Raman spectros...
The adoption of Continuous Manufacturing (CM) for Oral Solid Dosages (OSD) is often challenged by the limited sensitivity of traditional Process Analytical Technology (PAT), such as Near-infrared (NIR) and Raman spectroscopy, to provide sufficient accuracy for process monitoring and control of low-dose or fixed-dose formulations. This manuscript explores solutions by highlighting advanced control strategies and alternative manufacturing technologies. These strategies include enhanced spectroscopic methods (e.g., Spatially resolved-NIRS, Light-induced fluorescence) to provide improved accuracy/precision, the use of process data and process models (Residence Time Distribution, Multivariate Statistical Process Control) as soft sensors, hybrid PAT and process models and more traditional at-line/off-line monitoring using NIR, Raman or high-sensitivity liquid chromatography with stratified sampling and bracketing. Alternatively, several technologies inherently ensure high content uniformity, such as semi-Continuous Manufacturing (sCM) with accurate mini-batch dispensing and Dry Coating Technology. For Twin-Screw Hot Melt Extrusion (HME) molecular-level mixing delivers more uniform blends, but current low-dose applications still require pre-blending of the drug substance with suitable excipients. When fed with a uniform powder blend, twin screw wet granulation also ensures compliant content uniformity without the need for PAT monitoring. In conclusion, a successful CM of low dose products may be possible when strategically combining advanced spectral and data approaches, modelling, and innovative platforms to build robust and validated process controls. This has been demonstrated across multiple peer reviewed studies and is now gradually being incorporated into control strategies for the commercial manufacture of pharmaceutical products.
Blood-glucose Profile Evaluation with a Model-based Approach using Continuous Glucose Monitoring Data.
Kunina H, Chien JY, Garhyan P … +2 more , Geiser JS, Kjellsson MC
AAPS J · 2026 May · PMID 42091767 · Publisher ↗
Continuous glucose monitoring (CGM) is widely used in type 1 diabetes management. Although less common in type 2 diabetes (T2D), its application is increasing, especially among patients with T2D on insulin therapy. CGM p...
Continuous glucose monitoring (CGM) is widely used in type 1 diabetes management. Although less common in type 2 diabetes (T2D), its application is increasing, especially among patients with T2D on insulin therapy. CGM provides detailed, continuous glucose data that reveal daily glycemic fluctuations and help mitigate hyper- and hypoglycemic episodes. However, missing information on meal size and timing complicates the interpretation of data. To address these challenges, we propose a pharmacometric modeling approach that describes blood glucose profiles in patients with T2D receiving basal insulin in the absence of exact meal inputs. In this study, 73 individuals with T2D receiving insulin glargine plus oral antidiabetic medications (OAMs) underwent CGM assessments at four visits (Visit 3 on OAMs alone; Visits 13, 16, 20 on OAMs + insulin). Building upon the existing Integrated Glucose-Insulin (IGI) model, we incorporated a population meal model and an insulin glargine pharmacokinetic model, creating a comprehensive "meal-IGI-insulin" framework. The model identified three daily meal intakes, modeled as the sum of a surge function and a maximum bioavailable glucose amount of 7.83 g/hour. The model evaluation indicated adequate performance in predicting fasting blood glucose and HbA1c, though some discrepancies arose in forecasting hypoglycemic events. The developed modeling framework can facilitate prospective simulations of diverse meal patterns and insulin regimens, potentially accelerating antidiabetic drug development, simplify closed-loop automated insulin delivery algorithms, and optimize clinical strategies for patients with T2D.
Correction: Multicomponent Interactive Release (MIR) Model for Herbal Extract/Multidrug-Loaded Electrospun Nanofibers: A Mechanistic Framework Integrating Diffusion, Swelling, and Erosion.
Supaphol P
AAPS J · 2026 May · PMID 42091749 · Publisher ↗
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Quantitative Investigation of ATP Switch Concept of STA551 Through Combined In Vivo Tissue Distribution Studies and Physiologically Based Pharmacokinetic Modeling.
Nemoto T, Kuroi H, Shida-Kawazoe M … +1 more , Tachibana T
AAPS J · 2026 Apr · PMID 42026324 · Publisher ↗
STA551 is an anti-human CD137 (hCD137) switch antibody with adenosine triphosphate (ATP)-dependent antigen binding, developed to achieve potent anti-tumor effects and superior safety. Based on several reports, unlike in...
STA551 is an anti-human CD137 (hCD137) switch antibody with adenosine triphosphate (ATP)-dependent antigen binding, developed to achieve potent anti-tumor effects and superior safety. Based on several reports, unlike in normal tissues, high concentrations of ATP are considered to exist in the interstitial space of tumors, thus STA551 is expected to exhibit tumor-selective antigen (hCD137) binding (ATP switch concept). This study aims to quantitatively investigate this ATP switch concept in vivo by combining tissue distribution studies and physiologically based pharmacokinetic (PBPK) modeling. An iodinated conventional anti-hCD137 antibody, I-Ure-mIgG1, was administered as a tracer to tumor-bearing hCD137 knock-in (KI) mice. Co-administration of excess unlabeled Ure-mIgG1 at 20 mg/kg increased plasma tracer radioactivity levels and decreased the tissue-to-plasma (T/P) ratios in several normal tissues and tumors. However, co-administration of unlabeled Sta-MB (mouse surrogate antibody of STA551) at 1 or 20 mg/kg did not change the plasma tracer radioactivity levels but clearly reduced T/P ratios, mainly in tumors, strongly suggesting tumor-selective binding of Sta-MB. A PBPK model was developed to explain this distribution data, and parameters including non-specific clearance, interstitial uptake clearance, target-related parameters, and ATP switch molecule concentrations were estimated. Importantly, the ATP switch molecule concentration in the tumor interstitial space was estimated to reach approximately hundreds μM, with much lower concentrations in non-tumor tissues. In conclusion, this combination approach successfully demonstrated the ATP switch concept of STA551 in vivo. These findings will help guide clinical trials for STA551 and the development of future switch antibodies.
Natural Broccoli Sprout-Derived Exosomes Encapsulating Bioactive Molecules as a Novel Nanomedicine for Repair of Intestinal Inflammation.
Yang T, Canham S, Kasthuriarachchi T … +8 more , Kirkendall A, Kinney M, Rahman MA, Bae SH, Zhang T, Ishaq SL, Li Y, Bai S
AAPS J · 2026 Apr · PMID 42014622 · Publisher ↗
Dietary bioactives from broccoli sprouts exhibit anti-inflammatory properties in the prevention and management of inflammatory bowel disease (IBD), but are limited by instability during gastrointestinal (GI) transit and...
Dietary bioactives from broccoli sprouts exhibit anti-inflammatory properties in the prevention and management of inflammatory bowel disease (IBD), but are limited by instability during gastrointestinal (GI) transit and insufficient delivery to inflamed intestinal tissues. Here, we report the discovery and functional characterization of broccoli sprout-derived exosomes (BSDExo) as a naturally occurring nanomedicine that encapsulates endogenous bioactive molecules, including sulforaphane (SFN) and plant miRNAs, and promotes intestinal epithelial repair. BSDExo exhibited a nanoscale size of 40.1 ± 17.2 nm, expressed conserved exosomal protein markers, and were enriched in regulatory miRNAs. Importantly, BSDExo effectively protected encapsulated SFN under simulated gastric and intestinal conditions, demonstrating strong vesicle stability and controlled release. BSDExo (25 µg/mL quantified by total proteins) promoted the proliferation of normal colon epithelial CCD841 CoN cells with a cell viability of 154 ± 5% (p < 0.05). Cellular uptake of fluorescence-labeled BSDExo significantly increased with more severe inflammation stimulation in CCD841 CoN and Caco-2 cells. Secretion of interleukin 8 (IL-8) from inflammation-stimulated colon cells was significantly reduced by the BSDExo treatment (p < 0.05). BSDExo also significantly recovered the epithelial barrier integrity in Caco-2 monolayer that was damaged by LPS or DSS, as assessed by transepithelial electrical resistance (TEER) values (p < 0.05). This study identifies BSDExo as GI-stable, bioactive-rich nanovesicles that selectively target inflamed intestinal epithelium, enhance epithelial repair, and represent a first-in-class, diet-derived nanomedicine with translational potential for IBD.
p-Sulfonatocalixarene-Based Complexation Mitigates Hepatorenal Toxicity of Anticancer Alkaloids without Loss of Efficacy: A Strategy for Selective Detoxification.
Tan L, Jing Z, Yu X … +4 more , Liu Y, Liu Y, Wang M, Ren X
AAPS J · 2026 Apr · PMID 42010207 · Publisher ↗
p-Sulfonatocalix[n]arenes (SCnA, where n = 6, 8) have emerged as promising supramolecular hosts for encapsulating active pharmaceutical ingredients (APIs) through host-guest complexation, enhancing solubility, stability,...
p-Sulfonatocalix[n]arenes (SCnA, where n = 6, 8) have emerged as promising supramolecular hosts for encapsulating active pharmaceutical ingredients (APIs) through host-guest complexation, enhancing solubility, stability, and bioavailability. In this study, SCnA was employed to complex hepatotoxic and nephrotoxic alkaloids derived from Traditional Chinese Medicines (TCM), with the objective of reducing hepatorenal toxicity while preserving antitumor efficacy. The cytocompatibility of six alkaloids and their SCnA complexes was evaluated across human embryonic kidney (Hek293), normal liver (L02), breast cancer (MDA-MB-231), and hepatoma (HepG2) cell lines. A high-content assay (HCA) integrated with three fluorescent probes was utilized to simultaneously quantify multiparametric cellular changes, including nucleus number and area, mitochondrial count and area, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) levels. Complexation with SC6A or SC8A significantly reduced the cytotoxicity of tetrandrine, chelerythrine, and dauricine in Hek293 and L02 cells, while antitumor activity against MDA-MB-231 and HepG2 cells was maintained. HCA revealed that the complexes increased nuclei count, nuclear area, mitochondrial number, mitochondrial area, and MMP, while decreasing ROS levels. Notably, the suppression of normal cell proliferation correlated positively with binding constant values, yet complexation did not interfere with antiproliferative effects in tumor cells. We hypothesize that the heightened mitochondrial fission and oxidative stress susceptibility in cancer cells, owing to their reliance on mitochondrial energy production, underlie the differential cytotoxicity. These findings demonstrate that SCnA complexation selectively attenuates alkaloid-induced toxicity in normal cells without diminishing anticancer potency, underscoring its potential as a versatile strategy for safe and effective drug delivery.
Integrating In-vitro Permeability Assays within PBPK Modeling to Predict CNS Distribution of Standard and Engineered Antibodies.
Kim S, Lessard E, Ling B … +3 more , Rennie K, Haqqani A, Maharaj AR
AAPS J · 2026 Apr · PMID 41998432 · Publisher ↗
The typically low, molecule-dependent permeability of antibodies across the blood-brain barrier (BBB) has driven the development of engineered constructs with optimized BBB transcytosis to facilitate efficient brain deli...
The typically low, molecule-dependent permeability of antibodies across the blood-brain barrier (BBB) has driven the development of engineered constructs with optimized BBB transcytosis to facilitate efficient brain delivery. Physiologically-based pharmacokinetic (PBPK) modeling provides a framework to predict brain disposition and inform drug development; however, current models lack true a priori predictive capability and remain dependent on in-vivo data. In-vitro brain endothelial cell permeability (P) assays provide antibody-specific estimates of brain transport, though these assays have yet to be integrated into PBPK models. This study developed and cross-validated an integrated in-vitro-in-vivo-extrapolation (IVIVE) PBPK framework that uses P values to predict antibody-specific cerebrospinal fluid (CSF) concentrations a priori. Seven antibodies were evaluated, including four standard (non-FC5-fused) and three TMEM30A-binding constructs (FC5-fused). PBPK modeling was conducted using PK-Sim®/MoBi®. P values were used to estimate antibody-specific brain transport parameters. For comparison, a conventional modeling approach was implemented, where brain transport was inferred to be similar to a reference antibody (trastuzumab). Model performance was assessed by comparing predicted versus observed CSF exposures (area-under-the-concentration-time-curve) in rats following intravenous administration. Integration of P data substantially improved brain exposure predictions, reducing the absolute average percentage prediction error for CSF exposure from 296.1% (conventional approach) to 53.4% (IVIVE-PBPK). The framework accurately captured the brain disposition of both standard and FC5-fused antibodies without requiring pre-existing in-vivo CSF data. Overall, this P-informed PBPK modeling approach enables a priori, mechanistic prediction of antibody brain exposure, supporting candidate selection and reducing reliance on animal studies in brain drug development.
Single-Eye NfL Measurement Using NULISA Technology Enables Reduction in Animal Use.
Shim J, Chen J, Indjeian VB … +1 more , Fischer SK
AAPS J · 2026 Apr · PMID 41981365 · Publisher ↗
Neurofilament light chain (NfL) is a pivotal biomarker for neuroaxonal damage. However, its quantification in volume-limited matrices, such as mouse aqueous humor (AH) (2 to 6 µL per eye), has historically required pooli...
Neurofilament light chain (NfL) is a pivotal biomarker for neuroaxonal damage. However, its quantification in volume-limited matrices, such as mouse aqueous humor (AH) (2 to 6 µL per eye), has historically required pooling samples from multiple animals due to the low sensitivity and high sample volume requirements of standard immunoassays. Such pooling increases animal requirements and precludes individual-level data analysis. To overcome these limitations, we developed and evaluated a NfL HomeBrew (HB) assay using the NUcleic acid-Linked Immuno-Sandwich Assay (NULISA) technology. NULISA offers superior analytical sensitivity and requires less than 10 µL volume. Our results demonstrate that the NfL HB NULISA performs comparably to the Simoa reference assay and provides superior sensitivity to the Ella platform. Crucially, the assay reliably quantified NfL in as little as 2 µL of individual mouse AH, with 90% of samples yielding quantifiable results. This approach eliminates the need for sample pooling, effectively reducing animal use by up to eightfold while preserving data integrity at the individual animal level. These findings establish the NULISA platform as a highly sensitive, ethically advantageous solution for neurobiological research in volume-restricted models.
Biodistribution of Cerivastatin, Repaglinide, Glyburide, Rosuvastatin, and Valsartan in Cynomolgus Monkeys and PBPK Analysis.
Li R, Jordan S, Niosi M … +2 more , Varma MVS, Di L
AAPS J · 2026 Apr · PMID 41951999 · Publisher ↗
Cynomolgus monkeys are widely utilized for understanding and predicting human pharmacokinetics (PK) of OATP1B substrates due to their close evolutionary relationship with humans and the high degree of transporter protein...
Cynomolgus monkeys are widely utilized for understanding and predicting human pharmacokinetics (PK) of OATP1B substrates due to their close evolutionary relationship with humans and the high degree of transporter protein homology similarities. We note that some OATP1B tool substrates (e.g., cerivastatin and repaglinide) have steady state volume of distribution (V) values in monkeys that are larger than corresponding V values reported for humans. To understand V and tissue biodistribution of substrate drugs in monkeys, we have performed a series of monkey PK and tissue distribution studies, as well as data analysis with physiologically based pharmacokinetic (PBPK) modeling for several OATP1B substrates (i.e., cerivastatin, repaglinide, glyburide, rosuvastatin, and valsartan). We find that there are unexpectedly high accumulations of these compounds in monkey intestines potentially involving transporter mediated active uptake, which contributed to the higher-than-expected V values.
Predicting Aberrant Fc-fusion Protein Pharmacokinetics from In Silico Structural Properties and Physiologically Based Pharmacokinetic (PBPK) Modeling.
Tomasoni D, Paris A, Visintainer R … +5 more , Cook KD, Chen A, Figueroa I, Thomas VA, Marchetti L
AAPS J · 2026 Apr · PMID 41946860 · Publisher ↗
The fusion of therapeutic proteins to the Fc domain of monoclonal antibodies (mAbs) generally improves the proteins' pharmacokinetic (PK) characteristics, extending in vivo half-lives due to the binding of the Fc domain...
The fusion of therapeutic proteins to the Fc domain of monoclonal antibodies (mAbs) generally improves the proteins' pharmacokinetic (PK) characteristics, extending in vivo half-lives due to the binding of the Fc domain to the FcRn receptor. Yet, several of these Fc-fusion biologics have been observed to have unexpected rapid clearance associated with non-specific off-target binding. Variability in non-specific clearance is often challenging to predict, not well understood, and ultimately can delay the drug development process. In this investigation, we present a computational approach leveraging in silico protein structural properties to extend a physiologically based pharmacokinetic (PBPK) model of mAbs validated on in vivo plasma PK profiles in mice. Selected model parameters affecting protein half-life have been scaled by analytical functions of a panel of calculated in silico protein properties identified by a novel and ad hoc symbolic regression procedure. The resulting extended model has been successfully validated against an independent set of protein plasma PKs, indicating that it can generalize to novel biologics of the same class. Moreover, the extended PBPK model has a median absolute average fold error (AAFE) of 1.18 (min = 1.09; max = 1.51), where values less than 2 typically indicate a good fit. The results enable the de-risking of aberrant PK behaviors, ultimately leading to the selection of Fc-fusion proteins with increased therapeutic value for patients.
Spatiotemporal Profiling of Intratumoral Free Payload Distribution via MALDI Imaging Mass Spectrometry: Implications for Drug-to-Antibody Ratio Optimization in Antibody-Drug Conjugates.
Cai T, Li Z, Yan Q … +8 more , Huang G, Jia K, Chen X, Dun J, Zou J, Tan M, Wu Y, Wang F
AAPS J · 2026 Apr · PMID 41927976 · Publisher ↗
Antibody-drug conjugates (ADCs), comprising monoclonal antibodies and cytotoxic payloads, present inherent complexities in molecular design. The drug-to-antibody ratio (DAR) represents a critical determinant of ADC behav...
Antibody-drug conjugates (ADCs), comprising monoclonal antibodies and cytotoxic payloads, present inherent complexities in molecular design. The drug-to-antibody ratio (DAR) represents a critical determinant of ADC behavior, influencing pharmacokinetics and tissue distribution. In vivo studies in tumor-bearing murine models demonstrated comparable efficacy between DAR4 and DAR8 ADCs (DAR4: 6 mg/kg, DAR8: 3 mg/kg), suggesting that DAR alone does not dictate therapeutic outcome. Immunohistochemical (IHC) staining of human IgG, used to map intact ADC localization, demonstrated superior tumor penetration by DAR4 ADCs relative to their DAR8 counterparts. However, this enhanced penetration did not translate to improved therapeutic efficacy. To elucidate the mechanistic underpinning of DAR optimization, we leveraged matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) to spatially resolve the free payload distribution in tumors. The optimized MALDI imaging method enabled sensitive detection of released payload, revealing similar intensity and distribution pattern for both DAR4 and DAR8 ADCs at 2 and 24 h post-dosing. This spatiotemporal uniformity of payload correlated with consistent pharmacodynamic (PD) responses. Moreover, equivalent payload signal intensities across DAR variants corroborated quantitative analyses of tumor lysates and subsequent efficacy data, reinforcing the pivotal role of intratumoral payload in driving in vivo efficacy. These findings underscore that DAR optimization is both target-dependent and payload-specific, suggesting that ADC design should prioritize factors governing active payload release over passive distribution metrics. The MALDI-IMS methodology developed in this study provides unprecedented spatial resolution of bioactive payload dynamics, establishing a robust platform for dissecting efficacy determinants in preclinical ADC development.
Virtual Bioequivalence Assessment of Long-acting Injectable Suspensions Using PBPK Modeling: Part 1. Impact of particle Size on Formulation Variability.
Morris NM, Djehizian A, Mittapelly N … +10 more , Telaprolu KC, Holland BW, McNally K, Polak S, Jamei M, Alam K, Tsakalozou E, Donnelly M, Feng K, Bois FY
AAPS J · 2026 Apr · PMID 41927954 · Full text
This study presents a workflow for virtual bioequivalence (VBE) assessment of 3-month paliperidone palmitate (PP) long-acting injectable (LAI) suspensions using a novel physiologically-based pharmacokinetic (PBPK) model....
This study presents a workflow for virtual bioequivalence (VBE) assessment of 3-month paliperidone palmitate (PP) long-acting injectable (LAI) suspensions using a novel physiologically-based pharmacokinetic (PBPK) model. The mechanistic absorption and PBPK model was implemented in the Simcyp® Simulator and calibrated against individual concentration-time profiles derived from a published and validated population pharmacokinetic model. The model was able to accurately simulate drug concentration profiles after PP administration. Across 1000 subjects, four model-predicted bioequivalence (BE) metrics, including C and AUC, differed by at most 10% from validation data. The initial mean drug particle radius was assessed as the critical formulation attribute in the VBE analysis. We conducted extensive VBE simulations to evaluate the required sample size of parallel trial designs for a given statistical power. The statistical power of two-one-sided t tests (TOST) to declare BE was estimated from the passing rate of Monte Carlo simulated VBE trials. Power calculations using the validated model indicated that a VBE trial with a minimum of 160 subjects per arm is required to achieve at least 80% power for declaring BE when the formulations are identical in terms of mean particle size. If the mean drug particle radius between test and reference formulations differs by 20%, the required sample size for BE demonstration approximately doubles to maintain the same power. This suggests that particle size affects formulation variability. The power calculations demonstrated that BE assessments were very sensitive to formulation differences in drug particle radius and to the parametrization of the model. These findings emphasize the critical need for rigorous model validation to ensure reliable VBE assessments.
Virtual Bioequivalence Assessment of Long-Acting Injectable Suspensions Using PBPK Modeling: Part 2. Type I Error and Safe Space Analyses.
Morris NM, Jamei M, Alam K … +4 more , Tsakalozou E, Donnelly M, Feng K, Bois FY
AAPS J · 2026 Apr · PMID 41927781 · Full text
We present an analysis of statistical type I error and safe space calculations in virtual bioequivalence (VBE) assessments using a previously published physiologically-based pharmacokinetic (PBPK) model for 3-month long-...
We present an analysis of statistical type I error and safe space calculations in virtual bioequivalence (VBE) assessments using a previously published physiologically-based pharmacokinetic (PBPK) model for 3-month long-acting paliperidone palmitate (PP) injectable suspensions. The type I error for the two-one-sided t test (TOST) applied to virtual parallel design bioequivalence (BE) trials was estimated through approximation of 'simulated BE boundaries'. This was defined as the range of formulation critical quality attribute values (CQA, which in this paper pertains to mean drug particle radius), corresponding to simulated population-level geometric mean ratios (GMRs) for key pharmacokinetic (PK) metrics of between 0.8 to 1.25. Monte Carlo simulations were then used to combine these limits with power calculations to display estimates of the safe space for BE extending from a predefined particle radius. Type I error for detecting formulation difference in the model was controlled at 5% for PK endpoints. The simulated BE boundaries for 3-month PP LAI suspension mean particle radius extended over 5 µm, but acceptable statistical power (≥ 80%) was obtained only when the mean particle radius was within 1 µm of the reference formulation. For PBPK models, type I error calculations are notably more complex than power calculations because the simulated BE boundaries for CQAs need to be determined before the error assessment. This study appears to be the first to discuss the intersection of type I error control and safe space estimation in PBPK modeling for a BE assessment. Our case study shows the conditions that allow for a controlled type I error in a VBE assessment. Safe space is shown to depend on both formulation characteristics and the statistical power afforded by BE studies, offering valuable insights for formulation design considerations.
PBPK Modelling of PROTACs: Learnings from ARV-110 as a Case Example.
Salem F, Tabatabaeian Nimavardi A, Srivastava A … +7 more , Krollik K, Reichel A, Cebrian D, Taskar KS, Yates JWT, Rynn C, Duevel HM
AAPS J · 2026 Mar · PMID 41896448 · Publisher ↗
The study presents a comprehensive evaluation of physiologically-based pharmacokinetic (PBPK) modeling for Proteolysis Targeting Chimeras (PROTACs), using ARV-110 (Bavdegalutamide) as a case example. We sought to develop...
The study presents a comprehensive evaluation of physiologically-based pharmacokinetic (PBPK) modeling for Proteolysis Targeting Chimeras (PROTACs), using ARV-110 (Bavdegalutamide) as a case example. We sought to develop a PBPK model that accurately predicts the human pharmacokinetics (PK) of ARV-110 and began with a bottom-up approach to predict ARV-110 PK in mice and rats using available ADME and physicochemical data. Owing to the observed in vitro-in vivo extrapolation (IVIVE) gaps in clearance, the published in vivo data was used for refinement, resulting in a middle-out PBPK model bridging this discrepancy. PBPK predictions were extrapolated to human and validated against observed clinical PK for single and multiple doses in healthy volunteers and cancer patients revealing IVIVE gaps for human clearance. Similar to rodents, a middle-out modeling approach was then used to refine the human PBPK prediction. This model effectively captured plasma drug concentration-time profiles reported for preclinical and clinical studies, including studies involving impact of food and drug-drug interactions with itraconazole and esomeprazole. All observed human concentrations were within 5th and 95th percentile of predictions and PK parameters were within two-fold of the observed in vivo data. Following administration of a single dose (280 mg) of ARV-110, the observed vs. predicted AUC for high fat, medium fat and low fat studies were 13563.0 vs. 7646.0 ng.h/ml, 4358.0 vs. 4618.3 ng.h/ml and 1919.0 vs. 1403.3 ng.h/ml. This work provides a translational PBPK framework for predicting human oral PK of PROTACs and emphasizes challenges in generating robust preclinical data to enhance prediction accuracy.
Theoretical and Numerical Investigation of the Consistency of Model Comparisons in Pharmacometrics.
Appel LM, Steiert B
AAPS J · 2026 Mar · PMID 41882483 · Publisher ↗
Pharmacokinetic (PK) and pharmacodynamic (PD) models are essential tools in drug development, making the selection of an appropriate model critically important. When using likelihood ratio tests (LRTs) to compare nested...
Pharmacokinetic (PK) and pharmacodynamic (PD) models are essential tools in drug development, making the selection of an appropriate model critically important. When using likelihood ratio tests (LRTs) to compare nested models, it is crucial to ensure their validity, especially when parameters are fixed. This work examines the continuity of likelihood functions as a necessary condition for LRT validity within the framework of population modeling. By decomposing the Objective Function Value (OFV), we identify scenarios where parameter fixing leads to non-continuous likelihood behavior, potentially invalidating the LRT application. A proof and numerical examples illustrate that while fixing population parameters maintains continuity through compensatory behavior of terms within the OFV, fixing individual parameters introduces discontinuities. Overall, this work underscores the need for careful consideration of parameter fixation in population models: It shows that population parameters can be fixed without violating the continuity condition for LRTs and suggests that introducing covariates may provide a viable alternative for fixing individual parameters. Further investigation into the sufficiency of continuity as a condition for the LRT's validity is needed.
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