A translational platform PBPK model for antibody disposition in the brain

Quantitative systems pharmacology model of α-synuclein pathology in Parkinson's disease-like mouse for investigation of passive immunotherapy mechanisms

The main pathophysiological hallmark of Parkinson's disease (PD) is the accumulation of aggregated alpha-synuclein (αSyn). Microglial activation is an early event in PD and may play a key role in pathological αSyn aggregation and transmission, as well as in clearance of αSyn and immunotherapy efficacy. Our aim was to investigate how different proposed mechanisms of anti-αSyn immunotherapy may contribute to pathology reduction in various PD-like mouse models. Our mechanistic model of PD pathology in mouse includes αSyn production, aggregation, degradation and distribution in neurons, secretion into interstitial fluid, internalization, and subsequent clearance by neurons and microglia. It describes the influence of neuroinflammation on PD pathogenesis and dopaminergic neurodegeneration. Multiple data from mouse PD models were used for calibration and validation. Simulations of anti-αSyn passive immunotherapy adequately reproduce preclinical data and suggest that (1) immunotherapy is efficient in the reduction of aggregated αSyn in various models of PD-like pathology; (2) prevention of aSyn spread only does not reduce the pathology; (3) a decrease in microglial inflammatory activation and aSyn aggregation may be alternative therapy approaches in PD-like pathology.

Exploring How Antibody Format Drives Clearance from the Brain

Monoclonal antibodies (mAbs) have high binding specificity and affinity, making them attractive for treating brain diseases. However, their effectiveness is limited by poor blood-brain barrier (BBB) penetration and rapid central nervous system (CNS) clearance. Our group identified blood-brain barrier modulator (BBBM) peptides that improved mAb penetration across the BBB into the brain. In this study, we investigated the pharmacokinetics of a mAb delivered to the brain using BBBMs after intravenous (IV) administration and explored the impact of antibody format (size, neonatal Fc receptor (FcRn) binding, hyaluronic acid binding) on brain clearance following direct injection into the central nervous system (CNS) via intracerebroventricular (ICV) injection. IRDye800CW-labeled antibodies were administered into C57BL/6 mice via ICV or IV injection, and organ concentrations were measured after various time points. When a mAb was coadministered with a BBBM peptide, the permeation of mAb across the BBB was increased compared to mAb alone at early time points; however, the mAb was cleared within 2 h from the brain. ICV experiments revealed that an antibody Fab fragment had a higher brain exposure than a mAb, and that a Fab fused to a hyaluronic acid binding domain (Fab-VG1) showed remarkable improvement in brain exposure. These findings suggest that BBBMs and antibody format optimization may be promising strategies for enhancing brain retention of therapeutic antibodies.

Translational two-pore PBPK model to characterize whole-body disposition of different-size endogenous and exogenous proteins

Two-pore physiologically based pharmacokinetic (PBPK) modeling has demonstrated its potential in describing the pharmacokinetics (PK) of different-size proteins. However, all existing two-pore models lack either diverse proteins for validation or interspecies extrapolation. To fill the gap, here we have developed and optimized a translational two-pore PBPK model that can characterize plasma and tissue disposition of different-size proteins in mice, rats, monkeys, and humans. Datasets used for model development include more than 15 types of proteins: IgG (150 kDa), F(ab)2 (100 kDa), minibody (80 kDa), Fc-containing proteins (205, 200, 110, 105, 92, 84, 81, 65, or 60 kDa), albumin conjugate (85.7 kDa), albumin (67 kDa), Fab (50 kDa), diabody (50 kDa), scFv (27 kDa), dAb2 (23.5 kDa), proteins with an albumin-binding domain (26, 23.5, 22, 16, 14, or 13 kDa), nanobody (13 kDa), and other proteins (110, 65, or 60 kDa). The PBPK model incorporates: (i) molecular weight (MW)-dependent extravasation through large and small pores via diffusion and filtration, (ii) MW-dependent renal filtration, (iii) endosomal FcRn-mediated protection from catabolism for IgG and albumin-related modalities, and (iv) competition for FcRn binding from endogenous IgG and albumin. The finalized model can well characterize PK of most of these proteins, with area under the curve predicted within two-fold error. The model also provides insights into contribution of renal filtration and lysosomal degradation towards total elimination of proteins, and contribution of paracellular convection/diffusion and transcytosis towards extravasation. The PBPK model presented here represents a cross-modality, cross-species platform that can be used for development of novel biologics.

Quantitative systems pharmacology-based exploration of relevant anti-amyloid therapy challenges in clinical practice

INTRODUCTION

Addressing practical challenges in clinical practice after the recent approvals of amyloid antibodies in Alzheimer's disease (AD) will benefit more patients. However, generating these answers using clinical trials or real-world evidence is not practical, nor feasible.

METHODS

Here we use a Quantitative Systems Pharmacology (QSP) computational model of amyloid aggregation dynamics, well validated with clinical data on biomarkers and amyloid-related imaging abnormality-edema (ARIA-E) liability of six amyloid antibodies in clinical trials to explore various clinical practice challenges.

RESULTS

Treatment duration to reach amyloid negativity ranges from 12 to 44, 16 to 40, and 6 to 20 months for lecanemab, aducanumab, and donanemab, respectively, for baseline central amyloid values between 50 and 200 Centiloids (CL). Changes in plasma cerebrospinal fluid Aβ42 and the plasma Aβ42/ Aβ40 ratio-fluid biomarkers to detect central amyloid negativity-is greater for lecanemab than for aducanumab and donanemab, indicating that these fluid amyloid biomarkers are only suitable for lecanemab. After reaching amyloid negativity an optimal maintenance schedule consists of a 24-month, 48-month and 64-month interval for 10 mg/kg (mpk) lecanemab, 10 mpk aducanumab, and 20 mpk donanemab, respectively, to keep central amyloid negative for 10 years. Cumulative ARIA-E liability could be reduced to almost half by introducing a drug holiday in the first months. For patients experiencing ARIA-E, restarting treatment with a conservative titration strategy resulted in an additional delay ranging between 3 and 4 months (donanemab), 5 months (lecanemab), and up to 7 months (aducanumab) for reaching amyloid negativity, depending upon the timing of the incident. Clinical trial designs for Down syndrome patients suggested the same rank order for central amyloid reduction, but higher ARIA-E liability especially for donanemab, which can be significantly mitigated by adopting a longer titration period.

DISCUSSION

This QSP platform could support clinical practice challenges to optimize real-world treatment paradigms for new and existing amyloid drugs.

Mechanistic Modeling of Intrathecal Chemotherapy Pharmacokinetics in the Human Central Nervous System

PURPOSE

The pharmacokinetics of intrathecally administered antibody or small-molecule drugs in the human central nervous system (CNS) remains poorly understood. This study aimed to provide mechanistic and quantitative perspectives on the CNS pharmacokinetics of intrathecal chemotherapy, by using a physiologically based pharmacokinetic (PBPK) modeling approach.

EXPERIMENTAL DESIGN

A novel CNS PBPK model platform was developed and verified, which accounted for the human CNS general anatomy and physiologic processes governing drug distribution and disposition. The model was used to predict CNS pharmacokinetics of antibody (trastuzumab) and small-molecule drugs (methotrexate, abemaciclib, tucatinib) following intraventricular injection or intraventricular 24-hour infusion, and to assess the key determinants of drug penetration into the deep brain parenchyma.

RESULTS

Intraventricularly administered antibody and small-molecule drugs exhibited distinct temporal and spatial distribution and disposition in human CNS. Both antibody and small-molecule drugs achieved supratherapeutic or therapeutic concentrations in the cerebrospinal fluid (CSF) compartments and adjacent brain tissue. While intrathecal small-molecule drugs penetrated the deep brain parenchyma to a negligible extent, intrathecal antibodies may achieve therapeutic concentrations in the deep brain parenchyma. Intraventricular 24-hour infusion enabled prolonged CNS exposure to therapeutically relevant concentrations while avoiding excessively high and potentially neurotoxic drug concentrations.

CONCLUSIONS

CNS PBPK modeling, in line with available clinical efficacy data, confirms the therapeutic value of intrathecal chemotherapy with antibody or small-molecule drugs for treating neoplastic meningitis and warrants further clinical investigation of intrathecal antibody drugs to treat brain parenchyma tumors. Compared with intraventricular injection, intraventricular 24-hour infusion may mitigate neurotoxicity while retaining potential efficacy.

Investigation of Antibody Pharmacokinetics in the Brain Following Intra-CNS Administration and Development of PBPK Model to Characterize the Data

Despite the promising potential of direct central nervous system (CNS) antibody administration to enhance brain exposure, there remains a significant gap in understanding the disposition of antibodies following different intra-CNS injection routes. To bridge this knowledge gap, this study quantitatively investigated the brain pharmacokinetics (PK) of antibodies following intra-CNS administration. The microdialysis samples from the striatum (ST), cerebrospinal fluid (CSF) samples through cisterna magna (CM) puncture, plasma, and brain homogenate samples were collected to characterize the pharmacokinetics (PK) profiles of a non-targeting antibody, trastuzumab, following intracerebroventricular (ICV), intracisternal (ICM), and intrastriatal (IST) administration. For a comprehensive analysis, these intra-CNS injection datasets were juxtaposed against our previously acquired intravenous (IV) injection data obtained under analogous experimental conditions. Our findings highlighted that direct CSF injections, either through ICV or ICM, resulted in ~ 5-6-fold higher interstitial fluid (ISF) drug exposure than IV administration. Additionally, the low bioavailability observed following IST administration indicates the existence of a local degradation process for antibody elimination in the brain ISF along with the ISF bulk flow. The study further refined a physiologically based pharmacokinetic (PBPK) model based on new observations by adding the perivascular compartments, oscillated CSF flow, and the nonspecific uptake and degradation of antibodies by brain parenchymal cells. The updated model can well characterize the antibody PK following systemic and intra-CNS administration. Thus, our research offers quantitative insight into antibody brain disposition pathways and paves the way for determining optimal dosing and administration strategies for antibodies targeting CNS disorders.

Local Identifiability Analysis, Parameter Subset Selection and Verification for a Minimal Brain PBPK Model

Physiologically-based pharmacokinetic (PBPK) modeling is important for studying drug delivery in the central nervous system, including determining antibody exposure, predicting chemical concentrations at target locations, and ensuring accurate dosages. The complexity of PBPK models, involving many variables and parameters, requires a consideration of parameter identifiability; i.e., which parameters can be uniquely determined from data for a specified set of concentrations. We introduce the use of a local sensitivity-based parameter subset selection algorithm in the context of a minimal PBPK (mPBPK) model of the brain for antibody therapeutics. This algorithm is augmented by verification techniques, based on response distributions and energy statistics, to provide a systematic and robust technique to determine identifiable parameter subsets in a PBPK model across a specified time domain of interest. The accuracy of our approach is evaluated for three key concentrations in the mPBPK model for plasma, brain interstitial fluid and brain cerebrospinal fluid. The determination of accurate identifiable parameter subsets is important for model reduction and uncertainty quantification for PBPK models.

Whole-Body Disposition and Physiologically Based Pharmacokinetic Modeling of Adeno-Associated Viruses and the Transgene Product

To facilitate model-informed drug development (MIDD) of adeno-associated virus (AAV) therapy, here we have developed a physiologically based pharmacokinetic (PBPK) model for AAVs following preclinical investigation in mice. After 2E11 Vg/mouse dose of AAV8 and AAV9 encoding a monoclonal antibody (mAb) gene, whole-body disposition of both the vector and the transgene mAb was evaluated over 3 weeks. At steady-state, the following tissue-to-blood (T/B) concentration ratios were found for AAV8/9: ∼50 for liver; ∼10 for heart and muscle; ∼2 for brain, lung, kidney, adipose, and spleen; ≤1 for bone, skin, and pancreas. T/B values for mAb were compared with the antibody biodistribution coefficients, and five different clusters of organs were identified based on their transgene expression profile. All the biodistribution data were used to develop a novel AAV PBPK model that incorporates: (i) whole-body distribution of the vector; (ii) binding, internalization, and intracellular processing of the vector; (iii) transgene expression and secretion; and (iv) whole-body disposition of the secreted transgene product. The model was able to capture systemic and tissue PK of the vector and the transgene-produced mAb reasonably well. Pathway analysis of the PBPK model suggested that liver, muscle, and heart are the main contributors for the secreted transgene mAb. Unprecedented PK data and the novel PBPK model developed here provide the foundation for quantitative systems pharmacology (QSP) investigations of AAV-mediated gene therapies. The PBPK model can also serve as a quantitative tool for preclinical study design and preclinical-to-clinical translation of AAV-based gene therapies.

Pharmacokinetics of AAV9 Mediated Trastuzumab Expression in Rat Brain Following Systemic and Local Administration

INTRODUCTION

Recombinant adeno-associated viruses(rAAVs) are an attractive tool to ensure long-term expression monoclonal antibody(mAb) in the central nervous system(CNS). It is still unclear whether systemic injection or local CNS administration of AAV9 is more beneficial for the exposure of the expressed mAb in the brain. Hence, we compared the biodistribution and transgene expression following AAV9-Trastuzumab administration through different routes.

METHODS AND RESULT

In-house generated AAV9-Trastuzumab vectors were administered at 5E+11 Vgs/rat through intravenous(IV), intracerebroventricular(ICV), intra-cisterna magna(ICM) and intrastriatal(IST) routes. Vector and trastuzumab blood/plasma concentrations were assessed at different time points up to the terminal time point of 21 days. Different brain regions in addition to the spinal cord, cerebrospinal fluid(CSF) and interstitial fluid(ISF), were also analyzed at the terminal time point. Our results show that vector biodistribution and Trastuzumab expression in the brain could the ranked as follows: IST>ICM>ICV>IV. Rapid clearance of vector was observed after administration via the ICM and ICV routes. The ICV route produced similar expression levels across different brain regions, while the ICM route had better expression in the hindbrain and spinal cord region. The IST route had higher expression in the forebrain region compared to the hindbrain region. A sharp decline in trastuzumab plasma concentration was observed across all routes of administration due to anti-trastuzumab antibody response.

CONCLUSION

In this study we have characterized vector biodistribution and transgene mAb expression after AAV9 vector administration through different routes in rats. IST and ICM represent the best administration routes to deliver antibody genes to the brain.

Expansion of platform physiologically-based pharmacokinetic model for monoclonal antibodies towards different preclinical species: cats, sheep, and dogs

Monoclonal antibodies (mAbs) are becoming an important therapeutic option in veterinary medicine, and understanding the pharmacokinetic (PK) of mAbs in higher-order animal species is also important for human drug development. To better understand the PK of mAbs in these animals, here we have expanded a platform physiological-based pharmacokinetic (PBPK) model to characterize the disposition of mAbs in three different preclinical species: cats, sheep, and dogs. We obtained PK data for mAbs and physiological parameters for the three different species from the literature. We were able to describe the PK of mAbs following intravenous (IV) or subcutaneous administration in cats, IV administration in sheep, and IV administration dogs reasonably well by fixing the physiological parameters and just estimating the parameters related to the binding of mAbs to the neonatal Fc receptor. The platform PBPK model presented here provides a quantitative tool to predict the plasma PK of mAbs in dogs, cats, and sheep. The model can also predict mAb PK in different tissues where the site of action might be located. As such, the mAb PBPK model presented here can facilitate the discovery, development, and preclinical-to-clinical translation of mAbs for veterinary and human medicine. The model can also be modified in the future to account for more detailed compartments for certain organs, different pathophysiology in the animals, and target-mediated drug disposition.

A Minimal PBPK Model for Plasma and Cerebrospinal Fluid Pharmacokinetics of Trastuzumab after Intracerebroventricular Administration in Patients with HER2-Positive Brain Metastatic Localizations

BACKGROUND

Dosing regimens of trastuzumab administered by intracerebroventricular (icv) route to patients with HER2-positive brain localizations remain empirical. The objectives of this study were to describe pharmacokinetics (PK) of trastuzumab in human plasma and cerebrospinal fluid (CSF) after simultaneous icv and intravenous (iv) administration using a minimal physiologically-based pharmacokinetic model (mPBPK) and to perform simulations of alternative dosing regimens to achieve therapeutic concentrations in CSF.

METHODS

Plasma and CSF PK data were collected in two patients with HER2-positive brain localizations. A mPBPK model for mAbs consisting of four compartments (tight and leaky tissues, plasma and lymph) was enriched by an additional compartment for ventricular CSF. The comparison between observed and model-predicted concentrations was evaluated using prediction error (PE).

RESULTS

The developed mPBPK model described plasma and CSF trastuzumab concentrations reasonably well with mean PE for plasma and CSF data of 41.8% [interquartile range, IQR = -9.48; 40.6] and 18.3% [-36.7; 60.6], respectively, for patient 1 and 11.4% [-10.8; 28.7] and 22.5% [-27.7; 77.9], respectively, for patient 2. Trastuzumab showed fast clearance from CSF to plasma with Cmin,ss of 0.56 and 0.85 mg/L for 100 and 150 mg q1wk, respectively. Repeated dosing of 100 and 150 mg q3day resulted in Cmin,ss of 10.3 and 15.4 mg/L, respectively. Trastuzumab CSF target concentrations are achieved rapidly and maintained above 60 mg/L from 7 days after a continuous perfusion at 1.0 mg/h.

CONCLUSION

Continuous icv infusion of trastuzumab at 1.0 mg/h could be an alternative dosing regimen to rapidly achieve intraventricular CSF therapeutic concentrations.

Efficient PD-L1 imaging of murine glioblastoma with FUS-aided immunoPET by leveraging FcRn-antibody interaction

Rationale: The passage of antibodies through the blood-brain barrier (BBB) and the blood-tumoral barrier (BTB) is determinant not only to increase the immune checkpoint inhibitors efficacy but also to monitor prognostic and predictive biomarkers such as the programmed death ligand 1 (PD-L1) via immunoPET. Although the involvement of neonatal Fc receptor (FcRn) in antibody distribution has been demonstrated, its function at the BBB remains controversial, while it is unknown at the BTB. In this context, we assessed FcRn's role by pharmacokinetic immunoPET imaging combined with focused ultrasounds (FUS) using unmodified and FcRn low-affinity IgGs targeting PD-L1 in a preclinical orthotopic glioblastoma model. Methods: Transcranial FUS were applied over the whole brain in mice shortly before injecting the anti-PD-L1 IgG 89Zr-DFO-C4 or its FcRn low-affinity mutant 89Zr-DFO-C4Fc-MUT in a syngeneic glioblastoma murine model (GL261-GFP). Brain uptake was measured from PET scans acquired up to 7 days post-injection. Kinetic modeling was performed to compare the brain kinetics of both C4 formats. Results: FUS efficiently enhanced the delivery of both C4 radioligands in the brain with high reproducibility. 89Zr-DFO-C4Fc-MUT mean concentrations in the brain reached a significant uptake of 3.75±0.41%ID/cc with FUS against 1.92±0.45%ID/cc without, at 1h post-injection. A substantial and similar entry of both C4 radioligands was observed at a rate of 0.163±0.071 mL/h/g of tissue during 10.4±4.6min. The impaired interaction with FcRn of 89Zr-DFO-C4Fc-MUT significantly decreased the efflux constant from the healthy brain tissue to plasma compared with non-mutated IgG. Abolishing FcRn interaction allows determining the target engagement related to the specific binding as soon as 12h post-injection. Conclusion: Abolishing Fc-FcRn interaction confers improved kinetic properties to 89Zr-DFO-C4Fc-MUT for immunoPET imaging. FUS-aided BBB/BTB disruption enables quantitative imaging of PD-L1 expression by glioblastoma tumors within the brain.

Analysis of clinical failure of anti-tau and anti-synuclein antibodies in neurodegeneration using a quantitative systems pharmacology model

Misfolded proteins in Alzheimer's disease and Parkinson's disease follow a well-defined connectomics-based spatial progression. Several anti-tau and anti-alpha synuclein (aSyn) antibodies have failed to provide clinical benefit in clinical trials despite substantial target engagement in the experimentally accessible cerebrospinal fluid (CSF). The proposed mechanism of action is reducing neuronal uptake of oligomeric protein from the synaptic cleft. We built a quantitative systems pharmacology (QSP) model to quantitatively simulate intrasynaptic secretion, diffusion and antibody capture in the synaptic cleft, postsynaptic membrane binding and internalization of monomeric and oligomeric tau and aSyn proteins. Integration with a physiologically based pharmacokinetic (PBPK) model allowed us to simulate clinical trials of anti-tau antibodies gosuranemab, tilavonemab, semorinemab, and anti-aSyn antibodies cinpanemab and prasineuzumab. Maximal target engagement for monomeric tau was simulated as 45% (semorinemab) to 99% (gosuranemab) in CSF, 30% to 99% in ISF but only 1% to 3% in the synaptic cleft, leading to a reduction of less than 1% in uptake of oligomeric tau. Simulations for prasineuzumab and cinpanemab suggest target engagement of free monomeric aSyn of only 6-8% in CSF, 4-6% and 1-2% in the ISF and synaptic cleft, while maximal target engagement of aggregated aSyn was predicted to reach 99% and 80% in the synaptic cleft with similar effects on neuronal uptake. The study generates optimal values of selectivity, sensitivity and PK profiles for antibodies. The study identifies a gradient of decreasing target engagement from CSF to the synaptic cleft as a key driver of efficacy, quantitatively identifies various improvements for drug design and emphasizes the need for QSP modelling to support the development of tau and aSyn antibodies.

Translational physiologically-based pharmacokinetic model for ocular disposition of monoclonal antibodies

We have previously published a PBPK model comprising the ocular compartment to characterize the disposition of monoclonal antibodies (mAbs) in rabbits. While rabbits are commonly used preclinical species in ocular research, non-human primates (NHPs) have the most phylogenetic resemblance to humans including the presence of macula in the eyes as well as higher sequence homology. However, their use in ocular research is limited due to the strict ethical guidelines. Similarly, in humans the ocular samples cannot be collected except for the tapping of aqueous humor (AH). Therefore, we have translated this rabbit model to monkeys and human species using literature-reported datasets. Parameters describing the tissue volumes, physiological flows, and FcRn-binding were obtained from the literature, or estimated by fitting the model to the data. In the monkey model, the values for the rate of lysosomal degradation for antibodies (Kdeg), intraocular reflection coefficients (σaq, σret, σcho), bidirectional rate of fluid circulation between the vitreous chamber and the aqueous chamber (QVA), and permeability-surface area product of lens (PSlens) were estimated; and were found to be 31.5 h-1, 0.7629, 0.6982, 0.9999, 1.64 × 10-5 L/h, and 4.62 × 10-7 L/h, respectively. The monkey model could capture the data in plasma, aqueous humor, vitreous humor and retina reasonably well with the predictions being within twofold of the observed values. For the human model, only the value of Kdeg was estimated to fit the model to the plasma pharmacokinetics (PK) of mAbs and was found to be 24.4 h-1 (4.14%). The human model could also capture the ocular PK data reasonably well with the predictions being within two- to threefold of observed values for the plasma, aqueous and vitreous humor. Thus, the proposed framework can be used to characterize and predict the PK of mAbs in the eye of monkey and human species following systemic and intravitreal administration. The model can also facilitate the development of new antibody-based therapeutics for the treatment of ocular diseases as well as predict ocular toxicities of such molecules following systemic administration.

Computational neurosciences and quantitative systems pharmacology: a powerful combination for supporting drug development in neurodegenerative diseases

Successful clinical development of new therapeutic interventions is notoriously difficult, especially in neurodegenerative diseases, where predictive biomarkers are scarce and functional improvement is often based on patient's perception, captured by structured interviews. As a consequence, mechanistic modeling of the processes relevant to therapeutic interventions in CNS disorders has been lagging behind other disease indications, probably because of the perceived complexity of the brain. However in this report, we develop the argument that a combination of Computational Neurosciences and Quantitative Systems Pharmacology (QSP) modeling of molecular pathways is a powerful simulation tool to enhance the probability of successful drug development for neurodegenerative diseases. Computational Neurosciences aims to predict action potential dynamics and neuronal circuit activation that are ultimately linked to behavioral changes and clinically relevant functional outcomes. These processes can not only be affected by the disease state, but also by common genotype variants on neurotransmitter-related proteins and the psycho-active medications often prescribed in these patient populations. Quantitative Systems Pharmacology (QSP) modeling of molecular pathways allows to simulate key pathological drivers of dementia, such as protein aggregation and neuroinflammatory responses. They often impact neurotransmitter homeostasis and voltage-gated ion-channels or lead to mitochondrial dysfunction, ultimately leading to changes in action potential dynamics and clinical readouts. Combining these two modeling approaches can lead to better actionable understanding of the many non-linear pharmacodynamic processes active in the human diseased brain. Practical applications include a rational selection of the optimal doses in combination therapies, identification of subjects more likely to respond to treatment, a more balanced stratification of treatment arms in terms of comedications, disease status and common genotype variants and re-analysis of small clinical trials to uncover a possible clinical signal. Ultimately this will lead to a higher success rate of bringing new therapeutics to the right patient populations.

Mini-PBPK-Based Population Model and Covariate Analysis to Assess the Complex Pharmacokinetics and Pharmacodynamics of RO7449135, an Anti-KLK5/KLK7 Bispecific Antibody in Cynomolgus Monkeys

RO7449135, an anti-kallikrein (KLK)5/KLK7 bispecific antibody, is in development as a potential therapy against Netherton's syndrome (NS). In cynomolgus monkey studies, RO7449135 bound to KLK5 and KLK7, causing considerable accumulation of total KLKs, but with non-dose-proportional increase. To understand the complex PKPD, a population model with covariate analysis was developed accounting for target binding in skin and migration of bound targets from skin to blood. The covariate analysis suggested the animal batch as the categorical covariate impacting the different KLK5 synthesis rates between the repeat-dose study and single-dose study, and the dose as continuous covariate impacting the internalization rate of the binary and ternary complexes containing KLK7. To comprehend the mechanism underlying, we hypothesized that inhibition of KLK5 by RO7449135 prevented its cleavage of the pro-enzyme of KLK7 (pro-KLK7) and altered the proportion between pro-KLK7 and KLK7. Besides the pro-KLK7, RO7449135 can interact with other proteins like LEKTI through KLK7 connection in a dose-dependent manner. The different high-order complexes formed by RO7449135 interacting with pro-KLK7 or LEKTI-like proteins can be subject to faster internalization rate. Accounting for the dose and animal batch as covariates, the model-predicted free target suppression is well aligned with the visual target engagement check. The population PKPD model with covariate analysis provides the scientific input for the complex PKPD analysis, successfully predicts the target suppression in cynomolgus monkeys, and thereby can be used for the human dose projection of RO7449135.

Physiologically Based Pharmacokinetic Modeling to Characterize the Effect of Molecular Charge on Whole-Body Disposition of Monoclonal Antibodies

Motivated by a series of work demonstrating the effect of molecular charge on antibody pharmacokinetics (PK), physiological-based pharmacokinetic (PBPK) models are emerging that relate in silico calculated charge or in vitro measures of polyspecificity to antibody PK parameters. However, only plasma data has been used for model development in these studies, leading to unvalidated assumptions. Here, we present an extended platform PBPK model for antibodies that incorporate charge-dependent endothelial cell pinocytosis rate and nonspecific off-target binding in the interstitial space and on circulating blood cells, to simultaneously characterize whole-body disposition of three antibody charge variants. Predictive potential of various charge metrics was also explored, and the difference between positive charge patches and negative charge patches (i.e., PPC-PNC) was used as the charge parameter to establish quantitative relationships with nonspecific binding affinities and endothelial cell uptake rate. Whole-body disposition of these charge variants was captured well by the model, with less than 2-fold predictive error in area under the curve of most plasma and tissue PK data. The model also predicted that with greater positive charge, nonspecific binding was more substantial, and pinocytosis rate increased especially in brain, heart, kidney, liver, lung, and spleen, but remained unchanged in adipose, bone, muscle, and skin. The presented PBPK model contributes to our understanding of the mechanisms governing the disposition of charged antibodies and can be used as a platform to guide charge engineering based on desired plasma and tissue exposures.

The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment

Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally employed in the pharmaceutical industry and environmental health risk assessment. These models are recognized by regulatory authorities for predicting organ concentration-time profiles, pharmacokinetics and daily intake dose of xenobiotics. The extension of PBPK models to capture sensitive populations such as pediatric, geriatric, pregnant females, fetus, etc., and diseased populations such as those with renal impairment, liver cirrhosis, etc., is a must. However, the current modelling practices and existing models are not mature enough to confidently predict the risk in these populations. A multidisciplinary collaboration between clinicians, experimental and modeler scientist is vital to improve the physiology and calculation of biochemical parameters for integrating knowledge and refining existing PBPK models. Specific PBPK covering compartments such as cerebrospinal fluid and the hippocampus are required to gain mechanistic understanding about xenobiotic disposition in these sub-parts. The PBPK model assists in building quantitative adverse outcome pathways (qAOPs) for several endpoints such as developmental neurotoxicity (DNT), hepatotoxicity and cardiotoxicity. Machine learning algorithms can predict physicochemical parameters required to develop in silico models where experimental data are unavailable. Integrating machine learning with PBPK carries the potential to revolutionize the field of drug discovery and development and environmental risk. Overall, this review tried to summarize the recent developments in the in-silico models, building of qAOPs and use of machine learning for improving existing models, along with a regulatory perspective. This review can act as a guide for toxicologists who wish to build their careers in kinetic modeling.

Assessment of AAV9 distribution and transduction in rats after administration through Intrastriatal, Intracisterna magna and Lumbar Intrathecal routes

Challenges in obtaining efficient transduction of brain and spinal cord following systemic AAV delivery have led to alternative administration routes being used in clinical trials that directly infuse the virus into the CNS. However, data comparing different direct AAV injections into the brain remain limited making it difficult to choose optimal routes. Here we tested both AAV9-egfp and AAV9-fLuc delivery via intrastriatal (IST), intracisterna magna (ICM) and lumbar intrathecal (LIT) routes in adult rats and assessed vector distribution and transduction in brain, spinal cord and peripheral tissues. We find that IST infusion leads to robust transgene expression in the striatum, thalamus and cortex with lower peripheral tissue transduction and anti-AAV9 capsid titers compared to ICM or LIT. ICM delivery provided strong GFP and luciferase expression across more brain regions than the other routes and similar expression in the spinal cord to LIT injections, which itself largely failed to transduce the rat brain. Our data highlight the strengths and weaknesses of each direct CNS delivery route which will help with future clinical targeting.

CNS penetration of methotrexate and its metabolite 7-hydroxymethotrexate in mice bearing orthotopic Group 3 medulloblastoma tumors and model-based simulations for children

The brain penetration of methotrexate (MTX) and its metabolite 7-hydroxymethotrexate (7OHMTX) was characterized in non-tumor bearing mice and mice bearing orthotopic Group 3 medulloblastoma. Plasma pharmacokinetic studies and cerebral and ventricular microdialysis studies were performed in animals dosed with 200 or 1000 mg/kg MTX by IV bolus. Plasma, brain/tumor extracellular fluid (ECF) and lateral ventricle cerebrospinal fluid (CSF) MTX and 7OHMTX concentration-time data were analyzed by validated LC-MS/MS methods and modeled using a population-based pharmacokinetic approach and a hybrid physiologically-based model structure for the brain compartments. Brain penetration was similar for MTX and 7OHMTX and was not significantly different between non-tumor and tumor bearing mice. Overall, mean (±SD) model-derived unbound plasma to ECF partition coefficient K_p,uu were 0.17 (0.09) and 0.17 (0.12) for MTX and 7OHMTX, respectively. Unbound plasma to CSF K_p,uu were 0.11 (0.06) and 0.18 (0.09) for MTX and 7OHMTX, respectively. The plasma and brain model were scaled to children using allometric principles and pediatric physiological parameters. Model-based simulations were adequately overlaid with digitized plasma and CSF lumbar data collected in children receiving different MTX systemic infusions. This model can be used to further explore and optimize methotrexate dosing regimens in children with brain tumors.

A combined physiologically-based pharmacokinetic and quantitative systems pharmacology model for modeling amyloid aggregation in Alzheimer's disease

Antibody-mediated removal of aggregated β-amyloid (Aβ) is the current, most clinically advanced potential disease-modifying treatment approach for Alzheimer's disease. We describe a quantitative systems pharmacology (QSP) approach of the dynamics of Aβ monomers, oligomers, protofibrils, and plaque using a detailed microscopic model of Aβ₄₀ and Aβ₄₂ aggregation and clearance of aggregated Aβ by activated microglia cells, which is enhanced by the interaction of antibody-bound Aβ. The model allows for the prediction of Aβ positron emission tomography (PET) imaging load as measured by a standardized uptake value ratio. A physiology-based pharmacokinetic model is seamlessly integrated to describe target exposure of monoclonal antibodies and simulate dynamics of cerebrospinal fluid (CSF) and plasma biomarkers, including CSF Aβ₄₂ and plasma Aβ₄₂ /Aβ₄₀ ratio biomarkers. Apolipoprotein E genotype is implemented as a difference in microglia clearance. By incorporating antibody-bound, plaque-mediated macrophage activation in the perivascular compartment, the model also predicts the incidence of amyloid-related imaging abnormalities with edema (ARIA-E). The QSP platform is calibrated with pharmacological and clinical information on aducanumab, bapineuzumab, crenezumab, gantenerumab, lecanemab, and solanezumab, predicting adequately the change in PET imaging measured amyloid load and the changes in the plasma Aβ₄₂ /Aβ₄₀ ratio while slightly overestimating the change in CSF Aβ₄₂ . ARIA-E is well predicted for all antibodies except bapineuzumab. This QSP model could support the clinical trial design of different amyloid-modulating interventions, define optimal titration and maintenance schedules, and provide a first step to understand the variability of biomarker response in clinical practice.

Interspecies and in vitro-in vivo scaling for quantitative modeling of whole-body drug pharmacokinetics in patients: Application to the anticancer drug oxaliplatin

Quantitative systems pharmacology holds the promises of integrating results from laboratory animals or in vitro human systems into the design of human pharmacokinetic/pharmacodynamic (PK/PD) models allowing for precision and personalized medicine. However, reliable and general in vitro-to-in vivo extrapolation and interspecies scaling methods are still lacking. Here, we developed a translational strategy for the anticancer drug oxaliplatin. Using ex vivo PK data in the whole blood of the mouse, rat, and human, a model representing the amount of platinum (Pt) in the plasma and in the red blood cells was designed and could faithfully fit each dataset independently. A "purely physiologically-based (PB)" scaling approach solely based on preclinical data failed to reproduce human observations, which were then included in the calibration. Investigating approaches in which one parameter was set as species-specific, whereas the others were computed by PB scaling laws, we concluded that allowing the Pt binding rate to plasma proteins to be species-specific permitted to closely fit all data, and guaranteed parameter identifiability. Such a strategy presenting the drawback of including all clinical datasets, we further identified a minimal subset of human data ensuring accurate model calibration. Next, a "whole body" model of oxaliplatin human PK was inferred from the ex vivo study. Its three remaining parameters were estimated, using one third of the available patient data. Remarkably, the model achieved a good fit to the training dataset and successfully reproduced the unseen observations. Such validation endorsed the legitimacy of our scaling methodology calling for its testing with other drugs.

Application of physiologically-based pharmacokinetic models for therapeutic proteins and other novel modalities

The past two decades have seen diversification of drug development pipelines and approvals from traditional small molecule therapies to alternative modalities including monoclonal antibodies, engineered proteins, antibody drug conjugates (ADCs), oligonucleotides and gene therapies. At the same time, physiologically-based pharmacokinetic (PBPK) models for small molecules have seen increased industry and regulatory acceptance.This review focusses on the current status of the application of PBPK models to these newer modalities and give a perspective on the successes, challenges and future directions of this field.There is greatest experience in the development of PBPK models for therapeutic proteins, and PBPK models for ADCs benefit from prior experience for both therapeutic proteins and small molecules. For other modalities, the application of PBPK models is in its infancy.Challenges are discussed and a common theme is lack of availability of physiological and experimental data to characterise systems and drug parameters to enable a priori prediction of pharmacokinetics. Furthermore, sufficient clinical data are required to build confidence in developed models.The PBPK modelling approach provides a quantitative framework for integrating knowledge and data from multiple sources and can be built on as more data becomes available.

Modulation of Ligand-Gated Glycine Receptors Via Functional Monoclonal Antibodies

Ion channels are targets of considerable therapeutic interest to address a wide variety of neurologic indications, including pain perception. Current pharmacological strategies have focused mostly on small molecule approaches that can be limited by selectivity requirements within members of a channel family or superfamily. Therapeutic antibodies have been proposed, designed, and characterized to alleviate this selectivity limitation; however, there are no Food and Drug Administration-approved therapeutic antibody-based drugs targeting ion channels on the market to date. Here, in an effort to identify novel classes of engineered ion channel modulators for potential neurologic therapeutic applications, we report the generation and characterization of six (EC₅₀ < 25nM) Cys-loop receptor family monoclonal antibodies with modulatory function against rat and human glycine receptor alpha 1 (GlyRα1) and/or GlyRα3. These antibodies have activating (i.e., positive modulator) or inhibiting (i.e., negative modulator) profiles. Moreover, GlyRα3 selectivity was successfully achieved for two of the three positive modulators identified. When dosed intravenously, the antibodies achieved sufficient brain exposure to cover their calculated in vitro EC₅₀ values. When compared head-to-head at identical exposures, the GlyRα3-selective antibody showed a more desirable safety profile over the nonselective antibody, thus demonstrating, for the first time, an advantage for GlyRα3-selectivity. Our data show that ligand-gated ion channels of the glycine receptor family within the central nervous system can be functionally modulated by engineered biologics in a dose-dependent manner and that, despite high protein homology between the alpha subunits, selectivity can be achieved within this receptor family, resulting in future therapeutic candidates with more desirable drug safety profiles. SIGNIFICANCE STATEMENT: This study presents immunization and multiplatform screening approaches to generate a diverse library of functional antibodies (agonist, potentiator, or inhibitory) raised against human glycine receptors (GlyRs). This study also demonstrates the feasibility of acquiring alpha subunit selectivity, a desirable therapeutic profile. When tested in vivo, these tool molecules demonstrated an increased safety profile in favor of GlyRα3-selectivity. These are the first reported functional GlyR antibodies that may open new avenues to treating central nervous system diseases with subunit selective biologics.

PBPK-PD modeling for the preclinical development and clinical translation of tau antibodies for Alzheimer's disease

Disrupted tau proteostasis and transneuronal spread is a pathological hallmark of Alzheimer's disease. Neurodegenerative diseases remain an unmet medical need and novel disease modifying therapeutics are paramount. Our objective was to develop a mechanistic mathematical model to enhance our understanding of tau antibody pharmacokinetics and pharmacodynamics in animals and humans. A physiologically-based pharmacokinetic-pharmacodynamic (PBPK-PD) modeling approach was employed to support the preclinical development and clinical translation of therapeutic antibodies targeting tau for the treatment of Alzheimer's disease. The pharmacokinetics of a tau antibody was evaluated in rat and non-human primate microdialysis studies. Model validation for humans was performed using publicly available clinical data for gosuranemab. In-silico analyses were performed to predict tau engagement in human brain for a range of tau antibody affinities and various dosing regimens. PBPK-PD modeling enabled a quantitative understanding for the relationship between dose, affinity, and target engagement, which supported lead candidate optimization and predictions of clinically efficacious dosing regimens.

Investigating brain uptake of a non-targeting monoclonal antibody after intravenous and intracerebroventricular administration

Monoclonal antibodies play an important role in the treatment of various diseases. However, the development of these drugs against neurological disorders where the drug target is located in the brain is challenging and requires a good understanding of the local drug concentration in the brain. In this original research, we investigated the systemic and local pharmacokinetics in the brain of healthy rats after either intravenous (IV) or intracerebroventricular (ICV) administration of EGFRvIII-T-Cell bispecific (TCB), a bispecific monoclonal antibody. We established an experimental protocol that allows serial sampling in serum, cerebrospinal fluid (CSF) and interstitial fluid (ISF) of the prefrontal cortex in freely moving rats. For detection of drug concentration in ISF, a push-pull microdialysis technique with large pore membranes was applied. Brain uptake into CSF and ISF was characterized and quantified with a reduced brain physiologically-based pharmacokinetic model. The model allowed us to interpret the pharmacokinetic processes of brain uptake after different routes of administration. The proposed model capturing the pharmacokinetics in serum, CSF and ISF of the prefrontal cortex suggests a barrier function between the CSF and ISF that impedes free antibody transfer. This finding suggests that ICV administration may not be better suited to reach higher local drug exposure as compared to IV administration. The model enabled us to quantify the relative contribution of the blood-brain barrier (BBB) and Blood-CSF-Barrier to the uptake into the interstitial fluid of the brain. In addition, we compared the brain uptake of three monoclonal antibodies after IV dosing. In summary, the presented approach can be applied to profile compounds based on their relative uptake in the brain and provides quantitative insights into which pathways are contributing to the net exposure in the brain.

Revisiting Cerebrospinal Fluid Flow Direction and Rate in Physiologically Based Pharmacokinetic Model

The bidirectional pulsatile movement of cerebrospinal fluid (CSF), instead of the traditionally believed unidirectional and constant CSF circulation, has been demonstrated. In the present study, the structure and parameters of the CSF compartments were revisited in our comprehensive and validated central nervous system (CNS)-specific, physiologically based pharmacokinetic (PBPK) model of healthy rats (LeiCNS-PK3.0). The bidirectional and site-dependent CSF movement was incorporated into LeiCNS-PK3.0 to create the new LeiCNS-PK“3.1” model. The physiological CSF movement rates in healthy rats that are unavailable from the literature were estimated by fitting the PK data of sucrose, a CSF flow marker, after intra-CSF administration. The capability of LeiCNS-PK3.1 to describe the PK profiles of other molecules was compared with that of the original LeiCNS-PK3.0 model. LeiCNS-PK3.1 demonstrated superior description of the CSF PK profiles of a range of small molecules after intra-CSF administration over LeiCNS-PK3.0. LeiCNS-PK3.1 also retained the same level of predictability of CSF PK profiles in cisterna magna after intravenous administration. These results support the theory of bidirectional and site-dependent CSF movement across the entire CSF space over unidirectional and constant CSF circulation in healthy rats, pointing out the need to revisit the structures and parameters of CSF compartments in CNS-PBPK models.

Mathematical Models to Characterize the Absorption, Distribution, Metabolism, and Excretion of Protein Therapeutics

Therapeutic proteins (TPs) have ranked among the most important and fastest-growing classes of drugs in the clinic, yet the development of successful TPs is often limited by unsatisfactory efficacy. Understanding pharmacokinetic (PK) characteristics of TPs is key to achieving sufficient and prolonged exposure at the site of action, which is a prerequisite for eliciting desired pharmacological effects. PK modeling represents a powerful tool to investigate factors governing in vivo disposition of TPs. In this mini-review, we discuss many state-of-the-art models that recapitulate critical processes in each of the absorption, distribution, metabolism/catabolism, and excretion pathways of TPs, which can be integrated into the physiologically-based pharmacokinetic framework. Additionally, we provide our perspectives on current opportunities and challenges for evolving the PK models to accelerate the discovery and development of safe and efficacious TPs. SIGNIFICANCE STATEMENT: This minireview provides an overview of mechanistic pharmacokinetic (PK) models developed to characterize absorption, distribution, metabolism, and elimination (ADME) properties of therapeutic proteins (TPs), which can support model-informed discovery and development of TPs. As the next-generation of TPs with diverse physicochemical properties and mechanism-of-action are being developed rapidly, there is an urgent need to better understand the determinants for the ADME of TPs and evolve existing platform PK models to facilitate successful bench-to-bedside translation of these promising drug molecules.

Application of Physiologically Based Pharmacokinetic Modeling in Preclinical Studies: A Feasible Strategy to Practice the Principles of 3Rs

Pharmacokinetic characterization plays a vital role in drug discovery and development. Although involving numerous laboratory animals with error-prone, labor-intensive, and time-consuming procedures, pharmacokinetic profiling is still irreplaceable in preclinical studies. With physiologically based pharmacokinetic (PBPK) modeling, the in vivo profiles of drug absorption, distribution, metabolism, and excretion can be predicted. To evaluate the application of such an approach in preclinical investigations, the plasma pharmacokinetic profiles of seven commonly used probe substrates of microsomal enzymes, including phenacetin, tolbutamide, omeprazole, metoprolol, chlorzoxazone, nifedipine, and baicalein, were predicted in rats using bottom-up PBPK models built with in vitro data alone. The prediction's reliability was assessed by comparison with in vivo pharmacokinetic data reported in the literature. The overall predicted accuracy of PBPK models was good with most fold errors within 2, and the coefficient of determination (R2) between the predicted concentration data and the observed ones was more than 0.8. Moreover, most of the observation dots were within the prediction span of the sensitivity analysis. We conclude that PBPK modeling with acceptable accuracy may be incorporated into preclinical studies to refine in vivo investigations, and PBPK modeling is a feasible strategy to practice the principles of 3Rs.

Algorithmic multiscale analysis for the FcRn mediated regulation of antibody PK in human

A demonstration is provided on how algorithmic asymptotic analysis of multi-scale pharmacokinetics (PK) systems can provide (1) system level understanding and (2) predictions on the response of the model when parameters vary. Being algorithmic, this type of analysis is not hindered by the size or complexity of the model and requires no input from the investigator. The algorithm identifies the constraints that are generated by the fast part of the model and the components of the slow part of the model that drive the system within these constraints. The demonstration is based on a typical monoclonal antibody PK model. It is shown that the findings produced by the traditional methodologies, which require significant input by the investigator, can be produced algorithmically and more accurately. Moreover, additional insights are provided by the algorithm, which cannot be obtained by the traditional methodologies; notably, the dual influence of certain reactions depending on whether their fast or slow component dominates. The analysis reveals that the importance of physiological processes in determining the systemic exposure of monoclonal antibodies (mAb) varies with time. The analysis also confirms that the rate of mAb uptake by the cells, the binding affinity of mAb to neonatal Fc receptor (FcRn), and the intracellular degradation rate of mAb are the most sensitive parameters in determining systemic exposure of mAbs. The algorithmic framework for analysis introduced and the resulting novel insights can be used to engineer antibodies with desired PK properties.

Understanding the Blood-Brain Barrier and Beyond: Challenges and Opportunities for Novel CNS Therapeutics

This review addresses questions on how to accomplish successful central nervous system (CNS) drug delivery (i.e., having the right concentration at the right CNS site, at the right time), by understanding the rate and extent of blood‐brain barrier (BBB) transport and intra‐CNS distribution in relation to CNS target site(s) exposure. To this end, we need to obtain and integrate quantitative and connected data on BBB using the Combinatory Mapping Approach that includes in vivo and ex vivo animal measurements, and the physiologically based comprehensive LEICNSPK3.0 mathematical model that can translate from animals to humans. For small molecules, slow diffusional BBB transport and active influx and efflux BBB transport determine the differences between plasma and CNS pharmacokinetics. Obviously, active efflux is important for limiting CNS drug delivery. Furthermore, liposomal formulations of small molecules may to a certain extent circumvent active influx and efflux at the BBB. Interestingly, for CNS pathologies, despite all reported disease associated BBB and CNS functional changes in animals and humans, integrative studies typically show a lack of changes on CNS drug delivery for the small molecules. In contrast, the understanding of the complex vesicle‐based BBB transport modes that are important for CNS delivery of large molecules is in progress, and their BBB transport seems to be significantly affected by CNS diseases. In conclusion, today, CNS drug delivery of small drugs can be well assessed and understood by integrative approaches, although there is still quite a long way to go to understand CNS drug delivery of large molecules.

Minimal brain PBPK model to support the preclinical and clinical development of antibody therapeutics for CNS diseases

There are several antibody therapeutics in preclinical and clinical development, industry-wide, for the treatment of central nervous system (CNS) disorders. Due to the limited permeability of antibodies across brain barriers, the quantitative understanding of antibody exposure in the CNS is important for the design of antibody drug characteristics and determining appropriate dosing regimens. We have developed a minimal physiologically-based pharmacokinetic (mPBPK) model of the brain for antibody therapeutics, which was reduced from an existing multi-species platform brain PBPK model. All non-brain compartments were combined into a single tissue compartment and cerebral spinal fluid (CSF) compartments were combined into a single CSF compartment. The mPBPK model contains 16 differential equations, compared to 100 in the original PBPK model, and improved simulation speed approximately 11-fold. Area under the curve ratios for minimal versus full PBPK models were close to 1 across species for both brain and plasma compartments, which indicates the reduced model simulations are similar to those of the original model. The minimal model retained detailed physiological processes of the brain while not significantly affecting model predictability, which supports the law of parsimony in the context of balancing model complexity with added predictive power. The minimal model has a variety of applications for supporting the preclinical development of antibody therapeutics and can be expanded to include target information for evaluating target engagement to inform clinical dose selection.

Brain Disposition of Antibody-Based Therapeutics: Dogma, Approaches and Perspectives

Due to their high specificity, monoclonal antibodies have been widely investigated for their application in drug delivery to the central nervous system (CNS) for the treatment of neurological diseases such as stroke, Alzheimer’s, and Parkinson’s disease. Research in the past few decades has revealed that one of the biggest challenges in the development of antibodies for drug delivery to the CNS is the presence of blood–brain barrier (BBB), which acts to restrict drug delivery and contributes to the limited uptake (0.1–0.2% of injected dose) of circulating antibodies into the brain. This article reviews the various methods currently used for antibody delivery to the CNS at the preclinical stage of development and the underlying mechanisms of BBB penetration. It also describes efforts to improve or modulate the physicochemical and biochemical properties of antibodies (e.g., charge, Fc receptor binding affinity, and target affinity), to adapt their pharmacokinetics (PK), and to influence their distribution and disposition into the brain. Finally, a distinction is made between approaches that seek to modify BBB permeability and those that use a physiological approach or antibody engineering to increase uptake in the CNS. Although there are currently inherent difficulties in developing safe and efficacious antibodies that will cross the BBB, the future prospects of brain-targeted delivery of antibody-based agents are believed to be excellent.

Dose selection for intracerebroventricular cerliponase alfa in children with CLN2 disease, translation from animal to human in a rare genetic disease

Neuronal ceroid lipofuscinosis type 2 (CLN2 disease) is an ultra‐rare pediatric neurodegenerative disorder characterized by deficiency of the lysosomal enzyme tripeptidyl peptidase‐1 (TPP1). In the absence of adequate TPP1, lysosomal storage material accumulation occurs in the central nervous system (CNS) accompanied by neurodegeneration and neurological decline that culminates in childhood death. Cerliponase alfa is a recombinant human TPP1 enzyme replacement therapy administered via intracerebroventricular infusion and approved for the treatment of CLN2 disease. Here, we describe two allometric methods, calculated by scaling brain mass across species, that informed the human dose selection and exposure prediction of cerliponase alfa from preclinical studies in monkeys and a dog model of CLN2 disease: (1) scaling of dose using a human‐equivalent dose factor; and (2) scaling of compartmental pharmacokinetic (PK) model parameters. Source PK data were obtained from cerebrospinal fluid (CSF) samples from dogs and monkeys, and the human exposure predictions were confirmed with CSF data from the first‐in‐human clinical study. Nonclinical and clinical data were analyzed using noncompartmental analysis and nonlinear mixed‐effect modeling approaches. Both allometric methods produced CSF exposure predictions within twofold of the observed exposure parameters maximum plasma concentration (C_max) and area under the curve (AUC). Furthermore, cross‐species qualification produced consistent and reasonable PK profile predictions, which supported the allometric scaling of model parameters. The challenges faced in orphan drug development place an increased importance on, and opportunity for, data translation from research and nonclinical development. Our approach to dose translation and human exposure prediction for cerliponase alfa may be applicable to other CNS administered therapies being developed.

Harnessing cerebrospinal fluid circulation for drug delivery to brain tissues

Initially thought to be useful only to reach tissues in the immediate vicinity of the CSF circulatory system, CSF circulation is now increasingly viewed as a viable pathway to deliver certain therapeutics deeper into brain tissues. There is emerging evidence that this goal is achievable in the case of large therapeutic proteins, provided conditions are met that are described herein. We show how fluid dynamic modeling helps predict infusion rate and duration to overcome high CSF turnover. We posit that despite model limitations and controversies, fluid dynamic models, pharmacokinetic models, preclinical testing, and a qualitative understanding of the glymphatic system circulation can be used to estimate drug penetration in brain tissues. Lastly, in addition to highlighting landmark scientific and medical literature, we provide practical advice on formulation development, device selection, and pharmacokinetic modeling. Our review of clinical studies suggests a growing interest for intra-CSF delivery, particularly for targeted proteins.

A physiologically-based pharmacokinetic model to describe antisense oligonucleotide distribution after intrathecal administration

Antisense oligonucleotides (ASOs) are promising therapeutic agents for a variety of neurodegenerative and neuromuscular disorders, e.g., Alzheimer's, Parkinson's and Huntington's diseases, spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS), caused by genetic abnormalities or increased protein accumulation. The blood-brain barrier (BBB) represents a challenge to the delivery of systemically administered ASOs to the relevant sites of action within the central nervous system (CNS). Intrathecal (IT) delivery, in which drugs are administered directly into the cerebrospinal fluid (CSF) space, enables to bypass the BBB. Several IT-administered ASO therapeutics have already demonstrated clinical effect, e.g., nusinersen (SMA) and tofersen (ALS). Due to novelty of IT dosing for ASOs, very limited pharmacokinetic (PK) data is available and only a few modeling reports have been generated. The objective of this work is to advance fundamental understanding of whole-body distribution of IT-administered ASOs. We propose a physiologically-based pharmacokinetic modeling approach to describe the distribution along the neuroaxis based on PK data from non-human primate (NHP) studies. We aim to understand the key processes that drive and limit ASO access to the CNS target tissues. To elucidate the trade-off between parameter identifiability and physiological plausibility of the model, several alternative model structures were chosen and fitted to the NHP data. The model analysis of the NHP data led to important qualitative conclusions that can inform projection to human. In particular, the model predicts that the maximum total exposure in the CNS tissues, including the spinal cord and brain, is achieved within two days after the IT injection, and the maximum amount absorbed by the CNS tissues is about 4% of the administered IT dose. This amount greatly exceeds the CNS exposures delivered by systemic administration of ASOs. Clearance from the CNS is controlled by the rate of transfer from the CNS tissues back to CSF, whereas ASO degradation in tissues is very slow and can be neglected. The model also describes local differences in ASO concentration emerging along the spinal CSF canal. These local concentrations need to be taken into account when scaling the NHP model to human: due to the lengthier human spinal column, inhomogeneity along the spinal CSF may cause even higher gradients and delays potentially limiting ASO access to target CNS tissues.

Choroid Plexus and Drug Removal Mechanisms

Timely and efficient removal of xenobiotics and metabolites from the brain is crucial in maintaining the homeostasis and normal function of the brain. The choroid plexus (CP) forms the blood-cerebrospinal fluid barrier and vitally removes drugs and wastes from the brain through several co-existing clearance mechanisms. The CP epithelial (CPE) cells synthesize and secrete the cerebrospinal fluid (CSF). As the CSF passes through the ventricular and subarachnoid spaces and eventually drains into the general circulation, it collects and removes drugs, toxins, and metabolic wastes from the brain. This bulk flow of the CSF serves as a default and non-selective pathway for the removal of solutes and macromolecules from the brain interstitium. Besides clearance by CSF bulk flow, the CPE cells express several multispecific membrane transporters to actively transport substrates from the CSF side into the blood side. In addition, several phase I and II drug-metabolizing enzymes are expressed in the CPE cells, which enzymatically inactivate a broad spectrum of reactive or toxic substances. This review summarizes our current knowledge of the functional characteristics and key contributors to the various clearance pathways in the CP-CSF system, overviewing recent developments in our understanding of CSF flow dynamics and the functional roles of CP uptake and efflux transporters in influencing CSF drug concentrations.

Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions

With more than 90 approved drugs by 2020, therapeutic antibodies have played a central role in shifting the treatment landscape of many diseases, including autoimmune disorders and cancers. While showing many therapeutic advantages such as long half-life and highly selective actions, therapeutic antibodies still face many outstanding issues associated with their pharmacokinetics (PK) and pharmacodynamics (PD), including high variabilities, low tissue distributions, poorly-defined PK/PD characteristics for novel antibody formats, and high rates of treatment resistance. We have witnessed many successful cases applying PK/PD modeling to answer critical questions in therapeutic antibodies’ development and regulations. These models have yielded substantial insights into antibody PK/PD properties. This review summarized the progress, challenges, and future directions in modeling antibody PK/PD and highlighted the potential of applying mechanistic models addressing the development questions.

Current progress and limitations of AAV mediated delivery of protein therapeutic genes and the importance of developing quantitative pharmacokinetic/pharmacodynamic (PK/PD) models

While protein therapeutics are one of the most successful class of drug molecules, they are expensive and not suited for treating chronic disorders that require long-term dosing. Adeno-associated virus (AAV) mediated in vivo gene therapy represents a viable alternative, which can deliver the genes of protein therapeutics to produce long-term expression of proteins in target tissues. Ongoing clinical trials and recent regulatory approvals demonstrate great interest in these therapeutics, however, there is a lack of understanding regarding their cellular disposition, whole-body disposition, dose-exposure relationship, exposure-response relationship, and how product quality and immunogenicity affects these important properties. In addition, there is a lack of quantitative studies to support the development of pharmacokinetic-pharmacodynamic models, which can support the discovery, development, and clinical translation of this delivery system. In this review, we have provided a state-of-the-art overview of current progress and limitations related to AAV mediated delivery of protein therapeutic genes, along with our perspective on the steps that need to be taken to improve clinical translation of this therapeutic modality.

A modeling informed quantitative approach to salvage clinical trials interrupted due to COVID-19

Many ongoing Alzheimer's disease central nervous system clinical trials are being disrupted and halted due to the COVID-19 pandemic. They are often of a long duration' are very complex; and involve many stakeholders, not only the scientists and regulators but also the patients and their family members. It is mandatory for us as a community to explore all possibilities to avoid losing all the knowledge we have gained from these ongoing trials. Some of these trials will need to completely restart, but a substantial number can restart after a hiatus with the proper protocol amendments. To salvage the information gathered so far, we need out-of-the-box thinking for addressing these missingness problems and to combine information from the completers with those subjects undergoing complex protocols deviations and amendments after restart in a rational, scientific way. Physiology-based pharmacokinetic (PBPK) modeling has been a cornerstone of model-informed drug development with regard to drug exposure at the site of action, taking into account individual patient characteristics. Quantitative systems pharmacology (QSP), based on biology-informed and mechanistic modeling of the interaction between a drug and neuronal circuits, is an emerging technology to simulate the pharmacodynamic effects of a drug in combination with patient-specific comedications, genotypes, and disease states on functional clinical scales. We propose to combine these two approaches into the concept of computer modeling-based virtual twin patients as a possible solution to harmonize the readouts from these complex clinical datasets in a biologically and therapeutically relevant way.

Cross-species/cross-modality physiologically based pharmacokinetics for biologics: 89Zr-labelled albumin-binding domain antibody GSK3128349 in humans

Two-pore physiologically-based pharmacokinetics (PBPK) for biologics describes the tissue distribution and elimination kinetics of soluble proteins as a function of their hydrodynamic radius and the physiological properties of the organs. Whilst many studies have been performed in rodents to parameterize the PBPK framework in terms of organ-specific lymph flow rates, similar validation in humans has been limited. This is mainly due to the paucity of the tissue distribution time course data for biologics that is not distorted by target-related binding. Here, we demonstrate that a PBPK model based on rodent data provided good to satisfactory extrapolation to the tissue distribution time course of ⁸⁹Zr-labeled albumin-binding domain antibody (AlbudAb™) GSK3128349 in healthy human volunteers, including correct prediction of albumin-like plasma half-life, volume of distribution, and extravasation half-life. The AlbudAb™ used only binds albumin, and hence it also provides information about the tissue distribution kinetics and turnover of that ubiquitous and multifunctional plasma protein.

Whole-Body Pharmacokinetics of Antibody in Mice Determined using Enzyme-Linked Immunosorbent Assay and Derivation of Tissue Interstitial Concentrations

Here we have reported whole-body disposition of wild-type IgG and FcRn non-binding IgG in mice, determined using Enzyme-Linked Immunosorbent Assay (ELISA). The disposition data generated using ELISA are compared with previously published biodistribution data generated using radiolabelled IgG. In addition, we introduce a novel concept of ABC_IS values, which are defined as percentage ratios of tissue interstitial and plasma AUC values. These values can help in predicting tissue interstitial concentrations of monoclonal antibodies (mAbs) based on the plasma concentrations. Tissue interstitial concentrations derived from our study are also compared with previously reported values measured using microdialysis or centrifugation method. Lastly, the new set of biodistribution data generated using ELISA are used to refine the PBPK model for mAbs.

The biodistribution of therapeutic proteins: Mechanism, implications for pharmacokinetics, and methods of evaluation

Therapeutic proteins (TPs) are a diverse drug class that include monoclonal antibodies (mAbs), recombinantly expressed enzymes, hormones and growth factors, cytokines (e.g. chemokines, interleukins, interferons), as well as a wide range of engineered fusion scaffolds containing IgG1 Fc domain for half-life extension. As the pharmaceutical industry advances more potent and selective protein-based medicines through discovery and into the clinical stages of development, it has become widely appreciated that a comprehensive understanding of the mechanisms of TP biodistribution can aid this endeavor. This review aims to highlight the literature that has advanced our understanding of the determinants of TP biodistribution. A particular emphasis is placed on the multi-faceted role of the neonatal Fc receptor (FcRn) in mAb and Fc-fusion protein disposition. In addition, characterization of the TP-target interaction at the cell-level is discussed as an essential strategy to establish pharmacokinetic-pharmacodynamic (PK/PD) relationships that may lead to more informed human dose projections during clinical development. Methods for incorporation of tissue and cell-level parameters defining these characteristics into higher-order mechanistic and semi-mechanistic PK models will also be presented.