Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

Designing drugs optimized for both blood-brain barrier permeation and intra-cerebral partition

INTRODUCTION

With the increasing incidence and prevalence of neurological disorders globally, there is a paramount need for new pharmacotherapies. BBB effectively protects the brain but raises a profound challenge to drug permeation, with less than 2% of most drugs reaching the CNS.

AREAS COVERED

This article reviews aspects of the most recent design strategies, providing insights into ideas and concepts in CNS drug discovery. An overview of the products available on the market is given and why clinical trials are continuously failing is discussed.

EXPERT OPINION

Among the available CNS drugs, small molecules account for most successful CNS therapeutics due to their ability to penetrate the BBB through passive or carrier-mediated mechanisms. The development of new CNS drugs is very difficult. To date, there is a lack of effective drugs for alleviating or even reversing the progression of brain diseases. Particularly, the use of artificial intelligence strategies, together with more appropriate animal models, may enable the design of molecules with appropriate permeation, to elicit a biological response from the neurotherapeutic target.

Drug Repurposing, a Fast-Track Approach to Develop Effective Treatments for Glioblastoma

Glioblastoma (GBM) remains one of the most difficult tumors to treat. The mean overall survival rate of 15 months and the 5-year survival rate of 5% have not significantly changed for almost 2 decades. Despite progress in understanding the pathophysiology of the disease, no new effective treatments to combine with radiation therapy after surgical tumor debulking have become available since the introduction of temozolomide in 1999. One of the main reasons for this is the scarcity of compounds that cross the blood-brain barrier (BBB) and reach the brain tumor tissue in therapeutically effective concentrations. In this review, we focus on the role of the BBB and its importance in developing brain tumor treatments. Moreover, we discuss drug repurposing, a drug discovery approach to identify potential effective candidates with optimal pharmacokinetic profiles for central nervous system (CNS) penetration and that allows rapid implementation in clinical trials. Additionally, we provide an overview of repurposed candidate drug currently being investigated in GBM at the preclinical and clinical levels. Finally, we highlight the importance of phase 0 trials to confirm tumor drug exposure and we discuss emerging drug delivery technologies as an alternative route to maximize therapeutic efficacy of repurposed candidate drug.

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer's and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.

Design and Measurement of Drug Tissue Concentration Asymmetry and Tissue Exposure-Effect (Tissue PK-PD) Evaluation

The "free drug hypothesis" assumes that, in the absence of transporters, the steady state free plasma concentrations equal to that at the site of action that elicit pharmacologic effects. While it is important to utilize the free drug hypothesis, exceptions exist that the free plasma exposures, either at C_max, C_trough, and C_average, or at other time points, cannot represent the corresponding free tissue concentrations. This "drug concentration asymmetry" in both total and free form can influence drug disposition and pharmacological effects. In this review, we first discuss options to assess total and free drug concentrations in tissues. Then various drug design strategies to achieve concentration asymmetry are presented. Last, the utilities of tissue concentrations in understanding exposure-effect relationships and translational projections to humans are discussed for several therapeutic areas and modalities. A thorough understanding in plasma and tissue exposures correlation with pharmacologic effects can provide insightful guidance to aid drug discovery.

Drug Distribution in Brain and Cerebrospinal Fluids in Relation to IC50 Values in Aging and Alzheimer's Disease, Using the Physiologically Based LeiCNS-PK3.0 Model

Background

Very little knowledge exists on the impact of Alzheimer’s disease on the CNS target site pharmacokinetics (PK).

Aim

To predict the CNS PK of cognitively healthy young and elderly and of Alzheimer’s patients using the physiologically based LeiCNS-PK3.0 model.

Methods

LeiCNS-PK3.0 was used to predict the PK profiles in brain extracellular (brain_ECF) and intracellular (brain_ICF) fluids and cerebrospinal fluid of the subarachnoid space (CSF_SAS) of donepezil, galantamine, memantine, rivastigmine, and semagacestat in young, elderly, and Alzheimer’s patients. The physiological parameters of LeiCNS-PK3.0 were adapted for aging and Alzheimer’s based on an extensive literature search. The CNS PK profiles at plateau for clinical dose regimens were related to in vitro IC₅₀ values of acetylcholinesterase, butyrylcholinesterase, N-methyl-D-aspartate, or gamma-secretase.

Results

The PK profiles of all drugs differed between the CNS compartments regarding plateau levels and fluctuation. Brain_ECF, brain_ICF and CSF_SAS PK profile relationships were different between the drugs. Aging and Alzheimer’s had little to no impact on CNS PK. Rivastigmine acetylcholinesterase IC₅₀ values were not reached. Semagacestat brain PK plateau levels were below the IC₅₀ of gamma-secretase for half of the interdose interval, unlike CSF_SAS PK profiles that were consistently above IC_50.

Conclusion

This study provides insights into the relations between CNS compartments PK profiles, including target sites. CSF_SAS PK appears to be an unreliable predictor of brain PK. Also, despite extensive changes in blood-brain barrier and brain properties in Alzheimer’s, this study shows that the impact of aging and Alzheimer’s pathology on CNS distribution of the five drugs is insignificant.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-022-03281-3.

Nanomedicine for brain cancer

CNS tumors remain among the deadliest forms of cancer, resisting conventional and new treatment approaches, with mortality rates staying practically unchanged over the past 30 years. One of the primary hurdles for treating these cancers is delivering drugs to the brain tumor site in therapeutic concentration, evading the blood-brain (tumor) barrier (BBB/BBTB). Supramolecular nanomedicines (NMs) are increasingly demonstrating noteworthy prospects for addressing these challenges utilizing their unique characteristics, such as improving the bioavailability of the payloadsviacontrolled pharmacokinetics and pharmacodynamics, BBB/BBTB crossing functions, superior distribution in the brain tumor site, and tumor-specific drug activation profiles. Here, we review NM-based brain tumor targeting approaches to demonstrate their applicability and translation potential from different perspectives. To this end, we provide a general overview of brain tumor and their treatments, the incidence of the BBB and BBTB, and their role on NM targeting, as well as the potential of NMs for promoting superior therapeutic effects. Additionally, we discuss critical issues of NMs and their clinical trials, aiming to bolster the potential clinical applications of NMs in treating these life-threatening diseases.

Current Approaches of Building Mechanistic Pharmacodynamic Drug-Target Binding Models

Mechanistic pharmacodynamic models that incorporate the binding kinetics of drug-target interactions have several advantages in understanding target engagement and the efficacy of a drug dose. However, guidelines on how to build and interpret mechanistic pharmacodynamic drug-target binding models considering both biological and computational factors are still missing in the literature. In this chapter, current approaches of building mechanistic PD models and their advantages are discussed. We also present a methodology on how to select a suitable model considering both biological and computational perspectives, as well as summarize the challenges of current mechanistic PD models.

From blood to brain: blood cell-based biomimetic drug delivery systems

Brain drug delivery remains a major difficulty for several challenges including the blood-brain barrier, lesion spot targeting, and stability during circulation. Blood cells including erythrocytes, platelets, and various subpopulations of leukocytes have distinct features such as long-circulation, natural targeting, and chemotaxis. The development of biomimetic drug delivery systems based on blood cells for brain drug delivery is growing fast by using living cells, membrane coating nanotechnology, or cell membrane-derived nanovesicles. Blood cell-based vehicles are superior delivery systems for their engineering feasibility and versatile delivery ability of chemicals, proteins, and all kinds of nanoparticles. Here, we focus on advances of blood cell-based biomimetic carriers for from blood to brain drug delivery and discuss their translational challenges in the future.

Modelling the central nervous system: tissue engineering of the cellular microenvironment

With the increasing prevalence of neurodegenerative diseases, improved models of the central nervous system (CNS) will improve our understanding of neurophysiology and pathogenesis, whilst enabling exploration of novel therapeutics. Studies of brain physiology have largely been carried out using in vivo models, ex vivo brain slices or primary cell culture from rodents. Whilst these models have provided great insight into complex interactions between brain cell types, key differences remain between human and rodent brains, such as degree of cortical complexity. Unfortunately, comparative models of human brain tissue are lacking. The development of induced Pluripotent Stem Cells (iPSCs) has accelerated advancement within the field of in vitro tissue modelling. However, despite generating accurate cellular representations of cortical development and disease, two-dimensional (2D) iPSC-derived cultures lack an entire dimension of environmental information on structure, migration, polarity, neuronal circuitry and spatiotemporal organisation of cells. As such, researchers look to tissue engineering in order to develop advanced biomaterials and culture systems capable of providing necessary cues for guiding cell fates, to construct in vitro model systems with increased biological relevance. This review highlights experimental methods for engineering of in vitro culture systems to recapitulate the complexity of the CNS with consideration given to previously unexploited biophysical cues within the cellular microenvironment.

Chemical tools for epichaperome-mediated interactome dysfunctions of the central nervous system

Diseases are a manifestation of how thousands of proteins interact. In several diseases, such as cancer and Alzheimer’s disease, proteome-wide disturbances in protein-protein interactions are caused by alterations to chaperome scaffolds termed epichaperomes. Epichaperome-directed chemical probes may be useful for detecting and reversing defective chaperomes. Here we provide structural, biochemical, and functional insights into the discovery of epichaperome probes, with a focus on their use in central nervous system diseases. We demonstrate on-target activity and kinetic selectivity of a radiolabeled epichaperome probe in both cells and mice, together with a proof-of-principle in human patients in an exploratory single group assignment diagnostic study (ClinicalTrials.gov Identifier: NCT03371420). The clinical study is designed to determine the pharmacokinetic parameters and the incidence of adverse events in patients receiving a single microdose of the radiolabeled probe administered by intravenous injection. In sum, we introduce a discovery platform for brain-directed chemical probes that specifically modulate epichaperomes and provide proof-of-principle applications in their use in the detection, quantification, and modulation of the target in complex biological systems.

Here, the authors show structural, biochemical, and functional insights into the discovery of epichaperome‐ directed chemical probes for use in central nervous system diseases. Probes emerging from this work have translated to human clinical studies in Alzheimer’s disease and cancer.

Model-based Target Pharmacology Assessment (mTPA): An Approach Using PBPK/PD Modeling and Machine Learning to Design Medicinal Chemistry and DMPK Strategies in Early Drug Discovery

The optimal pharmacokinetic (PK) required for a drug candidate to elicit efficacy is highly dependent on the targeted pharmacology, a relationship that is often not well characterized during early phases of drug discovery. Generic assumptions around PK and potency risk misguiding screening and compound design toward nonoptimal absorption, distribution, metabolism, and excretion (ADME) or molecular properties and ultimately may increase attrition as well as hit-to-lead and lead optimization timelines. The present work introduces model-based target pharmacology assessment (mTPA), a computational approach combining physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling, sensitivity analysis, and machine learning (ML) to elucidate the optimal combination of PK, potency, and ADME specific for the targeted pharmacology. Examples using frequently encountered PK/PD relationships are presented to illustrate its application, and the utility and benefits of deploying such an approach to guide early discovery efforts are discussed.

Proteomics for Target Identification in Psychiatric and Neurodegenerative Disorders

Psychiatric and neurodegenerative disorders such as schizophrenia (SCZ), Parkinson's disease (PD), and Alzheimer's disease (AD) continue to grow around the world with a high impact on health, social, and economic outcomes for the patient and society. Despite efforts, the etiology and pathophysiology of these disorders remain unclear. Omics technologies have contributed to the understanding of the molecular mechanisms that underlie these complex disorders and have suggested novel potential targets for treatment and diagnostics. Here, we have highlighted the unique and common pathways shared between SCZ, PD, and AD and highlight the main proteomic findings over the last 5 years using in vitro models, postmortem brain samples, and cerebrospinal fluid (CSF) or blood of patients. These studies have identified possible therapeutic targets and disease biomarkers. Further studies including target validation, the use of large sample sizes, and the integration of omics findings with bioinformatics tools are required to provide a better comprehension of pharmacological targets.

Toward Closed-Loop Electrical Stimulation of Neuronal Systems: A Review

Biological neuronal cells communicate using neurochemistry and electrical signals. The same phenomena also allow us to probe and manipulate neuronal systems and communicate with them. Neuronal system malfunctions cause a multitude of symptoms and functional deficiencies that can be assessed and sometimes alleviated by electrical stimulation. Our working hypothesis is that real-time closed-loop full-duplex measurement and stimulation paradigms can provide more in-depth insight into neuronal networks and enhance our capability to control diseases of the nervous system. In this study, we review extracellular electrical stimulation methods used in in vivo, in vitro, and in silico neuroscience research and in the clinic (excluding methods mainly aimed at neuronal growth and other similar effects) and highlight the potential of closed-loop measurement and stimulation systems. A multitude of electrical stimulation and measurement-based methods are widely used in research and the clinic. Closed-loop methods have been proposed, and some are used in the clinic. However, closed-loop systems utilizing more complex measurement analysis and adaptive stimulation systems, such as artificial intelligence systems connected to biological neuronal systems, do not yet exist. Our review promotes the research and development of intelligent paradigms aimed at meaningful communications between neuronal and information and communications technology systems, "dialogical paradigms," which have the potential to take neuroscience and clinical methods to a new level.

Pharmacokinetic Principles and Their Application to Central Nervous System Tumors

Despite increasing knowledge of the biologic drivers of central nervous system tumors, most targeted agents trialed to date have not shown activity against these tumors in clinical trials. To effectively treat central nervous system tumors, an active drug must achieve and maintain an effective exposure at the tumor site for a long enough period of time to exert its intended effect. However, this is difficult to assess and achieve due to the constraints of drug delivery to the central nervous system. To address this complex problem, an understanding of pharmacokinetic principles is necessary. Pharmacokinetics is classically described as the quantitative study of drug absorption, distribution, metabolism, and elimination. The innate chemical properties of a drug, its administration (dose, route and schedule), and host factors all influence these four key pharmacokinetic phases. The central nervous system adds a level of complexity to standard plasma pharmacokinetics as it is a coupled drug compartment. This review will discuss special considerations of pharmacokinetics in the context of therapeutic development for central nervous system tumors.

Repairing blood-CNS barriers: Future therapeutic approaches for neuropsychiatric disorders

Central nervous system (CNS) drug development faces significant difficulties that translate into high rates of failure and lack of innovation. The pathophysiology of neurological and psychiatric disorders often results in the breakdown of blood-CNS barriers, disturbing the CNS microenvironment and worsening disease progression. Therefore, restoring the integrity of blood-CNS barriers may have a beneficial influence in several CNS disorders and improve treatment outcomes. In this review, pathways that may be modulated to protect blood-CNS barriers from neuroinflammatory and oxidative insults are featured. First, the participation of the brain endothelium and glial cells in disruption processes is discussed. Then, the relevance of regulatory systems is analysed, specifically the hypothalamic-pituitary axis, the renin-angiotensin system, sleep and circadian rhythms, and glutamate neurotransmission. Lastly, compounds of endogenous and exogenous origin that are known to mediate the repair of blood-CNS barriers are presented. We believe that enhancing the protection of blood-CNS barriers is a promising therapeutic strategy to pursue in the future.

Human Brain Neuropharmacology: A Platform for Translational Neuroscience

Central nervous system (CNS) drug development has been plagued by a failure to translate effective therapies from the lab to the clinic. There are many potential reasons for this, including poor understanding of brain pharmacokinetic (PK) and pharmacodynamic (PD) factors, preclinical study flaws, clinical trial design issues, the complexity and variability of human brain diseases, as well as species differences. To address some of these problems, we have developed a platform for CNS drug discovery comprising: drug screening of primary adult human brain cells; human brain tissue microarray analysis of drug targets; and high-content phenotypic screening methods. In this opinion, I summarise the theoretical basis and the practical development and use of this platform in CNS drug discovery.

From Riluzole to Dexpramipexole via Substituted-Benzothiazole Derivatives for Amyotrophic Lateral Sclerosis Disease Treatment: Case Studies

The 1,3-benzothiazole (BTZ) ring may offer a valid option for scaffold-hopping from indole derivatives. Several BTZs have clinically relevant roles, mainly as CNS medicines and diagnostic agents, with riluzole being one of the most famous examples. Riluzole is currently the only approved drug to treat amyotrophic lateral sclerosis (ALS) but its efficacy is marginal. Several clinical studies have demonstrated only limited improvements in survival, without benefits to motor function in patients with ALS. Despite significant clinical trial efforts to understand the genetic, epigenetic, and molecular pathways linked to ALS pathophysiology, therapeutic translation has remained disappointingly slow, probably due to the complexity and the heterogeneity of this disease. Many other drugs to tackle ALS have been tested for 20 years without any success. Dexpramipexole is a BTZ structural analog of riluzole and was a great hope for the treatment of ALS. In this review, as an interesting case study in the development of a new medicine to treat ALS, we present the strategy of the development of dexpramipexole, which was one of the most promising drugs against ALS.

Use of Stem Cell Extracellular Vesicles as a "Holistic" Approach to CNS Repair

Neurodegeneration is a hallmark of many diseases and disorders of the central nervous system (CNS). High levels of neuroinflammation are often associated with irreparable damage to CNS cells due to the dysregulation of signaling cascades that are unable to restore a homeostatic balance. Due to the inherent complexity of the CNS, development of CNS-related therapeutics has met limited success. While stem cell therapy has been evaluated in the context of CNS repair, the mechanisms responsible for their functional properties have not been clearly defined. In recent years, there has been growing interest in the use of stem cell extracellular vesicles (EVs) for the treatment of various CNS pathologies as these vesicles are believed to mediate many of the functional effects associated with their donor stem cells. The potency of stem cell EVs is believed to be largely driven by their biological cargo which includes various types of RNAs, proteins, and cytokines. In this review, we describe the characteristic properties of stem cell EVs and summarize their reported neuroprotective and immunomodulatory functions. A special emphasis is placed on the identification of specific biological cargo, including proteins and non-coding RNA molecules, that have been found to be associated with stem cell EVs. Collectively, this review highlights the potential of stem cell EVs as an alternative to traditional stem cell therapy for the repair of cellular damage associated with diverse CNS pathologies.

ABC Transporters at the Blood-Brain Interfaces, Their Study Models, and Drug Delivery Implications in Gliomas

Drug delivery into the brain is regulated by the blood-brain interfaces. The blood-brain barrier (BBB), the blood-cerebrospinal fluid barrier (BCSFB), and the blood-arachnoid barrier (BAB) regulate the exchange of substances between the blood and brain parenchyma. These selective barriers present a high impermeability to most substances, with the selective transport of nutrients and transporters preventing the entry and accumulation of possibly toxic molecules, comprising many therapeutic drugs. Transporters of the ATP-binding cassette (ABC) superfamily have an important role in drug delivery, because they extrude a broad molecular diversity of xenobiotics, including several anticancer drugs, preventing their entry into the brain. Gliomas are the most common primary tumors diagnosed in adults, which are often characterized by a poor prognosis, notably in the case of high-grade gliomas. Therapeutic treatments frequently fail due to the difficulty of delivering drugs through the brain barriers, adding to diverse mechanisms developed by the cancer, including the overexpression or expression de novo of ABC transporters in tumoral cells and/or in the endothelial cells forming the blood-brain tumor barrier (BBTB). Many models have been developed to study the phenotype, molecular characteristics, and function of the blood-brain interfaces as well as to evaluate drug permeability into the brain. These include in vitro, in vivo, and in silico models, which together can help us to better understand their implication in drug resistance and to develop new therapeutics or delivery strategies to improve the treatment of pathologies of the central nervous system (CNS). In this review, we present the principal characteristics of the blood-brain interfaces; then, we focus on the ABC transporters present on them and their implication in drug delivery; next, we present some of the most important models used for the study of drug transport; finally, we summarize the implication of ABC transporters in glioma and the BBTB in drug resistance and the strategies to improve the delivery of CNS anticancer drugs.

Stem Cell Extracellular Vesicles and their Potential to Contribute to the Repair of Damaged CNS Cells

Neurological diseases and disorders are leading causes of death and disability worldwide. Many of these pathologies are associated with high levels of neuroinflammation and irreparable tissue damage. As the global burden of these pathologies continues to rise there is a significant need for the development of novel therapeutics. Due to their multipotent properties, stem cells have broad applications for tissue repair; additionally, stem cells have been shown to possess both immunomodulatory and neuroprotective properties. It is now believed that paracrine factors, such as extracellular vesicles (EVs), play a critical role in the functionality associated with stem cells. The diverse biological cargo contained within EVs are proposed to mediate these effects and, to date, the reparative and regenerative effects of stem cell EVs have been demonstrated in a wide range of cell types. While a high potential for their therapeutic use exists, there is a gap of knowledge surrounding their characterization, mechanisms of action, and how they may regulate cells of the CNS. Here, we report the isolation, characterization, and functional assessment of EVs from two sources of human stem cells, mesenchymal stem cells and induced pluripotent stem cells. We demonstrate the ability of these EVs to enhance the processes of cellular migration and angiogenesis, which are critical for both normal cellular development as well as cellular repair. Furthermore, we investigate their reparative effects on damaged cells, specifically those with relevance to the central nervous system. Collectively, our data highlight the similarities and differences among these EV populations and support the view that stem cells EV can be used to repair or partially reverse cellular damage. Graphical Abstract Stem cell-derived Extracellular Vesicles (EVs) for repair of damaged cells. EVs isolated from human induced pluripotent stem cells and mesenchymal stem cells contribute to the partial reversal of phenotypes induced by different sources of cellular damage.

Development of a Semimechanistic Pharmacokinetic-Pharmacodynamic Model Describing Dextroamphetamine Exposure and Striatal Dopamine Response in Rats and Nonhuman Primates following a Single Dose of Dextroamphetamine

Acute central nervous system exposure to dextroamphetamine (d-amphetamine) elicits a multitude of effects, including dual action on the dopamine transporter (DAT) to increase extracellular dopamine, and induction of a negative feedback response to limit the dopamine increase. A semimechanistic pharmacokinetic and pharmacodynamic (PK/PD) model with consideration of these multiple effects as a basis was developed. Integrated pharmacokinetics of d-amphetamine in plasma, brain extracellular fluid (ECF) via microdialysis, and cerebrospinal fluid were characterized using a population approach. This PK model was then linked to an indirect-response pharmacodynamic model using as a basis the measurement of extracellular striatal dopamine, also via microdialysis. In both rats and nonhuman primates (NHPs), d-amphetamine stimulation of dopamine outflow (reverse transport) through DAT was primarily responsible for the dose-linear increase in dopamine. As well, in both species a moderator function was needed to account for loss of the dopamine response in the presence of a relatively sustained d-amphetamine ECF exposure, presumptive of an acute tolerance response. PK/PD model structure was consistent between species; however, there was a 10-fold faster return to baseline dopamine in NHPs in response to an acute d-amphetamine challenge. These results suggest preservation from rodents to NHPs regarding the mechanism by which amphetamine increases extracellular dopamine, but a faster system response in NHPs to tolerate this increase. This microdialysis-based PK/PD model suggests greater value in directing preclinical discovery of novel approaches that modify reverse transport stimulation to treat amphetamine abuse. General value regarding insertion of an NHP model in paradigm rodent-to-human translational research is also suggested.

Utilizing microphysiological systems and induced pluripotent stem cells for disease modeling: a case study for blood brain barrier research in a pharmaceutical setting

Microphysiological systems (MPS) may be able to provide the pharmaceutical industry models that can reflect human physiological responses to improve drug discovery and translational outcomes. With lack of efficacy being the primary cause for drug attrition, developing MPS disease models would help researchers identify novel targets, study mechanisms in more physiologically-relevant depth, screen for novel biomarkers and test/optimize various therapeutics (small molecules, nanoparticles and biologics). Furthermore, with advances in inducible pluripotent stem cell technology (iPSC), pharmaceutical companies can access cells from patients to help recreate specific disease phenotypes in MPS platforms. Combining iPSC and MPS technologies will contribute to our understanding of the complexities of neurodegenerative diseases and of the blood brain barrier (BBB) leading to development of enhanced therapeutics.

Physiologically Based Modeling Approach to Predict Dopamine D2 Receptor Occupancy of Antipsychotics in Brain: Translation From Rat to Human

Receptor occupancy (RO) is a translational biomarker for assessing drug efficacy and safety. We aimed to apply a physiologically based pharmacokinetic (PBPK) modeling approach to predict the brain dopamine D2 RO time profiles of antipsychotics. Clozapine and risperidone were modeled together with their active metabolites, norclozapine and paliperidone, First, in PK‐Sim a rat PBPK model was developed and optimized using literature plasma PK data. Then, blood‐brain barrier parameters including the expression and efflux transport kinetics of P‐glycoprotein were optimized using literature microdialysis data on brain extracellular fluid (brainECF), which were further adapted when translating the rat PBPK model into the human PBPK model. Based on the simulated drug and metabolite concentrations in brainECF, drug‐D2 receptor binding kinetics (association and dissociation rates) were incorporated in MoBi to predict RO. From an extensive literature search, 32 plasma PK data sets (16 from rat and 16 from human studies) and 23 striatum RO data sets (13 from rat and 10 from human studies) were prepared and compared with the model predictions. The rat PBPK‐RO model adequately predicted the plasma concentrations of the parent drugs and metabolites and the RO levels. The human PBPK‐RO model also captured the plasma PK and RO levels despite the large interindividual and interstudy variability, although it tended to underestimate the plasma concentrations and RO measured at late time points after risperidone dosing. The developed human PBPK‐RO model was successfully applied to predict the plasma PK and RO changes observed after risperidone dose reduction in a clinical trial in schizophrenic patients.

Blood-Based Biomarkers of Quinpirole Pharmacology: Cluster-Based PK/PD and Metabolomics to Unravel the Underlying Dynamics in Rat Plasma and Brain

A key challenge in the development of central nervous system drugs is the availability of drug target specific blood-based biomarkers. As a new approach, we applied cluster-based pharmacokinetic/pharmacodynamic (PK/PD) analysis in brain extracellular fluid (brain_ECF ) and plasma simultaneously after 0, 0.17, and 0.86 mg/kg of the dopamine D_2/3 agonist quinpirole (QP) in rats. We measured 76 biogenic amines in plasma and brain_ECF after single and 8-day administration, to be analyzed by cluster-based PK/PD analysis. Multiple concentration-effect relations were observed with potencies ranging from 0.001-383 nM. Many biomarker responses seem to distribute over the blood-brain barrier (BBB). Effects were observed for dopamine and glutamate signaling in brain_ECF , and branched-chain amino acid metabolism and immune signaling in plasma. Altogether, we showed for the first time how cluster-based PK/PD could describe a systems-response across plasma and brain, thereby identifying potential blood-based biomarkers. This concept is envisioned to provide an important connection between drug discovery and early drug development.

In Vitro Models of Brain Disorders

The brain is the most complex organ of the body, and many pathological processes underlying various brain disorders are poorly understood. Limited accessibility hinders observation of such processes in the in vivo brain, and experimental freedom is often insufficient to enable informative manipulations. In vitro preparations (brain slices or cultures of dissociated neurons) offer much better accessibility and reduced complexity and have yielded valuable new insights into various brain disorders. Both types of preparations have their advantages and limitations with regard to lifespan, preservation of in vivo brain structure, composition of cell types, and the link to behavioral outcome is often unclear in in vitro models. While these limitations hamper general usage of in vitro preparations to study, e.g., brain development, in vitro preparations are very useful to study neuronal and synaptic functioning under pathologic conditions. This chapter addresses several brain disorders, focusing on neuronal and synaptic functioning, as well as network aspects. Recent progress in the fields of brain circulation disorders, excitability disorders, and memory disorders will be discussed, as well as limitations of current in vitro models.

Fingerprints of CNS drug effects: a plasma neuroendocrine reflection of D2 receptor activation using multi-biomarker pharmacokinetic/pharmacodynamic modelling

BACKGROUND AND PURPOSE

Because biological systems behave as networks, multi-biomarker approaches increasingly replace single biomarker approaches in drug development. To improve the mechanistic insights into CNS drug effects, a plasma neuroendocrine fingerprint was identified using multi-biomarker pharmacokinetic/pharmacodynamic (PK/PD) modelling. Short- and long-term D2 receptor activation was evaluated using quinpirole as a paradigm compound.

EXPERIMENTAL APPROACH

Rats received 0, 0.17 or 0.86 mg·kg-1 of the D2 agonist quinpirole i.v. Quinpirole concentrations in plasma and brain extracellular fluid (brainECF ), as well as plasma concentrations of 13 hormones and neuropeptides, were measured. Experiments were performed at day 1 and repeated after 7-day s.c. drug administration. PK/PD modelling was applied to identify the in vivo concentration-effect relations and neuroendocrine dynamics.

KEY RESULTS

The quinpirole pharmacokinetics were adequately described by a two-compartment model with an unbound brainECF -to-plasma concentration ratio of 5. The release of adenocorticotropic hormone (ACTH), growth hormone, prolactin and thyroid-stimulating hormone (TSH) from the pituitary was influenced. Except for ACTH, D2 receptor expression levels on the pituitary hormone-releasing cells predicted the concentration-effect relationship differences. Baseline levels (ACTH, prolactin, TSH), hormone release (ACTH) and potency (TSH) changed with treatment duration.

CONCLUSIONS AND IMPLICATIONS

The integrated multi-biomarker PK/PD approach revealed a fingerprint reflecting D2 receptor activation. This forms the conceptual basis for in vivo evaluation of on- and off-target CNS drug effects. The effect of treatment duration is highly relevant given the long-term use of D2 agonists in clinical practice. Further development towards quantitative systems pharmacology models will eventually facilitate mechanistic drug development.