Utilizing an acute hyperthermia-induced seizure test and pharmacokinetic studies to establish optimal dosing regimens in a mouse model of Dravet syndrome

OBJECTIVE

The current standard of care for Dravet syndrome (DS) includes polytherapy after inadequate seizure control with one or more monotherapy approaches. Treatment guidelines are often based on expert opinions, and finding an optimal balance between seizure control and adverse drug effects can be challenging. This study utilizes the efficacy and pharmacokinetic assessment of a second-line treatment regimen that combines clobazam and sodium valproate with an add-on drug as a proof-of-principle approach to establish an effective therapeutic regimen in a DS mouse model.

METHODS

We evaluated the efficacy of add-on therapies stiripentol, cannabidiol, lorcaserin, or fenfluramine added to clobazam and sodium valproate against hyperthermia-induced seizures in Scn1aA1783V/WT mice. Clobazam, N-desmethyl clobazam (an active metabolite of clobazam), sodium valproate, stiripentol, and cannabidiol concentrations were quantified in plasma and brain using liquid chromatography-tandem mass spectrometry for the combinations deemed effective against hyperthermia-induced seizures. The concentration data were used to calculate pharmacokinetic parameters via noncompartmental analysis in Phoenix WinNonLin.

RESULTS

Higher doses of stiripentol or cannabidiol, in combination with clobazam and sodium valproate, were effective against hyperthermia-induced seizures in Scn1aA1783V/WT mice. In Scn1aWT/WT mice, brain clobazam and N-desmethyl clobazam concentrations were higher in the triple-drug combinations than in the clobazam monotherapy. Stiripentol and cannabidiol brain concentrations were greater in the triple-drug therapy than when given alone.

SIGNIFICANCE

A polypharmacy strategy may be a practical preclinical approach to identifying efficacious compounds for DS. The drug-drug interactions between compounds used in this study may explain the potentiated efficacy of some polytherapies.

Preventative treatment of tuberous sclerosis complex with sirolimus: Phase I safety and efficacy results

Objective

Tuberous sclerosis complex (TSC) results from overactivity of the mechanistic target of rapamycin (mTOR). Sirolimus and everolimus are mTOR inhibitors that treat most facets of TSC but are understudied in infants. We sought to understand the safety and potential efficacy of preventative sirolimus in infants with TSC.

Methods

We conducted a phase 1 clinical trial of sirolimus, treating five patients until 12 months of age. Enrolled infants had to be younger than 6 months of age with no history of seizures and no clinical indication for sirolimus treatment. Adverse events (AEs), tolerability, and blood concentrations of sirolimus measured by tandem mass spectrometry were tracked through 12 months of age, and clinical outcomes (seizure characteristics and developmental profiles) were tracked through 24 months of age.

Results

There were 92 AEs, with 34 possibly, probably, or definitely related to treatment. Of those, only two were grade 3 (both elevated lipids) and all AEs were resolved by the age of 24 months. During the trial, 94% of blood sirolimus trough levels were in the target range (5-15 ng/mL). Treatment was well tolerated, with less than 8% of doses held because of an AE (241 of 2941). Of the five patients, three developed seizures (but were well controlled on medications) at 24 months of age. Of the five patients, four had normal cognitive development for age. One was diagnosed with possible autism spectrum disorder.

Interpretation

These results suggest that sirolimus is both safe and well tolerated by infants with TSC in the first year of life. Additionally, the preliminary work suggests a favorable efficacy profile compared with previous TSC cohorts not exposed to early sirolimus treatment. Results support sirolimus being studied as preventive treatment in TSC, which is now underway in a prospective phase 2 clinical trial (TSC-STEPS).

Practical solutions for including sex as a biological variable (SABV) in preclinical neuropsychopharmacological research

Recently, many funding agencies have released guidelines on the importance of considering sex as a biological variable (SABV) as an experimental factor, aiming to address sex differences and avoid possible sex biases to enhance the reproducibility and translational relevance of preclinical research. In neuroscience and pharmacology, the female sex is often omitted from experimental designs, with researchers generalizing male-driven outcomes to both sexes, risking a biased or limited understanding of disease mechanisms and thus potentially ineffective therapeutics. Herein, we describe key methodological aspects that should be considered when sex is factored into in vitro and in vivo experiments and provide practical knowledge for researchers to incorporate SABV into preclinical research. Both age and sex significantly influence biological and behavioral processes due to critical changes at different timepoints of development for males and females and due to hormonal fluctuations across the rodent lifespan. We show that including both sexes does not require larger sample sizes, and even if sex is included as an independent variable in the study design, a moderate increase in sample size is sufficient. Moreover, the importance of tracking hormone levels in both sexes and the differentiation between sex differences and sex-related strategy in behaviors are explained. Finally, the lack of robust data on how biological sex influences the pharmacokinetic (PK), pharmacodynamic (PD), or toxicological effects of various preclinically administered drugs to animals due to the exclusion of female animals is discussed, and methodological strategies to enhance the rigor and translational relevance of preclinical research are proposed.

Fluid-Based Protein Biomarkers in Traumatic Brain Injury: The View from the Bedside

There has been an explosion of research into biofluid (blood, cerebrospinal fluid, CSF)-based protein biomarkers in traumatic brain injury (TBI) over the past decade. The availability of very large datasets, such as CENTRE-TBI and TRACK-TBI, allows for correlation of blood- and CSF-based molecular (protein), radiological (structural) and clinical (physiological) marker data to adverse clinical outcomes. The quality of a given biomarker has often been framed in relation to the predictive power on the outcome quantified from the area under the Receiver Operating Characteristic (ROC) curve. However, this does not in itself provide clinical utility but reflects a statistical association in any given population between one or more variables and clinical outcome. It is not currently established how to incorporate and integrate biofluid-based biomarker data into patient management because there is no standardized role for such data in clinical decision making. We review the current status of biomarker research and discuss how we can integrate existing markers into current clinical practice and what additional biomarkers do we need to improve diagnoses and to guide therapy and to assess treatment efficacy. Furthermore, we argue for employing machine learning (ML) capabilities to integrate the protein biomarker data with other established, routinely used clinical diagnostic tools, to provide the clinician with actionable information to guide medical intervention.

Which Small Molecule? Selecting Chemical Probes for Use in Cancer Research and Target Validation

Small-molecule chemical "probes" complement the use of molecular biology techniques to explore, validate, and generate hypotheses on the function of proteins in diseases such as cancer. Unfortunately, the poor selection and use of small-molecule reagents can lead to incorrect conclusions. Here, we illustrate examples of poor chemical tools and suggest best practices for the selection, validation, and use of high-quality chemical probes in cancer research. We also note the complexity associated with tools for novel drug modalities, exemplified by protein degraders, and provide advice and resources to facilitate the independent identification of appropriate small-molecule probes by researchers.

SIGNIFICANCE

Validation of biological targets and pathways will be aided by a shared understanding of the criteria of potency, selectivity, and target engagement associated with small-molecule reagents ("chemical probes") that enable that work. Interdisciplinary collaboration between cancer biologists, medicinal chemists, and chemical biologists and the awareness of available resources will reduce misleading data generation and interpretation, strengthen data robustness, and improve productivity in academic and industrial research.

Poor Translatability of Biomedical Research Using Animals - A Narrative Review

The failure rate for the translation of drugs from animal testing to human treatments remains at over 92%, where it has been for the past few decades. The majority of these failures are due to unexpected toxicity - that is, safety issues revealed in human trials that were not apparent in animal tests - or lack of efficacy. However, the use of more innovative tools, such as organs-on-chips, in the preclinical pipeline for drug testing, has revealed that these tools are more able to predict unexpected safety events prior to clinical trials and so can be used for this, as well as for efficacy testing. Here, we review several disease areas, and consider how the use of animal models has failed to offer effective new treatments. We also make some suggestions as to how the more human-relevant new approach methodologies might be applied to address this.

Back to the Future of Neuropsychopharmacology

Disappointments in translating preclinical findings into clinical efficacy have triggered a number of changes in neuroscience drug discovery ranging from investments diverted to other therapeutic areas to reduced reliance on efficacy claims derived from preclinical models. In this chapter, we argue that there are several existing examples that teach us on what needs to be done to improve the success rate. We advocate the reverse engineering approach that shifts the focus from preclinical efforts to "model" human disease states to pharmacodynamic activity as a common denominator in the journey to translate clinically validated phenomena to preclinical level and then back to humans. Combined with the research rigor, openness, and transparency, this reverse engineering approach is well set to bring new effective and safe medications to patients in need.

The era of high-quality chemical probes

Small-molecule chemical probes are among the most important tools to study the function of proteins in cells and organisms. Regrettably, the use of weak and non-selective small molecules has generated an abundance of erroneous conclusions in the scientific literature. More recently, minimal criteria have been outlined for investigational compounds, encouraging the selection and use of high-quality chemical probes. Here, we briefly recall the milestones and key initiatives that have paved the way to this new era, illustrate examples of recent high-quality chemical probes and provide our perspective on future challenges and developments.

Alzheimer's Disease, and Breast and Prostate Cancer Research: Translational Failures and the Importance to Monitor Outputs and Impact of Funded Research

Dementia and cancer are becoming increasingly prevalent in Western countries. In the last two decades, research focused on Alzheimer's disease (AD) and cancer, in particular, breast cancer (BC) and prostate cancer (PC), has been substantially funded both in Europe and worldwide. While scientific research outcomes have contributed to increase our understanding of the disease etiopathology, still the prevalence of these chronic degenerative conditions remains very high across the globe. By definition, no model is perfect. In particular, animal models of AD, BC, and PC have been and still are traditionally used in basic/fundamental, translational, and preclinical research to study human disease mechanisms, identify new therapeutic targets, and develop new drugs. However, animals do not adequately model some essential features of human disease; therefore, they are often unable to pave the way to the development of drugs effective in human patients. The rise of new technological tools and models in life science, and the increasing need for multidisciplinary approaches have encouraged many interdisciplinary research initiatives. With considerable funds being invested in biomedical research, it is becoming pivotal to define and apply indicators to monitor the contribution to innovation and impact of funded research. Here, we discuss some of the issues underlying translational failure in AD, BC, and PC research, and describe how indicators could be applied to retrospectively measure outputs and impact of funded biomedical research.

Leveraging preclinical models for the development of Alzheimer disease therapeutics

A large number of mouse models have been engineered, characterized and used to advance biomedical research in Alzheimer disease (AD). Early models simply damaged the rodent brain through toxins or lesions. Later, the spread of genetic engineering technology enabled investigators to develop models of familial AD by overexpressing human genes such as those encoding amyloid precursor protein (APP) or presenilins (PSEN1 or PSEN2) carrying mutations linked to early-onset AD. Recently, more complex models have sought to explore the impact of multiple genetic risk factors in the context of different biological challenges. Although none of these models has proven to be a fully faithful reproduction of the human disease, models remain essential as tools to improve our understanding of AD biology, conduct thorough pharmacokinetic and pharmacodynamic analyses, discover translatable biomarkers and evaluate specific therapeutic approaches. To realize the full potential of animal models as new technologies and knowledge become available, it is critical to define an optimal strategy for their use. Here, we review progress and challenges in the use of AD mouse models, highlight emerging scientific innovations in model development, and introduce a conceptual framework for use of preclinical models for therapeutic development.

The mouse as a model for neuropsychiatric drug development

Much has been written about the validity of mice as a preclinical model for brain disorders. Critics cite numerous examples of apparently effective treatments in mouse models that failed in human clinical trials, raising the possibility that the two species' neurobiological differences could explain the high translational failure rate in psychiatry and neurology (neuropsychiatry). However, every stage of translation is plagued by complex problems unrelated to neurobiological conservation. Therefore, although these case studies are intriguing, they cannot alone determine whether these differences observed account for translation failures. Our analysis of the literature indicates that most neuropsychiatric treatments used in humans are at least partially effective in mouse models, suggesting that neurobiological differences are unlikely to be the main cause of neuropsychiatric translation failures.

Building Robustness into Translational Research

Nonclinical studies form the basis for the decision whether to take a therapeutic candidate into the clinic. These studies need to exhibit translational robustness for both ethical and economic reasons. Key findings confirmed in multiple species have a greater chance to also occur in humans. Given the heterogeneity of patient populations, preclinical studies or at least programs comprising multiple studies need to reflect such heterogeneity, e.g., regarding strains, sex, age, and comorbidities of experimental animals. However, introducing such heterogeneity requires larger studies/programs to maintain statistical power in the face of greater variability. In addition to classic sources of bias, e.g., related to lack of randomization and concealment, translational studies face specific sources of potential bias such as that introduced by a model that may not reflect the full spectrum of underlying pathophysiology in patients, that defined by timing of treatment, or that implied in dosing decisions and interspecies differences in pharmacokinetic profiles. The balance of all these factors needs to be considered carefully for each study and program.

Preclinical Models of Alzheimer's Disease: Relevance and Translational Validity

The only drugs currently approved for the treatment of Alzheimer's Disease (AD) are four acetylcholinesterase inhibitors and the NMDA antagonist memantine. Apart from these drugs, which have minimal to no clinical benefit, the 40-year search for effective therapeutics to treat AD has resulted in a clinical failure rate of 100% not only for compounds that prevent brain amyloid deposition or remove existing amyloid plaques but also those acting by a variety of other putative disease-associated mechanisms. This indicates that the preclinical data generated from current AD targets to support the selection, optimization, and translation of new chemical entities (NCEs) and biologics to clinical trials is seriously compromised. While many of these failures reflect flawed hypotheses or a lack of adequate characterization of the preclinical pharmacodynamic and pharmacokinetic (PD/PK) properties of lead NCEs-including their bioavailability and toxicity-the conceptualization, validation, and interrogation of the current animal models of AD represent key limitations. The overwhelming majority of these AD models are transgenic, based on aspects of the amyloid hypothesis and the genetics of the familial form of the disease. As a result, these generally lack construct and predictive validity for the sporadic form of the human disease. The 170 or so transgenic models, perhaps the largest number ever focused on a single disease, use rodents, mainly mice, and in addition to amyloid also address aspects of tau causality with more complex multigene models including other presumed causative factors together with amyloid. This overview discusses the current animal models of AD in the context of both the controversies surrounding the causative role of amyloid in the disease and the need to develop validated models of cognitive function/dysfunction that more appropriately reflect the phenotype(s) of human aged-related dementias. © 2019 by John Wiley & Sons, Inc.

The selective cathepsin K inhibitor MIV-711 attenuates joint pathology in experimental animal models of osteoarthritis

BACKGROUND

MIV-711 is a highly potent and selective cathepsin K inhibitor. The current article summarizes the therapeutic effects of MIV-711 on joint pathology in rabbits subjected to anterior cruciate ligament transection (ACLT), and the prophylactic effects on joint pathology in dogs subjected to partial medial meniscectomy, two surgical models of osteoarthritis (OA).

METHODS

Starting 1 week after surgery, rabbits were dosed daily via oral gavage with either MIV-711 or vehicle (n = 7/group) for 7 weeks. The four treatment groups were: (1) sham + vehicle; (2) ACLT + vehicle; (3) ACLT + MIV-711, 30 µmol/kg and (4) ACLT + MIV-711, 100 µmol/kg. Subchondral bone and articular cartilage structures were assessed by µCT, histomorphometry, and scoring. Dogs subjected to partial medial meniscectomy received either MIV-711 (30 µmol/kg) or vehicle (n = 15/group) via oral gavage once daily, starting 1 day before meniscectomy, for 28 days. Cartilage degradation was assessed at the macroscopic and microscopic levels. The exposures of MIV-711 were assessed in both studies and biomarkers reflecting bone resorption (HP-1 in rabbits, CTX-I in dogs) and cartilage degradation (CTX-II) were measured.

RESULTS

In ACLT rabbits, MIV-711 decreased HP-1 levels by up to 72% (p < 0.001) and CTX-II levels by up to 74% (p < 0.001) compared to ACLT vehicle controls. ACLT surgery significantly reduced the total thickness of the subchondral bone plate and reduced trabecular bone volume in the femur and tibia. These effects were reversed by MIV-711. ACLT resulted in cartilage thickening, which was attenuated by MIV-711. MIV-711 did not affect osteophyte formation or Mankin scores. In dogs, MIV-711 reduced CTX-I and CTX-II levels by 86% (p < 0.001) and 80% (p < 0.001), respectively. Synovial CTX-II levels were reduced by 55-57% (p < 0.001) compared to baseline. MIV-711-treated animals had 25-37% lower macroscopic scores in the femur condyles and 13-33% lower macroscopic scores in the tibial plateaus.

CONCLUSIONS

MIV-711 prevents subchondral bone loss and partially attenuates cartilage pathology in two animal models of OA. These beneficial effects of MIV-711 on joint pathology are observed in conjunction with decreases in bone and cartilage biomarkers that have been shown to be clinically attainable in human. The data support the further development of MIV-711 for the treatment of OA.

Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era

Advances in next-generation sequencing technologies have generated the data supporting a large volume of somatic alterations in several national and international cancer genome projects, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. These cancer genomics data have facilitated the revolution of a novel oncology drug discovery paradigm from candidate target or gene studies toward targeting clinically relevant driver mutations or molecular features for precision cancer therapy. This focuses on identifying the most appropriately targeted therapy to an individual patient harboring a particularly genetic profile or molecular feature. However, traditional experimental approaches that are used to develop new chemical entities for targeting the clinically relevant driver mutations are costly and high-risk. Drug repositioning, also known as drug repurposing, re-tasking or re-profiling, has been demonstrated as a promising strategy for drug discovery and development. Recently, computational techniques and methods have been proposed for oncology drug repositioning and identifying pharmacogenomics biomarkers, but overall progress remains to be seen. In this review, we focus on introducing new developments and advances of the individualized network-based drug repositioning approaches by targeting the clinically relevant driver events or molecular features derived from cancer panomics data for the development of precision oncology drug therapies (e.g. one-person trials) to fully realize the promise of precision medicine. We discuss several potential challenges (e.g. tumor heterogeneity and cancer subclones) for precision oncology. Finally, we highlight several new directions for the precision oncology drug discovery via biotherapies (e.g. gene therapy and immunotherapy) that target the 'undruggable' cancer genome in the functional genomics era.

Disciplined approach to drug discovery and early development

Our modern health care system demands therapeutic interventions that improve the lives of patients. Unfortunately, decreased productivity in therapeutics research and development (R&D) has driven drug costs up while delivering insufficient value to patients. Here, I discuss a model of translational medicine that connects four components of the early R&D pipeline-causal human biology, therapeutic modality, biomarkers of target modulation, and proof-of-concept clinical trials. Whereas the individual components of this model are not new, technological advances and a disciplined approach to integrating all four areas offer hope for improving R&D productivity.

Translating genetic and preclinical findings into autism therapies

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by social deficits and repetitive/restrictive interests. ASD is associated with multiple comorbidities, including intellectual disability, anxiety, and epilepsy. Evidence that ASD is highly heritable has spurred major efforts to unravel its genetics, revealing possible contributions from hundreds of genes through rare and common variation and through copy-number changes. In this perspective, we provide an overview of the current state of ASD genetics and of how genetic research has spurred the development of in vivo and in vitro models using animals and patient cells to evaluate the impact of genetic mutations on cellular function leading to disease. Efforts to translate these findings into successful therapies have yet to bear fruit. We discuss how the valuable insight into the disorder provided by these new models can be used to better understand ASD and develop future clinical trials.

Screening of conventional anticonvulsants in a genetic mouse model of epilepsy

OBJECTIVE

Epilepsy is a common neurological disorder that affects 1% of the population. Approximately, 30% of individuals with epilepsy are refractory to treatment, highlighting the need for novel therapies. Conventional anticonvulsant screening relies predominantly on induced seizure models. However, these models may not be etiologically relevant for genetic epilepsies. Mutations in SCN1A are a common cause of Dravet Syndrome, a severe epileptic encephalopathy. Dravet syndrome typically begins in infancy with seizures provoked by fever and then progresses to include afebrile pleomorphic seizure types. Affected children respond poorly to available anticonvulsants. Scn1a^+/- heterozygous knockout mice recapitulate features of Dravet syndrome and provide a potential screening platform to investigate novel therapeutics. In this study, we conducted a screening of conventional anticonvulsants in Scn1a^+/- mice to establish assays that most closely correlate with human response data.

METHODS

On the basis of clinical response data from a large, single center, retrospective survey of Dravet syndrome case records, we selected nine drugs for screening in Scn1a^+/- mice to determine which phenotypic measures correlate best with human therapeutic response. We evaluated several screening paradigms and incorporated pharmacokinetic monitoring to establish drug exposure levels.

RESULTS

Scn1a^+/- mice exhibited responses to anticonvulsant treatment similar to those observed clinically. Sodium channel blockers were not effective or exacerbated seizures in Scn1a^+/- mice. Overall, clobazam was the most effective anticonvulsant in Scn1a^+/- mice, consistent with its effect in Dravet syndrome.

INTERPRETATION

Genetic models of spontaneous epilepsy provide alternative screening platforms and may augment the AED development process. In this study, we established an effective screening platform that pharmacologically validated Scn1a^+/- mice for preclinical screening of potential Dravet syndrome therapeutics.

Current Perspectives in Autism Spectrum Disorder: From Genes to Therapy

Autism spectrum disorder (ASD) is a constellation of neurodevelopmental presentations with high heritability and both phenotypic and genetic heterogeneity. To date, mutations in hundreds of genes have been associated to varying degrees with increased ASD risk. A better understanding of the functions of these genes and whether they fit together in functional groups or impact similar neuronal circuits is needed to develop rational treatment strategies. We will review current areas of emphasis in ASD research, starting from human genetics and exploring how mouse models of human mutations have helped identify specific molecular pathways (protein synthesis and degradation, chromatin remodeling, intracellular signaling), which are linked to alterations in circuit function and cognitive/social behavior. We will conclude by discussing how we can leverage the findings on molecular and cellular alterations found in ASD to develop therapies for neurodevelopmental disorders.

Advances and Future Directions for Tuberous Sclerosis Complex Research: Recommendations From the 2015 Strategic Planning Conference

On March 10 to March 12, 2015, the National Institute of Neurological Disorders and Stroke and the Tuberous Sclerosis Alliance sponsored a workshop in Bethesda, Maryland, to assess progress and new opportunities for research in tuberous sclerosis complex with the goal of updating the 2003 Research Plan for Tuberous Sclerosis (http://www.ninds.nih.gov/about_ninds/plans/tscler_research_plan.htm). In addition to the National Institute of Neurological Disorders and Stroke and Tuberous Sclerosis Alliance, participants in the strategic planning effort and workshop included representatives from six other Institutes of the National Institutes of Health, the Department of Defense Tuberous Sclerosis Complex Research Program, and a broad cross-section of basic scientists and clinicians with expertise in tuberous sclerosis complex along with representatives from the pharmaceutical industry. Here we summarize the outcomes from the extensive premeeting deliberations and final workshop recommendations, including (1) progress in the field since publication of the initial 2003 research plan for tuberous sclerosis complex, (2) the key gaps, needs, and challenges that hinder progress in tuberous sclerosis complex research, and (3) a new set of research priorities along with specific recommendations for addressing the major challenges in each priority area. The new research plan is organized around both short-term and long-term goals with the expectation that progress toward specific objectives can be achieved within a five to ten year time frame.