NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

Lo DC, Hughes RE, editors. Neurobiology of Huntington's Disease: Applications to Drug Discovery. Boca Raton (FL): CRC Press/Taylor & Francis; 2011.

Cover of Neurobiology of Huntington's Disease

Neurobiology of Huntington's Disease: Applications to Drug Discovery.

Show details

Chapter 8Pharmaceutical Development for Huntington’s Disease

, , , , , and .

INTRODUCTION

Huntington’s disease (HD) is a devastating neurological disorder caused by mutations in the human gene encoding the huntingtin protein, htt. Since the identification of the HD gene nearly 15 years ago, there has been enormous progress in understanding the molecular features of HD pathology at the cellular level, as well the development of a plethora of HD models in the mouse and other experimental organisms. These studies have led to the beginnings of a systematic process of target selection and validation in the service of formulating rational strategies for pharmaceutical development of HD therapeutics (see Chapter 4, this volume). Some of these targets have matured to the point of being the subjects of directed translational research programs in academia, biotechnology, and pharma organizations. This chapter will describe some of the features that have made the identification of treatments for HD a challenge and how the field is moving forward in the face of such challenges. In particular, we will focus on the activities of the CHDI Foundation, Inc. to bring disease-modifying treatments to the clinic.

People with HD Have Few Therapeutic Options

HD’s devastating and relentless progression motivates patients, families, and their physicians to try almost any potential disease-modifying treatment. A few treatments alleviate symptoms, including antidepressants, which improve mood and function; dopamine antagonists, which suppress involuntary movements; and sleeping medication. Only one compound, coenzyme Q (CoQ), has shown even a modest trend toward slowing disease progression [1]. Several clinical trials have attempted to evaluate the effectiveness of putative disease-modifying treatments, but thus far, no successful drug is available. The Huntington Study Group (HSG)—a nonprofit group of clinical investigators from the United States, Canada, Europe, and Australia—has conducted many of the HD clinical trials, including CoQ, ethyl-eicosapentaenoate (ethyl-EPA), tetrabenazine, memantine, phenylbutyrate, dimebolin hydrochloride, and minocycline, but none of these compounds was successful. Members of the European Huntington’s Disease Network (EHDN)—a similar group based in Europe—have evaluated riluzole, adding it to the list of unsuccessful drugs. (See Chapter 12, this volume, for more discussion of the clinical trial pipeline in HD.)

To date, the rationale for clinical trials has been the perceived ability to address some aspect of HD pathogenesis. For example, CoQ, available over the counter as a nutraceutical, is a naturally occurring and endogenous enzymatic cofactor that also functions as an antioxidant. CoQ participates in the mitochondrial respiratory chain and thereby contributes to ATP generation. In a small trial, CoQ demonstrated benefit in patients in the early phase of Parkinson’s disease, apparently slowing disease progression [2]. Because energy deficits and oxidative stress may also be important in HD pathogenesis and because CoQ is safe and readily available, HSG investigators set out to evaluate it first for safety, tolerability, and availability and then for possible benefit. However, in an open-label dose-escalating trial, HSG found only a trend toward benefit after 20 weeks of relatively high doses of CoQ [3]. A subsequent 30-month study reported a positive trend that did not reach statistical significance [3]. The CoQ study was the only trial to use disease progression, rather than chorea, as an endpoint. Similarly, a double-blinded placebo-controlled trial investigated the potential benefit of ethyl-EPA, a compound with multiple relevant putative mechanisms of action [4]. (See Chapter 2, this volume, for additional discussion of pathogenic mechanisms in HD.) Research subjects received 1 g/day of ethyl-EPA. A positive trend was noted in the total motor score among patients who followed the protocol, but the study did not meet the statistical significance endpoint [5].

Bonelli and Hofmann [1] have systematically reviewed all the published HD clinical evaluations and classified them according to study design. In their nomenclature, a “Level 1” study is a randomized controlled study with at least 2-week duration and more than 10 HD subjects enrolled for the entire study. Of the published Level 1 studies, only two—tetrabenazine and amantadine—showed clinical benefit. In both cases, the benefit was symptomatic. Tetrabenazine—an inhibitor of vesicular dopamine transport—is approved in Europe for the treatment of chorea, but the side effects of this compound are so severe that its use remains controversial. Amantadine—an inhibitor of N-methyl-d-aspartic acid (NMDA)-type glutamate receptors—showed a modest positive effect on chorea at 400 mg/day [6], but a subsequent study at a slightly lower dose (300 mg/day) found no evidence of decreased chorea [7].

All the compounds used so far in HD clinical trials fall into two classes, representing two strategies for drug discovery: nutraceuticals and pharmaceuticals developed for other indications. Each of these approaches has serious limitations but nonetheless merit exploration absent more rational alternatives. Nutraceuticals and other natural products often have no clear mechanism of action or molecular target, making it difficult to study structure–activity relationships (SARs) and to optimize their structures for HD therapy. Further, because nutraceutical manufacture is not regulated as is that of pharmaceuticals, the product quality is not consistent and the concentration of active ingredient may vary greatly. Still, because there is no available treatment for HD, a systematic empirical evaluation of nutraceuticals could benefit HD patients and families. If a nutraceutical were safe and well-tolerated, even with only a modest benefit, it would certainly be recommended by clinicians. From the perspective of drug development, pharmaceuticals developed for other indications are a more attractive route. If such a compound showed efficacy in HD, we could build on previous knowledge about its specific molecular target and its mode of action to improve its utility for HD. Further, such a compound, known to modulate a specific molecular target, can serve as a “validating ligand,” thereby providing a sharp tool with which to look for alternate points of intervention. Ultimately, none of the compounds used in clinical trials addressed a specific molecular target known to participate in HD pathogenesis. Even if one of these compounds had shown benefit for HD patients, no clear path for optimization would be obvious without knowing its mode of action.

The Landscape Is Favorable for HD Drug Discovery

As the population ages, neurodegenerative diseases have become particularly important to society. Both government and industry have increased their support for relevant drug development. HD is a “paradigmatic” neurodegenerative disease, offering many advantages to researchers and clinicians seeking new therapeutic routes. HD results from an autosomal dominant allele that can be identified long before disease onset, and its pathogenesis is likely to involve the same pathogenic processes implicated in other neurodegenerative disorders—excitotoxicity, mitochondrial dysfunction, apoptosis, and transcriptional dysregulation [8]. In addition, basic research into HD pathophysiology has already led to the development of powerful tools, including antibodies to htt, transgenic and knockin mice and rats, cell-based models of mutant htt-induced pathogenesis, invertebrate animal models, and new compounds that address HD-relevant pathogenic mechanisms. Cell-based HD models have been the focus of much effort to identify novel compounds and targets that can modify HD toxicity.

Cell-Based Models Suggest New Therapeutic Targets

Heterologous expression of mutant htt in yeast [9] has led to the identification of genes that modify pathogenesis and, using two-hybrid technology, to the elucidation of the network of proteins that interact directly and indirectly with Htt [10], [11]. This elaborated Htt “interactome” has already suggested new potential targets for drug discovery. Other cellular models include transiently transfected non-neuronal and neuronal cell lines, primary neuronal cultures, and inducible, stably transfected, neuron-like cell lines [12], as well as cell lines derived from murine HD models. Of the stable neuron-like cell lines, the pheochromocytoma 12 (PC12) [13] and the striatally derived ST14A [14] are the most frequently used. Another cell line of particular interest is STHdhQ111 [15], generated by the conditional immortalization of striatal neuron precursors from embryos of the HdhQ111 knockin mouse. These tools are not only contributing to basic research on HD pathogenesis but they are also providing platforms for screening chemical libraries.

In Vivo Models of Mutant Htt Action Are Available in Rats, Mice, Worms, and Flies

In vivo studies of HD pathogenesis have been problematic. Several invertebrate HD models have come from the roundworm Caenorhabditis elegans [16] and the fly Drosophila melanogaster [17]. Although these models are particularly convenient for genetic studies and perhaps for compound evaluation, their direct clinical relevance to human pathogenesis remains uncertain. HD researchers have also used at least 10 transgenic and knockin mouse models and one transgenic rat model [18, 19]. The most frequently used rodent models are the R6/2 and R6/1 transgenic mouse models [20], which each produce an exon 1-derived fragment of mutant Htt, with approximately 150 glutamine residues. Until now, most in vivo drug evaluation has used R6/2 because it develops neurological signs most rapidly. Although its rapid pathogenesis has led to its extensive characterization, it is less than an ideal model: (1) it contains only a small fragment of the entire htt gene; (2) it is genetically unstable, with the number of glutamine repeats varying from about 100 to more than 300; (3) it has a heterogeneous genetic background that segregates modifying genes; (4) unlike human HD, it shows no substantial neuronal loss in the striatum or cortex; and (5) its altered behavior and cognition do not fully mimic the human condition—not surprising for a mouse [21]. Full-length transgenic mouse models are also available. One model, now no longer available, derived its full-length htt from a full-length complementary DNA (cDNA) [22]. Others derived their mutant htt from a yeast artificial chromosome (YAC) and some from a bacterial artificial chromosome (BAC) 23–25. None of these models, however, develop abnormal behavior as rapidly as the R6/2 fragment model. (See Chapter 7, this volume, for extended discussion of transgenic mouse HD models.)

Htt-Expressing Cells Allow High-Throughput “Phenotypic Screening

Traditional drug discovery depends on target identification and validation, followed by the development of target-directed cell-free assays. Cell-based models can also provide “phenotypic assays” that allow screening of compound libraries. In this complementary “biology-driven HTS” (high-throughput screening) [26] approach, the drug developer seeks compounds that modulate phenotype in disease-relevant biological assays, for example, mutant htt-dependent cell death, that incorporate biological context and complexity upfront.

There are reports of several drug-like small molecules that rescue a mutant htt- dependent phenotype. One of these, called C2-8, emerged from a screen for small molecules that inhibited the aggregation of mutant exon 1-derived Htt fragments in PC12 cells [27]. Another compound, B2, emerged from a screen of compounds that induced aggregation but mitigated proteasome dysfunction [28]. Another screen found 29 molecules that prevented mutant htt exon 1 cytotoxicity in ST14A cells, a neuron-like cell line derived from E14 striatal primordia [29].

Since the discovery of the huntingtin gene, basic research has suggested more than 300 molecular targets where intervention could slow or stop pathogenesis [30]. During this time, the biotechnology and pharmaceutical industries, as well as government and university laboratories, have developed powerful new pharmacological tools under the rubric of “chemical genomics”—the application of the tools of small molecule drug discovery to the development of research tools that can improve our understanding of protein and cell function. Particularly useful products of this activity are “validating ligands,” which specifically interact with individual receptors, enzymes, and other proteins [31]. These new pharmacological and biological tools will be increasingly useful for the identification and validation of molecular targets that we can then address by traditional target-based discovery (see Chapter 4, this volume).

What Is the Function of Wild-Type Htt?

Despite the publication of more than 1,000 articles dealing with some aspect of htt, we still have little idea of its normal function(s). Htt is required for embryonic development, and it plays a role in regulating gene expression, especially in the transcription of the gene encoding brain-derived neurotrophic factor (BDNF) 32, 33. Htt also participates in intracellular trafficking 34–37. HD has long served as a textbook example of a disease that results from a dominant allele, and research has focused on understanding a toxic “gain of function.” Some investigators, however, have argued that the disease also results from a loss of normal function. Evidence for loss of function comes not only from studies in animal models but also from comparisons with other polyglutamine expansion diseases, such as the spinocerebellar ataxias.

In the most frequently used cell and animal models of HD, mutant exon 1-derived Htt fragments form nuclear and perinuclear aggregates. These aggregates that contain ubiquitinated Htt appear in many cases to increase sensitivity to toxic insults [38]. Similar aggregates—containing the mutant androgen receptor—accumulate in cell and animal models of spinal and bulbar muscular atrophy (SBMA) [39].

MUTANT HTT AFFECTS SOME CELLS MORE THAN OTHERS, BUT WE DO NOT KNOW WHICH AFFECTED CELLS CAUSE HD PATHOGENESIS

Htt itself, with 3,144 amino acid residues, has limited homology to any family of proteins. Although the presence of a long polyglutamine tract near its amino terminus is certainly the cause of HD, Htt is not obviously amenable to targeting with traditional drugs. Nor does Htt appear to have a specific molecular function that could be modulated by a protein biopharmaceutical. Therefore, the drug developer’s task is to look for intervention points both “upstream” (e.g., in transcription and translation) and “downstream” (e.g., in the signaling cascades affected by mutant Htt). Among the many “downstream” processes affected by mutant Htt are (1) mitochondrial dysfunction and impaired energy metabolism (decreased ATP levels), (2) inflammatory processes [40] and excitotoxicity [41], (3) caspase-mediated apoptosis [42], 43, and (4) oxidative stress and damage 44, 45.

The effects of mutant Htt vary greatly with cell type. In postmortem HD brains, the medium-sized spiny neurons (MSNs) of the striatum are the most affected [46, 47]. Although many researchers have adopted MSN vulnerability as the defining feature of HD [42], several recent studies suggest that MSN loss is not cell autonomous but rather results from the deprivation of trophic support from the cortex, specifically from the loss of BDNF [48, 49].

The question of cell autonomy is central to the development of appropriate cell models for drug development. Every HD drug developer seeks a cell system in which the cell autonomous action of mutant Htt recapitulates the disease process, but a single cell may never provide an accurate model. The most useful cell-based assay may instead require coculture of two or more cell types.

Essentially all cells make Htt, and despite substantial striatal cell loss, HD pathology may occur in the periphery and elsewhere in the brain. In particular, inflammation may contribute to early pathogenesis both in HD and in mouse models, with activation of microglia in the brain and movement of microglial precursors from the periphery. Microglia produce a number of enzymes in the kynurenine pathway, which is responsible for the degradation of tryptophan. Among the enzymes up-regulated in early HD is kynurenine monooxygenase (KMO), which converts kynurenine into 3-hydroxykynurenine [50], a precursor of quinolinic acid, a naturally occurring neurotoxin. Increased levels of 3-hydroxykynurenine and quinolinate are present in several transgenic mouse models of HD [51].

In fact, in a yeast model of mutant Htt toxicity, KMO deletion protects yeast from the cytotoxicity of mutant exon 1-derived Htt fragment [52]. Furthermore, treating R6/2 mice with Ro-61-8049, a potent inhibitor of KMO, leads to improved motor behavior in both the rotarod and open field tests. Although the results with the Ro-61-8049 inhibitor of KMO are interesting and suggest the involvement of inflammatory cells in HD pathogenesis, distribution studies indicate that the compound does not cross the blood–brain barrier (BBB). Thus, the observed effect has three possible explanations: (1) an active metabolite of Ro-61-8049 passes through the BBB and acts either on the KMO pathway or on an entirely different pathway; (2) the compound inhibits KMO in the periphery, altering metabolites in the body; or (3) the Ro-61-8049 exerts its effect systemically—either via the KMO pathway or an alternative pathway.

“Phenotypic” Cell-Based Screens Have Identified Molecules That Modulate Htt Cytotoxicity

Because of the lack of tractable validated molecular targets, cell-based drug discovery has focused on “phenotypic assays,” in which mutant htt expression induces a cytotoxic cascade. One advantage of such a phenotypic assay is that the researcher can simultaneously address multiple targets in a single assay. For such a phenotypic assay to be meaningful, however, the choice of the cell line used is crucial. Usually the cells used for such assays are easily manipulated cell lines, but few of these lines are of neuronal origin, possibly limiting their relevance to neuropathogenesis. Because HD’s most prominent pathology is the loss of MSNs in the striatum and of pyramidal cells in the cortex, a better strategy would use cells that derive from those cells or at least share as many characteristics as possible with them.

A cell-based phenotypic assay also requires a choice of pathogenic htt. Among the constructs used so far are pure polyglutamine, htt exon 1, otherwise truncated htt, and full-length htt [16, 53–57]. Cells that express mutant exon 1 show a more rapidly developing phenotype than those expressing longer fragments, but they do not allow the assessment of effects that depend on more carboxyl-terminal portions of Htt. Because mutant Htt is cytotoxic, the cell lines that constitutively express mutant htt die, unless they are resistant to such cytotoxicity. Such resistance can result from cellular adaptations, possibly from increased production of cellular machinery that sequesters toxic proteins, or from selection of mutant htt-resistant mutants. To minimize these problems, investigators have used inducible expression systems, enabling them to initiate the pathogenic cascade at will. Examples of cell lines used in HD drug discovery include PC12 cells with ecdysone-dependent expression of htt exon 1, primary embryonic striatal neurons transfected with htt exon 1, and a striatal cell line derived from a knockin mouse model [53, 58, 59]. Selecting a measurable readout poses yet another problem for a phenotypic assay. Choosing a single readout, such as cell death, may miss earlier and more subtle events of the cytotoxic cascade, but these early events may or may not be relevant to the cell loss that characterizes HD. Therefore, CHDI and our collaborators are developing and using high-content technologies, which can monitor multiple readouts simultaneously with the hope of a fuller understanding of cellular pathology.

Drug developers in companies and in universities have used several cell-based assay systems for HD phenotypic screening. For example, Trophos SA (Marseille, France) has driven cytotoxicity in rat embryo primary striatal neurons with a transfected 480-amino acid fragment of mutant htt. Their readout was fluorescence from an Htt carboxyl-terminal green fluorescent protein tag used as a marker of neuronal viability [60]. Cellumen’s (Pittsburgh, PA) high-content assay measures aggregation of exon 1-derived Htt fragments after ecdysone [53] induction in PC12 cells. CombinatoRx’s (Cambridge, MA) assay follows the subcellular distribution of mutant Htt in St111 cells, a line derived from a homozygous knockin model with 111 glutamine residues. Finally, Varma et al. [61] have used the ST14A cell line in cytotoxicity screens.

Transgenic Mice Allow In Vivo Evaluation of Compounds

The R6/2 mouse carries exon 1 of the human htt with between 105 and 225 CAG repeats [20]. Because the R6/2 develops abnormal behavior by 4–6 weeks, CHDI and others have used it most frequently to evaluate potential drugs. However, even when investigators have studied the same compounds in the R6/2 mouse model, they have found notable differences in outcome. These differences appear to arise from the different protocols for behavioral testing and from different husbandry [62]. High Q Foundation and CHDI, working with PsychoGenics (Tarrytown, NY), have developed standardized protocols for husbandry and testing to reduce variability and to increase the robustness of behavioral testing.

Furthermore, because R6/2 contains only htt exon 1, it is not useful for testing all candidate therapeutics, for example, compounds expected to inhibit the cleavage of full-length Htt or to alter the phosphorylation of residues not encoded by exon 1. Still, the R6/2’s rapid development recommends it, and its pathology resembles that of the Q150 knockin mouse, suggesting that full-length Htt is not necessary for the initiation of disease and that testing in R6/2 is not irrelevant [63]. Still lacking, however, are compounds that can serve as positive controls in cells and in several animal models. Validation of a compound—showing that it slows pathology in HD and in animal and cell models—would also validate those models, but this goal still appears distant. At least seven full-length mouse models are also available. These differ in behavior, pathology, and genetic background and thus far have had limited use for drug evaluation [25, 64]. (See Chapter 7, this volume, for extended discussion of transgenic mouse HD models.)

Potential HD Therapies Have Particularly Severe Safety Requirements

Because genetic testing can reveal the disease-causing allele long before clinical signs, we must anticipate long-term dosing of healthy young adults. Any HD therapeutic agent must be extremely safe and well tolerated, with “tolerable side effects” determined by the profile of the people who receive the therapy. Physicians and drug developers faced similar issues in treating chronic psychiatric illnesses and HIV-positive individuals. People with HIV, for example, often lead long and productive lives using the current triple therapy, but many of these drugs can cause serious side effects that reduce the quality of life. Physicians treating HIV-positive subjects assess the tolerability of medications by evaluating the impact of the side effects on daily living and on perceived quality of life [65]. Compounds used for HD treatment will require a better safety profile than compounds used for cancer because untreated illness so often leads to rapid death and patients receive medication for shorter times. The challenge for HD will be to identify disease-modifying compounds with a good therapeutic window.

THE DRUG DISCOVERY PROCESS

CHDI’S Mission Is to “Rapidly Discover and Develop Drugs That Prevent or Slow Huntington’s Disease

CHDI is unusual among drug developers: we are a not-for-profit foundation, and our motivation is time. Our strategy embraces both biology-based screening and traditional target-based drug discovery, and we are agnostic about therapeutic modality. We are pursuing—in parallel—options that range from small molecules, to proteins, to gene and cell-based therapies. Notwithstanding our unusual strategy, we use industry standards to pursue our goals, to track our successes, and to determine the appropriate level of resource commitment. Our metrics for pharmaceutical development, from target to investigational new drug (IND) (illustrated in Figure 8.1), are most applicable to small molecules but are easily adapted to our modality-agnostic approach. We adapt our definitions of common drug discovery terms (such as “hit,” “lead,” or “preclinical candidate”) from the ISOA/ARF Drug Development Tutorial [66] and the Assay Guidance Manual Version 4.1 (commonly called the NIH Quantitative Biology Manual) [67].

FIGURE 8.1. Representation of the pharmaceutical development process from target to IND.

FIGURE 8.1

Representation of the pharmaceutical development process from target to IND.

There are two kinds of screening strategies: “target based” and “phenotypic.” To help us prioritize potential targets for HD therapeutics, CHDI has developed a target validation (TV) scale, described in Chapter 4, this volume. Once we have decided that a target has a sufficiently high TV score, our next step is to develop an assay in which we can identify molecules that modulate that target. We then adapt the assay to a high-throughput format, usually a 386-well plate.

We have several metrics for a successful assay: (1) it should be inexpensive, costing less than $0.50 per well for a biochemical assay and less than $2.00 per well for a cell-based assay; (2) it must be robust, with an assay quality factor (Z′) greater than 0.5 (Z′ is 1.0, less three times the ratio of the sum of the standard deviations of signals from positive and negative controls to the difference of their means); (3) it must be reproducible, with a coefficient of variation of less than 20%; and (4) it must be quick, allowing a maximum turnaround for a set of tested compounds of 1 week and a total time for lead generation of 3 to 6 months. Once we have an assay that meets these criteria, we can initiate the production of reagents and the launching of the screen. At the same time, we start a program to study the selectivity and the mechanism of action of potential hits.

Figure 8.1 illustrates the stages of compound progression from “active” to “hit” to “lead.” A compound is called “active” when it meets a threshold level of activity in the primary screen. A compound becomes a “hit” only when it satisfies the following criteria: (1) confirmed identity and purity; (2) a reproducible dose–response curve, with a biochemical IC50 less than 5 μM or a cellular EC50 less than 30 μM; (3) confirmed mechanism and specificity; (4) a relationship between structure and activity across chemically related analogues; and (5) chemical tractability—the molecule must have no obvious intrinsic chemical liabilities. Declaration of a compound as a hit triggers the next sequence of activities: (1) selection of appropriate secondary biochemical and cell-based assays; (2) mechanistic studies; (3) synthesis of more chemical analogues to explore SAR; and (4) studies of absorption, distribution, metabolism, and excretion (ADME), as well as solubility, metabolic stability, cell permeability, and cytotoxicity.

Advancing a hit to a “lead requires the satisfaction of additional criteria: (1) a series of analogues of the lead compound must show selectivity and in vitro SAR consistent with the target; (2) the compound and its active analogues must be active in vivo; (3) at least one compound must have biochemical IC50 less than 100 nM or cellular EC50 less than 1 μM; (4) potential issues associated with physiochemical properties, in vivo ADME, and biopharmaceutical properties of the lead series must be identified; and (5) we must be able to plot a clear, data-supported path to lead optimization. Only when we declare that a compound is a lead do we commit resources for lead optimization. At that point, we again scale up the production of several related molecules for in vivo pharmacokinetic (PK) and (pseudo)efficacy studies. Lead optimization involves more ADME studies (tier 2 ADME) and toxicology, using appropriate surrogates, for broad-based pharmacological profiling, in vitro toxicological studies, protein binding, and the induction of cytochrome P450, which can selectively metabolize potential lead compounds.

The next step in our scheme is progression from lead to preclinical candidate, which requires that at least one molecule satisfy all the following criteria: (1) in vitro EC50 less than 100 nM, ideally in a cellular assay; (2) at least 100-fold selectivity compared with the most closely related target (including isoforms); (3) a useable formulation; (4) in vivo efficacy (or pseudoefficacy) in at least one (transgenic) animal model; (5) at least 25% bioavailability at 30 mg/kg; (6) a brain exposure greater than the EC50 with the selected route of administration and formulation, preferably in two animal species; (7) no genetic toxicity at 50 μM; and (8) acceptable in vivo safety in a 7-day rodent study.

Declaration of a compound as a preclinical candidate triggers an effort to determine whether it is an acceptable “clinical candidate,” in particular its synthesis at a scale that can support both in vivo efficacy studies and 14-day rodent toxicology. A backup molecule from the same series must also be selected at this point. Before filing an application for approval as an IND, a compound must meet the additional criteria of a “clinical candidate”: (1) reproducible and statistically significant positive results in at least one relevant outcome measure in at least one mammalian HD model; (2) demonstrated mechanism in vivo, as determined by direct or surrogate measurements; (3) acceptable subchronic toxicity in a 14-day non-Good Laboratory Practice (GLP) rodent and nonrodent toxicity study, with acceptable toxicokinetics; (4) acceptable ADME profile; and (5) low liability for cardiotoxicity as determined by QT interval prolongation in dog.

Declaration of clinical candidacy triggers scaled-up synthesis of the compound under conditions of GLP for the studies required for IND approval. Once the preferred formulation of the molecule is chosen, the chemical, manufacturing, and controls studies are initiated, including two safety studies of at least 28 days, with at least one study in a nonrodent species. Depending on the specific nature of the clinical candidate and its potential toxicities, the compound may also require additional in vitro evaluation and in vivo studies.

The Current Pipeline

Five distinct streams of candidate therapeutics, described below, currently feed CHDI’s in vivo testing program, which is hosted at several contract research organizations: (1) we have assembled a list of “validating ligands” for molecular targets of high interest, starting with those identified through the community-based Systematic Evaluation of Therapeutics for Huntington’s Disease (SET-HD) initiative [68]; we have added compounds used for other neurodegenerative disorders, including many that address specific molecular targets on our extended list; (2) we are working to improve a set of compounds identified in previous high-throughput screens, supported by the CHDI Foundation, that used several biology-driven phenotypic screens; (3) we are also attempting to improve compounds, such as CoQ, which are the subject of ongoing clinical trials, using medicinal chemistry to improve the therapeutic window; (4) we have assembled a portfolio of new target-based drug discovery programs, as well as programs that use new technologies; and (5) we have initiated several projects for nontraditional therapeutics, including antisense technology or gene therapy. We are presently using the R6/2 transgenic mouse as a frontline in vivo model to evaluate and prioritize candidate molecules.

Many of the validating ligands that CHDI has evaluated in vivo are molecules already used in clinical studies. The rationale for these choices was that, if a compound should exhibit efficacy, the regulatory hurdle to initiate a clinical study would be low, and clinical studies could be initiated rapidly. Among the 60 compounds already evaluated, about half come from the SET-HD process. Before choosing the compounds for in vivo testing, we reviewed each nominated compound for appropriate physical, chemical, PK, and safety properties. This process led us to reject SET-HD compounds such as geldanamycin, which is prohibitively expensive and had significant PK and toxicological liabilities [69]. In such cases, however, we sought alternative compounds that could address the same putative mechanism of action.

In addition to the SET-HD compounds, CHDI scientists nominated best-in-class ligands for specific targets and mechanisms. For example, to address the role of oxidative stress in HD pathogenesis, we chose to evaluate the free radical scavenger NXY-059 (Cerovive, AstraZeneca, Wilmington, DE), which had progressed to Phase III clinical trials for cerebrovascular ischemia [44]. Similarly, to examine the potential pathogenic role of adenosine 2A (A2A) receptors, we evaluated the A2A receptor antagonist KW-6002, which is in Phase III clinical trials for Parkinson’s disease [70].

Phenotypic cell-based screens have provided another list of compounds for in vivo evaluation. In 1998 the Cure Huntington Disease Initiative (predecessor of the current CHDI), initiated an HTS campaign, mostly using mutant exon 1 cytotoxicity assays in PC12 cells, Drosophila, C. elegans, and yeast. This primary screening campaign found 181 active compounds with EC50 less than 10 μM from a total of 815,000 compounds. These initial hits, together with commercially available analogues, were the input to a secondary screening campaign whose purpose was to confirm the original activity and to begin the elaboration of SAR required for lead optimization.

The first step in winnowing the original 181 active compounds and analogues to 12 compound series was computational filtering. Filtering keeps identified nonproductive types of compounds (“chemotypes”) from advancing further, thereby saving valuable chemistry resources. The computational filters identified molecules known to aggregate; to bind other molecules promiscuously; to have inappropriate, non-drug-like characteristics or reactive groups; and to be metabolically unstable. To facilitate the SAR studies we sometimes allowed some non-drug-like compounds, such as flavonoids (known to be difficult to optimize for therapeutic use), to pass the filters. However, when we ranked the ensuing compounds, they had low priorities.

The secondary screening campaign used seven assays to find 165 compounds, from 14 chemical classes, that showed activity in at least one assay. Of these, 45 exhibited activity in two assays, and five compounds were active in three assays. Four of these five represented chemotypes that were active in one or more assays. One singleton compound, with a chemotype unique among the original 165, was active in three assays. The structure of this compound predicts that it can penetrate the BBB and that it may function as a prodrug, converted to an active compound by enzymes present in the assay. Another singleton was an adenosine receptor A2B antagonist.

Thirteen compound classes showed promising SARs and underwent additional evaluation with the following criteria: (1) amenability to chemical modification at multiple sites; (2) potential to improve PK and ADME; (3) ease of analogue generation; (4) parallel chemistry synthesis; (5) drug-like characteristics; and (6) predicted ability to penetrate the BBB [71].

We classified the remaining compounds into chemical series based on common chemical scaffolds and listed 16 series and 30 singletons. The computational filters discussed above allowed us to reject compounds with reactive functionality, promiscuous binding, tendency to aggregate, and non-drug-like structures. We then grouped the resulting compounds into classes, prioritized them according to the activity of each class in multiple HD-relevant assays, and synthesized libraries of appropriate analogues for testing in PC12 and ST14A cell-based assays. The results of these ongoing tests will determine which analogues will move forward to in vivo evaluation.

Medicinal Chemistry May Be Able to Improve Compounds Already Evaluated in Clinical Trials

Several compounds—notably creatine and CoQ—have shown positive trends toward efficacy in HD clinical trials but only at extremely high doses. CHDI has tried to improve the efficacy and bioavailability of these two compounds. The treatment of HD patients with creatine and CoQ means to repair defects in energy metabolism and mitochondrial dysfunction associated with HD. Creatine is the metabolic precursor of phosphocreatine, as a temporary energy for ATP-derived high-energy phosphate, whereas CoQ participates in the mitochondrial respiratory chain. Both molecules have substantial deficiencies as drugs, and neither readily crosses the BBB. CoQ, with cLogP greater than 20, has very poor tissue distribution characteristics [72], 73. Creatine, at the high concentrations used in clinical trials, may well saturate BBB’s creatine transporter [74, 75].

CHDI has initiated two medicinal chemistry collaborations to improve these molecules, with the goal of shifting their therapeutic windows and allowing more definitive studies of the value of enhancing mitochondrial function in HD. We are working with Edison Pharmaceuticals (Mountain View, CA) to generate CoQ analogs that both are more bioavailable and have higher redox potential, and with XenoPort, Inc. (Santa Clara, CA) to develop a BBB-permeable prodrug that will generate phosphocreatine.

Edison has adopted a dual approach to re-engineering CoQ: (1) modifying the para-benzoquinone headgroup to optimize redox potential, and (2) simultaneously modifying the lipophilic tail to improve ADME properties. Edison has assembled a collection of CoQ analogues based on their performance in separate assays of redox potential and their ability to rescue cells from acute oxidative stress. To address the specific insult of mutant htt, Edison measures the ability of their CoQ analogues to rescue human HD fibroblasts producing Htt with 69 glutamine residues from an acute oxidative challenge. Although this assay allows them to rank compounds, the ordering may not be relevant to HD itself: the mitochondrial activities of dividing fibroblasts almost certainly differ from those of postmitotic neurons. Despite this reservation, Edison has identified a CoQ analogue with a cellular EC50 < 30 nM and is now testing this and other compounds in vivo.

XenoPort’s program is attempting to produce a prodrug of creatine phosphate that readily crosses the BBB. Their strategy is to attach nonpolar moieties around the highly charged phosphate group to produce a much less polar molecule whose highenergy phosphate is protected from plasma phosphatases. The attached moieties, which are also substrate BBB transporters, are designed to be cleaved by esterases within the brain. As a proof of principle, XenoPort has already shown that such prodrugs can rescue cells subjected to metabolic insult.

CHDI Is Developing Small Molecule Drugs to Address High-Priority TARGETS

In Chapter 4, this volume, our CHDI colleagues discuss our metrics of TV. The resulting ranking has allowed us to: (1) quantify our confidence that pharmacological intervention at a given target will modify disease progression; (2) specify additional experiments that can increase or decrease a target’s rank; and (3) prioritize targets for prosecution. Table 4.2 lists the highest ranking targets from those efforts (see Chapter 4, this volume). We expect that some of these targets are most amenable to small molecule therapeutics, and CHDI is trying to develop drugs that address these targets, which include (1) histone deacetylases (HDACs), especially class I and II; (2) caspase-6; (3) caspase-1; and (4) transglutaminase 2. Other targets on the list, however, including Htt and growth factor receptors (for BDNF, glial cell derived neurotrophic factor [GDNF], and fibroblast growth factor [FGF] 2) will probably require alternative modalities.

To choose among individual caspases and HDACs, CHDI has initiated a collaboration with Amphora Discovery Corporation (Research Triangle Park, NC). Amphora has profiled a collection of diverse compounds against individual caspases and HDACs, and has developed a database of the selectivity of each compound against all the enzymes tested [76]. By mining this database, Amphora has identified chemical scaffolds that can serve as seeds for subsequent library generation and additional screening, resulting in a dramatic shortening of hit-to-lead timelines for individual family members. Currently, CHDI’s HDAC and caspase projects are exploiting several identified scaffolds as lead series in the search for isoform-selective ligands with the requisite central nervous system (CNS) exposure needed for in vivo studies.

CHDI and CombinatoRx are exploring the existing pharmacopoeia (and some new chemical entities) for combinations that inhibit cytotoxicity in cell-based phenotypic assays. These empirical studies, which do not rely on previous knowledge of target interactions, have discovered unexpected synergies—the pharmacological equivalent of synthetic lethal interactions found in yeast and other model organisms [77]. Fully understanding these synergies will require a marriage of chemogenomics (using small molecules as biological probes) and systems biology (the study of complex interactions).

CombinatoRx argues that its platform may also dramatically reduce the time to the clinic because its starting compounds are already Food and Drug Administration (FDA)-approved drugs. Even if this program does not result immediately in an HD therapeutic, data about pair-wise interactions can lead to new insights relevant to our efforts to identify and validate HD drug targets [78].

Large Molecule Therapeutics Require Unconventional Delivery

Mutant Htt is the only fully validated target for HD, and reducing its concentration should suffice to slow or prevent HD. With this goal in mind, CHDI is exploring two routes to reduce Htt production—antisense oligodeoxynucleotides (ASO) and short-hairpin RNA interference [79, 80] (see Chapter 9, this volume). Our ASO approach, in partnership with Isis Pharmaceuticals (Carlsbad, CA), uses technology developed by Isis—single-stranded modified oligonucleotides complementary to htt mRNA. Once an ASO binds to a portion of the target mRNA, the mRNA becomes a substrate for nuclease digestion, thereby preventing its translation. Isis has the capacity to rapidly identify and optimize ASO drug candidates, as well as the means to determine efficacious dosing in humans and experimental animals. The company has previously characterized the subchronic toxicities of ASOs, and they have studied tissue (and brain) distribution and PK and pharmacodynamics (PD) after intracerebroventricular (ICV) or intrathecal delivery.

Isis’s work to date is promising. They have identified candidate htt ASOs from screens in human and murine cell lines, and they have confirmed the in vitro silencing of both wild-type and mutant htt. In vivo toxicology and pharmacology studies are complete in mice, and efficacy studies are underway in a transgenic HD model. Optimization of backbone chemistries and gap sizes for our CNS application of the ASOs are still pending, as are longer safety studies, but this program is on a fast track toward further IND-enabling studies.

Although the Isis ASO program now envisions direct injection into the brain or into cerebrospinal fluid, we are also working on methods that would allow oral or parenteral drugs to cross the BBB. The BBB, which protects the brain from blood-borne infectious agents, prevents circulating proteins and most small molecules from entering the brain, thereby posing an enormous challenge for neurotherapeutic agents [81]. Small molecules that passively cross the BBB—lipophilic compounds with molecular masses less than 500—represent but a tiny fraction of the chemical universe and do not include proteins and oligonucleotides. Some xenobiotics do cross the BBB, however, because they contain functional groups recognized by BBB transporters. The XenoPort phosphocreatine prodrug program, discussed previously, attempts to exploit such carrier-mediated transport.

We are seeking to exploit carrier-mediated transport to overcome the BBB’s barrier to large molecules such as proteins. In the meantime, we are exploring more invasive modalities to seek a proof of concept for potential therapeutics. A number of such techniques are available: (1) ICV injection, with convection enhanced diffusion; (2) transient chemical disruption of the BBB; (3) focal BBB disruption with high intensity focused ultrasound; and (4) transnasal delivery (for a restricted class of molecules). Such invasive modalities, however, cannot be used to treat a condition that may require life-long dosing. The much preferred route exploits the BBB’s own receptor-mediated transport (RMT), which is responsible for delivering selected protein or peptide cargoes to the brain. The best characterized of these transport systems involves the transferrin receptor [82]. This receptor can bind either transferrin or peptidomimetic monoclonal antibodies on the outside of the endothelial cells that comprise the BBB. These cells then move the receptor–ligand complex through the BBB by endocytosis. The RMT system acts as “molecular Trojan horses” to ferry drugs, proteins, and nonviral gene medicines across the BBB [81].

Investigators have developed several molecular targeting vectors, often monoclonal antibodies, that can carry macromolecules and immunoliposomes—phospholipid vesicles, about 90 nm in diameter, coated with targeting vectors—across rodent and nonhuman primate BBBs [83–88]. The monoclonal antibodies, which bind to the transferrin (or other) receptor, are attached to polyethylene glycol (PEG) that decorates the liposome exterior and protects it from metabolization. Therefore, the liposomes are said to be “PEGylated.” PEGylated immunoliposomes bind to the receptor and then move into the endothelial cells by endocytosis.

CHDI and Hermes Biosciences (South San Francisco, CA) have entered into a collaboration to explore the utility of immunoliposomes for HD drug delivery. Hermes has extensive experience with liposomal formulations for oncology, and it has demonstrated the ability to produce targeted immunoliposomal therapeutics with the standards required for human clinical trials [89, 90]. This collaboration has three goals: (1) delivery of small molecule validating ligands that would not otherwise be available in the brain; (2) delivery of therapeutic proteins, via nonviral gene therapy [91]; and (3) delivery of ASO therapeutics. Success with this platform would allow CHDI to explore the possible therapeutic use of neurotrophic factors such as BDNF, FGF2, and GDNF (and the genes encoding them).

A Validating Ligand Must Bind to Its Target In Vivo

To use a validating ligand to test a molecular target, that compound must engage the target in vivo. Such a demonstration requires adequate exposure in the tissue of interest, as well as PD markers of target engagement. Such measurements may be direct, for example, positron emission tomography (PET) measurements of receptor occupancy by radioligand displacement, or indirect, for example, histone acetylation after HDAC inhibition. In the antisense program, the PD marker is the level of Htt or of htt mRNA, whereas in the KMO program, the markers are the downstream metabolites of the kynurenine pathway. In the caspase program, the PD readout is the amount of Htt fragments, determined immunologically.

Although measures of target engagement at the preclinical efficacy stage have been stressed, their absence once a compound is on a clinical trajectory can prove costly; the failure of the NMDA receptor glycine site antagonist gavestinel may have been one such example [92].

The first requirement for pharmacological TV is a molecule that is sufficiently potent and selective in vitro. In vivo validation then requires identification of a suitable vehicle and the determination of a route for administration that gives appropriate exposure at the desired site of action. The design of TV experiments must be sensitive to mode of action: for example, it is pointless to evaluate a caspase-6 inhibitor in the R6/2 model because the exon 1-encoded Htt fragment does not contain the putative caspase-6 cleavage site. Similarly, the exon 1-derived htt mRNA in R6/2 does not contain the sequence complementary to the antisense oligonucleotides that Isis discovered to be most effective in reducing Htt levels in vitro; therefore, such studies must use a full-length (or at least sufficiently long) mutant transgene.

In Vivo Evaluation Requires Attention to Scaled-Up Synthesis and Formulation

Formulation, PK, and in vivo testing require much more compound than in vitro studies. Some compounds may be purchased, but others require contract synthesis. Once a sufficient quantity of a compound is acquired, it then enters CHDI’s chemical repository, where it is registered and checked for identity and purity (>95%). Next, we dispatch the compound for pre-efficacy formulation, whose goal is to produce a formulation and dosing regimen with an acceptable safety profile to test in mice for several months.

Pre-efficacy formulation starts with the determination of the aqueous solubility of the compound at pH 4.5, 7, and 8, the tolerable pH range in mouse models. The next step is to identify suitable formulations for both parenteral and oral administration. Ideally the compound should dissolve at concentrations of 20 mg/ml, enough to allow relatively high doses. In practice, however, we may need to settle for concentrations of 10 mg/ml or even 1 mg/ml. Some compounds have proven insoluble even at 1 mg/ml and require oral dosing as a methylcellulose suspension.

After pre-efficacy formulation, the next steps are to determine the route of administration and the compound’s ability to traverse the BBB. This evaluation, which uses a single-dose PK study in wild-type mice, measures the total plasma and brain exposure (the area under the curve, representing the integral of concentration over time) after intravenous (IV), subcutaneous, intraperitoneal, and oral administration. For a compound whose half-life is 12 hours or less, this study extends for 24 hours, during which time its concentration is measured eight times in the plasma and four times in the brain.

Single-dose PK studies have established dosing, route, and formulation for some 60 compounds of interest to CHDI, but 10 of these did not appear to penetrate the BBB. That is, these compounds reached a concentration in unperfused brain of less than 2%–4% that in the plasma, which is consistent with the contribution of blood in the unperfused brain [93]. Such a failure can prevent in vivo study, but not always, because some compounds act peripherally. For example, a pan-caspase inhibitor can modulate the inhibition of interleukin 1 induction in the periphery, thus reducing peripheral inflammatory response. This effect may also extend to immunomodulatory cells (macrophages and microglia) that may contribute to neuroinflammation within the CNS [94].

Compounds that are expected to act only within the CNS but that do not cross the BBB require re-evaluation. The single-dose PK protocol uses 5 mg/kg for IV administration and 10 mg/kg for other routes, and some compounds do not have significant CNS exposure at these doses. If the literature suggests that higher doses are tolerated and efficacious in disease models, then we move to a higher dose with the hope of finding sufficient compound exposure in the brain. In some cases, however, a compound does not penetrate the BBB even at higher concentrations, and our next step is to search for an active metabolite that does enter the brain. In the case of tetrabenazine, for example, a BBB-penetrant metabolite reduces chorea in HD, although tetrabenazine itself has little CNS exposure [95].

Even if a metabolite enters the brain, it may not act in the CNS. Peripheral exposure to the parent compound or its metabolite may be responsible for the pharmacological effect. For example, systemic administration of a compound may change the level of endogenous peripheral metabolites, and these compounds may cross the BBB and lead to effects within the CNS. To overcome such ambiguity requires both PK studies and PD readouts, as described previously. A compound may advance toward in vivo efficacy studies only if a target engagement correlates with plasma levels of the test compound, even in the absence of CNS exposure. A PD readout is required for such a conclusion, but such measurements are not available for every compound, and unfortunately we have not always been able to establish PK/PD correlations, especially because of the limited number of tools (such as PET radioligands) available for studying CNS effects.

After determining the optimal route and dosing regimen, the next goal is to establish tolerability, usually starting with a single-day toxicity study at three doses, typically at half-log steps. A second study follows, usually for 2 weeks with three doses. To prevent the selection of a dose that may confound the efficacy study, the tolerability study must encompass the range of doses contemplated for the longterm efficacy trial. The dose range follows from a review of the literature and an examination of the single-dose PK data. During the 2-week study, we monitor neurological signs with a modified Irwin test every 3 days [96], and we collect plasma and brain samples 24 hours after the last dose to determine the accumulation of compound.

Initial Efficacy Screening In Vivo

For each compound that jumps the hurdles discussed above, we now do efficacy testing in the R6/2 mouse using the determined formulation and dosing. The mice begin treatment at 4.5 weeks (about 10 days after weaning), and treatment continues until death. Our usual study design uses three cohorts, with two doses of each compound plus vehicle alone. Although three or more doses would give more information, such a design would significantly limit the number of tested compounds.

In collaboration with our colleagues at PsychoGenics, we have decided to stage our efficacy trials to increase the number of evaluated compounds. In this design, the first cohorts of mice (“stage 1”) are sufficient to detect a trend (0.05 < P < 0.3) of a 20% improvement in motor function or survival. With the robust tests now used, 12 mice per cohort are sufficient. When a positive trend appears, testing proceeds to “stage 2,” which is powered to achieve statistical significance (P < 0.05) for a 20% effect. Stage 2 includes a larger array of motor readouts than stage 1, as well as cognitive measurements and histological analysis.

Stage 1 evaluates multiple motor behaviors, including the rotarod, grip strength, and open field behavior (e.g., distance traveled, rearing, and speed) (Figure 8.2). Our current design uses separate cohorts to evaluate cognitive performance and histopathology, but—having discovered that the two types of tests do not interfere with one another—we are now in the process of combining motor and cognitive testing in the same stage 2 cohorts. If any of the stage 1 outcome measures exhibit a positive trend, the compound is considered for stage 2 testing. The decision to advance a compound to stage 2 depends partly on a comparison of stage 1 data with in vivo data from other compounds with similar molecular targets or mechanisms of action.

FIGURE 8.2. The R6/2 stage 1 testing paradigm that primarily measures motor and survival endpoints.

FIGURE 8.2

The R6/2 stage 1 testing paradigm that primarily measures motor and survival endpoints.

The evaluation of compounds in full-length models now takes close to a year, limiting the practical utility of these animals for initial compound screening. If stage 2 studies confirm a compound’s efficacy in R6/2 mice, however, we then test it in one of the more slowly developing full-length transgenic models, either in YAC128 or BAC-HD mice. Efforts are underway to establish early and robust readouts from these full-length models.

Compounds Entering the Clinic Must Be Safe

Demonstration of efficacy in one or more animal models still does not necessarily mean that a compound is an appropriate candidate for clinical evaluation. Any compound that enters the clinic must be safe, meaning that it must satisfy multiple in vitro and in vivo safety pharmacology studies before nomination as a clinical candidate. Generally, compounds that have already been in clinical studies for non-HD indications will be the easiest to advance to clinical studies for HD. Even FDA-approved compounds, however, may be unsuitable for HD clinical studies. For example, one group has reported that minocycline, an antibiotic, increases the lifetime of R6/2 mice, although not all reports concur [97–99]. The long-term safety of minocycline in humans has not been established because the drug is usually used acutely. Rodent studies suggest that its long-term use may increase autoimmune disorders, provoke serious hypersensitivity, and induce hyperpigmentation [100].

The FDA requires safety studies both before the initiation of clinical studies (before approval of an IND application) and again before the approval of a therapeutic agent (before approval of a new drug application [NDA]). The required length of these studies depends on the length of time over which the compound will be administered. Because HD treatment will require long-term administration, compounds approved for short-term use will require longer safety studies before initiating HD clinical trials.

Safety and Efficacy Studies Must Address Issues Identified by Regulatory Agencies

Dialogue with the U.S. FDA and European Medicines Agency (EMEA) can identify issues likely to be important in clinical studies well in advance, such as specific adverse effects known to be associated with a particular class of compound. One FDA guidance document, ICH Guidance for Industry S7A Safety Pharmacology Studies for Human Pharmaceuticals [101], underscores the need to evaluate such off-target adverse events as cardiac effects (QT interval prolongation), which may be independent of the primary PD effect. A compound can also have on-target or off-target adverse effects that derive from its binding to receptors or enzymes, necessitating broad surveys of potential targets. The scope and range of new safety studies must respond to concerns of regulatory agencies, as well as to the results of previous safety studies, secondary PD studies, and previous clinical investigations. Safety studies must address the potential for specific organ toxicity, including cardiovascular, respiratory, CNS, renal, and gastrointestinal systems, focusing on irreversible effects. (Transient disruption of these systems may also result from specific drug action, with no irreversible effects.)

The choice of species for preclinical safety studies depends on the potential of each species to reflect the likely human response to a given compound. Species may differ, for example, in the level of celland organ-specific expression of individual targets and in the distribution and metabolism of individual compounds. Safety studies must define the dose–response relationship for any observed adverse effect, and they should also encompass a dose range that achieves efficacious pharmacological exposure.

Discussions with regulatory agencies must also address the proper outcome measures and endpoints for efficacy trials in humans. Because HD is a late-onset, slowly progressing disease, clinical trials could benefit from the use of a surrogate endpoint defined by an appropriate biomarker [102]. Longitudinal observational studies, such as PREDICT-HD [103, 104, Pharos 105], TRACK-HD, and the HD Neuroimaging Initiative, are in the process of evaluating the biochemical, structural, clinical, cognitive, and behavior changes that occur before HD diagnosis, and these studies may also identify useful biomarkers and surrogate that will accelerate HD clinical trials.

CASTING A WIDE NET FOR POSSIBLE HD THERAPIES

HD undoubtedly results from the expression of mutant htt, but the supporting evidence for any of the competing pathogenic models is not compelling, and each model implicates many potential molecular targets. Therefore, CHDI’s drug development program cannot be limited to a single molecular target or a single point of intervention. Rather, the rapid identification of a disease-modifying HD therapeutic agent will require a portfolio of parallel programs.

CHDI is presently working on 18 therapeutic programs (see Table 8.1). Some of these are defined by traditional molecular targets such as the “Adenosine A2a receptor program.” However, others encompass a broader effort, such as the “In vivo program,” which encompasses our in vivo testing effort, including compound procurement or synthesis, formulation, PK, and dosing. Our objective for these parallel programs is accelerating the entrance of several molecules into clinical evaluation with the hope of identifying at least one disease-modifying treatment. We expect to evaluate more than one clinical candidate before we find a disease-modifying treatment, and we also expect that successful treatment of HD will require the combination of more than one therapy, as is the case for other serious, chronic illnesses, such as AIDS.

TABLE 8.1. Current CHDI Therapeutic Programs.

TABLE 8.1

Current CHDI Therapeutic Programs.

Clinical evaluation of potential therapies will require a synergistic collaboration of translational scientists and clinicians to ensure two-way traffic of observations and ideas. Such interaction will be particularly important in the development and evaluation of potential biomarkers and surrogate endpoints, whose incorporation into the drug discovery program will greatly improve its potential for success.

The goal of most of CHDI’s current efforts is to bring candidate therapeutics to the clinic, but we have begun to devote more resources to preparing for clinical evaluation. Our preclinical work increasingly attends to the magnitudes and correlations of therapeutic effects. Information from such preclinical studies can inform estimates of the number of subjects needed to observe a parallel effect in a clinical trial. Slowing or stopping HD will almost certainly require the treatment of premanifest gene carriers, people who carry the mutant htt gene but who have not developed the diagnostic signs. For these subjects, the Unified Huntington Disease Rating Scale (UHDRS) is useless because they appear clinically normal by almost every UHDRS measure [106]. One possible readout for a trial in premanifest subjects is “phenoconversion,” the development of HD-specific signs, particularly of chorea and other characteristic motor signs, but such a trial would require more than 3 years and more than 500 subjects. With these limitations in mind, CHDI is supporting the four studies mentioned previously—PREDICT, Pharos, TRACK-HD, and the HD Neuroimaging Initiative—to identify biomarkers and potential surrogate endpoints. Recent reports show increases in a number of inflammatory biomarkers, including microglial activation and inflammatory cytokine levels, in premanifest HD [40, 106]. Several neuroimaging studies also suggest that the size of brain, caudate, and putamen and the thinning of the cortex might be useful biomarkers [107], 108].

For HD, as for any chronic illness, the ideal medication would be a daily oral tablet with few or no side effects. Because no disease-modifying treatments are available, patients and their families are also likely to be receptive to almost any treatment modality, including implanted systems for direct CNS administration, such as those used in the treatment of chronic pain. Although such devices may overcome problems of brain exposure, potential side effects and adverse events will need further study. Maintaining compliance will be a challenge for any disease-modifying treatment that significantly reduces the quality of life for people with no overt symptoms or signs. Almost any longterm treatment regimen, however, raises significant issues of safety and compliance, and these issues will be magnified when there are significant side effects [109].

CHDI’s mission is to find treatments that slow or stop HD. Achievement of this mission will require close collaboration not only among the translational scientists and clinicians within CHDI but also among the scientists, clinicians, patients, and families of the entire HD community.

REFERENCES

1.
Bonelli RM, Hofmann P. A systematic review of the treatment studies in Huntington’s disease since 1990. Expert Opin Pharmacother. 2007;8:141–153. [PubMed: 17257085]
2.
Shults CW, Oakes D, Kieburtz K, Beal MF, Haas R, Plumb S, Juncos JL, Nutt J, Shoulson I, Carter J, et al. Effects of coenzyme q10 in early Parkinson disease: evidence of slowing of the functional decline. Arch Neurol. 2002;59:1541–1550. [PubMed: 12374491]
3.
Huntington Study Group. A randomized, placebo-controlled trial of coenzyme q10 and remacemide in Huntington’s disease. Neurology. 2001;57:397–404. [PubMed: 11502903]
4.
Murck H, Manku M. Ethyl-epa in Huntington disease: potentially relevant mechanism of action. Brain Res Bull. 2007;72:159–164. [PubMed: 17352940]
5.
Puri BK, Leavitt BR, Hayden MR, Ross CA, Rosenblatt A, Greenamyre JT, Hersch S, Vaddadi KS, Sword A, Horrobin DF. et al. Ethyl-epa in Huntington disease: a doubleblind, randomized, placebo-controlled trial. Neurology. 2005;65:286–292. [PubMed: 16043801]
6.
Verhagen, Metman L, Morris MJ, Farmer C, Gillespie M, Mosby K, Wuu J, Chase TN. Huntington’s disease: a randomized, controlled trial using the NMDA-antagonist amantadine. Neurology. 2002;59:694–699. [PubMed: 12221159]
7.
O’Suilleabhain P, Dewey RBJ. A randomized trial of amantadine in Huntington disease. Arch Neurol. 2003;60:996–998. [PubMed: 12873857]
8.
Leegwater-Kim J, Cha JJ. The paradigm of Huntington’s disease: therapeutic opportunities in neurodegeneration. NeuroRx. 2004;1:128–138. [PMC free article: PMC534918] [PubMed: 15717013]
9.
Meriin AB, Zhang X, He X, Newnam GP, Chernoff YO, Sherman MY. Huntington toxicity in yeast model depends on polyglutamine aggregation mediated by a prion-like protein RNQ1. J Cell Biol. 2002;157:997–1004. [PMC free article: PMC2174031] [PubMed: 12058016]
10.
Kaltenbach LS, Romero E, Becklin RR, Chettier R, Bell R, Phansalkar A, Strand A, Torcassi C, Savage J, Hurlburt A, et al. Huntingtin interacting proteins are genetic modifiers of neurodegeneration PLoS Genet 20073 p. e82. [PMC free article: PMC1866352] [PubMed: 17500595]
11.
Goehler H, Lalowski M, Stelzl U, Waelter S, Stroedicke M, Worm U, Droege A, Lindenberg KS, Knoblich M, Haenig C, et al. A protein interaction network links git1, an enhancer of huntingtin aggregation, to Huntington’s disease. Mol Cell. 2004;15:853–865. [PubMed: 15383276]
12.
Sipione S, Cattaneo E. Modeling Huntington’s disease in cells, flies, and mice. Mol Neurobiol. 2001;23:21–51. [PubMed: 11642542]
13.
Li SH, Cheng AL, Li H, Li XJ. Cellular defects and altered gene expression in pc12 cells stably expressing mutant huntingtin. J Neurosci. 1999;19:5159–5172. [PubMed: 10377328]
14.
Cattaneo E, Conti L. Generation and characterization of embryonic striatal conditionally immortalized st14a cells. J Neurosci Res. 1998;53:223–234. [PubMed: 9671979]
15.
Trettel F, Rigamonti D, Hilditch-Maguire P, Wheeler VC, Sharp AH, Persichetti F, Cattaneo E, MacDonald ME. Dominant phenotypes produced by the HD mutation in STHdh(q111) striatal cells. Hum Mol Genet. 2000;9:2799–2809. [PubMed: 11092756]
16.
Faber PW, Alter JR, MacDonald ME, Hart AC. Polyglutamine-mediated dysfunction and apoptotic death of a Caenorhabditis elegans sensory neuron. Proc Natl Acad Sci U S A. 1999;96:179–184. [PMC free article: PMC15113] [PubMed: 9874792]
17.
Marsh JL, Pallos J, Thompson LM. Fly models of Huntington’s disease Hum Mol Genet 2003. 12 Spec No 2R187–R193. [PubMed: 12925571]
18.
Hickey MA, Chesselet M. The use of transgenic and knock-in mice to study Huntington’s disease. Cytogenet Genome Res. 2003;100:276–286. [PubMed: 14526189]
19.
von Hörsten S, Schmitt I, Nguyen HP, Holzmann C, Schmidt T, Walther T, Bader M, Pabst R, Kobbe P, Krotova J, et al. Transgenic rat model of Huntington’s disease. Hum Mol Genet. 2003;12:617–624. [PubMed: 12620967]
20.
Mangiarini L, Sathasivam K, Seller M, Cozens B, Harper A, Hetherington C, Lawton M, Trottier Y, Lehrach H, Davies SW, et al. Exon 1 of the HD gene with an expanded CAG repeat is sufficient to cause a progressive neurological phenotype in transgenic mice. Cell. 1996;87:493–506. [PubMed: 8898202]
21.
Li JY, Popovic N, Brundin P. The use of the R6 transgenic mouse models of Huntington’s disease in attempts to develop novel therapeutic strategies. NeuroRx. 2005;2:447–464. [PMC free article: PMC1144488] [PubMed: 16389308]
22.
Reddy PH, Williams M, Charles V, Garrett L, Pike-Buchanan L, Whetsell WOJ, Miller G, Tagle DA. Behavioural abnormalities and selective neuronal loss in HD transgenic mice expressing mutated full-length HD CDNA. Nat Genet. 1998;20:198–202. [PubMed: 9771716]
23.
Hodgson JG, Agopyan N, Gutekunst CA, Leavitt BR, LePiane F, Singaraja R, Smith DJ, Bissada N, McCutcheon K, Nasir J, et al. A YAC mouse model for Huntington’s disease with full-length mutant huntingtin, cytoplasmic toxicity, and selective striatal neurodegeneration. Neuron. 1999;23:181–192. [PubMed: 10402204]
24.
Slow EJ, van Raamsdonk J, Rogers D, Coleman SH, Graham RK, Deng Y, Oh R, Bissada N, Hossain SM, Yang Y, et al. Selective striatal neuronal loss in a YAC128 mouse model of Huntington disease. Hum Mol Genet. 2003;12:1555–1567. [PubMed: 12812983]
25.
Yang X, Gong S. An overview on the generation of BAC transgenic mice for neuroscience research. Curr Protoc Neurosci. 2005. Unit 5. 20. [PubMed: 18428622]
26.
Griffioen G. Targeting disease, not disease targets: innovative approaches in tackling neurodegenerative disorders. IDrugs. 2007;10:259–263. [PubMed: 17390249]
27.
Zhang X, Smith DL, Meriin AB, Engemann S, Russel DE, Roark M, Washington SL, Maxwell MM, Marsh JL, Thompson LM, et al. A potent small molecule inhibits polyglutamine aggregation in Huntington’s disease neurons and suppresses neurodegeneration in vivo. Proc Natl Acad Sci U S A. 2005;102:892–897. [PMC free article: PMC545525] [PubMed: 15642944]
28.
Bodner RA, Outeiro TF, Altmann S, Maxwell MM, Cho SH, Hyman BT, McLean PJ, Young AB, Housman DE, Kazantsev AG. Pharmacological promotion of inclusion formation: a therapeutic approach for Huntington’s and Parkinson’s diseases. Proc Natl Acad Sci U S A. 2006;103:4246–4251. [PMC free article: PMC1449678] [PubMed: 16537516]
29.
Varma H, Voisine C, DeMarco CT, Cattaneo E, Lo DC, Hart AC, Stockwell BR. Selective inhibitors of death in mutant huntingtin cells. Nat Chem Biol. 2007;3:99–100. [PubMed: 17195849]
30.
Rego AC, de Almeida LP. Molecular targets and therapeutic strategies in Huntington’s disease. Curr Drug Targets CNS Neurol Disord. 2005;4:361–381. [PubMed: 16101555]
31.
Lazo JS, Brady LS, Dingledine R. Building a pharmacological lexicon: small molecule discovery in academia. Mol Pharmacol. 2007;72:1–7. [PubMed: 17405872]
32.
Zeitlin S, Liu JP, Chapman DL, Papaioannou VE, Efstratiadis A. Increased apoptosis and early embryonic lethality in mice nullizygous for the Huntington’s disease gene homologue. Nat Genet. 1995;11:155–163. [PubMed: 7550343]
33.
Zuccato C, Ciammola A, Rigamonti D, Leavitt BR, Goffredo D, Conti L, MacDonald ME, Friedlander RM, Silani V, Hayden MR, et al. Loss of huntingtin-mediated BDNF gene transcription in Huntington’s disease. Science. 2001;293:493–498. [PubMed: 11408619]
34.
Gunawardena S, Her L, Brusch RG, Laymon RA, Niesman IR, Gordesky-Gold B, Sintasath L, Bonini NM, Goldstein LSB. Disruption of axonal transport by loss of huntingtin or expression of pathogenic PolyQ proteins in Drosophila. Neuron. 2003;40:25–40. [PubMed: 14527431]
35.
Szebenyi G, Morfini GA, Babcock A, Gould M, Selkoe K, Stenoien DL, Young M, Faber PW, MacDonald ME, McPhaul MJ, et al. Neuropathogenic forms of huntingtin and androgen receptor inhibit fast axonal transport. Neuron. 2003;40:41–52. [PubMed: 14527432]
36.
Morfini G, Pigino G, Brady ST. Polyglutamine expansion diseases: failing to deliver. Trends Mol Med. 2005;11:64–70. [PubMed: 15694868]
37.
Truant R, Atwal R, Burtnik A. Hypothesis: huntingtin may function in membrane association and vesicular trafficking. Biochem Cell Biol. 2006;84:912–917. [PubMed: 17215878]
38.
Cooper JK, Schilling G, Peters MF, Herring WJ, Sharp AH, Kaminsky Z, Masone J, Khan FA, Delanoy M, Borchelt DR, et al. Truncated n-terminal fragments of huntingtin with expanded glutamine repeats form nuclear and cytoplasmic aggregates in cell culture. Hum Mol Genet. 1998;7:783–790. [PubMed: 9536081]
39.
Butler R, Leigh PN, McPhaul MJ, Gallo JM. Truncated forms of the androgen receptor are associated with polyglutamine expansion in x-linked spinal and bulbar muscular atrophy. Hum Mol Genet. 1998;7:121–127. [PubMed: 9384612]
40.
Tai YF, Pavese N, Gerhard A, Tabrizi SJ, Barker RA, Brooks DJ, Piccini P. Microglial activation in presymptomatic Huntington’s disease gene carriers. Brain. 2007;130:1759–1766. [PubMed: 17400599]
41.
Fan MMY, Raymond LA. N-Methyl-d-aspartate (NMDA) receptor function and excitotoxicity in Huntington’s disease. Prog Neurobiol. 2007;81:272–293. [PubMed: 17188796]
42.
Hickey MA, Chesselet MF. Apoptosis in Huntington’s disease. Prog Neuropsychopharmacol Biol Psychiatry. 2003;27:255–265. [PubMed: 12657365]
43.
Pattison LR, Kotter MR, Fraga D, Bonelli RM. Apoptotic cascades as possible targets for inhibiting cell death in Huntington’s disease. J Neurol. 2006;253:1137–1142. [PubMed: 16998646]
44.
Browne SE, Beal MF. Oxidative damage in Huntington’s disease pathogenesis. Antioxid Redox Signal. 2006;8:2061–2073. [PubMed: 17034350]
45.
Ramaswamy S, Shannon KM, Kordower JH. Huntington’s disease: pathological mechanisms and therapeutic strategies. Cell Transplant. 2007;16:301–312. [PubMed: 17503740]
46.
Vonsattel JP, Myers RH, Stevens TJ, Ferrante RJ, Bird ED, Richardson EPJ. Neuropathological classification of Huntington’s disease. J Neuropathol Exp Neurol. 1985;44:559–577. [PubMed: 2932539]
47.
Albin RL, Young AB, Penney JB, Handelin B, Balfour R, Anderson KD, Markel DS, Tourtellotte WW, Reiner A. Abnormalities of striatal projection neurons and n-methyl-d-aspartate receptors in presymptomatic Huntington’s disease. N Engl J Med. 1990;322:1293–1298. [PubMed: 1691447]
48.
Zuccato C, Cattaneo E. Role of brain-derived neurotrophic factor in Huntington’s disease. Prog Neurobiol. 2007;81:294–330. [PubMed: 17379385]
49.
Strand AD, Baquet ZC, Aragaki AK, Holmans P, Yang L, Cleren C, Beal MF, Jones L, Kooperberg C, Olson JM, et al. Expression profiling of Huntington’s disease models suggests that brain-derived neurotrophic factor depletion plays a major role in striatal degeneration. J Neurosci. 2007;27:11758–11768. [PubMed: 17959817]
50.
Guidetti P, Luthi-Carter RE, Augood SJ, Schwarcz R. Neostriatal and cortical quinolinate levels are increased in early grade Huntington’s disease. Neurobiol Dis. 2004;17:455–461. [PubMed: 15571981]
51.
Guidetti P, Bates GP, Graham RK, Hayden MR, Leavitt BR, MacDonald ME, Slow EJ, Wheeler VC, Woodman B, Schwarcz R. Elevated brain 3-hydroxykynurenine and quinolinate levels in Huntington disease mice. Neurobiol Dis. 2006;23:190–197. [PubMed: 16697652]
52.
Giorgini F, Guidetti P, Nguyen Q, Bennett SC, Muchowski PJ. A genomic screen in yeast implicates kynurenine 3-monooxygenase as a therapeutic target for Huntington disease. Nat Genet. 2005;37:526–531. [PMC free article: PMC1449881] [PubMed: 15806102]
53.
Aiken CT, Tobin AJ, Schweitzer ES. A cell-based screen for drugs to treat Huntington’s disease. Neurobiol Dis. 2004;16:546–555. [PubMed: 15262266]
54.
Miyashita T, Matsui J, Ohtsuka Y, Mami U, Fujishima S, Okamura-Oho Y, Inoue T, Yamada M. Expression of extended polyglutamine sequentially activates initiator and effector caspases. Biochem Biophys Res Commun. 1999;257:724–730. [PubMed: 10208851]
55.
Wyttenbach A, Swartz J, Kita H, Thykjaer T, Carmichael J, Bradley J, Brown R, Maxwell M, Schapira A, Orntoft TF, et al. Polyglutamine expansions cause decreased Cremediated transcription and early gene expression changes prior to cell death in an inducible cell model of Huntington’s disease. Hum Mol Genet. 2001;10:1829–1845. [PubMed: 11532992]
56.
MacDonald ME, Gines S, Gusella JF, Wheeler VC. Huntington’s disease. Neuromolecular Med. 2003;4:7–20. [PubMed: 14528049]
57.
Wang J, Gines S, MacDonald ME, Gusella JF. Reversal of a full-length mutant huntingtin neuronal cell phenotype by chemical inhibitors of polyglutamine-mediated aggregation. BMC Neurosci. 2005;6:1. [PMC free article: PMC548150] [PubMed: 15649316]
58.
Sipione S, Rigamonti D, Valenza M, Zuccato C, Conti L, Pritchard J, Kooperberg C, Olson JM, Cattaneo E. Early transcriptional profiles in huntingtin-inducible striatal cells by microarray analyses. Hum Mol Genet. 2002;11:1953–1965. [PubMed: 12165557]
59.
Gines S, Ivanova E, Seong I, Saura CA, MacDonald ME. Enhanced Akt signaling is an early pro-survival response that reflects N-methyl-D-aspartate receptor activation in Huntington’s disease knock-in striatal cells. J Biol Chem. 2003;278:50514–50522. [PubMed: 14522959]
60.
CHDI Inc. 3rd Annual HD Therapeutics Conference: a forum for drug discovery and development; Palm Springs, CA: Feb 4–7, 2008.
61.
Varma H, Cheng R, Voisine C, Hart AC, Stockwell BR. Inhibitors of metabolism rescue cell death in Huntington’s disease models. Proc Natl Acad Sci U S A. 2007;104:14525–14530. [PMC free article: PMC1964858] [PubMed: 17726098]
62.
Carter RJ, Hunt MJ, Morton AJ. Environmental stimulation increases survival in mice transgenic for exon 1 of the Huntington’s disease gene. Mov Disord. 2000;15:925–937. [PubMed: 11009201]
63.
Woodman B, Butler R, Landles C, Lupton MK, Tse J, Hockly E, Moffitt H, Sathasivam K, Bates GP. The Hdh(q150/q150) knock-in mouse model of HD and the R6/2 exon 1 model develop comparable and widespread molecular phenotypes. Brain Res Bull. 2007;72:83–97. [PubMed: 17352931]
64.
Levine MS, Cepeda C, Hickey MA, Fleming SM, Chesselet M. Genetic mouse models of Huntington’s and Parkinson’s diseases: illuminating but imperfect. Trends Neurosci. 2004;27:691–697. [PubMed: 15474170]
65.
Loutfy MR, Harris M, Raboud JM, Antoniou T, Kovacs C, Shen S, Dufresne S, Smaill F, Rouleau D, Rachlis A, et al. A large prospective study assessing injection site reactions, quality of life and preference in patients using the biojector vs standard needles for enfuvirtide administration. HIV Med. 2007;8:427–432. [PubMed: 17760734]
66.
Eckstein J. ISOA/ARF drug development tutorial. 2005 2007 October 5 Available online at http://www​.alzforum.org​/drg/tut/ISOATutorial.pdf. accessed.
67.
Eli Lilly and Company and NIH Chemical Genomics Center Assay guidance manual version 4. 1 Available online at http://www​.ncgc.nih.gov​/guidance/manual_toc.html 2005. accessed October52007.
68.
Ravina B, Di Prospero N, Fagan SC, Fischbeck K, Harrison M, Hart R, Heemskerk J, Murphy D, Profenno L, Blumenstein R, Signer ER. (for Huntington Study Group) Cambridge, MA: Aug 16, Dec 16, 2004. 2007. Systematic Evaluation of Treatments for Huntington’s Disease (SET-HD) An interim report. Presented at the Hereditary Disease Foundation CAG Symposium. Available online at http://www​.huntingtonproject.org: accessed.
69.
Hay DG, Sathasivam K, Tobaben S, Stahl B, Marber M, Mestril R, Mahal A, Smith DL, Woodman B, Bates GP. Progressive decrease in chaperone protein levels in a mouse model of Huntington’s disease and induction of stress proteins as a therapeutic approach. Hum Mol Genet. 2004;13:1389–1405. [PubMed: 15115766]
70.
Kase H, Aoyama S, Ichimura M, Ikeda K, Ishii A, Kanda T, Koga K, Koike N, Kurokawa M, Kuwana Y, et al. Progress in pursuit of therapeutic A2A antagonists: the adenosine A2A receptor selective antagonist KW6002: research and development toward a novel nondopaminergic therapy for Parkinson’s disease Neurology 200361 p. S97–100. [PubMed: 14663020]
71.
Qikprop. Schrodinger, Inc; New York: Jorgensen WL; The many roles of computation in drug discovery. Science. 2005;2004;303:1813–1818. version 3. 0. [PubMed: 15031495]
72.
Kamzalov S, Sumien N, Forster MJ, Sohal RS. Coenzyme Q intake elevates the mitochondrial and tissue levels of coenzyme Q and alpha-tocopherol in young mice. J Nutr. 2003;133:3175–3180. [PubMed: 14519806]
73.
Miles MV. The uptake and distribution of coenzyme q10. Mitochondrion. 2007;7 Suppl:S72–S77. [PubMed: 17446143]
74.
Ohtsuki S, Tachikawa M, Takanaga H, Shimizu H, Watanabe M, Hosoya K, Terasaki T. The blood-brain barrier creatine transporter is a major pathway for supplying creatine to the brain. J Cereb Blood Flow Metab. 2002;22:1327–1335. [PubMed: 12439290]
75.
Prass K, Royl G, Lindauer U, Freyer D, Megow D, Dirnagl U, Stöckler-Ipsiroglu G, Wallimann T, Priller J. Improved reperfusion and neuroprotection by creatine in a mouse model of stroke. J Cereb Blood Flow Metab. 2007;27:452–459. [PubMed: 16773141]
76.
Janzen WP, Hodge CN. A chemogenomic approach to discovering target-selective drugs. Chem Biol Drug Des. 2006;67:85–86. [PubMed: 16492154]
77.
Keith CT, Borisy AA, Stockwell BR. Multicomponent therapeutics for networked systems. Nat Rev Drug Discov. 2005;4:71–78. [PubMed: 15688074]
78.
Lehár J, Zimmermann GR, Krueger AS, Molnar RA, Ledell JT, Heilbut AM, Short GF3, Giusti LC, Nolan GP, Magid OA, et al. Chemical combination effects predict connectivity in biological systems. Mol Syst Biol. 2007;3:80. [PMC free article: PMC1828746] [PubMed: 17332758]
79.
Boado RJ, Kazantsev A, Apostol BL, Thompson LM, Pardridge WM. Antisense-mediated down-regulation of the human huntingtin gene. J Pharmacol Exp Ther. 2000;295:239–243. [PubMed: 10991985]
80.
Harper SQ, Staber PD, He X, Eliason SL, Martins IH, Mao Q, Yang L, Kotin RM, Paulson HL, Davidson BL. RNA interference improves motor and neuropathological abnormalities in a Huntington’s disease mouse model. Proc Natl Acad Sci U S A. 2005;102:5820–5825. [PMC free article: PMC556303] [PubMed: 15811941]
81.
Pardridge WM. The blood-brain barrier: bottleneck in brain drug development. NeuroRx. 2005;2:3–14. [PMC free article: PMC539316] [PubMed: 15717053]
82.
Skarlatos S, Yoshikawa T, Pardridge WM. Transport of [125i]transferrin through the rat blood-brain barrier. Brain Res. 1995;683:164–171. [PubMed: 7552351]
83.
Kissel K, Hamm S, Schulz M, Vecchi A, Garlanda C, Engelhardt B. Immunohistochemical localization of the murine transferrin receptor (tfr) on blood-tissue barriers using a novel anti-tfr monoclonal antibody. Histochem Cell Biol. 1998;110:63–72. [PubMed: 9681691]
84.
Lee HJ, Engelhardt B, Lesley J, Bickel U, Pardridge WM. Targeting rat antimouse transferrin receptor monoclonal antibodies through blood-brain barrier in mouse. J Pharmacol Exp Ther. 2000;292:1048–1052. [PubMed: 10688622]
85.
Friden PM, Walus LR, Musso GF, Taylor MA, Malfroy B, Starzyk RM. Antitransferrin receptor antibody and antibody-drug conjugates cross the blood-brain barrier. Proc Natl Acad Sci U S A. 1991;88:4771–4775. [PMC free article: PMC51748] [PubMed: 2052557]
86.
Wu D, Yang J, Pardridge WM. Drug targeting of a peptide radiopharmaceutical through the primate blood-brain barrier in vivo with a monoclonal antibody to the human insulin receptor. J Clin Invest. 1997;100:1804–1812. [PMC free article: PMC508366] [PubMed: 9312181]
87.
Wu D. Neuroprotection in experimental stroke with targeted neurotrophins. NeuroRx. 2005;2:120–128. [PMC free article: PMC539332] [PubMed: 15717063]
88.
Pardridge WM. Tyrosine hydroxylase replacement in experimental Parkinson’s disease with transvascular gene therapy. NeuroRx. 2005;2:129–138. [PMC free article: PMC539333] [PubMed: 15717064]
89.
Nellis DF, Giardina SL, Janini GM, Shenoy SR, Marks JD, Tsai R, Drummond DC, Hong K, Park JW, Ouellette TF, et al. Preclinical manufacture of anti-her2 liposome-inserting, scfv-peg-lipid conjugate. 2. Conjugate micelle identity, purity, stability, and potency analysis. Biotechnol Prog. 2005;21:221–232. [PubMed: 15903261]
90.
Nellis DF, Ekstrom DL, Kirpotin DB, Zhu J, Andersson R, Broadt TL, Ouellette TF, Perkins SC, Roach JM, Drummond DC, et al. Preclinical manufacture of an anti-her2 scfv-peg-dspe, liposome-inserting conjugate. 1. Gram-scale production and purification. Biotechnol Prog. 2005;21:205–220. [PubMed: 15903260]
91.
Hayes ME, Drummond DC, Kirpotin DB, Zheng WW, Noble CO, Park JW, Marks JD, Benz CC, Hong K. Genospheres: self-assembling nucleic acid-lipid nanoparticles suitable for targeted gene delivery. Gene Ther. 2006;13:646–651. [PubMed: 16341056]
92.
Pangalos MN, Schechter LE, Hurko O. Drug development for CNS disorders: strategies for balancing risk and reducing attrition. Nat Rev Drug Discov. 2007;6:521–532. [PubMed: 17599084]
93.
Davies B, Morris T. Physiological parameters in laboratory animals and humans. Pharm Res. 1993;10:1093–1095. [PubMed: 8378254]
94.
Hopkins SJ. Central nervous system recognition of peripheral inflammation: a neural, hormonal collaboration Acta Biomed 2007. 78 Suppl 1231–247. [PubMed: 17465337]
95.
Mehvar R, Jamali F. Concentration-effect relationships of tetrabenazine and dihydrotetrabenazine in the rat. J Pharm Sci. 1987;76:461–465. [PubMed: 3625491]
96.
Irwin S. Comprehensive observational assessment: Ia. A systematic, quantitative procedure for assessing the behavioral and physiologic state of the mouse. Psychopharmacologia. 1968;13:222–257. [PubMed: 5679627]
97.
Mievis S, Levivier M, Communi D, Vassart G, Brotchi J, Ledent C, Blum D. Lack of minocycline efficiency in genetic models of Huntington’s disease. Neuromolecular Med. 2007;9:47–54. [PubMed: 17114824]
98.
Smith DL, Woodman B, Mahal A, Sathasivam K, Ghazi-Noori S, Lowden PAS, Bates GP, Hockly E. Minocycline and doxycycline are not beneficial in a model of Huntington’s disease. Ann Neurol. 2003;54:186–196. [PubMed: 12891671]
99.
Wang X, Zhu S, Drozda M, Zhang W, Stavrovskaya IG, Cattaneo E, Ferrante RJ, Kristal BS, Friedlander RM. Minocycline inhibits caspase-independent and -dependent mitochondrial cell death pathways in models of Huntington’s disease. Proc Natl Acad Sci U S A. 2003;100:10483–10487. [PMC free article: PMC193587] [PubMed: 12930891]
100.
Hoefnagel JJ, van Leeuwen RL, Mattie H, Bastiaens MT. [Side effects of minocycline in the treatment of acne vulgaris] Ned Tijdschr Geneeskd. 1997;141:1424–1427. [PubMed: 9542866]
101.
FDA. ICH guidance for industry S7A safety pharmacology studies for human pharmaceuticals. Feb 23, 2010. Available online at http://www​.fda.gov/RegulatoryInformation​/Guidances/ucm129150.htm: accessed.
102.
Biomarkers Definition Workgroup. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69:89–95. [PubMed: 11240971]
103.
Duff K, Paulsen JS, Beglinger LJ, Langbehn DR, Stout JC. Psychiatric symptoms in Huntington’s disease before diagnosis: the predict-HD study. Biol Psychiatry. 2007;62:1341–1346. [PubMed: 17481592]
104.
Paulsen JS, Hayden M, Stout JC, Langbehn DR, Aylward E, Ross CA, Guttman M, Nance M, Kieburtz K, Oakes D, et al. Preparing for preventive clinical trials: the predict-HD study. Arch Neurol. 2006;63:883–890. [PubMed: 16769871]
105.
Huntington Study Group PHAROS Investigators. At risk for Huntington disease: the PHAROS (Prospective Huntington At Risk Observational Study) cohort enrolled. Arch Neurol. 2006;63:991–996. [PubMed: 16831969]
106.
Huntington Study Group. Unified Huntington’s disease rating scale: reliability and consistency. Huntington Study Group. Mov Disord. 1996;11:136–142. [PubMed: 8684382]
107.
Aylward EH. Change in MRI striatal volumes as a biomarker in preclinical Huntington’s disease. Brain Res Bull. 2007;72:152–158. [PubMed: 17352939]
108.
Rosas HD, Feigin AS, Hersch SM. Using advances in neuroimaging to detect, understand, and monitor disease progression in Huntington’s disease. NeuroRx. 2004;1:263–272. [PMC free article: PMC534942] [PubMed: 15717027]
109.
Dunbar-Jacob J, Erlen JA, Schlenk EA, Ryan CM, Sereika SM, Doswell WM. Adherence in chronic disease. Annu Rev Nurs Res. 2000;18:48–90. [PubMed: 10918932]
Copyright © 2011 by Taylor and Francis Group, LLC.
Bookshelf ID: NBK56003PMID: 21882420

Views

  • PubReader
  • Print View
  • Cite this Page

Other titles in this collection

Related information

  • PMC
    PubMed Central citations
  • PubMed
    Links to PubMed

Similar articles in PubMed

See reviews...See all...

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...