Improving and Accelerating Therapeutic Development for Nervous System Disorders: Workshop Summary (2014)

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4 Target Validation Key Points  Establishing pharmacologically relevant exposure levels and engage- ment are two key steps in target validation.  There is a need for better biomarkers to objectively measure biologi- cal states and therapeutic effects.  In addition to target validation, several participants highlighted the im- portance of rapid target invalidation.  Understanding and examining the specific metrics of target validation and qualification may be useful for portfolio assessment.  Going directly into first-in-human trials might be feasible for highly val- idated targets. NOTE: The items in this list were addressed by individual speakers and participants and were identified and summarized for this report by the rap- porteurs, not the workshop participants. This list is not meant to reflect a consensus among workshop participants. Target validation ensures that engagement of the target has potential therapeutic benefit; like target identification, this is a critical step in drug development. If a target cannot be validated, then it will not proceed in the drug development process. Early validation of targets along with im- proved biomarkers were two opportunities discussed by Samuel Gandy, professor in the departments of neurology and psychiatry and associate director of Mount Sinai’s Alzheimer’s Disease Research Center, and Reisa Sperling, director of the Center for Alzheimer’s Research and 41 

42 THERAPEUTIC DEVELOPMENT FOR NERVOUS SYSTEM DISORDERS Treatment and professor of neurology at Harvard Medical School. In addition, Kalpana Merchant, chief scientific officer of Tailored Therapeutics–Neuroscience at Eli Lilly and Company, offered a portfolio assessment tool outlining specific metrics for target validation and qualification, which could help assess confidence in a drug throughout the development process. EARLY VALIDATION OF TARGETS Gandy discussed how early validation of targets can accelerate ther- apeutic development using examples from Alzheimer’s disease (AD) and traumatic encephalopathy1 (acute and chronic). One pathological feature shared by these conditions is abnormal extracellular deposits of β- amyloid42.2 In the case of AD, the accumulation of β-amyloid42 or its as- sembly form, oligomeric β-amyloid, begins as early as 15 years prior to symptoms (Rowe et al., 2010). Gandy evaluated β-amyloid42 and oligomeric β-amyloid against a list of criteria for an ideal drug target to determine whether or not they were strong targets for therapeutic development (see Box 4-1). Gandy noted that β-amyloid42 fulfills most of the criteria, with three exceptions: (1) there is ambiguous evidence regarding proven function in pathophysiol- ogy of diseases; (2) it is uniformly distributed throughout the body, which can lead to peripheral side effects when modulated; and (3) a biomarker for monitoring therapeutic efficacy or target modulation is not entirely perfected. However, Gandy noted that even though there is much interest in oligomeric β-amyloid because some experts believe it may be the toxin associated with many degenerative diseases, it is not a well- established drug target, and there are currently limited biomarkers for this peptide (Reitz, 2012). Gandy suggested that the current paradigm of drug development might require change, and that change might best occur via the develop- ment of novel approaches such as timing of the intervention; novel sys- tems for screening drugs; novel approaches to known targets; and development of novel biological antagonists against aggregated proteins. 1 Diffuse disease of the brain that alters brain function or structure (e.g., trauma, tumor, infectious agents, etc.) (NINDS, 2010). 2 β-amyloid42 is a fragment of the amyloid precursor protein with 42 amino acids. There are other β-amyloids that range from 37 to 49 amino acids. 

TARGET VALIDATION 43 BOX 4-1 Properties of an Ideal Drug Target  Disease modifying and/or proven function in the pathophysiology  Highly selective to reduce adverse events  If needed, a three-dimensional structure for the target is available  Target has favorable “biochemical and/or cellular assays for binding and function,” enabling high-throughput screening  Can be validated experimentally for a specified indication; therapeu- tic use might be broadened to additional indications  Genomics and phenotypic screening may add to the understanding of the disease model and predictive validity of potential side effects (e.g., knockout mouse, somatic mutations, etc.)  A mechanistic biomarker exists to monitor efficacy  The use of the target does not infringe on the intellectual property rights of others (no competitors on target, freedom to operate) SOURCE: Adapted from Gashaw et al., 2011. In particular, Gandy’s laboratory is interested in this last strategy for Alzheimer’s disease: the prevention of β-amyloid production at the syn- apse through development of antagonists. Gandy and colleagues studied the generation of β-amyloid in synaptosomes3 in a mouse with the human transgene for APP. When the investigators depolarized the synaptosomes, the depolarization activated secretases that selectively spliced APP into β-amyloid42, but not β-amyloid40 (Kim et al., 2010). That finding propelled them to search for transmitter signaling pathways that mimic depolarization. They found that an agonist for Group II metabotropic glutamate receptor also selectively produced β-amyloid42 in the synaptosomes. Having established the signaling pathway, they then sought to block β-amyloid42 production by pretreatment with a Group II metabotropic glutamate receptor antagonist, which was successful in in- hibiting generation of β-amyloid42 (Kim et al., 2010). Employing this novel strategy led to administration of two different Group II glutamate antagonists in the transgenic mouse. The drug BCI- 838 was found to reduce oligomeric β-amyloid accumulation. Behavior- ally, the drug improved learning and reduced anxiety behaviors. Results also show increased neurogenesis using three different markers of prolif- eration. Gandy raised the question of whether neurogenesis can act as an 3 Synaptosomes are isolated intact nerve terminals. 

44 THERAPEUTIC DEVELOPMENT FOR NERVOUS SYSTEM DISORDERS unconventional biological antagonist of β-amyloid toxicity. He and col- leagues are now testing BCI-838 in Phase I studies. Thus far, they have shown that BCI-838 is well tolerated in healthy controls. The next step is to test the drug in a geriatric population diagnosed with prodromal or mild AD. Gandy and colleagues are also considering the drug for use in tauopathies and TBI. In summary, Gandy suggested that the drug discov- ery paradigm for AD and other diseases could potentially change through the use of novel approaches outlined. A NEED FOR BETTER BIOMARKERS Sperling discussed the utility of biomarkers for AD. Their greatest utility, in her view, is for selecting participants for clinical trials who have target pathology by measuring and predicting disease progression or prognosis and assisting with patient stratification (IOM, 2011). How- ever, the greatest challenge is that there are deficiencies in the number of biomarkers currently available that track and predict therapeutic re- sponse. Two clinical trials of monoclonal antibodies against β-amyloid showed lower β-amyloid with positron emission tomography (PET) amy- loid imaging as the biomarker. The issue was that the antibodies did not improve cognition in these Phase II studies (Ostrowitzki et al., 2012; Rinne et al., 2010). Better biomarkers are needed of synaptic dysfunc- tion, which, according to the β-amyloid hypothesis, occurs much earlier than cognitive decline. Biomarkers of synaptic dysfunction—using new imaging modalities such as task-functional magnetic resonance imaging (fMRI) and resting state (task-free) functional connectivity, or fc-MRI— could be studied along with PET amyloid imaging to determine the bene- fits of anti-β-amyloid therapies. For example, fMRI and PET amyloid imaging were combined to study asymptomatic and minimally impaired older individuals to demonstrate that amyloid pathology was linked to neural dysfunction of the default network in cortical regions implicated in AD (Sperling et al., 2009). Imaging modalities may be better as useful measures of therapeutic response, because cognitive impairment occurs too late in the disease process of AD. However, imaging does not consti- tute a surrogate endpoint, but rather a correlate that is a measurement of biological activity (Fleming and Powers, 2012). Sperling suggested potential solutions for targeting and developing biomarkers for β-amyloid that might also apply to other nervous system disorders: 

TARGET VALIDATION 45  embed multiple biomarkers in Phase I/IIa trials in order to develop pharmacodynamic profiles quickly;  develop synaptic and other biomarkers in humans that can give a functional readout in a short timeframe;  test drugs aimed at upstream processes before irreversible down- stream damage;  find more potent drugs without dose-limiting toxicity; and  use combination therapies and start them before symptoms appear. In the case of psychiatric disorders and Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria, John Krystal, Robert L. McNeil, Jr., professor of translational research and chair of the depart- ment of psychiatry at Yale University School of Medicine, commented there needs to be a willingness to explore subgroups of patients with mechanistic homogeneity. Connecting genetic networks and quantitative traits might build the case for proof-of-concept studies; the studies would be based on quantitative information rather than behavioral readouts and could be tested in specific patient groups. In summary, Chas Bountra, head of the Structural Genomics Consortium and professor of transla- tional medicine at the University of Oxford, noted that unless biomarkers are discovered, the field faces continued high failure rates in Phase IIa clinical trials. At this stage of drug development, the majority of novel compounds fail (Paul et al., 2010). As a result, target validation, or inval- idation, is delayed. PORTFOLIO ASSESSMENT TOOL FOR TARGET VALIDATION AND QUALIFICATION Merchant provided her perspective on factors considered when mak- ing investment decisions in neuroscience portfolios. Merchant began by noting that attrition in drug development is very high in Phase II studies, with an approximate rate of 66 percent. Major causes of failure in Phase II are related to inadequacies in efficacy, safety, the overall strategic plan, and bioavailability and pharmacokinetic properties (Paul et al., 2010). High attrition underscores the need for better target validation and biomarkers to avoid selection of the wrong target, the wrong patient pop- ulation, or the wrong dose. Merchant suggested that target validation is best accomplished in humans, while animal models are important for 

46 THERAPEUTIC DEVELOPMENT FOR NERVOUS SYSTEM DISORDERS target qualification, which is a step in the process to determine the scien- tific validity and safety of a target (see Figure 4-1). Target Validation There are three major components of target validation using human data: tissue expression, genetics, and clinical experience. For each of the- se components, several metrics might guide decisions to invest in a par- ticular therapy (see Figure 4-1). Merchant identified specific metrics that might apply in ascending order of priority (see Table 4-1). Merchant noted that each step toward target validation provides an increasing level of importance on how to interpret data and build con- fidence in what projects to bring forward. All the components—tissue expression, genetics, and clinical experience—can inform disease pathways. It is an iterative learning problem. How can what is learned from tissue expression integrate with genetics and integrate with the clinic? Increasing Importance Clinical Translational experience endpoints Genetically Genetics engineered models Tissue expression Pharmacology Human Data Preclinical Data Target Validation Target Qualification FIGURE 4-1 Major components of target validation and qualification. SOURCE: Merchant presentation and Lilly Research Laboratories, April 9, 2013. 

TARGET VALIDATION 47 TABLE 4-1 Metrics of Target Validation Components of Metrics Target Validation Increasing Confidence Pharmacology Target protein Target mRNA Target protein is expressed or expression is expression is active in the altered by the altered in desired organ/ disease disease/tissue subregion/cell types Genetically Genetic Polygenic Monogenic Engineered association with association with association with Models disease occurs modest effect large effect size in small, under- size and known and known powered, or function of the function of gene non-replicated variant, or variant Increasing Importance studies without association with knowing the common, low- function of the risk variant in a variant gene that also has rare variant associated with large effect size, or in the best case Translational Clinically Clinically At least one Endpoints relevant effica- relevant effica- ligand with an cy observed in cy is observed analogous mode a small trial, but with at least one of action on the knowledge of ligand with a target/target engagement of different mode pathway has specific target/ of target modu- “approvable” pathway is lation or with efficacy in the lacking two ligands on indication of biomarkers pre- interest and viously shown robust evidence to predict of target efficacy engagement NOTE: mRNA = messenger ribonucleic acid. SOURCE: Merchant presentation, April 9, 2013. 

48 THERAPEUTIC DEVELOPMENT FOR NERVOUS SYSTEM DISORDERS Target Qualification Target qualification consists of evaluating a target to ensure that it has a clear role in the disease process (Cambridge Healthtech Institute, 2013). Three major components of target qualification in preclinical data, according to Merchant, are pharmacology, genetically engineered mod- els, and translational endpoints (see Figure 4-1). For each component, Merchant specified metrics that could be used to guide decisions and in what order of priority (see Table 4-2). Merchant concluded by saying that the outlined metrics and compo- nents could be used as a portfolio management tool for target assessment. Merchant also emphasized the need for researchers to conduct molecular phenotyping of disorders in order to create molecularly defined disease states and not simply syndromes. During the discussion, a participant asked how researchers can know, definitively, when a target is invalidat- ed. Merchant suggested examining target engagement in clinical trials within the targeted population. Several participants noted that it is possible to move directly into clinical trials for highly validated targets. However, Krystal said researchers cannot go directly into the patient population without knowing whether the biology of the animal models applies to healthy humans. The drug development process is exploratory; it is an iterative process of testing specific mechanistic hypotheses across cellular and animal studies, healthy human subjects, and clinical trials. A participant asked if going into first-in-human trials would be an appropriate risk– benefit decision for serious conditions with short life expectancies such as amyotrophic lateral sclerosis. Merchant agreed that it would be ap- propriate and said that is the case for oncology drugs in which researchers and companies go to first-in-human trials in patients with clear biomarkers. Target validation is a multilayered step in drug de- velopment that is critical to the success of a drug. Validated targets and biomarkers, along with assessment tools, are needed to ensure that the drug is actively engaging the target to produce an expected therapeutic effect. 

TARGET VALIDATION 49 TABLE 4-2 Metrics of Target Qualification Components of Metrics Target Qualification Increasing Confidence Pharmacology A pharmacolog- Ligands with Ligands with ical tool (e.g., a the intended intended mode small molecule, mode of action of action modu- antibody, or modulate late disease- peptide) modu- disease- associated lates disease associated pathway in vivo associated with pathway ex and target pathway in vitro vivo or in engagement– or in heterolo- native tissue, or activity gous cell lines in the best case relationships at appropriate are established concentrations Increasing Importance Genetically Genetic modu- Genetic modu- Human patho- Engineered lation in a non- lation in a genic mutation Models mammalian rodent/non- of the target in a model organism human primate rodent/primate produces produces mimics disease disease- or disease-relevant pathway and/or treatment- endophenotype genetic modula- relevant tion of the tar- phenotype get mitigates the same Translational Target or PK/PD PK/PD Endpoints pathology is relationship and relationship and known and margin of margin of safety demonstration safety are are established of target phar- established using a macology iden- using a translational tical to human translational biomarker native tissue biomarker of historically assays target associated with engagement/ clinical efficacy modulation NOTE: PK/PD = pharmacokinetic/pharmacodynamic. SOURCE: Merchant presentation, April 9, 2013.