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  • 1. 647© 2013 David G. Wild. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/B978-0-08-097037-0.00054-3 Ligand binding assays (LBAs), which include immunoas- says (IAs), are used throughout the development of phar- maceuticals. LBAs depend on the intrinsic high affinity and specific interaction between an “analyte of interest” and a bio-macromolecule. These bio-macromolecules include antibodies, carrier proteins, and receptors. Hence, IAs are a subset of protein LBAs. Pharmaceutical develop- ment is commonly broken in distinct stages, from discov- ery to post-marketing support, and schematically shown in Fig. 1. While scientific rigor is always required, the degree of regulatory oversight depends on how the data are going to be used. Regulated bioanalysis is typically defined as data that is intended for submission to regulatory agen- cies in support of the safety and/or efficacy of a therapeu- tic agent. While much has been written on regulated bioanalysis, less has been focused on how LBAs are used as a basic tool to understand the mechanisms of action (MOA). This is the basis for the first section of this chap- ter. It discusses how LBAs are used in the discovery of new therapeutics. Most therapeutics require a binding to a target that imparts its activity. Therefore, in its simplest form, binding is the basis of both the design of therapeu- tics and of high-throughput screening (HTS). In HTS the binding of a molecule to an isolated receptor tells only a part of the story, in that a potential therapeutic must be able to be delivered to the site of activity in a whole organism. This leads to another way where LBAs are used in early discovery: the estimation of the pharma- cokinetics (PK) of potential therapeutics. In a sense, PK measurements are a surrogate for estimating potential pharmacodynamics (PD). This leads into the next section where LBAs in support of preclinical development is discussed. These are the reg- ulated animal studies used to elucidate a safety profile and establish initial clinical doses. We then discuss LBAs in clinical development, focusing primarily on the assessment of PK of the therapeutic in the target population, assessing immunogenicity and pos- sible efficacy biomarkers. For these, LBA regulatory over- sight is aligned with good laboratory practice (GLP) regulations, which are officially applied to preclinical safety assessments. While not legally mandated, GLPs are used to guide clinical assay application and sometimes referred to as “GLP-like.” In the clinical section, we dis- cuss how clinical development of a therapeutic is an exten- sion of the work done preclinically. We highlight how clinical assays differ from methods used in earlier animal models. The final section of this chapter discusses the role of LBAs in the clinical lab during therapeutic development. These tests typically are not specific to a therapeutic agent. Ligand Binding Assays in Drug Development Jeffrey M. Sailstad (sailstad@aol.com) Ronald R. Bowsher Omar F. Laterza William Nowatzke C H A P T E R 8.2 FIGURE 1 Drug and biologic research and development continuum. (The color version of this figure may be viewed at www.immunoassayhandbook.com).
  • 2. 648 The Immunoassay Handbook These methods are applied in panels to assess the impact of the therapeutic on overall biological functions. Since these methods are typically applied based on therapeutic class rather than a specific therapeutic agent, they are gov- erned by Clinical Laboratory Improvement Amendments (CLIA) regulations rather than GLP regulations. Basic Research EARLY PHASE DISCOVERY—IDENTIFYING THE LEAD The identification of new compounds in the pharmaceuti- cal industry is typically done through a process known as high-throughput screening (HTS). The main aim of this process is the identification of compounds that modulate a certain biochemical pathway. Since thousands of different compounds are subjected to this screening, HTS must be highly automated. HTS typically consists of the addition of compounds to microtiter plates in which a biochemical reaction takes place and a detection mechanism is respon- sible for measuring or detecting this event. HTS involves the use of sophisticated liquid-handling robotics, com- puter software, and detection tools. However, the funda- mentalsofthedetectionsystemareultimatelyabiochemical reaction or event that needs to be observed by the end user. One of the most widely used detection methods for the screening of novel therapeutic compounds (small mole- cules) is cell-based assays. In these assays, potential thera- peutic compounds interact with receptors on the surface of the cell and/or intracellular protein targets. This interac- tion ultimately triggers downstream events that result in the generation of molecules that can be measured by differ- ent methods. Although enzyme activity assays are often used, LBAs play an important role in this area as well. Since there are thousands of compounds to be tested, HTS meth- ods must employ rather simple, robust, high-throughput detection methods. One commonly used LBA in HTS is a homogeneous method based on time-resolved fluorescence (TRF) linked to fluorescence resonance energy transfer (FRET). FRET makes use of two fluorophores (donor and acceptor), which are coupled to antigen and/or antibody. The basis of TR-FRET is that when the donor is excited by an energy source (e.g., a laser) it triggers an energy transfer to the acceptor, but only when they are in proximity to each other. In turn, the acceptor emits light at a specific wave- length. Since the energy transfer only occurs when the acceptor and donor are in close proximity with each other, the detection of analyte binding to antibody can be done without the need to separate bound from unbound, which translates into significant cost and time savings during the screening process. See HOMOGENEOUS IMMUNOASSAYS. TRF adds another advantage to the process since the flourophores known as lanthanides, such as samarium (Sm), europium (Eu), terbium (Tb), and dysprosium (Dy), have large Stokes’ shifts and long-emission half-lives when compared to more traditional fluorophores. This is impor- tant since compounds and proteins in biological fluids flu- oresce naturally and can contribute to high background signals. This technology is highly desirable in HTS due to its “mix and read” nature and its compatibility with cell- based assays. Cells may remain intact during the testing until the final detection step. This technology has been employed to assess intracellular messengers such as cAMP, cGMP, and other small molecules or proteins such as histamine, cortisol, aldosterone, PGE2, LTB4, estradiol, glucagon, and T3. TR-FRET assays have the versatility to be used as immunometric (sandwich) or competitive assays. When used in sandwich IAs, the two antibodies are coupled to a donor or an acceptor. The signal intensity is proportional to the number of antibody–antigen complexes. However, when used in competitive assays, the acceptor is generally coupled to purified antigen and the antibody coupled to a donor. The antigen (Ag) present in the sample competes for binding with the labeled antibody (Ab) and thereby prevents FRET from occurring. FRET intensity decreases with the amount of dissociated Ab–Ag complexes (i.e., inversely proportional to Ag concentration). HTS experiments allow the identification of lead com- pounds (lead identification), which is considered the foundation for further development and refining of the chemical or biological entity (lead optimization). Other methods for LBAs used in lead identification and lead optimization include traditional ELISAs with either colorimetric, fluorescence, or chemiluminescence detec- tions. More advanced technologies are those that include electrochemiluminescence detection, even though the sensitivity offered by such technologies is often not needed in the early HTS process. Another technology that is com- monly used for its ease of use is the AlphaLisa® technol- ogy. The acronym “Alpha” stands for Amplified Luminescent Proximity Homogeneous assay. This is a bead-based technology similar to the FRET technology described above, in which capture and detection antibod- ies are coated onto donor or acceptor beads. The donor beads are loaded with a photosensitizer, phthalocyanine, which converts ambient O2 to an excited and reactive form, singlet oxygen, upon excitation at 680nm. The acceptor beads contain thioxene derivatives, which pro- duce light upon excitation with the singlet oxygen mole- cule. This can only occur when the acceptor and donor beads are in proximity, which happens when the ligand– antibody sandwich is formed. These are homogeneous (no-wash) IAs with high sensitivity and wide dynamic ranges. They are used in measuring proteins (secreted, intracellular, or membrane-bound) and other analytes. Since they are simple for the user and easily automated, they are highly desirable in the lead identification and lead optimization spaces. LEAD OPTIMIZATION Compounds that were identified during HTS are moved to the next step in drug development known as Lead Optimization (Fig. 1). During lead optimization, com- pounds are chemically modified further to improve their potency, selectivity, and/or PK properties. This is neces- sary since some of the entities identified in HTS, which engage the target, may not have the ideal properties to eventually become a drug.
  • 3. 649CHAPTER 8.2 Ligand Binding Assays in Drug Development During this process, the most promising candidates are tested in preclinical species in order to better understand their characteristics, more importantly their safety and efficacy. LBAs also play a critical role in obtaining infor- mation about the safety and efficacy of compounds at the preclinical level. Bridging Preclinical to Clinical It is essential to bridge the preclinical data to the clinical data. Biomarkers have been identified as important tools that can improve the efficiency and cost-effectiveness of drug development. This is especially true in early clinical development, where critical decisions are often made on the fate of compounds based on biomarker data. In order to make sound decisions early in the clinical development of a compound, it is essential that these biomarkers are thoroughly studied and understood in preclinical species and that a good bridging strategy between preclinical spe- cies and humans is properly considered. Below are some examples of how biomarkers that were well characterized in preclinical species helped expedite early clinical decisions. Sitagliptin The DPP-4 enzyme is responsible for inactivation of GLP-1, a gut hormone responsible for regulating blood glucose levels. Biomarkers that were carefully character- ized in preclinical species included target engagement bio- markers such as DPP-4 activity, proximal biomarkers such as active and inactive GLP-1 peptides in plasma, and dis- ease-related biomarkers such as glucose. Specifically, pre- clinical experimental studies during the development of Sitagliptin, the first DPP-4 inhibitor approved by the FDA, demonstrated that ∼80% inhibition of DPP-4 activity was associated with maximal lowering of glucose levels. This also correlated with an increase in plasma GLP-1 concentration (Kim et al., 2005). In studies performed in early clinical development, PK/PD modeling revealed that the EC80 of plasma DPP-4 inhibition corresponded to a plasma sitagliptin concentration of approximately 100nM. (The EC80 is the concentration that leads to 80% of the maximal response, also called the ED80 (estimated dose)). It was also determined that a single dose of 100mg provided DPP-4 inhibition (>80%) for 24h (Herman et al., 2006). This allowed the rapid determination of the ideal dose to move to the next steps in clinical development. This was only possible due to the thorough characterization of these biomarkers in preclinical species and the creation of a bridging strategy. Even though the assessment of DPP-4 activity was performed through enzymatic methods, LBA played an important role in the measurement of circulating GLP-1 peptides. Thiazolidinediones A number of chemical entities known as thiazolidinediones (peroxisome proliferator-activated receptor (PPAR) ago- nists) have been developed for the treatment of diabetes. During clinical development, thiazolidinediones lacked a tar- get engagement biomarker that could be used in dose selec- tion. This represented a hindrance in their development. Since the development of the initial thiazolidinediones, such as troglitazone, rosiglitazone, and pioglitazone, the bio- marker adiponectin has been identified (Wagner, 2002). Adi- ponectin, also known as ACRP 30, is a 30kDa protein that is specifically expressed in adipocytes. It is composed of 247 amino acids and has some homology to complement factor C1q. It contains an amino terminal collagenous domain and a C-terminal globular domain. Thiazolidinediones increase the plasma concentration of adiponectin in a dose-dependent manner. Furthermore, recent studies have shown that low levels of adiponectin are linked to insulin sensitivity. Years later, the Biomarkers Consortium, a public– private platform for precompetitive collaboration specific to biomarker research, endorsed adiponectin as a predictor of metabolic responses to PPAR agonists in type 2 diabetics (Wagner, 2009), and adiponectin became a putative target engagement biomarker. Adiponectin was initially measured using a quantitative western blot adapted from a procedure developed in the laboratory of Dr. Philipp Scherer at Albert Einstein Col- lege of Medicine. Years later an ELISA assay became available. This ELISA uses a mouse monoclonal anti- (human) adiponectin capture antibody and a rabbit detec- tion antibody conjugated to horseradish peroxidase. This method also requires a sample denaturation step with SDS followed by a large dilution (approximately 1:5000) prior to addition of the sample to the plate. This method showed a good correlation to the quantitative western blot. In addition to efficacy and target engagement biomark- ers, safety biomarkers also play a critical role in lead opti- mization studies. Safety Biomarkers Safety biomarkers have been used for decades both in preclinical and clinical research. Since these tests have become mainstream tests, they have been fully automated for both animal and human testing. Among the most com- mon safety tests are those for liver function (e.g., transami- nases, bilirubin, alkaline phosphatase) and kidney function (e.g., serum creatinine, creatinine clearance, cystatin C). Others include markers of skeletal muscle (e.g., myoglo- bin) or cardiac muscle injury (e.g., CK-MB, troponin I), as well as bone biomarkers (e.g., bone-specific alkaline phos- phatase). Some of these markers are based on enzyme activity but there has been an increasing number of LBAs over the last few years. Examples of LBAs used in assessing safety in preclinical studies include cystatin C (kidney), troponin I (heart), and skeletal troponin I, myoglobin (skeletal muscle). There is also an effort to identify novel biomarkers of tissue injury. A good example of this is the FDA/EMA qualification process of nephrotoxicity biomarkers pro- posed and studied by the Predictive Safety Testing Con- sortium (PSTC, 2010). Twenty-three biomarkers of kidney toxicity were reviewed and ultimately seven bio- markers (albumin, β2-microgobulin, clusterin, cystatin C, KIM-1, TFF3, and total urinary protein) were selected as qualified biomarkers for nonclinical nephrotoxicity. It was also concluded that the use of these biomarkers in clinical trials should be considered on a case-by-case basis.
  • 4. 650 The Immunoassay Handbook Assay Validation: Fit for the Purpose of Discovery Biomarker method validation is the assessment of the assay’s performance characteristics. It is well accepted that method validation should be performed on a fit-for-purpose basis (Lee et al., 2006). This means that the performance charac- teristics of a specific method need to be reliable for the intended application. Ultimately, the purpose of the assays dictates the rigor or level of validation that is applied to a specific assay. There are currently no regulatory guidelines for the use of LBAs in the discovery space. Furthermore, and perhaps surprisingly, there is no clear regulatory guidance on assay validation requirements for biomarker assay validation in clinical use. As we know, clinical application of biomarker assays is governed by GCP. However, CGP is vague with respect to analytical validation. Therefore, there are two competing approaches for method validation. These include CLIA/CLSI (clinical chemistry approach) or GLP (drug assay approach). There is FDA guidance on bioanalytical method validation (BMV) for the pharmaceutical industry. However, this guidance is ill suited for biomarkers since it focuses on the validation of assays for small molecule drugs. It is imaginable that the same fit-for-purpose principles that are applied to clinical assays could be applied to LBAs that are used in the discovery space. Keeping in mind that the purpose of discovery assays is to identify new chemical entities that engage a target with high affinity and specific- ity, efforts will likely be focused on building specific and robust assays. It is important to build assays that recognize target engagement in a specific way and demonstrate that the method is reliable over a period of days and months, since thousands or millions of compounds need to be screened. These assays tend to be more qualitative in nature and less emphasis is placed on the true quantitation of the analyte. Quality control in the HTS process also plays an important role in ensuring acceptable perfor- mance of the assay in a given run. Application of LBAs in Nonclinical Drug Development LBA technology, principally immunoassay, is used exten- sively to support the nonclinical phase of drug development for both conventional small molecular weight drugs and biotherapeutics. Bioanalytical applications in which LBAs are used include assays to quantify the drug of interest for supporting PK and toxicokinetic (TK) assessments, quan- titative determination of biomarkers, and in immunogenic- ity testing for the detection and characterization of antidrug antibodies (ADAs) (Table 1). Nonclinical drug development is comprised of activities that occur largely during Late Phase Discovery (Lead optimization) and the initial stage in devel- opment, Nonclinical Development (ADME and Toxicology) and involves a combination of safety and efficacy testing and ADME evaluation in animals and animal models (Fig. 1). Lead optimization occurs in late phase discovery and typically involves evaluation of a series of drug candidates to identify a lead molecule for entry into the development phase where it undergoes extensive ADME and toxicologi- cal evaluation (Fig. 1). Even though new innovative small molecule xenobiotic drug candidates and biotherapeutics share a common developmental pathway that culminates in submission of a New Drug Application (NDA) or Bio- logics License Application (BLA) followed by regulatory drug approval, the constellation of activities carried out during nonclinical development typically differs due to inherent differences in their molecular properties and drug disposition (Findlay et al., 2000). The Lead Optimization and Nonclinical Development (toxi- cological evaluation) stages differ in several important ways with respect to their bioanalytical expectations. Chief among these are differences in the accepted industry requirements for establishing and documenting analytical performance. Even though Lead Optimization is an important early devel- opmental activity, data from this stage are usually used for internal bioanalytical-based decision making and not sub- mitted to regulatory agencies. Consequently, formal require- ments that govern pre-study BMV and the conduct of in-study assays for quantification of the drug of interest do not apply and the level of BMV is left to the discretion of the company. In contrast, drug bioanalysis that is intended to support TK assessments of a biotherapeutic must comply with established requirements for various global regulatory agencies (i.e., FDA, EMEA, OECD, and ICH) to represent suitable pre-study and in-study BMV data to support drug submission. The terms validated and non-validated (some- times termed qualified) are commonly used to signify the extent of performance evaluation that a method has under- gone and that an assay has met a priori criteria for acceptable pre-study analytical method performance. Caution should be exercised in judging the acceptability of study data that were generated by a “validated” assay without first reviewing the scope and results of the pre-study BMV. Method valida- tion does vary from laboratory to laboratory and not all vali- dated methods necessarily meet regulatory expectations to be adequate for supporting GLP-compliant bioanalysis dur- ing the nonclinical stage of drug development for biothera- peutics. These criteria are specified in a number of regulatory guidance documents and industry white papers (DeSilva et al., 2003; EMEA, 2012; Findlay et al., 2000; Miller et al., 2001; Shah et al., 1992; US FDA, 2001; Viswanathan et al., 2007). The Lead Optimization phase has no formal regula- tory requirements for analytical method performance, whereas assays to document drug exposure during toxico- logical evaluations are required to undergo extensive BMV in order to be GLP compliant for meeting expectations for regulated bioanalysis. While the components of BMV are TABLE 1 Application of LBAs in Drug Development Type of Drug Candidate PK/TK Biomarker Immunoge- nicity Small molecule drug Seldom Yes, often Rarely Biotherapeutic Yes, methodology of choice Yes, often Yes, methodology of choice
  • 5. 651CHAPTER 8.2 Ligand Binding Assays in Drug Development generally agreed upon, a harmonized common global stan- dardized process does not exist (GBC, 2011). Consequently, subtle differences in recommendations and requirements are known to exist across different documents. Nonetheless, there are a number of key publications that have been pub- lished over the past one to two decades that make specific BMV recommendations for LBAs that are intended for measuring drug concentrations to support PK/TK assess- ments (DeSilva et al., 2003; EMEA, 2012; Findlay et al., 2000; Miller et al., 2001; Shah et al., 1992; US FDA, 2001; Viswanathan et al., 2007). Table 2 summarizes some analyti- cal performance characteristics and their target acceptance criteria that are commonly included in the BMV of LBAs. Finally it is worth emphasizing that in the USA, the BMV process for bioanalytical assays used to support drug devel- opment adheres to GLP guidelines (EMEA, 2012; Shah et al., 1992; US FDA, 2001; Viswanathan et al., 2007), whereas assays used to support diagnosis and treatment of disease are regulated by different guidelines that are pub- lished by NCCLS/CLSI (Lightfoote et al., 2008). Notable differences between these method validation approaches are exemplified by the analytical performance characteristic of sensitivity. Whereas the CLSI approach for establishment of assay sensitivity involves determination of the limit of detec- tion (LOD) and/or a limit of quantitation (LOQ), GLP bio- analysis requires establishment of lower (LLOQ) and upper (ULOQ) limits of quantitation. For both philosophical approaches, assay sensitivity is determined empirically dur- ing method validation. It is worth pointing out that, in GLP bioanalysis, the range of analyte concentrations between the LLOQ and ULOQ defines the calibration curve’s validated range for interpolation of responses for study samples. LBAs FOR SUPPORT OF DRUG PKs AND TKs As traditional low-molecular weight drugs and macromol- ecules differ markedly in terms of their molecular proper- ties (Table 3), it should not be too surprising that different technologies are commonly used to support their bioanalysis. Today the most widely used technology for conducting regulated bioanalysis of conventional drugs is modern liq- uid chromatography–mass spectrometric methodology (e.g., LC-MS and LC-MS/MS). Because of advancements in instrumentation the analytical capabilities of LC-MS has continued to evolve with the technology now being ever more broadly applied in drug bioanalysis, including peptide-based therapeutics. In contrast, LBAs still repre- sent the principal technology for conducting regulated bioanalysis of macromolecules and biotherapeutics. LBAs possess the following attributes that make them well suited for bioanalysis of biotherapeutics. These include good sensitivity, often in the pM range, a requirement for mini- mal sample cleanup (e.g., often only sample dilution), batch analysis, high sample throughput, relatively inex- pensive instrumentation vis-à-vis LC-MS, and well suited for quantitative determination of macromolecules. Differ- ences in the analytical characteristics between LC-MS and LBAs are summarized in Table 4. Both competitive (e.g., RIA) and immunometric/non- competitive (e.g., sandwich ELISA) LBA formats are used to support regulated bioanalysis of biotherapeutics, the TABLE 2 Analytical Performance Characteristics Specificity and selectivity Matrix selection, sample preparation, and minimum required dilution (MRD) Calibration model assessment Precision and accuracy Range of quantification (LLOQ/ULOQ) Sample stability Dilutional linearity Parallelism Robustness and ruggedness TABLE 3 Molecular Properties of Small Molecular Drugs vs. Macromolecules Characteristics Small Molecular Drugs Macromolecules Size Small (<1000Da) Large (>5000Da) Structure Organic molecules Biopolymers Purity Homogeneous Heterogeneous Solubility Often hydrophobic Often hydrophilic Stability Chemical Chemical, physical, and biological Presence in matrix Xenobiotic (foreign) Endogenous Synthesis Organic synthesis Produced biologically Catabolism Defined Not well defined Serum binding Albumin (low affinity/high capacity) Specific carrier proteins (high affinity/low capacity) TABLE 4 Analytical Characteristics of LC-MS and LBAs Characteristics LC-MS Assays LBAs Basis of measure Physical properties Analyte binding Detection method Direct Indirect Analytical reagents Widely available Unique, not available Analyses Small molecules Small+macromol- ecules Sample cleanup Yes Usually No Internal standard Yes No Calibration model Linear Nonlinear Calibration variance Homoscedasticity Heteroscedasticity Assay range Usually broad Limited (2 logs) Assay environment Contains organic Aqueous (pH 6–8) Development time Weeks Months (Ab prep) Imprecision (%CV) Low Moderate Imprecision source lntra-batch Inter-batch Analysis mode Series, batch Batch
  • 6. 652 The Immunoassay Handbook predominant one being the immunometric format since it is well suited for quantifying monoclonal antibodies and other diverse biotherapeutics. LBA methodology used to support regulated bioanalysis during the nonclinical phase of drug development is basically the same, in terms of design, as the methodology used for clinical phase bioanal- ysis. However, the nonclinical phase of drug development poses some unique bioanalytical challenges that warrant additional discussion. These include: 1. A frequent limitation in sample volume 2. The presence of endogenous equivalents in test samples 3. Sequence differences across different species 4. The occurrence of a wide range of plasma drug con- centrations in TK studies 5. The production of ADAs following repeated admin- istration of a human biotherapeutic. As rodents, such as mice and rats, are used commonly for conducting toxicological assessments of candidate drugs, limitations in their blood volume (mice about 1.5mL and rats about 15–20mL) are often a challenge for study design to permit elucidation of a drug’s PK/TK profile. Conse- quently, a strategy involving sparse sampling in which the TK profile is defined by pooling plasma concentration data from across multiple animals is used often to support nonclinical studies. The issue of the availability of a small sample volume demands that LBAs intended to support nonclinical PK/TK possess high analytical sensitivity. Even though some biotherapeutics, such as human mono- clonal antibodies, are dosed often at high concentrations (e.g., often >10mg/kg), high analytical sensitivity (i.e., 1–10pM or less) is desirable to allow accurate character- ization of the drug’s terminal elimination phase. To accomplish this objective, LBAs to support regulated bio- analysis are often designed to employ highly sensitive detection systems, such as fluorescence, chemilumines- cence, and radioactivity (i.e., 125I), as an alternative to basic colorimetric ELISAs (i.e., horseradish peroxidase and alkaline phosphatase). The second issue that impacts the application of LBAs in regulated bioanalysis, the presence of endogenous equivalents in test samples, is not an analytical issue but rather a characteristic of biotherapeutic drugs. While most small molecule drugs are xenobiotic (i.e., foreign and not found endogenously), biotherapeutics are often either endogenous or are constructed to possess naturally occurring domains. Thus unlike in the bioanalysis of small molecules, assays for biotherapeutics are frequently characterized by a “background” level present in a test sample. This issue poses a challenge for pre-study BMV in several ways. First, it complicates the preparation of matrix-based standards (calibrators) and validation (QC) samples. Second, it hinders the assessment of establishing the assay’s LLOQ. Lastly, during test sample analysis, this issue presents a challenge for matrix-based dilutions of test samples when their respective concentrations exceed the assay’s ULOQ. Various strategies have been proposed to address the issue surrounding quantitative determination of “endogenous” analytes (Findlay et al., 2000). However, at this time there is not a consensus on the standardized approach to address this common issue for biotherapeutics, and the issue is addressed on a case- by-case manner. A third issue that impacts the application of LBAs for bioanalysis in the nonclinical phase of drug development is species differences between the human biotherapeutic and the species’ endogenous equivalent protein/peptide. While this potential concern is mitigated somewhat by the fact that nonclinical TK studies typically involve adminis- tration of high levels of a human biotherapeutic, the issue can be evident in pre-dose samples and after administra- tion of low doses. Sequence difference(s) between the human biotherapeutic and endogenous equivalent can often complicate pre-study BMV, as these entities display altered reactivity with the reagent antibodies. This issue results in an assay bias and in some cases a lack of parallel- ism and can complicate achieving the pre-defined a priori criteria for method acceptance. It should be pointed out that this potential issue is particularly problematic for assays designed to quantify endogenous biomarkers. Accordingly if the reference standard lacks complete homology with the endogenous biomarker(s), an analyti- cal bias can often be observed during BMV. In such cases where the endogenous analyte and reference calibrator lack complete homology, the resulting LBA can be regarded as providing “relative quantitative” results (Lee et al., 2006). The fourth issue that is somewhat unique to LBAs dur- ing nonclinical testing is the wide range of plasma analyte concentrations that are encountered during bioanalysis of test samples. What makes this issue unique in relation to small molecule bioanalysis by LC-MS is the fact that LBAs have a nonlinear standard curve concentration–response relationship which is typically sigmoidal in nature when the assay’s response is plotted versus the log of the stan- dard (calibrator) concentrations (Findlay et al., 2000; Findlay and Dillard, 2007). Thus, unlike chromato- graphic-based assays that can be engineered to possess a broad validated range for quantification of an analyte(s), LBAs are usually restricted to a useable quantitative range of about 2–3logs. Thus, LBAs must rely on test sample dilution as a means for quantifying analyte concentrations that are present at high concentrations (i.e., >ULOQ). Consequently, the analytical lab must ensure that accept- able dilutions are employed to result in analyte concentra- tions that fall within the assay’s standard curve validated range. In addition, the pre-study validation needs to include an assessment of an ample number of freeze-thaw cycles or has a defined process for reporting test sample results when multiple values are obtained within a single analytical run. The fifth issue that often impacts the application of LBAs during nonclinical testing is the generation of host ADAs following repeated administration of a human bio- therapeutic. Unlike LC-MS assays, LBAs are often con- ducted with little to no treatment of the test sample matrix. While this attribute is appealing from the perspec- tive of reducing the overall amount of work and facilitat- ing sample analysis, it does make LBAs prone to interference from the test sample matrix (Findlay et al., 2000; Kricka, 1999; Findlay, 2008). ADAs are a specific example of an interfering substance (Shankar et al., 2007; Ponce et al., 2009) that is common to nonclinical studies
  • 7. 653CHAPTER 8.2 Ligand Binding Assays in Drug Development of human proteins/peptides. Depending on the assay design, ADA can either result in false-negative or false- positive values. The determination of ADA in TK studies involving biotherapeutics is important to ensure that the Tox species is exposed adequately to the investigational drug (US FDA, 2009). Thus, regulatory agencies require that samples from Tox studies be screened for the pres- ence of ADA (EMEA, 2007; US FDA, 2009). Over the past decade a number of key white papers (Mire-Sluis et al., 2004; Shankar et al., 2008) and guidance documents (EMEA, 2007; US FDA 2009) have been published regarding immunogenicity testing for biotherapeutics. This has led to a standardized approach for ADA testing that involves sequential steps for screening (detection), confirmation (usually competitive inhibition), and titer assessment (quantitative reporting). The standardized process for immunogenicity testing is depicted in Fig. 2. Clinical Phase An integral component of clinical development is the application of appropriate bioanalytical tests. Clinical tri- als are defined as research studies conducted in volunteer participants and are designed to answer specific questions about the safety and/or effectiveness of drugs, vaccines, biologics, and other therapies or new ways of using exist- ing treatments. For most biologics, emerging as a result of the recombinant technologies, LBAs have been an integral part of their discovery and preclinical development. This reliance on LBAs continues throughout clinical development. Clinical development involves three phases: Phase 1 tri- als usually take place in healthy volunteers and assess the safety and dosing of the therapeutic. Phase 2 trials are used to get an initial reading of efficacy and further explore safety in small numbers of patients with the condition that the therapeutic is intended to treat. Phase 3 trials are often large-scale pivotal trials to determine safety and efficacy in sufficiently large numbers of patients. There are occasions when altering the phases of clinical development can enhance a study for ethical or scientific reasons without changing the integrity or validity of the trials. Often with biologics, the proposed mechanism of action is sufficiently understood in relation to a specific patient population. This results in an alteration to the conventional design of Phase 1. The potential therapeutic is administered directly to patients rather than healthy volunteers. These are commonly referred to as Phase 1–2 trials. One such scenario where a Phase 1–2 trials would be appropriate would be if the initial exposure to the therapeutic is expected to have unfavorable side effects but the potential good for the patient outweighs the side effects. Traditionally, cytotoxic chemotherapeu- tic antitumor agents have been initially tested directly in patients. While this example would be an ethical consid- eration there are also times when it makes scientific sense to combine Phase 1 and Phase 2 testing. Such is the case when the potential therapeutic modulates the biological systems that are out of sync or different than those pres- ent in healthy volunteers. An example of this would be a treatment that targets a deficiency. In this instance the administration of an agent to healthy volunteers might produce toxicity by putting a system out of homeostasis. If a potential therapeutic was predicted to, or had the potential to, produce side effects or toxicity in healthy volunteers, but positive results in patients with a known condition, it makes sense to combine Phase 1 and Phase 2 testing. Both PKs and PDs are routinely monitored in clinical trials using LBAs. This is a natural extension of the testing done during preclinical development. Methods developed for clinical use in drug development have unique chal- lenges, the amounts (doses) of the agent administered are escalated, beginning with small amounts that are typically assumed to be sub-therapeutic. This is to protect the clini- cal volunteer or patient as the dose increases through sub- sequent rounds. Side effects are monitored and the dose is raised incrementally to what is expected to be therapeutic levels. The challenge for the bioanalytical scientist is to have a method sensitive enough to monitor the drug levels during the initial low doses. PK profiles, namely the relationship of drug concentra- tion to the time of dosing, are pivotal. Specifically, this information, when assessed across a patient population, is used to assign dosing routines. The PK understanding goes on to be the foundation of the package insert content that directs physicians when and how to administer the drug. FIGURE 2 Tiered immunogenicity testing. (The color version of this figure may be viewed at www.immunoassayhandbook.com).
  • 8. 654 The Immunoassay Handbook Traditionally, efficacy for new therapeutics was mea- sured by overtly observable clinical end points. Some of the examples include tumor reduction, lower blood pres- sure, and even patient survival. While such end points still play an important role, alternative clinical end points pro- vided by bioanalytical methods are gaining regulatory acceptance. This is assuming that the measured biomark- ers (PD biomarkers) correlate with efficacy. The emerg- ing reliance on such biomarkers shows a natural progression in how new biologics are discovered, namely by understanding the biological pathways and altering those pathways. Downstream biological changes are mon- itored by changes to biomolecule concentrations mea- sured by LBAs. Much has been written about how biomarkers are used throughout the drug development continuum. It has been recognized that what is required to validate such diverse applications should be considered fit- for-purpose (Lee et al., 2006). Validation for a biomarker, which is the basis of an efficacy claim, would be more extensive than what might be done in assessing a number of potential downstream biomarkers earlier in the biolog- ics development. Clinical immunogenicity testing is another natural extension of the methods used during preclinical testing. As a class, clinical immunogenicity tests are referred to as anti-drug antibody (ADA) or anti-therapeutic antibody (ATA) methods. As with PK testing, the need for enhanced sensitivity is expected by regulatory agencies. When admin- istering a biologic intended for humans to animals it will most likely elicit a robust immune response. The desire of most biologics is to show efficacy without eliciting a robust immune response. Hence there is a need for more sensitiv- ity in clinical immunogenicity testing. Most biologics, even those considered fully humanized, elicit various degrees of immune response. The paradigm of tiered immunogenicity testing has become well established over the past 10 years and well described in a number of white papers (Mire-Sluis et al., 2004; Shankar et al., 2008) as well as regulatory guidances (EMEA, 2007; US FDA, 2009). This leads to another application of LBAs, specifically used to assign the ability of antibodies to neutralize the activity of the therapeutics. As a group these are called neutralizing antibody (NAb) assays. There are many types of NAb assays, traditionally they are cell-based assays, based on the assay used to assign the potency of a biologic, and these have been favored by the regulators at the FDA. This is because the potency assay has to be related to the projected activity of the bio- logic. Using such cell-based assays the ability of ADA to mitigate the activity of the therapeutic can be assessed. Yet NAb assays based on platforms other than cell-based assays are sometimes acceptable and might even be pre- ferred. This again returns to the ever-improving under- standing of the biological basis of the therapeutics activity. For example, if a biologic’s activity depends solely on the binding of the agent to a receptor, measuring the ability of an antibody to block that binding may be the basis of a highly relevant NAb assay. Assuming downstream bio- markers are being accepted as an indication of clinical effi- cacy, the lack of, or the appearance of, diminished efficacy in patients without or with ADAs can be asserted to assess neutralization. As clearly seen across many therapeutic classes, the appearance of even high levels (measured as titers) of antibodies does not necessarily equate dimin- ished activity. While ADAs may not directly interfere with a drug’s clinical activity, they can alter the PKs of the drug, enhancing clearance as well as prolonging exposure (both have been seen). It is for this reason that PK results are reviewed in relation to immunogenicity results. PK, PD, and immunogenicity results that all might have been LBA based can be pivotal in understanding and predicting clinical responses. CLINICAL LABORATORY Traditionally, the clinical laboratory has been utilized in support of clinical trials for diagnostic purposes to: G Identify subject participant eligibility (inclusion/exclu- sion criteria), G Evaluate drug safety and organ tolerability upon expo- sure to a novel therapeutic. Additionally, methods may be used in support of preclini- cal studies to measure analytes that are species indepen- dent (e.g., glucose, cholesterol, electrolytes). Often, the clinical laboratory is located at the investiga- tional site (Phase I) or within the vicinity or same town. For late phase, multicenter studies, samples may be pro- cessed at the investigator sites and sent frozen to central laboratories for analysis. Testing usually includes chemis- tries (electrolytes, albumin, liver function tests, etc.), com- plete blood counts, coagulation status, and urinalysis. Additional sub-disciplines include toxicology, drugs of abuse, therapeutic drug monitoring, and molecular diag- nostic testing. Clinical chemistry analyzers are routinely operated by a single medical technologist, processing many hundreds of samples per hour in a random-access fashion. Analyzers may operate uninterrupted except for performing routine maintenance. Redundancy is critical in the event that an instrument malfunction occurs. To ensure site-to-site consistency within and between studies, laboratories often exchange test samples to demonstrate harmonization. Blinded sample evaluation is performed formally on an annual basis utilizing a process called proficiency testing. Because the analyzers and the reagents used to support analysis are regulated as medical devices (21 CFR Part 820) or in vitro diagnostic devices, the systems, when uti- lized for diagnostic testing and reporting patient results, are restricted for use without modification. The impact is that laboratories may not modify methods (e.g., include additional calibration curve points, decrease sample dilu- tion to enhance sensitivity, etc.) or add novel biomarkers to the test menu. However, a wide variety of platforms are available that utilize a diverse range of technologies, allow- ing the measurement of most analytes of interest (Table 5). There are limited cases where systems are available that allow esoteric biomarker analysis, either through the use of third-party reagent suppliers or the in-house development of Laboratory-Developed Tests (LTDs). LTDs are reg- ulated for diagnostic testing through the Clinical Labora- tory Improvement Amendments of 1988 (CLIA). Furthermore, the reagents used in these methods are termed analyte-specific reagents (ASRs) and are considered
  • 9. 655CHAPTER 8.2 Ligand Binding Assays in Drug Development restricted medical devices. Some of the advantages of using random-access clinical chemistry analyzers are highlighted in Table 6. LBA LABORATORY In contrast, LBA laboratories supporting drug development programs typically operate in an FTE (full-time equivalents) heavy mode. Essentially all sample and reagent manipula- tions are performed in a modular fashion employing pipettes, shakers, incubators, wash stations, and instruments designed to detect various signals (RIA, electrochemiluminescence, UV/VIS, fluorescence, etc). Efficiency may be gained by using automation, ranging from liquid handling in the prep- aration of calibrators and diluting samples to complete walk- away workstations. However, due to the unique nature of many of the analytes measured—a traditional ELISA method may have >400,000 permutations—the system must be flexible with respect to assay method conditions and an experienced programmer must oversee the system. Labora- tories are not formally certified as competent to generate bioanalytical data and regulation occurs primarily through the threat of data rejection based upon FDA study and site inspections. Laboratories absorb the burden of generating, selecting, characterizing, and maintaining critical reagents to support biopharmaceutical PK and ADA programs. Occasionally commercial antibodies are available for mar- keted products, and this practice may increase as biosimilar products replace the original innovator therapeutics. Com- mercial assay kits may be purchased for the measurement of biomarkers. Except for routine diagnostic markers, all com- mercial assay kits are sold for research use only (RUO). In vitro diagnostic kits may be purchased by GxP laboratories; TABLE 5 Clinical Diagnostic Bioanalytical Methodologies Methodology Platform Example Analytes Immunoturbidimet- ric, turbidimetric, nephelometry Chemistry analyzer Immunoglobulins Electrode Chemistry analyzer Sodium, potassium, chloride Activity Chemistry analyzers Liver function tests (ALT, AST, GGT, etc.) Enzyme-multiplied immunoassay technique (EMIT) Chemistry analyzer Therapeutic drug monitoring/Drugs of abuse Fluorescence polarization immunoassay (FPIA) Chemistry analyzer Therapeutic drug monitoring/drugs of abuse GC-MS Chromatography/ mass spectrometry Ethanol LC-MS/MS Chromatography/ mass spectrometry Neurotransmitters Radioimmunoassay Gamma counter Hormones Cloned enzyme donor immunoassay (CEDIA) Chemistry analyzer Therapeutic drug monitoring/drugs of abuse Substrate-labeled fluorescence immunoassay Chemistry analyzer Therapeutic drug monitoring/drugs of abuse Fluorescence resonance excitation transfer (FRET) immunoassay Chemistry analyzer Allergens, Class I MHC molecules, Fluorescence correlation spectroscopy (FCS) immunoassay Chemistry analyzer Cytokines Array immunoana- lyzers Proprietary analyzers (Randox, Affymetrics, SQI, etc.) Molecular diagnostics, proteins, immuno- globulins, etc. Flow cytometry Chemistry analyzers Cytokines, proteins, etc. TABLE 6 Advantages and Disadvantages when Utilizing Clinical Diagnostic Assays to Support Drug Development Programs Parameter Advantage Disadvantage Analyte menu High throughput, on-board detection of hemolyzed, lipemic and icteric samples Closed system, expensive instru- mentation required Sample throughput 100s/h Method validation Performed by vendor according to CLSI standards May not meet BMV regulatory guidance requirements Reagent control Regulated Laboratory-defined tests (LDTs) regulations not always clear Measurement performance Excellent. Verified by PMA or 510k Specific for the diagnostic community Cost Reagents are comparable to LBA Additional overhead is a factor Lot–lot consistency GMP reagent manufacturing and proficiency testing Differences still remain between vendors, and other factors continue to contribute to variability (e.g., analysts, laboratory temperature) Study-to-study consistency Excellent. Profi- ciency testing and use of common reference standards when available Analysts Specific degrees are granted (medical technologist) Fewer FTEs More cost Lab space Analyzers may require more room and retrofitting for plumbing Regulations Certification and inspections required May not meet 21 CFR Part 58 GLP Regulations Technical support Excellent
  • 10. 656 The Immunoassay Handbook however, lacking CLIA certification, the data generated from these kits may not be utilized for patient care. Because Clinical Diagnostic kits have regulatory oversight and are often manufactured to a higher quality standard, they are desirable to use in support of drug development programs (Nowatzke et al., 2010). It is recommended that a fit-for- purpose approach be used to further validate IVD kits to address the intended use of the data. Although guided by different regulatory practices, clinical analyzers and LBA methods support similar bio- analytical needs in diagnostics and drug development (Table 7). THE CLINICAL LABORATORY: BEYOND DIAGNOSTIC TESTING Recently, several large pharma companies have imple- mented in-house clinical testing (CLIA certified) or developed contractual relationships with independent CLIA laboratories to support personalized medicine test- ing. As traditional GLP pharmaceutical scientists discover the advantages of clinical analyzers, some are asking: “If properly validated, can PD markers be moved to clinical analyzer platforms?” Indeed, an argument may be made that data generated from clinical analyzers are used to manage patient care and may be involved in life-and-death decisions. Several hundred FDA-approved diagnostic analytes that are currently measured on clinical analyzers would be attractive to the drug development community (Table 8). However, in the case of preclinical studies, GLPs (21 CFR Part 58) are required for the conduct of the study, and CLIA laboratories (42 CFR Part 493) do not strictly meet the GLP requirements. Ultimately, the decision is made based upon acceptability by regulatory agencies. Pharma tends to be risk adverse, and therefore unlikely to convert to or incorporate the CLIA regulatory environ- ment to generate PDs data. However, there are increasing opportunities to generate molecular diagnostic data in support of personalized medicine and identifying those patients who are likely to respond to specific therapeutic interventions. TABLE 7 Comparable Study Applications between Drug Development and Clinical Diagnostic Applications Drug Development Clinical Diagnostic Non-human studies Preclinical bioanalysis Veterinarian instruments Measurement of pharmaceuticals PK bioanalysis Therapeutic drug monitoring Detection of antibodies ADA bioanalysis Immunology Biochemical responses Biomarker/PD bioanalysis Diagnostic testing Assay format Research use only or LDTs FDA-approved commercial assay kits TABLE 8 Examples of Diagnostic Biomarkers that May be Used for Proof of Concept Analyte PD indication Alphafetoprotein (AFP) Liver, germ cell tumors Aldosterone Hypertension Apolipoproteins Cholesterol-lowering therapy Beta-2-microglobulin (β2M) Multiple myeloma, chronic lymphocytic leukemia; some lymphomas Beta-human chorionic gonadotropin (βhCG) Testicular cancer, choriocarci- noma B-natriuretic protein (BNP), N-terminal pro-BNP Congestive heart failure CA15-3/CA27.29 Breast cancer CA19-9 Pancreatic cancer, gallbladder cancer, bile duct cancer, gastric cancer Calcitonin Medullary thyroid cancer Carcinoembryonic antigen (CEA) Colorectal cancer, breast cancer CD20 Non-Hodgkin lymphoma Chromogranin A (CgA) Neuroendocrine tumors Cholesterol panels (including HDL, LDL, etc.) Cholesterol-lowering therapy C-peptide Diabetes Creatinine Kidney function, GFR C-telopeptide Osteoporosis Deoxypyridinoline (DPD) Osteoporosis Des-gamma-carboxyl prothrom- bin (DCP) Hepatocellular carcinoma Estrogen receptor (ER)/ progesterone receptor (PR) Breast cancer Fibrin/fibrinogen Bladder cancer Glucose Diabetes screening HbA1c Diabetes HE4 Ovarian cancer HER2/neu Breast cancer, gastric cancer, esophageal cancer hsCRP Inflammation Immunoglobulins Multiple myeloma, Walden- ström macroglobulinemia Insulin Diabetes KIT Gastrointestinal stromal tumor, mucosal melanoma Lactate dehydrogenase Germ cell tumors N-Telopeptide Osteoporosis Nuclear matrix protein 22 Bladder cancer Osteocalcin Osteoporosis P1NP (Procollagen type 1 N-terminal propeptide) Osteoporosis Prostate-specific antigen Pyridinium Osteoporosis Renin, plasma renin activity Hypertension
  • 11. 657CHAPTER 8.2 Ligand Binding Assays in Drug Development References DeSilva, B., Smith, W. and Weiner, R. Recommendations for the bioanalytical method validation of ligand-binding assays to support pharmacokinetic assess- ments of macromolecules. Pharm. Res. 20, 1885–1900 (2003). EMEA Guideline on Immunogenicity Assessment of Biotechnology-Derived Therapeutic Proteins. <http://www.emea.europa.eu/docs/en_GB/document_library/Scientific_ guideline/2009/09/WC500003946.pdf> (2007). EMEA Guideline on Bioanalytical Method Validation. <http://www.ema.europa.eu/ docs/en_GB/document_library/Scientific_guideline/2011/08/WC500109686. pdf> (2012). Findlay, J.W.A., Smith, W.C., Lee, J.W., et al. Validation of immunoassay for bioanalysis: a pharmaceutical industry perspective. J. Pharm. Biomed. Anal. 21, 1249–1273 (2000). Findlay, J.W.A. and Dillard, R.F. Appropriate calibration curve fitting in ligand binding assays. AAPS J. 9, E261–267 (2007). Findlay, J.W.A. Specificity and accuracy data for ligand-binding assays for macro- molecules should be interpreted with caution. AAPS J. 10, 433–434 (2008). GBC Global Bioanalysis Consortium on Harmonization of Bioanalytical Guidance. <http://www.globalbioanalysisconsortium.org/index/> (2011). Goodsaid, F., Dieterle, F., Sistare, F., et al. Renal biomarker qualification submis- sion: a dialog between the FDA-EMEA and Predictive Safety Testing Consortium. Nature Biotechnology 28, 455–462 (2010). http://www.nature.com/ nbt/journal/v28/n5/abs/nbt.1625.html. Herman, G.A., Bergman, A., Stevens, C., et al. Effect of single oral doses of sita- gliptin, a dipeptidyl peptidase-4 inhibitor, on incretin and plasma glucose levels following an oral glucose tolerance test in patients with type 2 diabetes. J. Clin. Endocrinol. Metab. 91, 4612–4619 (2006). Kim, D., Wang, L., Beconi, M., et al. (2R)-4-oxo-4-[3-(trifluoromethyl)-5,6- dihydro[1,2,4]triazolo[4,3-a]pyrazin-7(8H)-yl]-1-(2,4,5-trifluorophenyl)butan- 2-amine: a potent, orally active dipeptidyl peptidase IV inhibitor for the treatment of type 2 diabetes. J. Med. Chem. 48, 141–151 (2005). Kricka, L.J. Human anti-animal antibody interferences in immunological assays. Clin. Chem. 45, 942–956 (1999). Lee, J.W., Devanarayan, V., Barrett, Y.C., et al. Fit-for-purpose method develop- ment and validation for successful biomarker measurement. Pharm. Res. 23, 312–328 (2006). Lightfoote, M.M., Ball, D.J., Hannon, W.H. et al. Clinical Evaluation of Immunoassays; Approved Guideline, 2nd edn, vol. 28 (Issue 22 of Clinical and Laboratory Standards Institute, I/LA21–A2, 2008). Miller, K.J., Bowsher, R.R., Celniker, A., et al. Workshop on bioanalytical methods validation for macromolecules: summary report. Pharm. Res. 18, 1373–1383 (2001). Mire-Sluis, A.R., Barrett, Y.C., Devanarayan, V., et al. Recommendations for the design and optimization of immunoassays used in the detection of host antibod- ies against biotechnology products. J. Immunol. Methods 289, 1–16 (2004). Nowatzke, W.L., Cole, T.G. and Bowsher, R.R. Systematic approach for analytical validation of commercial test kits for conducting biomarker determinations in support of drug development. Bioanalysis 2, 237–247 (2010). Ponce, R., Abad, L., Amaravadi, L., et al. Immunogenicity of biologically-derived therapeutics: Assessment and interpretation of nonclinical safety studies. Regul. Toxicol. Pharmacol. 54, 164–182 (2009). Shah, V.P., Midha, K.K., Dighe, S., et al. Analytical methods validation: bioavail- ability, bioequivalence and pharmacokinetic studies. Pharm. Res. 9, 588–592 (1992). Shankar, G., Pendley, C. and Stein, K.E. A risk-based bioanalytical strategy for the assessment of antibody immune responses against biological drugs. Nat. Biotechnol. 25, 555–561 (2007). Shankar, G., Devanarayan, V., Amaravadi, L., et al. Recommendations for the validation of immunoassays used for detection of host antibodies against bio- technology products. J. Pharm. Biomed. Anal. 48, 1267–1281 (2008). US FDA Guidance for Industry—Bioanalytical Method Validation. <http://www.fda. gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/ Guidances/UCM070107.pdf> (2001). US FDA Guidance for Industry—Assay Development for Immunogenicity Testing of Therapeutic Proteins. <http://www.fda.gov/downloads/Drugs/Guidance ComplianceRegulatoryInformation/Guidances/UCM192750.pdf> (2009). Viswanathan, C.T., Bansal, S., Booth, B., et al. Workshop/conference report— Quantitative bioanalytical methods validation and implementation: Best prac- tices for chromatographic and ligand binding assays. AAPS J. 9, E30–E42 (2007). Wagner, J.A. Early clinical development of pharmaceuticals for type 2 diabetes mellitus: from preclinical models to human investigation. J. Clin. Endocrinol. Metabol. 87, 5362–5366 (2002). Wagner, J.A., Wright, E.C., Ennis, M.M., et al. Utility of adiponectin as a bio- marker predictive of glycemic efficacy is demonstrated by collaborative pooling of data from clinical trials conducted by multiple sponsors. Clin. Pharmacol. Ther. 86, 619–625 (2009). TABLE 8 Examples of Diagnostic Biomarkers that May be Used for Proof of Concept (Continued) Analyte PD indication Rheumatoid factor Rheumatoid arthritis Tartrate-resistant acid phosphatase (TRAP) 5b Osteoporosis Thyroid testing (total T3, free T3, TSH, T4, free T4, thyroid panel; thyroid antibodies) Hypo/hyperthyroidism Thyroglobulin Thyroid cancer Urokinase plasminogen activator (uPA) and plasminogen activator inhibitor (PAI-1) Breast cancer