Immunogenicity of biologically-derived therapeutics: Assessment and interpretation of nonclinical safety studies

Regulatory Toxicology and Pharmacology 54 (2009) 164–182

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Immunogenicity of biologically-derived therapeutics: Assessment and interpretation of nonclinical safety studies Rafael Ponce a,*, Leslie Abad b, Lakshmi Amaravadi c, Thomas Gelzleichter d, Elizabeth Gore e, James Green c, Shalini Gupta i, Danuta Herzyk f, Christopher Hurst c, Inge A. Ivens g, Thomas Kawabata h, Curtis Maier e, Barbara Mounho i, Bonita Rup j, Gopi Shankar k, Holly Smith l, Peter Thomas m, Dan Wierda l a

ZymoGenetics, Inc., 1201 Eastlake Ave. E., Seattle, WA 98102, USA Imclone Systems, Inc., NY, USA BiogenIdec, Cambridge, MA, USA d Genentech, South San Francisco, CA, USA e GlaxoSmithKline, King of Prussia, PA, USA f Merck and Co., Inc., West Point, PA, USA g Bayer HealthCare LLC, Richmond, CA, USA h Pfizer, Inc., New London, CT, USA i Amgen, Thousand Oaks, CA, USA j Wyeth, Andover, MA, USA k Centocor Research & Development, Inc., Radnor, PA, USA l Eli Lilly and Company, Greenfield, IN, USA m Covance Laboratories, Inc., Madison, WI, USA b c

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Article history: Received 23 January 2009 Available online 2 April 2009 Keywords: Nonclinical safety Immunogenicity Recombinant protein

a b s t r a c t An evaluation of potential antibody formation to biologic therapeutics during the course of nonclinical safety studies and its impact on the toxicity profile is expected under current regulatory guidance and is accepted standard practice. However, approaches for incorporating this information in the interpretation of nonclinical safety studies are not clearly established. Described here are the immunological basis of antidrug antibody formation to biopharmaceuticals (immunogenicity) in laboratory animals, and approaches for generating and interpreting immunogenicity data from nonclinical safety studies of biotechnologyderived therapeutics to support their progression to clinical evaluation. We subscribe that immunogenicity testing strategies should be adapted to the specific needs of each therapeutic development program, and data generated from such analyses should be integrated with available clinical and anatomic pathology, pharmacokinetic, and pharmacodynamic data to properly interpret nonclinical studies. Ó 2009 Elsevier Inc. All rights reserved.

1. Introduction Immunogenicity testing of biologically-derived pharmaceuticals during nonclinical and clinical drug development is rapidly evolving as evidenced by numerous articles on this subject (see reviews by Schellekens, 2005; Gupta et al., 2007; Shankar et al., 2007; Wadhwa and Thorpe, 2007) and by proposed regulatory guidance (EMEA, 2007). The majority of these documents focus on optimizing detection and characterization of anti-drug antibody (ADA)1 formation. This emphasis has resulted in generally accepted standards for * Corresponding author. Present address: Amgen, 1201 Amgen Court West, AW1/ J3120, Seattle, WA 98119-3105, USA. Fax: +1 206 216 5929. E-mail address: [email protected] (R. Ponce). 1 Abbreviations used: ADA, anti-drug antibody; AUC, area under the concentration vs. time curve; Cmax, maximum concentration; DC, dendritic cell; ELISA, enzyme-linked immunosorbent assay; EMEA, European Medicines Agency; FDA, U.S. Food and Drug Administration; Ig, immunoglobulin; MHC, major histocompatibility class; nADA, neutralizing anti-drug antibody; PD, pharmacodynamics; PEG, polyethylene glycol; PK, pharmacokinetics; PRCA, pure red cell aplasia; SC, subcutaneous; TPO, thrombopoietin; UV, ultraviolet. 0273-2300/$ - see front matter Ó 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.yrtph.2009.03.012

developing immunoassays capable of detecting nanogram per milliliter quantities of ADA in biological matrices from either animals or humans. Whereas the effect of immunogenicity on clinical safety and efficacy of these novel therapeutic proteins in patient populations has been documented for many agents, nonclinical immunogenicity has received comparatively less attention. In general, an immune response to human or humanized proteins is expected to be greater in animals than in humans due to species differences in protein structure and the perceived foreignness of the drug construct in the animal model. As a result, animal models tend to have low predictive value and often over-estimate biopharmaceutical immunogenicity rates and the incidence of adverse immune-mediated events in the human subjects (reviewed in Wierda et al., 2001; Bugelski and Treacy, 2004). Nevertheless, immunogenicity data derived from nonclinical studies have important utility. Specifically, data from ADA evaluations in animal studies are crucial for their adequate interpretation, especially when alterations in drug pharmacokinetic (PK) or pharmacodynamic

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(PD) parameters are observed (Shankar et al., 2006). Such data may reveal a potential safety hazard, particularly associated with neutralization of a critical endogenous protein, and can aid in the interpretation of observed tissue injury. In cases where no toxicity or alterations in pharmacodynamic activity are observed, the absence of neutralizing antibodies together with pharmacokinetics can support the availability of active drug. Finally, immunogenicity data have been proposed as a tool to identify potential consequences of manufacturing changes or to allow comparative analysis of the relative immunogenicity among different manufactured lots of biopharmaceuticals (EMEA, 2007). Although this latter use of immunogenicity data is discussed in detail later, there remains some controversy in industry about the merit or utility of comparative data in animals given the inability to relate immunogenicity data in nonclinical species to human immunogenicity. The potential impact of drug immunogenicity during repeated dose nonclinical safety studies is recognized by current regulatory guidance that advises collection of ADA data (i.e., titer, number of responding animals, and neutralizing activity) to assist in the study interpretation (ICH, 1997). Since publication of this guidance, substantial experience has been gained in the development of therapeutic proteins. This manuscript reviews immunogenicity testing in the context of incorporating the newer immunoassay technologies in interpretation of nonclinical safety studies and assessing potential human risks using practical case examples. The aims of this effort are to understand the limitations of our animal models and analytical methods, and to establish sound scientific practices around immunogenicity assessments that meaningfully inform nonclinical study interpretation. 1.1. Factors that influence immunogenicity of biotechnology-derived therapeutics Immunogenicity refers to the inherent properties of a molecule to stimulate an immune response. A number of factors influence the immune response to therapeutic administration, including protein structure, host immune status, host genetics, the presence of conditions that activate immunity, and the means and regimen of administration, as described below. 1.1.1. Protein structure The primary features underlying the development of the immune response towards a biologically-derived therapeutic relate to inherent structural properties of the molecule, including crossspecies differences in protein sequence, differences in the nature or extent of glycosylation and other post-translational modifications, and the presence of neo-epitopes (e.g., creation of fusion proteins, Skipper et al., 1996; Meadows et al., 1997; Molberg et al., 1998; Wood and Elliott, 1998; Doyle and Mamula, 2001; Rudd et al., 2001; Bugelski and Treacy, 2004). Enzymatic cleavage and ‘aging’ can lead to oxidative degradation or spontaneous formation of isoaspartyl peptides under physiologic conditions and can create neoantigenic sites on previously tolerized proteins and promote antibody formation (Mamula et al., 1999). In addition, manufacturing production steps may create neoantigenic sites as demonstrated by development of inhibitors to plasma-derived Factor VIII and attributed to the addition of a second viral inactivation step (pasteurization at 63 °C for 10 h, Peerlinck et al., 1997). Protein aggregation, defined by Rosenberg to include ‘‘high molecular weight proteins composed of multimers of natively conformed or denatured monomers”, has been associated with increased immunogenicity for a number of decades (Rosenberg, 2006). Although precise mechanisms are lacking, protein aggregation is proposed to enhance a T cell-independent immunogenicity by presenting high molecular weight, repeating subunits (multi-

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mers) to B cells or to induce a T cell-dependent response via enhanced antigen binding to B cell receptor (reviewed by Rosenberg, 2006). The role of aggregation in enhancing immunity has been demonstrated for interferon-a in a murine model system, although the immunogenicity of interferon-a is likely also related to immunostimulation associated with the pharmacodynamic activity of the cytokine and other factors including dose, frequency and route of administration (Braun et al., 1997; Palleroni et al., 1997; Schellekens, 2005). The immunostimulatory activity of this cytokine likely underlies its high incidence of ADA formation (see Table 1), and may also contribute to interferon-a-induced autoimmunity in humans (reviewed in Gribble et al., 2007). PEGylation of recombinant therapeutics can protect the protein from degradation and increase the size of the molecule, thus reducing kidney filtration (Veronese and Pasut, 2005). This reduced protein degradation presumably underlies the reportedly reduced immunogenicity of PEGylated proteins (Katre, 1990; He et al., 1999; Deckert et al., 2000; Avgerinos et al., 2001; Basu et al., 2006), although in some cases PEGylation has been associated with increased immunogenicity (personal communication, Ron Wange, US FDA, November 21, 2008). Newer methods involving polysialylation may also prove advantageous in reducing immunogenicity (Gregoriadis et al., 2005). The development of anti-PEG antibodies is possible, although in practice these are rarely reported (e.g., Ganson et al., 2006), and their detection may reflect non-specific binding in the assay. 1.1.2. Immunosuppressive treatment Tolerance may be achieved in some cases by the use of antiinflammatory or immunosuppressive drugs, such as glucocorticoids, cyclosporine or anti-CD52 monoclonal antibody. For example, immunosuppressive treatment was used to control an anaphylactic reaction in dogs that was elicited by human serum albumin in the formulation for darbepoetin alfa (see Table 1). The use of immunosuppressive agents in the course of nonclinical safety studies is not generally accepted practice because of the potential for interfering with the interpretation of the study and is not discussed further here. UV exposure of skin can deplete the dermis of Langerhans cells, leading to local immune system ignorance towards agents administered topically or via SC injection. Langerhans cells are epidermally localized dendritic cells, constituting up to 5% of the epidermis (Murphy et al., 1981). This response towards UV irradiation of skin has been associated with impaired immunity towards cutaneous antigens and may underlie increased skin cancer rates in areas with increased UV exposure (Lynch et al., 1983; Cooper et al., 1992; McGee et al., 2006). Such UV exposure could theoretically be used to induce tolerance to therapeutic agents applied topically or via SC injection. However, this form of tolerance may interfere with the generalization of study findings to normal animals because these cells may play important roles in the distribution and biological activity of the therapeutic agent, particularly for immune system-modifying agents, and leave the animal open to opportunistic infection. 1.1.3. Genetic deficiency Central tolerance derives from clonal lymphocyte deletion of immature B cells (in the bone marrow) and T cells (in the thymus) that are reactive to self-peptides during the course of normal lymphocyte development. In this process, T cells with high affinity for self-peptides and autoreactive B cells undergo selective deletion (Goodnow et al., 1990; Wardemann et al., 2003; Hogquist et al., 2005). Thus, central tolerance provides a means for recognition of and tolerance towards ‘self’ proteins. When an individual is genetically deficient in a specific protein, the immune system does not have the opportunity to develop central tolerance towards that

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Table 1 Reported immunogenicity of marketed biological therapeutics in nonclinical species and treated human patients. Species

Dosing

Summary of findings

Immunogenicity rate in humans

Amevive (alefacept) dimeric fusion protein

Cynomolgus monkeys, baboons Rats, dogs

IV once or twice weekly for up to 44 weeks IV or SC once or thrice weekly for up to 6 months

3% (package insert)

Avastin (bevacizumab) chimeric IgG1

Cynomolgus monkeys

Avonex (interferon beta 1a) recombinant glycoprotein

Rhesus monkeys

IV twice weekly for up to 26 weeks SC 2–9 weeks (including recovery)

Campath (alemtuzumab) humanized IgG1 k monoclonal antibody

Cynomolgus monkeys, rats, rabbits, and mice

A low incidence (not specified) of ADA detected. Reportedly, did not affect interpretation of study data. Anaphylaxis observed in dogs by week 3 in all treatment groups (including controls). Severity and incidence decreased over time. Attributed to human serum albumin present in formulation. Animals treated with epinephrine and antihistamine to control reaction and allow dose continuation. Exposure in dogs reportedly unaffected by ADA. ADA reported among evaluated rats in a PK satellite group. Use of satellite animals for PK/ADA assessments limited ability to extrapolate findings to main study animals. No detectable ADA were observed in treated animals, however drug levels (>40 lg/ mL) at all ADA sampling times may have interfered with assay results. Among drug-related clinical effects, elevated body temperature, decreased food consumption, decreased platelet counts and slightly decreased serum albumin concentrations were negated by nADA that became evident within 2 weeks after initiation of treatment. Across studies, up to 100% of animals had evidence of ADA. Development of nADA was reported in cynomolgus monkeys, rats and rabbits, and limited the duration of a chronic study in cynomolgus monkeys to 30 days (vs. 12 weeks planned in humans).

Aranesp (darbepoetin alfa) analog of recombinant human erythropoietin

SC

Fabrazyme (agalsidase beta) recombinant human a-galactosidase A homodimeric glycoprotein

Herceptin (trastuzumab) recombinant humanized monoclonal antibody Humira/trudexa (adalimumab) recombinant human IgG1 monoclonal antibody

Cynomolgus monkeys, rhesus monkeys Cynomolgus monkeys

Intron-A (interferon alpha-2b) recombinant interferon-a

Cynomolgus monkeys

Line missing

SC and IV weekly or monthly exposure for up to 6 months

IM daily, up to 3 months

Severe hypoactivity, cyanosis, labored breathing and swelling of the extremities observed by week 3. Symptoms prevented by diphenhydramine pre-treatment. The majority of animals developed ADA after 12 weeks. Some ADA-positive animals did not show a detectable antibody titer at week 24, which was attributed to development of tolerance. No relationship between antibody titer and dose or sex. No information provided on possible masking of toxicity by nADA and pre-treatment with diphenhydramine. Neutralizing ADA detected from weeks 5–26 in one low-dose female cynomolgus monkey (incidence = 1.2%). Formation of ADA observed in up to 100% of treated animals starting as early as day 12 of treatment. Whereas increasing ADA increased with duration of treatment among low-dose animals, only low titer antibodies observed in high-dose animals. Among low-dose animals, ADA titers in the monkeys receiving monthly treatments were higher than those from monkeys receiving weekly treatments, and titers in monkeys receiving IV treatment were higher than in monkeys receiving SC treatment. Formation of ADA increased drug clearance in most animals. Reviewer reported ready development of nADA in study animals upon repeated dosing, which curtailed longer-term studies. In one study, ADA were observed in approximately half of all treated animals from weeks 4–13. nADA were detected in 4/ 8 low-dose and 1/8 mid-dose animals at week 13. The presence of drug in sera from high-dose animals may have interfered with detection of ADA and nADA activity.

4% (chronic renal failure), 3% (cancer) (package insert)

1.9% (chronic lymphocytic leukemia), 63% (rheumatoid arthritis) (package insert); (Weinblatt et al., 1995) 89% (package insert)

0.1% (package insert) 12% (monotherapy) (package insert)

0–13% (package insert)

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Product

Pegasys (peginterferon alfa-2a) PEGylated recombinant interferon-a

SC daily or twice weekly for up to 4 weeks Unclear regimen for up to 13 weeks

A dose-related increase observed in the development of ADA. 100% of high-dose animals demonstrating ADA. High nADA titers were observed in 100% of animals in mid- and high groups at 72-hr after the last dose. Decreased drug levels were observed with increased ADA titer and nADA activity. In one 4-week study, exposure was undetectable after 2 weeks of dosing. In contrast, drug levels at later time points during the course of the 13-week study were increased over expected levels and attributed to development of bADA (however, the presence of ADA did not permit an accurate estimate of drug exposure).

9% bADA (3% nADA) (Hepatitis C virus), 29% bADA (13% nADA) (Hepatitis B virus) (package insert)

Cynomolgus monkeys (additional safety studies in mice and rats were not deemed relevant species) Cynomolgus monkeys, rats

SC regimen unclear

nADA detected in the majority of animals as early as week 3 were associated with decreased exposure and reversal of the hematologic toxicities.

8–15% bADA (2% nADA) (package insert)

SC injection, 26-weeks (cynomolgus) IM or IV, daily for 13 weeks (rats)

24–31% nADA (package insert)

Remicade (Infliximab (cA2)) chimeric IgG1

Mice chimpanzee and cynomolgus monkeys

IV (both species) IP (mice) regimen unclear

Rituxan (rituximab) Chimeric IgG1 Mab

Cynomolgus monkeys

IV twice weekly for 4 or 8 weeks

Simulect (basilixumab) chimeric human/ murine IgG1 k TNKase (tenectaplase)

Cynomolgus and rhesus monkeys Dog and rabbit

Route and regimen unclear

ADA to human serum albumin and drug were detected in both species, and tended to be greater after IM than after IV administration. Antibody titers generally increased up to 4 weeks of dosing. In cynomolgus monkeys, ADA were observed in 100% of treated animals. Development of ADA and nADA activity was associated with decreased drug exposure and decreased pharmacodynamic activity (as assessed by serum neopterin). The ADA response among mice and monkeys treated at higher doses appeared to be affected by the presence of free drug, which interfered with detection. A low-level ADA response was observed in chimpanzees, but not cynomolgus monkeys, which did not increase with subsequent injections. Development of ADA modified both the pharmacological and pharmacokinetic effects of the drug. Antibodies were directed toward the joining region of the construct. A reported increased clearance in the low-dose animals was attributed to the appearance of ADA in 75% of the animals after 4 weeks of treatment. ADA were detected in 100% of treated rabbits by day 8 and 100% of dogs by day 18. A dose-related increase in ADA titer was reported in rabbits. The induction of antibodies could not be evaluated in most samples because the assay systems were highly susceptible to disturbance by either the presence of omaluzimab or omaluzimab: IgE complexes. Some of the sera which could be evaluated were positive. The nonclinical safety program was conducted in cynomolgus monkeys comparing a murine and humanized version of the antibody. Summary statements report greater ADA response to the murine antibody compared to the humanized antibody.

29% bADA (13% nADA) (Hepatitis B virus) (package insert) PEG-INTRON (peginterferon alfa-2b) PEGylated recombinant interferon-a

Rebif (IFN beta-1a) recombinant human cytokine

IV, daily for 2 weeks (rabbit) SC, Daily for 2 weeks (dog)

Xolair (omalizumab) humanized IgG1

Zenapax (daclizumab) humanized IgG1

Cynomolgus monkeys

Route and regimen unclear

10–61% (package insert, Baert et al., 2003)

1.1% (package insert)

1.2–3.5% (package insert, two doses)

<0.1% (package insert)

8.4% (package insert)

No immunogenicity data was reported for Epogen/procrit (epoetin alfa); Erbitux (cetuximab); Actimmune (interferon-gamma 1b); Activase (alteplase); ReoPro (abciximab); Roferon-a (interferon alfa 2a); Synagis (palivizumab); Proleukin (aldesleukin); Pulmozyme (Dornase alfa); Raptiva (efalizumab); Infergen (interferon alfacon-1); Betaseron (interferon beta-1b).

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Cynomolgus monkeys

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protein. Thus, the lack of central tolerance underlies the observed immune response of genetically deficient individuals upon treatment with a recombinant or purified replacement factor (e.g., Astermark, 2006; Evans and Morgan, 1998). Whereas this form of immunogenicity has important implications for clinical therapy in genetically deficient humans, it is unlikely to underlie immunogenicity observed in genetically normal species typically used in nonclinical studies. 1.1.4. Adjuvants, product formulation, and inflammation The immune system may remain ignorant of antigen exposures that occur in parenchymal tissues. This form of tolerance may underlie the relatively low immunogenicity associated with intramuscular compared to SC injection of interferon-b in humans (Perini et al., 2001). However, this tolerance may be broken in the presence of tissue injury, inflammation or infections that stimulate a local immune response (reviewed in Khoruts and Jenkins, 1996; Mondino et al., 1996), supporting the important role of having a sterile and physiologically compatible formulation to minimize immunogenicity as discussed below. The induction of co-stimulatory molecules on dendritic cells by MHC–peptide complex is a fundamental requirement for the initiation of T cell priming (and loss of tolerance or induction of autoimmunity) (Kubo et al., 2004), and the nature of the T cell-DC interaction determines whether tolerance or activation results towards an exogenous antigen (reviewed in Henrickson and von Andrian, 2007; Skokos et al., 2007). In contrast, sub-optimal T cell receptor–antigen interactions in the absence of inflammation/costimulation lead to tolerance (reviewed in Khoruts and Jenkins, 1996; Arnold, 2002). The observation of exogenous antigen crosspresentation by DC to CD8+ T cells via peptide-MHC class I, rather than the traditional presentation to CD4+ T cells via MHC class II, may lead to deletion of these T cells in the absence of T cell help, thus also resulting in tolerance (Steinman et al., 2000; Heath and Carbone, 2001; Kurts et al., 2001). This pathway may be particularly relevant to the induction of tolerance to exogenous proteins in the absence of co-stimulation (Kurts et al., 1998). In addition, the observation of self-antigen trafficking by resting (unactivated) DC may be associated with tolerance to self-peptides (Steinman et al., 2000; Mahnke et al., 2002; Yoshino et al., 2006), and antigen presented on resting B cells, which do not express co-stimulatory molecules, is tolerogenic to T cells (Eynon and Parker, 1992; Fuchs and Matzinger, 1992). Components of the product formulation can stimulate immunogenicity, including impurities such as endotoxin; host cell DNA or proteins, that act as adjuvants and provoke an immune response by evoking ‘‘danger signals”; or nonphysiological pH/osmolality that cause tissue injury and immune system activation (Dresser, 1962; Palleroni et al., 1997). Exposure to a ‘‘danger signal” such as an infection or an adjuvant can activate Toll-like receptors on antigen presenting cells or dendritic cells leading to an up-regulation of MHC and co-stimulatory molecules on these cells and the accumulation of peptide-MHC complexes on the cell surface, thereby facilitating antigen presentation (Ichikawa et al., 2002; Pasare and Medzhitov, 2003). Such an effect may underlie, in part, greater clinical immunogenicity rates reported for recombinant proteins derived from Escherichia coli compared to mammalian cells such as interferon-b (Abdul-Ahad et al., 1997) or growth hormone (Valls et al., 1991a,b), although other factors such as aggregation, carbohydrate structure, and other physical characteristics may predominate (Scagnolari et al., 2002). Tight control of manufacturing and purification processes should minimize these impurities in the administered product and their immunogenic potential. Several cases of pure red-cell aplasia (PRCA) were reported in patients administered a particular formulation of recombinant hu-

man erythropoietin (rhuEPO; epoetin alfa; Eprex) (Casadevall et al., 2002; Gershon et al., 2002; Casadevall, 2004). These patients developed anti-erythropoietin antibodies, which cross-reacted and neutralized endogenous erythropoietin resulting in PRCA (Casadevall et al., 2002; Swanson et al., 2004; Bennett et al., 2005; Rossert, 2005). The observation of PRCA among patients treated with epoetin-a (EprexÒ/ErypoÒ) coinciding with manufacturing and delivery changes in Europe stimulated intensive evaluation of the plausible causes, which include speculation of a relationship to changes in the formulation, the presence of leachates from rubber used in the syringe, and/or the formation of aggregates (Casadevall, 2004; Schellekens, 2005). In addition, restrictions against SC injection were put in place by European regulators as this relatively new treatment route was associated with the predominance of PRCA cases (see Schellekens, 2005). 1.1.5. Effect of dose route, dose, and regimen In the previous section, we reviewed immune system activation associated with subcutaneous protein injection. This immune response is highly efficient at surveillance and response to protect the host against opportunistic infections arising from a breach of the external surface of the skin. In contrast, the presentation of oral antigens pose a unique challenge to the immune system, which must preserve tolerance towards benign antigens and enable nutritional balance, while identifying harmful agents for elimination. Thus, the immune system must establish tolerance via oral exposure to allow the host to thrive on a variety of foods. It is for these reasons that the route of exposure plays a central role in modulating the immune response to therapeutic proteins. The concept of oral tolerance has been established for almost a century (Wells, 1911; reviewed in Strobel and Mowat, 1998). Oral administration of soluble protein can lead to tolerance, with greater, more frequent doses associated with an increased incidence and longer lasting tolerance to the antigen (Dresser, 1962). The basis for this tolerance has been linked to either anergy (with high-doses, Whitacre et al., 1991; Friedman and Weiner, 1994) or cytokine-mediated immunosuppression associated with a novel regulatory T cell (with low-doses Chen et al., 1994; Friedman and Weiner, 1994), although selective deletion of antigen-specific clonal T cells may also occur (Chen et al., 1995). Similarly, intravenous injection of highdoses of soluble protein has also been associated with tolerance, attributable to central and peripheral clonal T cell deletion as well as T cell receptor desensitization (Liblau et al., 1996). As a result, SC injection is generally perceived to be a more immunogenic route of exposure compared to intravenous administration (e.g., Braun et al., 1997). However, this is not always the case (see Section 3) and for specific therapeutic agents there remains a need to perform comparative studies by various administration routes to understand the impact on immunogenicity. The basis for peripheral tolerance to exogenous antigens is a rapidly evolving field, particularly with respect to the role of regulatory T cells, and is beyond the scope of this review. However, interested readers may find the following articles of interest (Vignalli et al., 2008; Apostolou et al., 2002; Zhang et al., 2001). Relatively less has been documented on the comparative immunogenicity of therapeutic protein administration by inhalation, intraocular injection, or other routes, although clinical data on inhaled insulin suggests a relatively greater ADA response relative to SC injection (de Galan et al., 2006). Of interest will be evaluation of dose-dependency, dose-frequency, the role of adjuvants or inflammation, and the mechanisms of immunosurveillance and immune system activation by these routes and how these affect the nature of the formed ADA.

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2. Effect of immunogenicity on study interpretation Various types of ADA responses can develop in nonclinical animal studies using biological therapeutics. Because most biological therapeutics are recombinant human proteins and, more recently, human or humanized antibodies, it is not unexpected that their administration to species commonly used in toxicology studies (e.g., rodents, dogs, non-human primates) would result in the development of antibodies against the drug (Wierda et al., 2001). In many cases, the development of ADA has no impact on the outcome and data interpretation of nonclinical toxicology studies [Case Study 1]. Some ADA responses, however, can alter the pharmacokinetics or the pharmacological activity of the drug [Case Studies 2–6], thus affecting the interpretation of toxicology studies. In these cases, the development of ADA responses in nonclinical toxicology studies can potentially generate misleading toxicity data and/or underestimate human risk (ICH, 1997; Serabian and Pilaro, 1999). Development of ADA responses in nonclinical safety and PK studies commonly present in one of three ways: (1) binding ADA that enhance the clearance of the drug [Case Studies 2–6]; (2) binding ADA that neutralize the pharmacological action of the drug [Case Study 5]; (3) ADA that bind and neutralize the pharmacological action of the drug and the endogenous protein counterpart (cross reaction), potentially leading to a deficiency syndrome. Other, less common, types of ADA responses may arise, including binding ADA that reduce the clearance of the drug, formation of immune-complexes, and ADA that result in anaphylaxis/hypersensitivity reactions. Although rare, there is some evidence that ADA may also enhance the pharmacological activity of a biotechnology-derived therapeutic (personal communication, Ron Wange, US FDA, November 21, 2008). Because ADA can alter exposure and pharmacodynamic activity of the drug in various combinations, it is not always possible to establish causality for a specific finding. In general, the nature of the immunogenic response is not characterized with regards to antibody subclass, although various animal species and humans differ in antibody subclass repertoire. In addition to the effects of ADA on exposure to active drug in the animal as discussed above, ADA may also interfere with the detection of drug as assessed using a target-binding format PK assay, resulting in an apparent abnormal PK profile; however, this is not always the case [Case Study 7]. Such ADA responses and their impact on study outcomes are described below. 2.1. Antibody-mediated changes in pharmacokinetics Antibodies that increase the plasma or serum clearance rate of the drug are often referred to as ‘‘clearing antibodies”. In this circumstance, the formation of antibody complexes with the biological therapeutic are recognized and removed from systemic circulation by the reticuloendothelial system (Gesser et al., 1998), thus increasing the rate of drug clearance and decreasing distribution of the drug to target organs (Koren et al., 2002). These antibodies differ in their inhibitory activity to the drug. Because clearing antibodies can significantly reduce drug exposure in the animals and impact the interpretation of the toxicology study, it is important to detect the presence of ADA and determine if the ADA responses correlate with altered pharmacology or pharmacokinetics, and/or toxicity observed in the study (ICH, 1997; Koren et al., 2002; Shankar et al., 2006). Similar to clearing ADA, sustaining antibodies bind to drug and alter its pharmacokinetics. Sustaining ADA, however, reduce the plasma or serum clearance of the drug, resulting in prolonged systemic exposure and increased distribution to target organs (Pendley et al., 2003), possibly mediated through FcRn-mediated drug

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recirculation (e.g., Datta-Mannan et al., 2007). Prolonged drug exposure in animals can potentially result in increased pharmacodynamic activity and/or increased toxicity, thus also ultimately confounding the interpretation of the toxicology studies. Prolonged circulation time and enhanced activity have been reported upon ADA development for both cytokines and hormones (reviewed in Aston et al., 1989; Rehlaender and Cho, 1998). 2.2. Neutralizing antibodies Anti-drug antibodies that reduce or neutralize the pharmacological activity of the drug are often referred as ‘‘neutralizing antibodies”. Neutralizing anti-drug antibodies (nADA) bind to or near the target-binding domain of the drug, which inhibits the drug’s ability to bind to the target. The inability of the drug to bind to its target not only results in decreased efficacy/pharmacological activity, but also may decrease potential toxicity, which could lead to an underestimation of human risk. Thus, the development of nADA and clearing ADA may both lead to an apparent reduction in pharmacologic or toxicologic activity, although with very distinct mechanisms that can best be discriminated with appropriately designed analytical methods. In the case of recombinant human IL-3, ADA were produced in rhesus monkeys when the cytokine was administered either by the IV or SC route for up to 3 months (Mayer et al., 1989; Gunn, 1997). In the latter study, the presence of ADA correlated with a drop in circulating levels of the cytokine as well as a loss of pharmacological activity. The antibody response did not result in immune complex disease, nor was there any indication of toxicity. By contrast, in clinical studies, anti-rhuIL-3 antibodies were seen in approximately 3% of patients tested, with one exhibiting neutralizing antibody to the drug. The authors concluded that the low incidence of immunogenicity may have been because most patients were immunocompromised to begin with (Gunn, 1997), although the therapeutic may be less immunogenic in humans compared to non-human primates. 2.3. Cross-reactive neutralizing antibodies There are also cross-reactive antibodies that not only bind and neutralize the drug, but also bind and neutralize the biological function of an endogenous protein counterpart. When the protein mediates a unique biological function, its neutralization can result in a clinical crisis in animals or humans. For example, topical hemostasis of humans with purified bovine thrombin results in ADA development among 20–90% of treated patients (reviewed in Heffernan et al., 2007). This ADA response includes the formation of neutralizing anti-factor V antibodies (where factor V is an impurity in the purified product), which have been associated with a profound bleeding disorder in a fraction of surgical patients treated with bovine thrombin (Streiff and Ness, 2002; Lawson, 2006). In the case of recombinant human thrombopoietin (rhTPO), administration to chimpanzees and rhesus monkeys led to the development of neutralizing antibodies capable of binding to endogenous thrombopoietin. Thrombopoietin is a hematopoietic growth factor that stimulates the production of platelets. Thus, animals that were positive for neutralizing anti-rhTPO antibodies showed decreased platelet counts and thrombocytopenia (Hardy et al., 1997). A reduction in platelet counts with coinciding antiTPO antibodies was also observed in rhesus monkeys administered recombinant rhesus monkey TPO and mice administered murine recombinant TPO (Hardy et al., 1997). A similar phenomenon occurred clinically with PEGylated recombinant megakaryocyte growth and development factor (PEGrhMGDF), which is a nonglycosylated molecule that contains the N-terminal 163 amino acids of endogenous TPO (Kuter, 1998; Li

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et al., 2001). Thrombocytopenia developed in several subjects administered PEG-rhMGDF, and anti-PEGrhMGDF antibodies that cross-reacted and neutralized endogenous human TPO were detected in the most severely thrombocytopenic subjects (Li et al., 2001). Thus, in the case of TPO, the thrombocytopenia caused by neutralizing anti-TPO antibodies observed in humans was predicted by the nonclinical animal studies. The presence of neutralizing antibody to an externally administered recombinant protein can also impact the function of the analogous endogenous protein in the species tested. Such was the case in dogs treated with recombinant human MpL ligand to induce thrombocytopenia (Dale et al., 1997) and in dogs given recombinant human G-CSF (Keller and Smalling, 1993). In the latter case, no such changes were seen in monkeys treated with this cytokine, nor were there significant reports of immunogenicity in subsequent clinical trials with G-CSF. Similarly, severe anemia subsequent to the development of cross-reactive antibodies occurred in animals treated with certain recombinant forms of human erythropoietin, which mimicked the development of PRCA described for erythropoietin (Coscarella et al., 1998; Cowgill et al., 1998). Although these autoimmune reactions are relatively rare in humans, the potential for such responses should be evaluated in both clinical and nonclinical studies. 2.4. Hypersensitivity reactions The development of ADA in animal toxicology studies may result in the formation of immune complexes. Although the occurrence is rare, these antibody–drug complexes can deposit in various tissues such as joint cavities or the renal glomerulus and consequently result in immune complex-mediated toxicity. For example, intramuscular administration of recombinant human interferon (rHuIFN-c) to cynomolgus monkeys resulted in the development of ADA and glomerulonephritis, which morphologically resembled an immune complex glomerulitis. Thus, the glomerulonephritis observed in these monkeys may have been secondary to the deposition of anti-rHuIFN-c antibody complexes in the renal glomeruli (Terrell and Green, 1993). Under the most benign conditions, antibody development will have no notable effect on drug exposure or activity. However, under the most severe conditions, anti-drug antibodies can initiate a life-threatening immune response, including an anaphylactic reaction. A few examples of anaphylactoid responses in nonclinical species treated repeatedly with biotechnology-derived therapeutics have been reported (see Table 1). In such cases, the anaphylactic reaction may be treated with anti-histamine drugs and/or immunosuppressive therapy to enable continued dosing.

3. Immunogenicity of approved therapeutic agents in nonclinical species In an effort to document currently available information on the relative immunogenicity of biotechnology-derived therapeutics in nonclinical species, immunogenicity data for marketed biologic therapeutics were extracted from publicly available FDA (http:// www.accessdata.fda.gov/scripts/cder/drugsatfda/) and EMEA (http://www.emea.europa.eu/htms/human/epar/a.htm) approval documents and product labels. These data are summarized in Table 1. For some biologic products, no immunogenicity data were provided in the available approval documents; in these cases it remains uncertain whether immunogenicity evaluations were conducted or whether the regulatory authority felt no need to describe these data in the approval documents. Given the marked differences in methods used, assay sensitivity, susceptibility to interference, and other factors, it is not meaningful to try and compare relative immunoge-

nicity rates across agents summarized in Table 1. These data provide insight on the nature of the immunogenic response to biologic therapeutics in nonclinical species, including relative immunogenicity rates by route, relationship to observed toxicities, or effects on PK or PD. Also presented are published data on the relative immunogenicity of the therapeutic in humans. Overall, the available information was highly variable with regards to the assay format, design details of the nonclinical studies, blood sampling schedule, interference in PK and antibody assays, incidence rates for antibody development, and whether the development of antibodies affected pharmacokinetics or pharmacodynamic responses in treated animals. The available data demonstrate the potential for both decreased and increased drug exposure with biologically-derived therapeutics in nonclinical species. However, there was not always a clear concordance between an ADA response and a concomitant PK/PD response. For some products, including Campath and interferon-a-based therapies, the formation of antibodies interfered with the feasibility of chronic toxicity studies. As presented in Table 1, interference by drug, particularly among higher-dosed animals, may have limited the ability to detect antibodies for some therapeutics. Conversely, the presence of antibodies reportedly interfered with determination of drug exposure. This suggests that challenges remain in establishing appropriate serum sampling schedules and/or bioanalytical assays for some agents. Moreover, there remains a need to develop improved methods to detect drug/antibody in the presence of interfering antibody/drug, respectively. Review of Table 1 also identifies anaphylactoid reactions in test animals upon administration of Aranesp (darbepoetin alfa) and Fabrazyme (agalsidase beta), which necessitated immunosuppressive therapy to allow continued dosing. The anaphylaxis associated with darbepoetin alfa in dogs was attributed to the presence of human serum albumin present in the drug formulation and occurred in animals treated with the vehicle control as well as drug. This example highlights the importance of a formulation control in the conduct of nonclinical safety studies. Although subcutaneous injection is often presumed to be associated with a higher degree of immunogenicity compared to intravenous injection, review of Table 1 suggests at least one example (Humira, adalimumab) wherein intravenous injection was associated with a greater degree of reported immunogenicity (although specifics of study design and assay format were not reported). Although a substantial amount of information has been collected on immunogenicity by dose route, much of the data pertaining to biotechnology-derived therapeutics are proprietary and not publicly available, thus hindering elaboration on this issue. Review of the relative immunogenicity rates across species demonstrates generally poor concordance between results in animals and humans. With few exceptions immunogenicity rates in animals were generally greater than those in humans, confirming previous findings of Bugelski and Treacy (2004). As mentioned previously, this poor correlation stems from cross-species differences in the immunogenicity towards the biologic therapeutic as well as differences in assay formats used to characterize immunogenicity in animals and humans. Given that the data in Table 1 reflect available data for currently marketed therapeutics, data are lacking regarding relative immunogenicity rates for newer generation agents such as fully human/humanized antibodies or fusion proteins, or for drugs that failed prior to market approval.

4. Study design considerations An assessment of the effects of ADA formation on study outcomes begins with the recognition that there are limitations to

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ADA assays. ADA assay performance characteristics such as sensitivity and drug tolerance (i.e., the relative sensitivity of an ADA assay in the presence of drug) are evaluated by the available positive control antibodies which, very often, differ from actual study samples in terms of their affinity, avidity, isotype, epitope specificity, etc. Validated ADA assays assure system suitability for evaluation of ADAs from study subjects, however, the performance of actual study samples may vary from positive controls used in the assay. Therefore, it should be recognized that although ADA assay results are one aspect of the immunogenicity assessment, all contributing parameters such as pharmacokinetics, pharmacodynamics, and adverse event profile should be taken into consideration when designing and interpreting results of a safety study for a biotherapeutic. Although the assessment of ADA response is not obligatory for all studies, samples should be collected and stored for possible ADA analysis from all nonclinical toxicity studies in which animals will be exposed to drug for greater than 7 days. Antibodies in frozen serum are known to be stable for long periods of time (Fineberg et al., 1996; Harlow and Lane, 1988). Therefore, we recommend ADA samples to be stored at < 20 °C for possible future ADA analysis. These samples may also be used as a resource to develop and validate ADA assays in the species of interest. The decision to analyze samples for ADA should depend on the utility of these data to meaningfully add to study interpretation when considered with other parameters (i.e., PK, PD, toxicity data). An overview of the considerations and possible decisions related to ADA analysis are summarized below and represented as a decision tree (Fig. 1). For example, ADA may bind to the drug but have no observable effect on the pharmacodynamic (PD) and/or pharmaco-

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kinetic (PK) profile of the drug and hence, have no effect on efficacy or the drug exposure, respectively. When the PK and PD properties can be monitored effectively and are not adversely altered, and potential ADA-associated changes in the toxicity profile are not noted during the study, measurement and evaluation of ADA may not add value to interpretation of the study and ADA analysis may not be necessary. In contrast, ADA may:  alter exposure to active drug through blocking the active site resulting in loss of activity as assessed by monitoring the PD or toxicity profile of the drug over the course of the study,  alter the clearance of the drug from circulation, often, but not always, resulting in reduced exposure as assessed by the PK profile of the drug over the course of the study,  interfere with the detection of drug as assessed using a targetbinding format PK assay, resulting in an apparent abnormal PK profile, or  a combination of the above resulting in either an increase or decrease in the net pharmacological activity of the therapeutic. In such cases, analysis of samples for the presence of ADA may help to discriminate true alterations in animal exposure from interference in the PK assay arising from the presence of ADA, and may aid interpretation of observed study effects. Thus, whereas the measurement of ADA may not be necessary to confirm drug exposure and activity if the PK, PD, or toxicity profiles are not altered, it should be performed to aid in the interpretation of altered PK, PD, and toxicity profiles observed over the course of a study. A well designed sample collection schedule for ADA, PK and PD assessments together with development of robust ADA

1. Nonclinical Safety Study:

ADA Screen

Multiple dose and/or Exposure > 7 days

not warranted

2. Is a PD biomarker available? 4.

3. Is the PK assay sensitive to ADA ? e.g. target binding design

Is PD or PK altered?

Possible ADA-driven changes in toxicity profile?

Perform ADA Screen

Quasi-Quantify ADA+

Perform ADA characterization

(Titer or Relative Conc.)

as warranted by risk or for study interpretation

Fig. 1. Decision tree for conducting ADA analyses to support nonclinical study interpretation. The decision tree is intended to guide the investigator through a series of considerations to determine whether ADA analysis is necessary to aid in the interpretation of a study. (1) The impact of ADA on study parameters usually cannot be predicted a priori, therefore, for nonclinical safety studies consisting of multiple doses and/or drug exposure exceeding 7 days, samples should be collected for possible immunogenicity assessment. (2) The validity of a nonclinical safety study relies upon the demonstration of active drug exposure throughout the dosing phase of the study. If continued pharmacologic activity of the drug can be demonstrated through an appropriate pharmacodynamic (PD) marker, the ADA screen may not be necessary. If a PD marker is not available, a PK assay with an appropriate format may provide similar information about exposure to active drug. (3) If the PK assay relies upon the binding of the drug to its intended target, the effect of ADA that either neutralize the activity of the drug or cause a change in drug clearance would be visible in the results of the PK assay. When an ADA-sensitive PK assay is used and the PK profile is not altered, the probability that ADA have affected active drug exposure is low and therefore an ADA screen may not be warranted. If the PK assay is not sensitive to the presence of neutralizing ADA, and no alterations are noted in the resulting PK profile, without a PD marker, no assumptions regarding the presence or absence of neutralizing ADA can be made. In this latter scenario, the performance of the ADA screen is warranted. In addition, if the PK is altered, performance of ADA analysis is warranted to confirm the association with ADA. (4) The toxicity profile of the study must be taken into consideration with the available PD and/or PK profiles. If there are unexpected observations in the study parameters (e.g., clinical observations, clinical pathology or histopathology) that could be attributed to the presence of ADA, the performance of the ADA screen is warranted. This decision tree is intended to provide a framework for reducing the burden of developing, validating and performing ADA analysis when such analysis is unlikely to be informative. It is not a requirement and is not intended to discourage decisions to proactively perform ADA analysis based on other considerations (e.g., when the investigator expects immunogenicity issues or due to drug development timeline considerations).

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characterization and analysis methods are critical pre-study activities to ensure proper interpretation of the data obtained in the study. Moreover, the selected PD biomarker(s) should be both robust and sensitive to changes in exposure to biologically active drug and thus suitable for this purpose. 4.1. Sample collection and analysis considerations Sample collection for possible immunogenicity analysis should be included in all toxicology studies where data on ADA may inform study interpretation; we propose a decision tree to facilitate this evaluation as described in Fig. 1. The samples may be stored to ensure availability of sample for analysis should it be necessary. As demonstrated in Table 1, ADA have been detected in nonclinical studies as early as 1 week after initiation of treatment. Thus, even short-term preliminary toxicology or dose range finding studies may require immunogenicity testing, particularly for agents that are highly immunogenic. 4.1.1. Timing of sample collection Sample collection time points to adequately assess the ADA response should be carefully considered during study design. Because samples from some animals may have pre-existing crossreactive antibodies or high levels of background, sample collection before administration of the first dose (termed pre-dose or baseline samples) is essential. Analysis of samples from vehicle-treated control animals may also be informative and can be used to identify misdosing. After dosing has been initiated, one must consider the possibility of drug interference in the ADA assay, when drug is present in the sample. The degree to which drug will interfere with the detection of antibodies is highly dependent on both the characteristics of the antibodies that develop and the assay format. Ideally, samples should be collected at regular intervals during the study when drug levels are low or absent to minimize assay interference, although this may be problematic for biologically-derived therapeutics with long half-lives and/or that are administered at highdoses. To circumvent assay interference, studies may be designed to include a wash-out period with an assigned recovery group to allow an assessment of ADA when drug levels are low or absent. However, in such cases it may not be possible to directly establish the ADA status of animals sacrificed prior to drug wash-out. In addition, when ADA are detected during the recovery period it may be difficult or impossible to establish when the response initiated and the affect such ADA might have had during the dosing phase. Ideally, analysis of the baseline samples and an appropriate end-of-study sample after a drug wash-out period will provide definitive evidence of the ADA response of animals during the conduct of the study. For therapeutic agents with short half-lives or with availability of assays that have minimal drug interference, it may be possible to evaluate samples collected during the dosing phase for the presence of ADA. Such analyses are particularly relevant when there is evidence that ADA may alter PK or PD during the dosing phase. To allow a subsequent analysis of ADA during the dosing phase, sera may be banked for contingent analysis (e.g., to investigate unusual PK data or toxicological findings) (Shankar et al., 2007). For each sample collected for ADA, samples should also be obtained to determine whether drug is present, with the understanding that the PK assay may be affected by the presence of ADA. The strategy for reporting ADA results is discussed in Section 4.4. The evaluation of the drug tolerance of an assay, using positive controls, is helpful in the selection of the appropriate assay format and optimization of assay conditions for use in the detection of ADA. However, the drug tolerance level determined in these exper-

iments is applicable only in the context of the positive control antibodies that were utilized in this evaluation. Because study subjects will vary in their ADA repertoire, the true drug tolerance in the context of antibodies present in the study samples may be different from that obtained with the positive controls. As may be inferred from the preceding discussion, an evaluation of sera for the development of ADA and the correlation of these antibodies with alterations in PK or PD is best realized using species that are large enough to allow both serial sampling and parallel analysis of serum samples for PK, PD, and ADA endpoints. Whereas this is practical when using non-human primates, it may not be possible when conducting studies using rodents, particularly mice. In such cases, the study may be designed to allow discrete analyses of toxicity, PK, PD and ADA endpoints from similarly treated cohorts of mice with collection at similar study time points to allow inferential analysis of effects observed across treatment groups. Preferably, one would like to have PK and ADA data from the same mouse, although this may limit the amount of blood available for clinical pathology or PD analyses. In the end, this is a challenging situation and one may be constrained to making correlations or associations between similarly treated animals when one might want to have all the data in the same animal. 4.2. Characterizing the immune response In general, immune responses should be characterized to the extent necessary to interpret the study, including whether antibodies may underlie changes in exposure, PD response, or toxicity. An ADA screening assay should be performed on samples collected at appropriate time points throughout the study to determine which animals are positive for immune responses. The screening assay should be designed to detect binding antibodies (IgG and IgM, with IgA and IgE as appropriate) in test samples based on a conservative approach of accepting a greater false positive rate rather than false negatives. It is also a common practice to determine a relative concentration of ADA in the samples. Typically ADA results are reported in titer units, but other data formats such as ‘‘mass units” and ED50 have also been used. Because ‘‘mass units” results will be highly dependent on the positive control used for preparing the calibrator curve, parallelism will need to be demonstrated between this ‘calibrator’ reagent and study samples; in such cases it may be best to avoid the mass units approach and use the titer approach instead. Regardless of method, linearity should be established to identify potential prozone effects. Although recommended in ICH S6 to implement a tiered approach to characterizing ADA screen positive samples (ICH, 1997) and highly advised for clinical evaluation of ADA (Koren et al., 2008), confirmation of specificity is generally not needed in animal studies, especially when sample volume is limited or titers are high. It may be useful to confirm the specificity of samples when the result is suspected to be aberrant (i.e., when a placebo or a pre-dose sample yields a positive result) using methods such as competitive inhibition (Koren et al., 2008; Shankar et al., 2008). When competitive inhibition is used to confirm specificity, the concentration of drug used to compete should be carefully evaluated because high titer and IgM responses may be difficult to diminish. The study samples may also need to be diluted to enable confirmation with excess drug in nonclinical studies, due to the presence of high levels of drug that may already be present in the samples. Other characterization may be appropriate depending on the toxicity findings that may be attributable to ADA; some examples of toxicity observations that may be attributable to ADA include:  allergic manifestations,  complement activation,

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 neutralization of an endogenous homolog,  cytolytic activity (e.g., due to binding of cell membrane associated drug),  immune complex-mediated toxicological findings. The scope of such efforts and evaluation of their attribution to the development of ADA is beyond the scope of this review, but may be critical to understanding the pathophysiological effects of ADA in the nonclinical species. 4.2.1. Assay validation considerations The screening assay to detect binding antibodies should be validated to establish its sensitivity, reproducibility, susceptibility to matrix effects and to establish the ADA assay cut-point that will be used to distinguish positive and negative samples. Recommendations for the development and validation of the assays have been extensively described in other publications (ICH, 1995a,b; MireSluis et al., 2004; Geng et al., 2005; Shankar et al., 2008). The extent of validation may increase as the candidate drug moves through preclinical and clinical stages of development. Discussions between the sponsor and regulatory representatives are encouraged to determine validation expectations. Assay validation is facilitated with availability of positive control samples. The positive control will likely differ from actual study samples in terms of affinity and avidity for the drug, and in terms of isotype, epitope specificity, and antibody concentration. In some cases, the positive control may not even be from the same species as the toxicity model. Therefore the performance of actual samples in the assay may vary from that determined for the positive control. However, the validation does serve to demonstrate the suitability and reliability of the test system. Sera from animals used in short-term, non-terminal toxicology or efficacy studies may be used to generate a positive control ADA reagent, which is critical to the development and validation of ADA assays. The animals from such short-term studies may be transferred to another study in which weekly or bi-weekly doses of drug in adjuvant (e.g., TiterMax) are administered (via intramuscular or subcutaneous routes) to generate high titer positive control for ADA studies. When purified positive controls are not available, alternatives such as use of polyclonal antisera or commercially available anti-species antibodies can be used as positive controls, with reporting of sensitivity in terms of concentrations or titers as appropriate. The ADA screening assay should have a cut-point that is used to distinguish positive and negative samples. The assay cut-point may be established statistically based on evaluation of a large panel of individual representative animal samples. One statistical approach to establishing a cut-point for human immunogenicity assays relies on the 5% false positive rate in detecting ADA from drug-naïve individuals (e.g., mean + 1.645  SD for normally distributed data; Mire-Sluis et al., 2004; Geng et al., 2005). The false positives detected are then eliminated by a second tier confirmation assay typically based on antibody specificity. The 5% false positive rate (a) has been recommended as a conservative approach for human clinical immunogenicity assays by potentially allowing a high proportion of false positives when the ADA incidence rate is low to ensure detection of true positives (Mire-Sluis et al., 2004; Shankar et al., 2008). There is no currently accepted standard for establishing nonclinical immunogenicity assay cut-points, and the default has often been to rely on the approach used for human assays. Because the goal of nonclinical immunogenicity evaluation is to understand the impact of ADAs on drug exposure and activity, the approach of incorporating a 5% false positive rate, while acceptable, is not generally necessary. A 1% false positive rate may be justified for these studies (e.g., mean + 2.33  SD for normally distributed data or using empirical estimates of the 99th percentile). Other ap-

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proaches such as the use of the median and median absolute deviation may be used, provided that the approach is appropriately justified and based on the assessed immunogenic risk of the drug and the assay methodology (e.g., Klakamp et al., 2007; Shankar et al., 2007, 2008; Koren et al., 2008). It is not uncommon to find the study animals obtained from a single source can be significantly different from the population utilized to derive the assay cut-point during assay development/validation. In these cases, differences in the background of these different populations can lead to erroneous results because the assay cut-point is derived from background reading of negative samples. In these cases, it is recommended that pre-dose samples (if at all possible) be obtained as early as possible and evaluate the appropriateness of the cut-point or derive a study-specific cutpoint if necessary. 4.3. Neutralizing antibodies in nonclinical studies The presence of ADA may not only affect systemic exposure, but also interfere with or neutralize drug activity at the site of action. As stated in the ICH S6 guidance document, ADA responses that are detected in repeat dose toxicity studies should be characterized to aid in the interpretation of the study and suggests determination of neutralizing and non-neutralizing activity as an example. In this guidance document, a neutralizing antibody response refers to a response that causes substantially reduced drug activity in vivo. Under many circumstances, confirmation that drug activity has not been reduced (i.e., substantial neutralizing activity is not present) can be performed by measuring exposure and evaluating PD markers of activity in the animal to confirm activity. Alternatively, confirmation of activity may be assessed using plasma concentration data with an ex vivo drug activity (potency) assay. A third option is testing for neutralization potential in an in vitro test system including the following: a functional bioassay, a cell-based receptor (i.e., target) binding assay, or an non-cell-based ligand-binding assay whereby capture or detection reagents rely upon an available target binding site of the drug. However, even with neutralizing ADA data, the lack of exposure or observed biological response due to reasons other that neutralizing ADA (such as partial degradation, inhibition by soluble target receptor, etc.) will remain unexplained. Because ADA binding data along with PK and PD data (when available/appropriate) should generally be sufficient to interpret the study, the relative merits of data from a neutralizing antibody assay should be balanced against the effort and time necessary to develop the assay. In their review, Shankar et al. rightly questioned the need for characterization of neutralizing ADA responses in nonclinical studies (Shankar et al., 2007). In cases where the protein drug sequence is highly conserved across species and there is the potential for neutralization of critical endogenous proteins, the neutralizing antibody assay may inform a potential safety risk and the potential impact of endogenous homolog neutralization by ADA. In this situation, the cross-reactivity of the neutralizing ADA to the endogenous counterpart should also be tested. Alternatively, a neutralizing ADA activity assay may be useful if there are no useful PD biomarkers and in the absence of an ex vivo drug activity assay. 4.4. Data presentation and interpretation 4.4.1. Data presentation ADA data should be presented along with toxicokinetic (TK) data as a standard element of the bioanalytical portion of the nonclinical study report or they may be reported as a separate report. Data tables should be included showing the individual and group ADA results (as titer or other quantitative measure) at each time point tested, including baseline results. Summary data (as tables or fig-

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ures) should be prepared that facilitate analyses of PK, toxicity, and/ or relevant PD endpoints among animals with and without ADA. Such analyses will be made by regulatory toxicologists of data that are submitted for regulatory review, and it is in the best interest of the sponsor to understand the relationship between antibody status and effects on PK (e.g., AUC or Cmax), PD or toxicity by preparing summaries of these data prior to submission. In such cases, it may no longer be relevant to refer to nominal dose groups to ‘bin’ animals for summary analyses, but to use alternative binning (e.g., antibody high and low, or based on range of measured exposures). The determination of a reportable ‘‘positive” ADA response is typically based upon the sample response in comparison to a threshold or cut-point value established during assay validation. In such an analysis, a positive result means that antibody was detected and a negative result means that antibody was not detected at any time during the study (or other pre-specified criteria). In addition, the number of animals in each group with an increased ADA response over baseline (% incidence of antibody induction) should be reported. This is usually reported as the percent of animals that had any positive (or elevated) post-treatment sample. In cases where baseline samples may not be available, any positive post-treatment sample would be considered evidence of an immune response. To facilitate the association of toxicity findings likely to be related to immune response the prevalence of positive results at each time point should be reported for each group, including positive results obtained in pre-dose (baseline) samples. Because the development of ADA may affect animal drug exposure by increasing or decreasing clearance, an analysis of PK parameters (Cmax, AUC, terminal half-life) among ADA+ and ADA animals should be conducted. Such a comparison would provide information as to whether apparent exposure is increased or decreased as a result of ADA formation, and whether these alterations in apparent exposure contribute to alterations in PD or toxicity (e.g., see Case Study 5). In the end, the development of ADA may increase the variability of both apparent exposure and response of animals within any dose cohort, and an assessment of the observed effects among individual animals may need to be conducted based on exposure rather than administered dose. Whereas dose vs. exposure ratios are normally based on results from all animals in a group, if there are clear differences in toxicity due to immunemediated findings that are not expected to occur in humans, it may be appropriate to report the exposure ratios separately. Presentation of summary tables combining ADA, pertinent exposure data (e.g., AUC, Cmax), and key PD parameter(s) for each individual animal over time would facilitate interpretation and regulatory review of the nonclinical study. 4.4.2. Baseline ADA response Due to the variability of the immunogenicity assays, frequently encountered matrix interference, and potential for endogenous cross-reactive antibodies including pre-existing antibodies towards human antigens, low-level reactivity may be observed in baseline samples or in control animals that cannot always be attributed to non-specific reactivity. The sample or animal must be reported as positive and test results in dosed animals should be interpreted in the context of the positive baseline/control reactivity. If positive results were not expected in baseline or control samples (e.g., based on known presence of cross-reacting endogenous antibodies, or based on positive results in the validation matrix interference evaluation) an investigation should be performed to eliminate the possibility that the presence of ADA was due to accidental exposure to the drug. In cases of confirmed pre-existing titers at baseline, a twofold increase in titer post-treatment is usually considered a treatment-emergent ADA-positive sample. MireSluis et al. (2004) describe an alternative statistical approach to identify the minimum significant fold ratio during assay validation.

4.4.3. Assessment of interference In addition, the possibility of drug interference in the ADA assay should be considered when interpreting the reported results. Determining the relative sensitivity of an ADA assay in the presence of drug, ‘‘drug tolerance”, is a regulatory expectation during the selection and validation of the assay, and yet it is not directly applicable to study samples because the actual drug tolerance of each sample will vary depending on the sample ADA affinity, avidity, and titer. For ADA assays that are affected by the presence of drug, a statement of possible drug interference should accompany the results (Koren et al., 2008), regardless of the drug tolerance determined during validation of the assay. The presence of drug in a study sample may impact detection of ADA (resulting in false negatives) or may underestimate titers, and therefore make interpretation of PK, PD, and other study observations difficult. Even when the presence of circulating drug limits the usefulness of the immunogenicity assay data for making a conclusion about presence of antibodies, the PK profile may often show patterns consistent with an immune response. Newer analytical methods are being developed and used in an effort to minimize or eliminate assay interference (e.g., Sickert et al., 2008; Neubert et al., 2008). 4.5. Comparability studies Whereas immunogenicity results may be compared when the samples have been analyzed with a particular assay, it is much more challenging (and may not be possible) to compare immune responses between different products. Changes introduced during the production process, including those associated with glycosylation, deamination, oxidation, aggregation, PEGylation, process-derived impurities (e.g., host cell proteins), and package leachates may affect immunogenicity of a given therapeutic (reviewed in Chirino and Mire-Sluis, 2004; Rosenberg, 2006; Sharma, 2007). The in vivo assessment of immunogenicity in nonclinical studies has been suggested as a key opportunity for evaluating the antigenic and immunogenic characteristics of different biopharmaceutical variants or formulations after manufacturing changes (reviewed in Wierda, 2008). Recent EMEA draft guidance supports the use of animal models as ‘‘. . .part of the comparability exercise both for similar biological medicinal products and for changes in manufacturing processes.” (EMEA, 2007). Consistent with previous conclusions made in this review, the goal of such an analysis is not to predict either the incidence rate or antibody titer that may occur during human therapeutic use with biopharmaceuticals. Instead, their utility is in providing a means to select biopharmaceuticals with the most favorable immunogenic profile following testing in a vertebrate animal with an intact immune system and to provide verification of bioanalytical similarities between formulations if the latter is an issue. As stated earlier, controversy in industry remains about the merit or utility of such comparative immunogenicity data in animals given the lack of relationship to human immunogenicity. In addition, data generated in such a study may be difficult to interpret given limitations of study power, assay variability, and other factors that may make such a tool relatively insensitive to subtle effects. The comparative evaluation of immunogenicity has been conducted using transgenic mice that express the human protein of interest (insulin, tissue plasminogen activator, interferon-b1a (IFN-b1a), and Fas ligand inhibitory protein, see Wierda, 2008). However, a transgenic protein may not be expressed with the same structures (e.g., isoforms and post-translational modifications) or concentrations as in humans and the therapeutic protein may interact differently with the animals’ immune system components (MHC etc.), therefore transgenic models may not be predictive of the immunogenicity of the therapeutic in humans. Recently, Jaber and coworkers (2007) used non-transgenic Balb/C mice to screen

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and select a less immunogenic formulation of RebifÒ (human IFNb1a) (Jaber et al., 2007). The selected formulation proved to be less immunogenic in a Phase I clinical trial when compared to a second formulation or to the current therapeutic IFN-b1a. Also of promise for comparative immunogenicity testing, the human histocompatibility leukocyte antigen transgenic mouse has been utilized in vaccine development to identify T cell epitopes and other immunogenic epitopes relevant to man (Wierda, 2008). Thus, animal models have been useful for interrogating the relative immunogenic properties of biopharmaceuticals, especially in comparison to an appropriate control such as the native molecule intended for replacement with a human therapeutic biological, or a formulation preparation that is well characterized. Additionally, there is now the possibility of a degree of standardization that can be accomplished with these models, which should improve the interpretation of the data based on the comparability of responses, and efforts are being made at developing predictive in vitro screening assays as well (e.g., Jaber and Baker, 2007). However, consistent with previous conclusions in this review, results of comparative immunogenicity studies in nonclinical species may have little or no relevance for predicting relative immunogenicity of the therapeutic in humans. The conduct of such comparative immunogenicity analyses is complicated by the need to ensure that the ADA assays used to establish comparability have similar performance. In some cases, these technical issues may be resolved because the assay format can use the same test article and detection reagents. However, establishing comparable assay performance may be an extremely difficult issue if each assay requires different test articles or capture/detection reagents, with different affinities and susceptibility to interference. Unless this issue is resolved, there may be no way to separate differences in immunogenicity from differences in assay performance with the two test articles. In addition, analytical methods that involve modifications to the drug, such as labeling with biotin or ruthenium, introduce the possibility of altering assay performance and confounding the study interpretation. Finally, one should consider that animals treated with therapeutic proteins are variable with respect to incidence, titer, time of onset and persistence/transience of the ADA response. Therefore, one must carefully consider the study size/power, sampling time, and signal/noise when conducting comparative immunogenicity studies to ensure that the design will be sufficient to address the question. As discussed above, an evaluation of alterations in PK and PD in conjunction with the ADA data may also support data evaluation and interpretation, and inform selection of the best candidate for manufacturing.

5. Managing the effects of antibody formation in nonclinical programs In cases where immunogenicity is anticipated to interfere with the interpretation of the toxicology studies; it may be necessary to adapt the design of nonclinical studies to minimize or overcome immunogenicity. Evaluation of available screening studies can inform whether one may expect the development of ADA with longer-term dosing, and whether these ADA may impact the exposure/ PD to the test article or induce toxicity. Some strategies to continue the toxicological characterization of the biotherapeutic in the presence of ADA are discussed below. 5.1. Dosing through In cases where ADA are detectable but are not neutralizing/ clearing the exposure to active drug, it is reasonable to consider conduct of toxicology studies of standard duration. However, the

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development of clearing/neutralizing ADA may limit exposure to active drug. In such situations, a decrease in exposure due to neutralizing or clearing antibodies initiates an unintended recovery period for the animal, and toxicity information is only relevant during the period of active exposure before antibodies have formed. The administration of very high-doses of drug may overwhelm the available ADA or may induce tolerance (see discussion below). Design of nonclinical studies using dose levels intended to overwhelm the ADA response is commonly called ‘‘dosing through” the ADA response. When dosing through is used to overcome the ADA, the effective exposure of the animal to active drug may be difficult to establish as each animal will vary over time in terms of ADA titer and affinity. In this case, an assessment of study data using the techniques described in Section 4 should inform study interpretation. Theoretically, one should generally be able to dose through an ADA response. However, in practice, this may not be feasible due to limitations of dose administration or due to study design limitations. When considering use of dosing though, there are a number of pragmatic questions to be addressed in the study design, which can be well informed by data from previously conducted studies. For example, Data from previous studies may show that the lowdose groups are expected to lose exposure, thus one could consider eliminating these groups from future studies. Alternatively, data from previous studies may provide data on expected immunogenicity rates, thus informing expected variability in exposure and response, which can help in establishing group size. Other decisions to consider include whether to adjust individual doses based on measured exposure and whether to consider stopping rules based on monitoring of drug exposure (if practical) so as to obtain meaningful toxicological information for animals during periods of active exposure. These issues are compounded in small animals where it may not be possible to obtain full pharmacokinetic profiles to document drug exposure over time due to blood draw limitations and the need to collect concurrent clinical pathology data. In this regard, use of satellite cohorts to collect clinical pathology, PK and/or ADA data are discouraged as it defeats the informational value of getting concurrent data on exposure and toxicity in the same animal. If dosing though does not appear feasible or informative, the conduct of subsequent nonclinical studies including sub-chronic, chronic, and reproductive toxicity studies may not be possible and other techniques are required, as discussed below. 5.2. Staged dosing Nonclinical toxicology studies investigating the reproductive and developmental toxicity of therapeutic biotechnology-derived drugs can be challenging if the development of ADA ablates drug exposure. One strategy to assess the toxicity of a biotechnologyderived drug in longer-term studies, specifically reproductive and developmental toxicity studies, is the use of ‘‘staged” dosing. In this strategy, the test agent would be administered for shorter periods during critical periods of development rather than administering the drug for the entire duration of the study. For example, in a developmental toxicity study to assess the effects of the drug on pre-natal and post-natal development, the drug would typically be administered from implantation to the end of lactation. In nonhuman primates the duration of this study could be many weeks to months. Using the staged dosing model, the drug would be administered for shorter periods during this time frame so that potential immunogenicity would not confound the results. ADA may develop within 2–3 weeks of dosing, so animals could be dosed until the formation of ADA. This strategy provides a means to evaluate the reproductive and developmental toxicity during critical time peri-

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ods even if neutralizing antibodies are developed in a short time frame. 5.3. Induced tolerance In certain cases immune tolerance may be achieved by continuous dosing or by using a tolerogenic regimen, such as observed for agalsidase beta (Table 1). However, the systemic induction of tolerance is not easily predicted, challenging the practical utility of this technique. In contrast, the induction of oral tolerance, reviewed above, appears to have more general applicability, and has been reported for a number of agents under various conditions, including tolerance in the presence of adjuvant. Prior oral exposure was used by Meritet et al. to induce tolerance towards a subsequent SC treatment of mice with recombinant human IFN-a and this strategy significantly reduced the IgG antibody response detected 28 days after SC administration of GM-CSF (Meritet et al., 2001). These results demonstrate the feasibility of oral tolerance towards a subsequent parenteral administration of recombinant proteins in nonclinical species. Recently, De Groot et al. (2008a) have reported induced tolerance to dust mite allergen in sensitized mice upon administration of a murine IgG-derived peptide that induced activation of natural regulatory T cells. Induced tolerance, whether by the methods of Meritet et al. or De Groot et al., is an approach of future interest as alternatives to immunosuppressive intervention. However, many practical questions remain to be answered before these may be generalized and/or accepted by regulatory agencies as a means to overcome immunogenicity concerns in more standardized nonclinical studies. Use of immunosuppressive therapy is also a possible option to suppress an immune response to the therapeutic protein. Such strategies were used to suppress anaphylactic reactions towards agalsidase beta and darbepoetin alfa (see Table 1), allowing progression of the studies. These strategies should only be considered with caution as they will affect the general interpretation of the study and leave the animal open to opportunistic infection. 5.4. Use of a protein homologue Even though a homologous protein may induce an immune responses (as seen with treatment of recombinant proteins in humans, Bugelski and Treacy, 2004), use of a homologous protein (i.e., surrogate molecule) may minimize immunogenicity in the toxicology species. This should only be an option if the actual drug intended for human use is an unmodified human protein that is expected to have a minimal immune response in humans. The generation of homologous proteins that can support regulated toxicology studies is a time and resource consuming effort and may be warranted only in specific cases. Although development of a protein homologue is a theoretical option for circumventing treatment-limiting immunogenicity, the practical limitations of developing and qualifying the homologue restrict the application of this approach. 5.5. Use of genetically modified species Genetically modified species (e.g., transgenic mice with human T cell epitopes, rFVIII deleted mice/hemophilia A mice) may be used to assess toxicity or efficacy in cases where other relevant species are not available (e.g., Bugelski et al., 2000). It is important that these animal systems are well characterized to assure that findings can be correctly interpreted, although these models may pose certain challenges because only some parameters are modified in transgenic mice while other tissues and organs are still mouse specific.

5.6. In silico and ex vivo prediction of immunogenicity Recently in silico approaches to predict immunogenicity of drugs and vaccines have emerged and are being applied to predict the immunogenicity of therapeutic proteins in humans (Flower and Doytchinova, 2002; Korber et al., 2006; De Groot and Moise, 2007; De Groot et al., 2008b; Evans, 2008). Potentially such methods can be used to de-immunize a protein by modifying highly immunogenic epitopes using computational models generated from information on human immune responses to therapeutic proteins and vaccines. In addition to in silico modeling, ex vivo systems may be used to identify and evaluate immunogenic epitopes of therapeutic proteins (reviewed in De Groot et al., 2008b). Currently these methods may not be predictive for nonclinical species, and there is limited clinical data to validate the approach (e.g., Jaber et al., 2007; Koren et al., 2007; Tatarewicz et al., 2007). Of course, regardless of the in silico or ex vivo predictions, other factors will influence the observed clinical and nonclinical immunogenicity, including individual genetics and the pharmacological properties of the molecule, formulation, and mode of administration, which may circumvent tolerance pathways as described previously. For example, in one case, in vitro proliferation of human T cells towards peptide epitope regions of interferon-b was associated with individual donors with a specific haplotype (DRB11501-DQB10602; Stickler et al., 2004) distinct from the haplotype of patients who develop an anti-interferon-b antibody response (DRB10701; Barbosa et al., 2006).

6. Case studies Presented below are case studies illustrating possible effects of ADA on nonclinical study interpretation. All procedures involving the use of animals were reviewed and approved by appropriate Institutional Animal Care and Use Committees under guidelines contained within the ILAR Guide for the Care and Use of Laboratory Animals (Institute for Laboratory Animal Research, 1996), and within animal care programs accredited by the Association of the Assessment and Accreditation of Laboratory Animal Care International. 6.1. Case Study 1: ADA present but minimal impact on PK or PD The first case study describes the evaluation process for a recombinant human IgG1 antibody that is directed to a soluble protein. In this example, ADA responses were encountered in many of the test animals, but the impact on PK, PD and study interpretation were minimal. As part of validation studies, the degree of interference from both drug and target were evaluated over a range of concentrations. In some but not all studies, additional assays were conducted to identify epitope site (e.g., Fc vs. Fab). Neutralization assays were not conducted for nonclinical safety studies. In general, sera for ADA analyses were collected weekly or less frequently throughout dosing periods. To minimize drug interference, samples were typically collected just prior to dose administration. During recovery periods, samples were collected every 2–4 weeks. As an example, one 6-month study included sampling on days 27, 0 (pre-dose), 14, 28, 91, and 182 of the dosing period and on days 3, 17, 31, 59, 73, 87, 101, 129, 157, and 182 of the recovery period. In a 6-month subcutaneous (SC) safety study, 5/60 cynomolgus monkeys were ADA-positive with onset occurring between 2 and 4 weeks post-first dose. In a separate 6-month SC safety study, 3/ 20 cynomolgus monkeys were ADA-positive with onset occurring between 2 and 13 weeks post-first dose. In all cases, there was no clear impact on PK in ADA-positive animals and during recovery

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the presence of ADA did not have a significant impact on clearance. For this reason, ADA-positive individuals were not excluded from consideration in assessing PK parameters. There was no clear impact on drug PD nor were there any ADA-associated adverse events. Based on these findings, the impact of ADA on study results and interpretation was considered minimal and long-term studies in monkeys were considered to be feasible without the need to incorporate specific ADA-related design modifications. 6.2. Case Study 2: drug interference in ADA detection When pronounced ADA responses are encountered, PK, PD, and safety data must be carefully evaluated to ensure a proper study interpretation. In the following example, a therapeutic recombinant human monoclonal Ab was evaluated in cynomolgus monkeys with weekly SC dosing up to doses of 100 mg/kg for 6 weeks (seven doses) with 8 weeks of recovery. Drug concentrations were determined by antigen-capture ELISA. Lower than expected drug levels for one animal in the high-dose group were observed prior to dosing on days 29, 36 and 43, as well as at each time point after the 7th dose administration on day 43 (recovery phase). Rapid apparent drug clearance and the temporal onset (by day 29) in this individual were taken as indirect evidence of a prominent ADA response. ADA titers were measured at the end of dosing (day 43), and during the recovery phase at 4 and 8 weeks after last dose. All three samples were positive for the individual in question. As the presence of drug may impact the accuracy of the ADA assay it is often important to assess this impact to adequately understand how much drug is physically present in circulation. In this example, a solid-phase extraction with acid dissociation procedure was used in an effort to reduce the drug interference in the ADA assay. During the assay validation process it was determined that drug levels of 10 lg/mL or less had minimal impact on assay performance. However, as drug concentrations in the high-dose group reached levels of approximately 4000 lg/mL, the potential for drug interference exists and the potential for false negatives or aberrantly low ADA results can and should be expected. For this reason, adequate sampling during the recovery phase is important as ADA responses may be less masked as drug clears. In this case, ADA titers were more prominent after 4 weeks of recovery than immediately following the last dose. Because values for the ADApositive animal were lower as compared with other animals given 100 mg/kg and because, except for this animal, exposure parameters of the high-dose group (AUC and Cmax) for days 1, 36, and 43 of the dosing phase were dose linear when compared with those of the low- and mid-dose groups, this individual was excluded from mean and standard deviation calculations in the 100 mg/kg dose group. 6.3. Case Study 3: utility of PD markers in assessing drug exposure Apparent decreases in PK are not always associated with loss of PD activity. In the following example, lower than expected PK levels were encountered in most treated animals; however, careful examination of PD did not detect a concomitant loss of drug activity. Monkeys were treated once weekly with a therapeutic monoclonal IgG (25 mg/kg/week; IV) for 2 weeks and subsequently monitored during a 4-week recovery period. Lower than expected drug levels were observed in 4/6 animals as determined by the TK immunoreactive ELISA. The reduced TK profile was attributed to the formation of ADA. ADA were measured by surface plasmon resonance (i.e., BiacoreÒ) in samples collected at the end of the 4week recovery phase to allow for drug wash-out. ADA were confirmed to be present in all four of the monkeys with altered TK, however, the PD of the drug were not impacted by the presence of the ADA as determined by the monitoring of a PD marker. The

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PD biomarker demonstrated continued activity of the drug up to 10 days post final dose. As a result, the drug exposures were considered sufficient to enable adequate evaluation of safety. However, it is also important to consider the dynamic range or response of the PD marker. For example, drug impact on a PD response may be saturated above a given drug concentration. Alternatively, the PD marker may require a finite duration of time after treatment is initiated to be elicited or may persist for some time after loss of exposure before the response is reversed. Therefore, knowledge of the expected PD response profile during drug wash-out will provide important information in determining the extent of drug exposure and the potential effects of ADA. Because activity of the drug was demonstrated in the presence of ADA, the PD biomarker was known to be sensitive to drug activity, and the PD recovery profiles were not substantially impacted by ADA, the alteration of PK was assumed to be an assay interference issue rather than a loss of circulating drug. 6.4. Case Study 4: study design changes to minimize impact of ADA In some cases the prominence of ADA necessitates modifications to study design to ensure adequate exposures. The following example illustrates how a prominent ADA response was addressed during the development of a recombinant chimeric IgG1 antibody that was designed to target circulating immune cells. As drug activity was restricted to non-human primates, acute, chronic and reproductive nonclinical safety studies were conducted in cynomolgus monkeys. In one early study, cynomolgus monkeys were administered 20 mg/kg/week by IV injection for four or 8 weeks. As the chimeric monoclonal Ab contained both murine and human constant regions, an ELISA was used to detect antibodies produced against either the mouse or human protein sequences. Samples were collected pre-dose and 24 h post-dose and weekly throughout recovery. Altogether, 5/12 drug-exposed animals were ADA-positive. All ADA-positive animals had a marked decrease in Cmax, Ctrough, and AUC beginning on study day 15. Typically, ADA were detected within the first 2–4 weeks of dosing. In three animals, ADA were not detected until the drug washout period (study days 29–37); however, as PK profiles were substantially impacted as early as day 15 of dosing for these animals it was presumed that drug interference masked the presence of ADA. ADA was associated with decreased PD activity as measured by changes in circulating target. Epitope mapping studies identified the mouse/human joining region as a major site of ADA binding. There was weak reactivity against the murine variable region and no activity against the human constant region. The presence of ADA did partially impact the power of the study. Given the limited number of ADA-negative animals, descriptive PK parameters were not calculated for the dosing cohorts. In subsequent studies, the impact of ADA was mitigated by the several strategies. For example, adequate PK exposures could be maintained by administering higher dose levels (50 and 100 mg/kg/week). At these doses the impact on PK was minimal and the presence of ADA did not impact PD. This strategy is often referred to as ‘‘dosing through” an ADA response. In the case of some immunomodulatory drugs, the direct targeting of immune cells may also serve to blunt the humoral response, particularly if the target is involved with the development, maturation or production of Ig responses. Another strategy commonly employed for reproductive safety studies is to include additional cohorts with narrow but overlapping windows of dosing to ensure adequate exposure throughout the period of study. In this example, a pre- and post-natal development study in cynomolgus monkeys was designed to evaluate reproductive risk from gestation day 20 through day 28 postpartum. Because it was not certain that adequate drug levels could be maintained for the entire period of study, additional cohorts

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were added with smaller windows of dosing to minimize impact of ADA formation. In this case, two additional cohorts with 8-week windows of dosing (gestation days 76–132 and gestation day 132-day 28 postpartum) were added. Overall, sera from 19% of drug-treated monkeys were ADA-negative. Because the presence of ADA did not clearly impact serum drug concentrations, no animals were excluded from PK analyses and group PK parameters were computed for all cohorts. The incidence of ADA in this study may have been affected, in part, by the decreased humoral response often encountered in pregnant animals (Hibma and Griffin, 1987). 6.5. Case Study 5: difficulties in delineating ADA impact on PD

20 Cycle 1

Recovery Cycle 2 Cycle 3

15

Cycle 4

Legend Control (0 mg/kg)

10

0.01 mg/kg 0.1 mg/kg 0.5 mg/kg

5

Day 75

Day 61

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Day 43

Day 39

Day 34

Day 29

Day 25

Day 20

Day 15

Day 6

Day 11

Day 1

0 Week-1

C-reactive protein concentration (mg/dL)

In this case study, animals received a recombinant immune stimulatory cytokine via daily intravenous injection for 5 days followed by nine dose-free days, which constituted a 2-week treatment cycle that mimicked the proposed human treatment regimen. The study evaluated response to treatment over four treatment cycles, followed by a 28-day recovery period. For the purposes of this case study, we limit the discussion to several key indicators of biological activity (i.e., C-reactive protein and hematocrit), drug PK and ADA formation. ADA titers were quantified by sandwich ELISA using Protein Ghorseradish peroxidase, which recognizes cynomolgus IgG, for the detection reagent. Given the relatively short drug half-life (<1 h) no drug-related interference in ADA detection was anticipated. A cellbased bioassay was also developed and qualified to assess the neutralizing potential of cynomolgus serum samples. This bioassay used a BaF3 cell line engineered to express the human cytokine receptor, which required presence of cytokine for growth and prevention of apoptosis. IV injection of the cytokine induced increases in serum CRP, with peak levels occurring at the end of the dosing period and partial or complete reversibility during the dose-free periods of each treatment cycle. The magnitude of these responses diminished over the course of successive treatment cycles (Fig. 2). To evaluate whether the diminished response could be attributed to antibodyrelated changes in pharmacokinetics, the t1/2, Cmax, and AUC were evaluated over successive treatment cycles among binding antibody positive and negative animals (Fig. 3, data shown for AUC only). Despite a high degree of variability, analysis of PK in individual animals demonstrated a decreased exposure between the first and last treatment cycles as assessed by t1/2, AUC and Cmax. How-

Fig. 2. Case Study 5: effect of cytokine treatment on group median serum Creactive protein (CRP) concentration (as an indicator of immune system stimulation) over the course of four treatment cycles of five daily intravenous injections followed by nine dose-free days. Dose-related maxima in serum CRP were observed at the end of the dosing-phase followed by recovery during the dose-free periods of each treatment cycle. A decrease in maximum CRP stimulation was observed over the course of four treatment cycles.

ever, the presence of antibodies alone may not be sufficient to explain these effects as evidenced by the lack of change between the first and second dosing cycles, when the majority of animals became ADA-positive. One noted finding was a relative increase in ADA titer over the course of successive treatment cycles (data not shown), which may contribute to the observed decrease in exposure. In addition, it is possible that the nature of the antibody response changed over the course of successive treatment cycles, including a shift towards higher affinity antibodies. Sera from binding antibody-positive animals were subsequently evaluated for the presence of neutralizing activity. Because 7 of 8 animals were binding antibody positive by the second treatment cycle, and all animals were positive in subsequent treatment cycles, the effect of neutralizing antibody formation on cytokinemediated changes in CRP may be evaluated by comparing the pharmacodynamic effects among animals with and without neutralizing antibodies (Fig. 3). These analyses suggest diminished pharmacodynamic effects of the cytokine associated with development of neutralizing antibody activity. Taken together, the binding antibody and neutralizing antibody assays demonstrated both decreased exposure and decreased pharmacodynamic activity of the cytokine over the course of successive treatment cycles. However, these effects appear to explain only some of the observed decreased activity of the cytokine over the course of the study, suggesting that other physiological effects may contribute to diminished response. Some of these effects may include changes in receptor expression, changes in the number of receptor expressing cells, or changes in the population composition of target cells (e.g., a shift toward a younger erythrocyte population). Alternatively, the available assays may have only captured part of the ADA repertoire in treated animals. This case study demonstrates the inherent limitations of current ADA methods for explaining observed changes in nonclinical safety studies, which should be kept in mind when interpreting study results. 6.6. Case Study 6: ADA may often impact some but not all PD markers Recombinant human IL-18 (rHuIL-18), a pluripotent immunostimulatory agent currently being developed for cancer therapy (Jonak et al., 2002), is an example of a protein therapeutic that induced neutralizing ADA in nonclinical species. The immunogenicity of rHuIL-18 was demonstrated early in toxicology studies with an impact on the feasibility and extent of animal studies planned to support the initiation of clinical trials involving repeat administration of the drug over a prolonged period of time, e.g., up to 1 month. To mimic a possible clinical study design, rHuIL-18 was administered to rhesus monkeys daily for 28 days by subcutaneous injection at doses of 0.1, 0.3 or 1.0 mg/kg/day. While rhesus monkey IL18 and rHuIL-18 share 96% sequence homology, data derived from the study indicated an ADA response in all rHuIL-18-treated monkeys by day 14 of the dosing period. Peak ADA response was observed on day 28, and the magnitude of the ADA response (1200–2500 lg/mL) among the treatment groups showed a dose-dependent pattern (Fig. 4). Plasma ADA concentrations declined during the off-treatment period of approximately 6 weeks. The high incidence and magnitude of the ADA response following daily subcutaneous injections with rHuIL-18 corresponded to a decrease in systemic exposure. Systemic exposure to rHuIL-18 was dose-related and increased between days 1 and 7 with quantifiable levels in plasma up to 24 h post dose (AUC0 t 970 3000 ng h/ mL); however, drug concentrations were decreased by day 28 with detectable levels in plasma only up to 8 h post dose (AUC0 t 20– 200 ng h/mL). The markedly lower drug concentrations at the end of the 28-day dosing period were attributed to antibody-mediated clearance.

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0.5 mg/kg, 3

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hr*µg/mL

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2000% 0

1

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2

3

4

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Fig. 3. Case Study 5: drug exposure (as assessed by the areaunder-the curve of the concentration vs. time profile) was evaluated among high-dose animals (0.5 mg/kg) as a function of binding antibody status (ADA+ or ADA , left panels). In addition, peak C-reactive protein (as a percentage change from baseline) was evaluated as a function of neutralizing antibody status (nADA+ or nADA , right panels).

Anti-rHuIL-18 Antibodies (ug/mL)

3500 0.1 mg/kg/day 0.3 mg/kg/day 1.0 mg/kg/day

3000

2500

2000

1500

1000

500

0 Pre-Dose

Day 14

Day 28

Fig. 4. Case Study 6: plasma anti-rHuIL-18 antibody concentrations in rhesus monkeys following daily subcutaneous administration of rHu-IL-18 (days 1–28).

In addition to the effect on systemic exposure, the ADA response resulted in reduced pharmacologic activity of rHuIL-18. Biomarkers of rHuIL-18 activity in monkeys include the induction of IL-12 and neopterin. While both biomarkers were significantly and dose-dependently elevated in plasma of rHu-IL-18-treated monkeys after 1 week of dosing, there was minimal or no detectable difference in neopterin or IL-12 plasma concentrations in the rHuIL-18 treated monkeys by the end of the dosing period, coinciding with high ADA plasma concentrations (Table 2). Interestingly, pharmacologic effects of rHuIL-18 on hematologic parameters (e.g., decreased neutrophils, increased monocytes and

Table 2 Case Study 6: biomarkers of rHu-IL18 activity in rhesus monkeys following daily subcutaneous administration of rHuIL-18 (days 1–28). rHuIL-18 (mg/kg/day) 0 0.1 0.3 1.0 a

Neopterin (ng/mL)a

IL-12 (pg/mL)a

Pre-dose

Day 7

Day 28

Pre-dose

Day 7

Day 28

4.1 3.8 4.5 4.5

3.6 (0.7) 7.5 (2.4) 13.4 (5.1) 17.2 (7.7)

3.7 4.1 6.4 7.6

132 125 123 137

134 155 228 279

169 116 169 176

(0.98) (0.3) (1.3) (1.6)

Group mean ± SE (n = 4/sex/group).

(0.6) (1.1) (2.0) (1.9)

(26) (19) (18) (28)

(31) (18) (41) (55)

(30) (15) (37) (44)

large unstained cells; Herzyk et al., 2002) were still evident at the end of the dosing period, particularly in the high-dose group, despite evidence of antibody-mediated clearance and neutralization of activity. It is possible that the effects of rHuIL-18 on leukocyte populations, established early in the treatment phase, were sustained in the absence of active drug and therefore not reflective of concurrent pharmacologic activity. Alternatively, residual free drug, which was detectable in the TK evaluation, may have contributed to the persisting effect. In summary, the anti-drug antibodies to rHuIL-18 substantially reduced the systemic exposure to the drug and neutralized specific activity associated with rHuIL-18 treatment. The ADA response in the study was consistent with a dose-dependent (dose levels and number of administered doses) immunogenicity observed in previous toxicity studies involving shorter duration (5-day cycles) and intravenous administration of higher doses (up to 75 mg/kg/day; Herzyk et al., 2003). In monkey repeat cycle studies, ADA were associated with severe anaphylactic-like reactions (Herzyk et al., 2003). Furthermore ADA were characterized as neutralizing in an IL-18 dependent cell-based bioassay (Soos et al., 2003). Collectively, the data indicated that chronic toxicity studies would not be feasible due to the high frequency of clearing and neutralizing ADA responses, and adverse reactions attributed to ADA, however sub-chronic studies provided sufficient safety information to progress into oncology clinical programs. Interestingly, in initial clinical studies, rHuIL-18 was immunogenic in some patients, however the response was weak and comparable to most marketed therapeutic proteins (Kirkwood et al., 2006). 6.7. Case Study 7: evidence of drug exposure in the presence of a robust immune response ADA data from nonclinical studies are typically considered of low utility in predicting clinical immunogenicity. In this case study, nonclinical immunogenicity was found to be predictive of undesirable immunogenicity in the clinic. This case also illustrates an example where binding ADA do not substantively impact PK during the dosing period. A recombinant human fusion protein (FPX) consisting of a human Fc region fused with two identical novel 24 amino acid peptides at its N-terminal was administered three times weekly via either SC or IV injections to cynomolgus monkeys at the following doses: 0 mg/kg (SC), 10 mg/kg (SC), 30 mg/kg (SC), 100 mg/kg (SC)

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and 100 mg/kg (IV). After a 1-month dosing period, the animals were allowed to recover for an 8-week period. Antibody samples were collected prior to dosing, on days 15 and 29 of the dosing phase and in the recovery phase at days 36, 57, and 86 from all animals. ADA were detected using a validated surface plasmon resonance (SPR)-based biosensor immunoassay using the Biacore 3000TM instrument. Samples that tested positive in the immunoassay were tested in a validated cell-based assay for development of neutralizing ADA (nADA) to FPX. Also, since a robust PD marker for FPX treatment was not available, the bioactivity of circulating FPX was measured in study samples using a cell-based assay and the results were compared to the PK ELISA results obtained for the same samples. Antibody analysis showed that binding antibodies to FPX were detected in 39/40 dosed animals of which 20% were positive for neutralizing ADA. The binding antibody response was detectable as early as day 15 and neutralizing ADA were detectable in the recovery phase. The comparison of PK profiles of ADA-positive and ADA-negative animals within the dosing phase of the study did not show any significant differences. The bioactive FPX concentrations measured by a cell-based bioassay correlated well with drug levels measured by the PK ELISA demonstrating that the animals were exposed to biologically active FPX despite a robust antibody response during the dosing phase. No significant differences were apparent upon comparison of any toxicological findings in neutralizing ADA-positive vs. neutralizing ADA-negative animals. While in most cases immunogenicity data obtained with protein therapeutics from nonclinical studies is typically not considered to be predictive of immunogenicity in humans, FPX demonstrated immunogenicity in the clinic after a single administration and further development of this molecule was discontinued (Koren et al., 2007). In silico analysis results obtained after the start of the clinical study predicted T cell epitopes in the region of amino acids 11-23 in the carboxy terminal of the peptide portion of FPX. Serum antibody data and in vitro lymphocyte responses provided evidence that the in silico predicted immunogenic T cell epitopes within the carboxy terminal of the FPX peptide region was accurate. It is concluded that the presence of specific T cell epitopes in FPX resulted in the observed immunogenicity of the molecule in both nonclinical and clinical settings. 7. Conclusions The development of an immunogenic response to biotechnology-derived therapeutics designed for human administration pose unique challenges to the interpretation of nonclinical safety studies conducted in animals. The available data suggest that there are a number of factors associated with the therapeutic agent, its formulation, and its administration that contribute to the development of an ADA response in nonclinical species. These factors may be understood in the context of well-established immunological principles, providing opportunities for relating responses in animals to those that may develop in exposed humans. However, there is ever increasing data to conclude that the incidence rate of ADA development in animals is not predictive of responses in humans. Nevertheless, an evaluation of ADA responses in animals remains a critical component for interpreting observed effects in nonclinical studies, including alterations in PK, PD and toxicity endpoints. Such a determination of ADA effects on study outcome requires an integrated approach where available PK, PD and toxicity data are evaluated among ADA+ and ADA animals, and with consideration of the strengths and limitations of the methods currently available for assessing PK and ADA formation. Because the formation of ADA can have various, diverse effects on the conduct and interpretation of nonclinical studies, there is a significant

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