In contrast to new chemical entities, biotherapeutic drugs are potentially immunogenic, and, in rare cases, treatment with such products can lead to severe and devastating illnesses in humans. Therefore, the importance in understanding how immunogenicity affects drug exposure, efficacy, and toxicity at all stages of the drug development process can not be overstated.
There are more than 200 biotechnology products currently on the market with 400-plus additional therapies in clinical trials targeting diseases such as cancer, Alzheimer’s, rheumatoid arthritis, multiple sclerosis, and HIV/AIDS. In 2014, it’s predicted that 50% of the top 100 drug sales will be biologics, an increase of 28% from 2008.
In contrast to chemically synthesized drugs, biotherapeutics such as proteins, peptides, and antibodies generally possess large and complex structures often modified by glycosylation or pegylation, and may be non-human in orignin. These characteristics greatly increase the potential to induce an antibody-mediated immune response over their small-molecule counterparts, and in consequence cause severe illness in humans. Immunogenicity testing is thus an important part of developing a large-molecule drug for eventual FDA licensure and marketing.
The principal function of an immune system is to protect the body against infection. Most non-self antigens will elicit an antibody-mediated immune response, termed immunogenicity, in animals and humans. This adaptive response to a particular antigen is heterogeneous; no two biological systems react in the same manner, and the response of a single system will change over time. The immune response is used advantageously in vaccinations, however, a primary concern in the development of non-vaccine therapeutics is understanding, measuring, and mitigating an unwanted, drug-induced antibody response.
The myriad of factors that cause immunogenicity within a particular system can be catergorized as drug-related or patient-related. Drug-related factors are related to protein structures plus route of administration, dose level, and frequency of dosing. Patient-related factors include genetic dispostion, immune status, disease state, and the presence of co-medications.
Impact of Immune Response
Since a critical part of the drug development process is to accurately address drug exposure to determine bioavailability in the test species, it is important to understand how the presence of anti-drug antibodies (ADA, also anti-therapeutic antibodies, ATA) may impact this assessment. The antibodies produced as a result of drug challenge may be sustaining, clearing, or neutralizing, all of which can affect the pharmacokinetic and pharmacodynamic properties of the drug.
Understanding the antibody response to drug exposure is necessary to evaluating the significance of that response. Determining the magnitude of response is important in understanding and ultimately determining the safety and efficacy of a particular drug which may include: response duration, occurrence of adverse events such as allergic reactions, evaluating the production of neutralizing antibodies, and correlating change in PK/TK profiles.
Preclinical and Clinical Implications of Immunogenicity
Until recently, the focus of regulatory agencies and opinion papers has largely been the design and application of immunogenicity studies on human subjects, but an important part of any drug development program are preclinical toxicology studies. However, preclinical studies are generally poor predictors of immunogenicty in humans. Therefore, preclinical toxicology studies to evaluate immunogenicty are used mostly to help interpret the PK and PD properties of the drug, as well as any toxicity findings.
Overall, the immunogenicity rates discovered in preclinical studies do not necessarily preclude the initiation of clinical studies. Therefore, any new biotherapeutic under consideration for marketing and licensure goes through a proper risk assessment that considers the probability of generating an immune response and the consequences of such a response. After the risk is categorized (as low, medium, or high), a bioanlytical testing strategy is defined accordingly.
Following assessment of immunogenic potential, consideration of the possible clinical sequelae, as well as whether the target indication is a life-threatening disease is needed to develop a risk-management plan. The type of risk inherent to a particular drug dictates the testing and sampling strategy. For instance, low and medium risk drugs should have ADA samples taken frequently in Phase I and Phase II trials to help understand the human immune response to the drug, with testing less frequent in Phase III. By contrast, a high risk drug, one with potential to cross react with and neutralize an endogenous counterpart, might require frequent sampling and ADA analysis at all stages of clinical development, or sequential patient dosing to better mitigate risks. At a minimun, all immunogenicity assessments during clinical trials should include screen, confirmatory, and tier analysis.
Approaches to attenuate immunogenicty and minimize patient risk include drug redesign, change in dose and/or dosing procedure, and exclusion of sensitive subjects. Once immunogenicty is observed, the clinician must decide the best path forward for the patient.
Follow-on biologics, or biosimilars, are large-molecule therapeutics similar to a licensed drug, but manufactured by a third-party following patent expiration of the innovator molecule. While there is currently no mechanism for approval and licensure of biosimilars in the U.S., the EU and Japan both have a legal, regulated process that includes assessment of immunogenicity between the innovator drug and follow-on biologic at all stages of the development process to ensure comparable, quality, safety, and efficacy.
Overall, the complexity of the immune response necessitates production of a sound risk-assessment strategy and a fit-for-purpose approach in testing of preclinical and clinical samples. Whatever the application, properly designed and validated immunoanalytical methods provide confidence in the data used for these purposes.